User login
Using telemedicine to improve maternal safety
SAN DIEGO – Utah hospitals reported improved implementation of an obstetrics hemorrhage bundle following a series of teleconferencing sessions.
“There is an increasing body of evidence to support the use of protocols and bundles in obstetrics to improve outcomes for pregnant women and their babies,” Brett D. Einerson, MD, MPH, lead study author, said in an interview. “In Utah and throughout the Mountain West, we face the unique challenge of disseminating information and education on the latest evidence-based treatments to smaller rural hospitals that still need to be prepared for events like severe postpartum hemorrhage but do not have the volume, or sometime the resources, to be adequately prepared.”
“Telehealth allowed us to reach providers who otherwise could not travel the distance to attend frequent training sessions and gave the whole state access to expertise at the region’s large tertiary care hospitals,” Dr. Einerson said. “As far as we know, this is one of the first uses of telehealth as a tool for disseminating patient safety and quality improvement education for health care providers on a statewide scale.”
Dr. Einerson and his associates invited all Utah hospitals to participate in the Obstetric Hemorrhage Collaborative, an evidence-based educational program aimed at facilitating implementation of the obstetric hemorrhage bundle. The program involved two in-person training meetings and twice-monthly teleconferencing with expert mentorship over 6 months. In-person sessions consisted of hands-on training and strategy building, while telehealth sessions were led by regional and national leaders in the field of obstetric hemorrhage.
A statewide self-assessment survey of 38 bundle elements was administered before initiation of the project and after completion. The researchers used modified Likert scales to describe participant responses. Means and proportions were compared before and after the training.
Of Utah’s obstetric hospitals, representing every hospital system in the state, 27 (61%) completed the needs-assessment survey, and 15 (34%) participated in the Obstetric Hemorrhage Collaborative, which included four bundle domains:
- Recognition and Prevention: Conducting a risk assessment and active management of the Third Stage of labor.
- Response: Creating a checklist and a rapid response team.
- Readiness: Establishing a blood bank, hemorrhage cart, and conducting simulation/team drills.
- Reporting and Learning: Fostering a culture of debriefing, conducting a multidisciplinary review, and measuring outcomes and processes.
Hospitals reported implementation, or progress toward implementation, of significantly more elements of the bundle after the educational program, compared with before the collaborative (a mean of 33.3 vs. 19 bundle elements; P less than 0.001). Hospitals reported increased implementation of elements in all four bundle domains. All participants (100%) reported that teleconferencing sessions were “very helpful,” and 14 (93%) said that they were “very satisfied” with the collaborative.
“Hospitals in the state of Utah generally had the right tools to treat and prevent obstetric hemorrhage but did not have the systems in place to be sure that the tools were used correctly,” Dr. Einerson said. “For instance, 80% of hospitals had access to a cart with supplies for treating bleeding, but less than 15% were systematically measuring blood loss after delivery. What surprised me most, however, was that most hospitals did not track their rates of postpartum bleeding. In my mind, you can’t set goals for treatment until you know how good – or bad – you are doing. Knowing your baseline rate of outcomes can help set goals and measure progress toward achieving them. Before training, less than 50% of Utah hospitals knew their own rate of hemorrhage, but all participating hospitals reported tracking their rates after the intervention.”
He acknowledged certain limitations of the study, including the fact that it did not measure obstetric outcomes. “We are in the process of measuring the effectiveness of our telehealth intervention by monitoring hemorrhage rates and complications over time,” Dr. Einerson said. “This survey of participants in the statewide telehealth bundle program is the first step.”
Dr. Einerson reported having no financial disclosures.
SAN DIEGO – Utah hospitals reported improved implementation of an obstetrics hemorrhage bundle following a series of teleconferencing sessions.
“There is an increasing body of evidence to support the use of protocols and bundles in obstetrics to improve outcomes for pregnant women and their babies,” Brett D. Einerson, MD, MPH, lead study author, said in an interview. “In Utah and throughout the Mountain West, we face the unique challenge of disseminating information and education on the latest evidence-based treatments to smaller rural hospitals that still need to be prepared for events like severe postpartum hemorrhage but do not have the volume, or sometime the resources, to be adequately prepared.”
“Telehealth allowed us to reach providers who otherwise could not travel the distance to attend frequent training sessions and gave the whole state access to expertise at the region’s large tertiary care hospitals,” Dr. Einerson said. “As far as we know, this is one of the first uses of telehealth as a tool for disseminating patient safety and quality improvement education for health care providers on a statewide scale.”
Dr. Einerson and his associates invited all Utah hospitals to participate in the Obstetric Hemorrhage Collaborative, an evidence-based educational program aimed at facilitating implementation of the obstetric hemorrhage bundle. The program involved two in-person training meetings and twice-monthly teleconferencing with expert mentorship over 6 months. In-person sessions consisted of hands-on training and strategy building, while telehealth sessions were led by regional and national leaders in the field of obstetric hemorrhage.
A statewide self-assessment survey of 38 bundle elements was administered before initiation of the project and after completion. The researchers used modified Likert scales to describe participant responses. Means and proportions were compared before and after the training.
Of Utah’s obstetric hospitals, representing every hospital system in the state, 27 (61%) completed the needs-assessment survey, and 15 (34%) participated in the Obstetric Hemorrhage Collaborative, which included four bundle domains:
- Recognition and Prevention: Conducting a risk assessment and active management of the Third Stage of labor.
- Response: Creating a checklist and a rapid response team.
- Readiness: Establishing a blood bank, hemorrhage cart, and conducting simulation/team drills.
- Reporting and Learning: Fostering a culture of debriefing, conducting a multidisciplinary review, and measuring outcomes and processes.
Hospitals reported implementation, or progress toward implementation, of significantly more elements of the bundle after the educational program, compared with before the collaborative (a mean of 33.3 vs. 19 bundle elements; P less than 0.001). Hospitals reported increased implementation of elements in all four bundle domains. All participants (100%) reported that teleconferencing sessions were “very helpful,” and 14 (93%) said that they were “very satisfied” with the collaborative.
“Hospitals in the state of Utah generally had the right tools to treat and prevent obstetric hemorrhage but did not have the systems in place to be sure that the tools were used correctly,” Dr. Einerson said. “For instance, 80% of hospitals had access to a cart with supplies for treating bleeding, but less than 15% were systematically measuring blood loss after delivery. What surprised me most, however, was that most hospitals did not track their rates of postpartum bleeding. In my mind, you can’t set goals for treatment until you know how good – or bad – you are doing. Knowing your baseline rate of outcomes can help set goals and measure progress toward achieving them. Before training, less than 50% of Utah hospitals knew their own rate of hemorrhage, but all participating hospitals reported tracking their rates after the intervention.”
He acknowledged certain limitations of the study, including the fact that it did not measure obstetric outcomes. “We are in the process of measuring the effectiveness of our telehealth intervention by monitoring hemorrhage rates and complications over time,” Dr. Einerson said. “This survey of participants in the statewide telehealth bundle program is the first step.”
Dr. Einerson reported having no financial disclosures.
SAN DIEGO – Utah hospitals reported improved implementation of an obstetrics hemorrhage bundle following a series of teleconferencing sessions.
“There is an increasing body of evidence to support the use of protocols and bundles in obstetrics to improve outcomes for pregnant women and their babies,” Brett D. Einerson, MD, MPH, lead study author, said in an interview. “In Utah and throughout the Mountain West, we face the unique challenge of disseminating information and education on the latest evidence-based treatments to smaller rural hospitals that still need to be prepared for events like severe postpartum hemorrhage but do not have the volume, or sometime the resources, to be adequately prepared.”
“Telehealth allowed us to reach providers who otherwise could not travel the distance to attend frequent training sessions and gave the whole state access to expertise at the region’s large tertiary care hospitals,” Dr. Einerson said. “As far as we know, this is one of the first uses of telehealth as a tool for disseminating patient safety and quality improvement education for health care providers on a statewide scale.”
Dr. Einerson and his associates invited all Utah hospitals to participate in the Obstetric Hemorrhage Collaborative, an evidence-based educational program aimed at facilitating implementation of the obstetric hemorrhage bundle. The program involved two in-person training meetings and twice-monthly teleconferencing with expert mentorship over 6 months. In-person sessions consisted of hands-on training and strategy building, while telehealth sessions were led by regional and national leaders in the field of obstetric hemorrhage.
A statewide self-assessment survey of 38 bundle elements was administered before initiation of the project and after completion. The researchers used modified Likert scales to describe participant responses. Means and proportions were compared before and after the training.
Of Utah’s obstetric hospitals, representing every hospital system in the state, 27 (61%) completed the needs-assessment survey, and 15 (34%) participated in the Obstetric Hemorrhage Collaborative, which included four bundle domains:
- Recognition and Prevention: Conducting a risk assessment and active management of the Third Stage of labor.
- Response: Creating a checklist and a rapid response team.
- Readiness: Establishing a blood bank, hemorrhage cart, and conducting simulation/team drills.
- Reporting and Learning: Fostering a culture of debriefing, conducting a multidisciplinary review, and measuring outcomes and processes.
Hospitals reported implementation, or progress toward implementation, of significantly more elements of the bundle after the educational program, compared with before the collaborative (a mean of 33.3 vs. 19 bundle elements; P less than 0.001). Hospitals reported increased implementation of elements in all four bundle domains. All participants (100%) reported that teleconferencing sessions were “very helpful,” and 14 (93%) said that they were “very satisfied” with the collaborative.
“Hospitals in the state of Utah generally had the right tools to treat and prevent obstetric hemorrhage but did not have the systems in place to be sure that the tools were used correctly,” Dr. Einerson said. “For instance, 80% of hospitals had access to a cart with supplies for treating bleeding, but less than 15% were systematically measuring blood loss after delivery. What surprised me most, however, was that most hospitals did not track their rates of postpartum bleeding. In my mind, you can’t set goals for treatment until you know how good – or bad – you are doing. Knowing your baseline rate of outcomes can help set goals and measure progress toward achieving them. Before training, less than 50% of Utah hospitals knew their own rate of hemorrhage, but all participating hospitals reported tracking their rates after the intervention.”
He acknowledged certain limitations of the study, including the fact that it did not measure obstetric outcomes. “We are in the process of measuring the effectiveness of our telehealth intervention by monitoring hemorrhage rates and complications over time,” Dr. Einerson said. “This survey of participants in the statewide telehealth bundle program is the first step.”
Dr. Einerson reported having no financial disclosures.
AT ACOG 2017
Key clinical point:
Major finding: Hospitals reported implementation, or progress toward implementation, of significantly more elements of the bundle after the educational program, compared with before the collaborative (a mean of 33.3 vs. 19 bundle elements; P less than 0.001).
Data source: Results from 15 Utah hospitals that participated in the Obstetric Hemorrhage Collaborative.
Disclosures: The researchers reported having no financial disclosures.
More than one-third of genetic tests misordered, study finds
SAN DIEGO – A review of genetic tests ordered during a 3-month period found that more than one-third were misordered, leading to more than $20,000 in unnecessary health care costs, results from a single-center quality improvement project showed.
“We know there is an ever-expanding number of genetic tests available for clinicians to order, and there is more direct marketing to the patient,” Kathleen Ruzzo, MD, the lead study author, said in an interview prior to the annual clinical and scientific meeting of the American College of Obstetricians and Gynecologists. “It can be difficult to stay on top of that as we have so many different clinical responsibilities.”
Of genetic tests ordered for the 114 patients, 44 (39%) were deemed to be misordered based on published clinical practice guidelines. Of the rest, 24 tests were misordered/not indicated, 8 tests were misordered/false reassurance, and 12 tests were misordered/inadequate.
The costs of ordered genetic testing totaled approximately $75,000, while the cost of recommended testing following the chart review was approximately $54,000, a difference of more than $20,000.
When Dr. Ruzzo shared results of the study with her colleagues at Naval Medical Center San Diego, “I think it opened a lot of people’s eyes … to be more meticulous about [genetic] testing and to ask for help when you need help,” she said. “Having trained individuals, reviewing genetic tests could save money in the health care system more broadly. We could also approve the appropriate testing for the patient.”
She acknowledged certain limitations of the study, including the fact that it “reviewed a very narrow scope of [genetic] tests for a short amount of time, so we think we underestimated the appropriate health care expenditures. Additionally, we didn’t focus on the clinical ramifications of the misordering for patients.”
Study coauthor Monica A. Lutgendorf, MD, a maternal-fetal medicine physician at the medical center, characterized the study findings as “a call to action in general for ob.gyns. to get additional training and resources to handle the ever-expanding number of [genetic] tests,” she said. “I don’t think that this is unique to any specific institution. I think this is part of the new environment of practice that we’re in.”
Physicians can learn more about genetic testing from ACOG and from the Perinatal Quality Foundation, Dr. Lutgendorf said. The study won first prize among oral abstracts presented at the ACOG meeting. The researchers reported having no financial disclosures.
SAN DIEGO – A review of genetic tests ordered during a 3-month period found that more than one-third were misordered, leading to more than $20,000 in unnecessary health care costs, results from a single-center quality improvement project showed.
“We know there is an ever-expanding number of genetic tests available for clinicians to order, and there is more direct marketing to the patient,” Kathleen Ruzzo, MD, the lead study author, said in an interview prior to the annual clinical and scientific meeting of the American College of Obstetricians and Gynecologists. “It can be difficult to stay on top of that as we have so many different clinical responsibilities.”
Of genetic tests ordered for the 114 patients, 44 (39%) were deemed to be misordered based on published clinical practice guidelines. Of the rest, 24 tests were misordered/not indicated, 8 tests were misordered/false reassurance, and 12 tests were misordered/inadequate.
The costs of ordered genetic testing totaled approximately $75,000, while the cost of recommended testing following the chart review was approximately $54,000, a difference of more than $20,000.
When Dr. Ruzzo shared results of the study with her colleagues at Naval Medical Center San Diego, “I think it opened a lot of people’s eyes … to be more meticulous about [genetic] testing and to ask for help when you need help,” she said. “Having trained individuals, reviewing genetic tests could save money in the health care system more broadly. We could also approve the appropriate testing for the patient.”
She acknowledged certain limitations of the study, including the fact that it “reviewed a very narrow scope of [genetic] tests for a short amount of time, so we think we underestimated the appropriate health care expenditures. Additionally, we didn’t focus on the clinical ramifications of the misordering for patients.”
Study coauthor Monica A. Lutgendorf, MD, a maternal-fetal medicine physician at the medical center, characterized the study findings as “a call to action in general for ob.gyns. to get additional training and resources to handle the ever-expanding number of [genetic] tests,” she said. “I don’t think that this is unique to any specific institution. I think this is part of the new environment of practice that we’re in.”
Physicians can learn more about genetic testing from ACOG and from the Perinatal Quality Foundation, Dr. Lutgendorf said. The study won first prize among oral abstracts presented at the ACOG meeting. The researchers reported having no financial disclosures.
SAN DIEGO – A review of genetic tests ordered during a 3-month period found that more than one-third were misordered, leading to more than $20,000 in unnecessary health care costs, results from a single-center quality improvement project showed.
“We know there is an ever-expanding number of genetic tests available for clinicians to order, and there is more direct marketing to the patient,” Kathleen Ruzzo, MD, the lead study author, said in an interview prior to the annual clinical and scientific meeting of the American College of Obstetricians and Gynecologists. “It can be difficult to stay on top of that as we have so many different clinical responsibilities.”
Of genetic tests ordered for the 114 patients, 44 (39%) were deemed to be misordered based on published clinical practice guidelines. Of the rest, 24 tests were misordered/not indicated, 8 tests were misordered/false reassurance, and 12 tests were misordered/inadequate.
The costs of ordered genetic testing totaled approximately $75,000, while the cost of recommended testing following the chart review was approximately $54,000, a difference of more than $20,000.
When Dr. Ruzzo shared results of the study with her colleagues at Naval Medical Center San Diego, “I think it opened a lot of people’s eyes … to be more meticulous about [genetic] testing and to ask for help when you need help,” she said. “Having trained individuals, reviewing genetic tests could save money in the health care system more broadly. We could also approve the appropriate testing for the patient.”
She acknowledged certain limitations of the study, including the fact that it “reviewed a very narrow scope of [genetic] tests for a short amount of time, so we think we underestimated the appropriate health care expenditures. Additionally, we didn’t focus on the clinical ramifications of the misordering for patients.”
Study coauthor Monica A. Lutgendorf, MD, a maternal-fetal medicine physician at the medical center, characterized the study findings as “a call to action in general for ob.gyns. to get additional training and resources to handle the ever-expanding number of [genetic] tests,” she said. “I don’t think that this is unique to any specific institution. I think this is part of the new environment of practice that we’re in.”
Physicians can learn more about genetic testing from ACOG and from the Perinatal Quality Foundation, Dr. Lutgendorf said. The study won first prize among oral abstracts presented at the ACOG meeting. The researchers reported having no financial disclosures.
AT ACOG 2017
Key clinical point:
Major finding: Of genetic tests ordered by clinicians, 39% were deemed to be misordered.
Data source: A review of 114 genetic tests ordered over a 3-month period at a single center.
Disclosures: The researchers reported having no financial disclosures.
Adult vaccination is low, with minimal improvement in recent years
Only minimal improvements have been made in vaccination coverage among U.S. adults in recent years, reported Walter W. Williams, MD, of the National Center for Immunization and Respiratory Diseases, Atlanta, and his associates.
In an analysis of data from the 2015 National Health Interview Survey, the researchers looked at adult vaccine coverage for influenza, pneumococcal, tetanus, hepatitis A, hepatitis B, herpes zoster, and human papillomavirus. Although vaccine coverage rose in several of the seven vaccines studied from 2014 to 2015, these were small increases, they noted (MMWR Surveill Summ. 2017 May 5;66[11]:1-28).
Two or more doses of hepatitis A vaccination coverage in 2015 was 9% for adults aged 19 years or older, similar to the estimate for 2014. Three or more doses of hepatitis B vaccination coverage among adults was 24.6% for adults aged 19 years or older in 2015, similar to that in 2014. However, hepatitis B vaccination coverage among health care providers aged 19 years and older was 64.7%, a 4.1% increase compared with 2014.
In women aged 19-26 years, 41.6% received at least 1 dose of human papillomavirus vaccine in 2015, similar to that reported for 2014. In adults aged 60 years and older, 30.6% reported receiving herpes zoster vaccination to prevent shingles in 2015, 2.7% higher than in 2014.
The results showed that racial and ethnic differences in vaccine coverage persisted for all vaccines researched in this report, with higher coverage for whites compared with most other groups such as African Americans and Hispanics. The differences widened for vaccines such as pneumococcal and herpes zoster. Whites also reported receiving vaccinations more often than other groups, the researchers said.
The data in this report are subject to some limitations, such as exclusion of people in the military and those residing in institutions. Self-report of vaccination may be subject to recall bias, as young adults likely are not able to remember accurately the number of vaccines they’ve received as children or as adults, the researchers noted.
The awareness of the need for vaccines by adults is low among the general population. Health care provider recommendations for vaccinations are strongly associated with a patient’s receiving vaccines. Integrating assessment of adult patients’ vaccination needs, recommendations, and offers of vaccination as a part of routine adult clinical care could greatly improve the adult vaccination rate, according Dr. Williams and his associates.
No conflict of interest was reported.
Only minimal improvements have been made in vaccination coverage among U.S. adults in recent years, reported Walter W. Williams, MD, of the National Center for Immunization and Respiratory Diseases, Atlanta, and his associates.
In an analysis of data from the 2015 National Health Interview Survey, the researchers looked at adult vaccine coverage for influenza, pneumococcal, tetanus, hepatitis A, hepatitis B, herpes zoster, and human papillomavirus. Although vaccine coverage rose in several of the seven vaccines studied from 2014 to 2015, these were small increases, they noted (MMWR Surveill Summ. 2017 May 5;66[11]:1-28).
Two or more doses of hepatitis A vaccination coverage in 2015 was 9% for adults aged 19 years or older, similar to the estimate for 2014. Three or more doses of hepatitis B vaccination coverage among adults was 24.6% for adults aged 19 years or older in 2015, similar to that in 2014. However, hepatitis B vaccination coverage among health care providers aged 19 years and older was 64.7%, a 4.1% increase compared with 2014.
In women aged 19-26 years, 41.6% received at least 1 dose of human papillomavirus vaccine in 2015, similar to that reported for 2014. In adults aged 60 years and older, 30.6% reported receiving herpes zoster vaccination to prevent shingles in 2015, 2.7% higher than in 2014.
The results showed that racial and ethnic differences in vaccine coverage persisted for all vaccines researched in this report, with higher coverage for whites compared with most other groups such as African Americans and Hispanics. The differences widened for vaccines such as pneumococcal and herpes zoster. Whites also reported receiving vaccinations more often than other groups, the researchers said.
The data in this report are subject to some limitations, such as exclusion of people in the military and those residing in institutions. Self-report of vaccination may be subject to recall bias, as young adults likely are not able to remember accurately the number of vaccines they’ve received as children or as adults, the researchers noted.
The awareness of the need for vaccines by adults is low among the general population. Health care provider recommendations for vaccinations are strongly associated with a patient’s receiving vaccines. Integrating assessment of adult patients’ vaccination needs, recommendations, and offers of vaccination as a part of routine adult clinical care could greatly improve the adult vaccination rate, according Dr. Williams and his associates.
No conflict of interest was reported.
Only minimal improvements have been made in vaccination coverage among U.S. adults in recent years, reported Walter W. Williams, MD, of the National Center for Immunization and Respiratory Diseases, Atlanta, and his associates.
In an analysis of data from the 2015 National Health Interview Survey, the researchers looked at adult vaccine coverage for influenza, pneumococcal, tetanus, hepatitis A, hepatitis B, herpes zoster, and human papillomavirus. Although vaccine coverage rose in several of the seven vaccines studied from 2014 to 2015, these were small increases, they noted (MMWR Surveill Summ. 2017 May 5;66[11]:1-28).
Two or more doses of hepatitis A vaccination coverage in 2015 was 9% for adults aged 19 years or older, similar to the estimate for 2014. Three or more doses of hepatitis B vaccination coverage among adults was 24.6% for adults aged 19 years or older in 2015, similar to that in 2014. However, hepatitis B vaccination coverage among health care providers aged 19 years and older was 64.7%, a 4.1% increase compared with 2014.
In women aged 19-26 years, 41.6% received at least 1 dose of human papillomavirus vaccine in 2015, similar to that reported for 2014. In adults aged 60 years and older, 30.6% reported receiving herpes zoster vaccination to prevent shingles in 2015, 2.7% higher than in 2014.
The results showed that racial and ethnic differences in vaccine coverage persisted for all vaccines researched in this report, with higher coverage for whites compared with most other groups such as African Americans and Hispanics. The differences widened for vaccines such as pneumococcal and herpes zoster. Whites also reported receiving vaccinations more often than other groups, the researchers said.
The data in this report are subject to some limitations, such as exclusion of people in the military and those residing in institutions. Self-report of vaccination may be subject to recall bias, as young adults likely are not able to remember accurately the number of vaccines they’ve received as children or as adults, the researchers noted.
The awareness of the need for vaccines by adults is low among the general population. Health care provider recommendations for vaccinations are strongly associated with a patient’s receiving vaccines. Integrating assessment of adult patients’ vaccination needs, recommendations, and offers of vaccination as a part of routine adult clinical care could greatly improve the adult vaccination rate, according Dr. Williams and his associates.
No conflict of interest was reported.
FROM MMWR
CAR T-cell data expected soon in mantle cell lymphoma
Final data collection for primary outcome measures is anticipated in September for ZUMA-2, a Phase II multicenter study of the chimeric antigen receptor (CAR) T-cell product KTE-C19 in patients with relapsed/refractory mantle cell lymphoma.
ZUMA-2 (NCT02601313), with a planned enrollment of 70 patients, is expected to release the overall response rate at 12 months. Secondary outcome measures include duration of response, best objective response, and progression-free survival.
Subjects can have up to five prior regimens, which must include anthracycline or bendamustine-containing chemotherapy, anti-CD20 monoclonal antibody therapy, and ibrutinib. Study subjects cannot have received allogeneic stem cell transplantation, prior CD19 targeted therapy, or prior CAR or other genetically modified T cell therapy.
Trial participants must be adults with an Eastern cooperative oncology group (ECOG) performance status of 0 or 1, an absolute neutrophil count of at least 1000/µL, and a platelet count of at least 50,000/µL. All need to have adequate renal function, defined as a serum creatinine of 1.5 mg/dL or less; adequate hepatic function, defined as a serum ALT/AST of 2.5 the upper limit of normal or less; and a total bilirubin of 1.5 mg/dL or less (except in subjects with Gilbert’s syndrome), and adequate cardiac function, defined as a cardiac ejection fraction of 50% or more with no evidence of pericardial effusion.
Exclusion criteria include a history of another cancer other than nonmelanomatous skin cancer or carcinoma in situ (for example, cervix, bladder, breast) unless disease free for at least 3 years, known infection with HIV or hepatitis B or C virus, metastases in cerebrospinal fluid or brain, and a history of a seizure disorder, cerebrovascular ischemia/hemorrhage, dementia, cerebellar disease, or any autoimmune disease with CNS involvement.
The study is sponsored by Kite Pharma, the makers of KTE-C19.
Final data collection for primary outcome measures is anticipated in September for ZUMA-2, a Phase II multicenter study of the chimeric antigen receptor (CAR) T-cell product KTE-C19 in patients with relapsed/refractory mantle cell lymphoma.
ZUMA-2 (NCT02601313), with a planned enrollment of 70 patients, is expected to release the overall response rate at 12 months. Secondary outcome measures include duration of response, best objective response, and progression-free survival.
Subjects can have up to five prior regimens, which must include anthracycline or bendamustine-containing chemotherapy, anti-CD20 monoclonal antibody therapy, and ibrutinib. Study subjects cannot have received allogeneic stem cell transplantation, prior CD19 targeted therapy, or prior CAR or other genetically modified T cell therapy.
Trial participants must be adults with an Eastern cooperative oncology group (ECOG) performance status of 0 or 1, an absolute neutrophil count of at least 1000/µL, and a platelet count of at least 50,000/µL. All need to have adequate renal function, defined as a serum creatinine of 1.5 mg/dL or less; adequate hepatic function, defined as a serum ALT/AST of 2.5 the upper limit of normal or less; and a total bilirubin of 1.5 mg/dL or less (except in subjects with Gilbert’s syndrome), and adequate cardiac function, defined as a cardiac ejection fraction of 50% or more with no evidence of pericardial effusion.
Exclusion criteria include a history of another cancer other than nonmelanomatous skin cancer or carcinoma in situ (for example, cervix, bladder, breast) unless disease free for at least 3 years, known infection with HIV or hepatitis B or C virus, metastases in cerebrospinal fluid or brain, and a history of a seizure disorder, cerebrovascular ischemia/hemorrhage, dementia, cerebellar disease, or any autoimmune disease with CNS involvement.
The study is sponsored by Kite Pharma, the makers of KTE-C19.
Final data collection for primary outcome measures is anticipated in September for ZUMA-2, a Phase II multicenter study of the chimeric antigen receptor (CAR) T-cell product KTE-C19 in patients with relapsed/refractory mantle cell lymphoma.
ZUMA-2 (NCT02601313), with a planned enrollment of 70 patients, is expected to release the overall response rate at 12 months. Secondary outcome measures include duration of response, best objective response, and progression-free survival.
Subjects can have up to five prior regimens, which must include anthracycline or bendamustine-containing chemotherapy, anti-CD20 monoclonal antibody therapy, and ibrutinib. Study subjects cannot have received allogeneic stem cell transplantation, prior CD19 targeted therapy, or prior CAR or other genetically modified T cell therapy.
Trial participants must be adults with an Eastern cooperative oncology group (ECOG) performance status of 0 or 1, an absolute neutrophil count of at least 1000/µL, and a platelet count of at least 50,000/µL. All need to have adequate renal function, defined as a serum creatinine of 1.5 mg/dL or less; adequate hepatic function, defined as a serum ALT/AST of 2.5 the upper limit of normal or less; and a total bilirubin of 1.5 mg/dL or less (except in subjects with Gilbert’s syndrome), and adequate cardiac function, defined as a cardiac ejection fraction of 50% or more with no evidence of pericardial effusion.
Exclusion criteria include a history of another cancer other than nonmelanomatous skin cancer or carcinoma in situ (for example, cervix, bladder, breast) unless disease free for at least 3 years, known infection with HIV or hepatitis B or C virus, metastases in cerebrospinal fluid or brain, and a history of a seizure disorder, cerebrovascular ischemia/hemorrhage, dementia, cerebellar disease, or any autoimmune disease with CNS involvement.
The study is sponsored by Kite Pharma, the makers of KTE-C19.
SUMMARY FROM CLINICALTRIALS.GOV
Isothiazolinone allergy frequent and underdiagnosed in children
Sensitization to the isothiazolinones MCI (methylchloroisothiazolinone) and MI (methylisothiazolinone), which are used as preservatives in a wide variety of personal and household products, is both frequent and underdiagnosed in U.S. children, according to a report published in Pediatric Dermatology.
These agents are compatible with surfactants and emulsifiers, and because they maintain biocidal activity across a broad range of pH levels they are frequently used as preservatives in products such as wet wipes; shampoos and hair conditioners; soaps, cleansers, and disinfectants; and laundry products. However, they are known to cause contact dermatitis very frequently, and are among the top five contact allergens identified in infants’ patch tests.
A recent survey showed that among 152 pediatric skin care products available at major retail stores, 20% contained MI. These were specifically targeted to infants and children, advertised as being “hypoallergenic,” “natural,” good for “sensitive” skin, and containing “gentle ingredients,” said Alina Goldenberg, MD, of the department of dermatology at the University of California, San Diego, and her associates.
During the past 10 years, only 35 U.S. cases of a positive patch-test reaction to MCI and/or MI have been reported in the literature. To get a more accurate estimate of the true prevalence of pediatric sensitization to MCI and MI, the investigators analyzed information in a database of patch-test results, the Provider Contact Dermatitis Registry. They focused on 1,056 patch tests performed during a 1-year period.
They found 37 positive reactions to combined MCI/MI and another 39 reactions that were negative to combined MCI/MI but positive to MI alone. This shows how important it is to test for sensitization to both formulations separately, Dr. Goldenberg and her associates noted (Pediatr Dermatol. 2017 Mar;34[2]:138-43).
In stark contrast to the reported 35 cases across the entire country during a 10-year period, the investigators found 76 cases (1%) in 1,056 patch tests during a 1-year period.
When test results for MCI/MI and MI alone were compared with those for all other allergens, children sensitized to the isothiazolinones showed marked differences: They were significantly younger, and the location of their dermatitis was more likely to involve the groin and buttocks. This probably is due to the increased use of wet wipes containing MCI and MI being used to clean up urinary and fecal accidents in young children, the researchers said.
The Society for Pediatric Dermatology supported the work. Dr. Goldenberg reported having no relevant financial disclosures; an associate reported serving as a consultant for Johnson & Johnson.
Sensitization to the isothiazolinones MCI (methylchloroisothiazolinone) and MI (methylisothiazolinone), which are used as preservatives in a wide variety of personal and household products, is both frequent and underdiagnosed in U.S. children, according to a report published in Pediatric Dermatology.
These agents are compatible with surfactants and emulsifiers, and because they maintain biocidal activity across a broad range of pH levels they are frequently used as preservatives in products such as wet wipes; shampoos and hair conditioners; soaps, cleansers, and disinfectants; and laundry products. However, they are known to cause contact dermatitis very frequently, and are among the top five contact allergens identified in infants’ patch tests.
A recent survey showed that among 152 pediatric skin care products available at major retail stores, 20% contained MI. These were specifically targeted to infants and children, advertised as being “hypoallergenic,” “natural,” good for “sensitive” skin, and containing “gentle ingredients,” said Alina Goldenberg, MD, of the department of dermatology at the University of California, San Diego, and her associates.
During the past 10 years, only 35 U.S. cases of a positive patch-test reaction to MCI and/or MI have been reported in the literature. To get a more accurate estimate of the true prevalence of pediatric sensitization to MCI and MI, the investigators analyzed information in a database of patch-test results, the Provider Contact Dermatitis Registry. They focused on 1,056 patch tests performed during a 1-year period.
They found 37 positive reactions to combined MCI/MI and another 39 reactions that were negative to combined MCI/MI but positive to MI alone. This shows how important it is to test for sensitization to both formulations separately, Dr. Goldenberg and her associates noted (Pediatr Dermatol. 2017 Mar;34[2]:138-43).
In stark contrast to the reported 35 cases across the entire country during a 10-year period, the investigators found 76 cases (1%) in 1,056 patch tests during a 1-year period.
When test results for MCI/MI and MI alone were compared with those for all other allergens, children sensitized to the isothiazolinones showed marked differences: They were significantly younger, and the location of their dermatitis was more likely to involve the groin and buttocks. This probably is due to the increased use of wet wipes containing MCI and MI being used to clean up urinary and fecal accidents in young children, the researchers said.
The Society for Pediatric Dermatology supported the work. Dr. Goldenberg reported having no relevant financial disclosures; an associate reported serving as a consultant for Johnson & Johnson.
Sensitization to the isothiazolinones MCI (methylchloroisothiazolinone) and MI (methylisothiazolinone), which are used as preservatives in a wide variety of personal and household products, is both frequent and underdiagnosed in U.S. children, according to a report published in Pediatric Dermatology.
These agents are compatible with surfactants and emulsifiers, and because they maintain biocidal activity across a broad range of pH levels they are frequently used as preservatives in products such as wet wipes; shampoos and hair conditioners; soaps, cleansers, and disinfectants; and laundry products. However, they are known to cause contact dermatitis very frequently, and are among the top five contact allergens identified in infants’ patch tests.
A recent survey showed that among 152 pediatric skin care products available at major retail stores, 20% contained MI. These were specifically targeted to infants and children, advertised as being “hypoallergenic,” “natural,” good for “sensitive” skin, and containing “gentle ingredients,” said Alina Goldenberg, MD, of the department of dermatology at the University of California, San Diego, and her associates.
During the past 10 years, only 35 U.S. cases of a positive patch-test reaction to MCI and/or MI have been reported in the literature. To get a more accurate estimate of the true prevalence of pediatric sensitization to MCI and MI, the investigators analyzed information in a database of patch-test results, the Provider Contact Dermatitis Registry. They focused on 1,056 patch tests performed during a 1-year period.
They found 37 positive reactions to combined MCI/MI and another 39 reactions that were negative to combined MCI/MI but positive to MI alone. This shows how important it is to test for sensitization to both formulations separately, Dr. Goldenberg and her associates noted (Pediatr Dermatol. 2017 Mar;34[2]:138-43).
In stark contrast to the reported 35 cases across the entire country during a 10-year period, the investigators found 76 cases (1%) in 1,056 patch tests during a 1-year period.
When test results for MCI/MI and MI alone were compared with those for all other allergens, children sensitized to the isothiazolinones showed marked differences: They were significantly younger, and the location of their dermatitis was more likely to involve the groin and buttocks. This probably is due to the increased use of wet wipes containing MCI and MI being used to clean up urinary and fecal accidents in young children, the researchers said.
The Society for Pediatric Dermatology supported the work. Dr. Goldenberg reported having no relevant financial disclosures; an associate reported serving as a consultant for Johnson & Johnson.
FROM PEDIATRIC DERMATOLOGY
Key clinical point:
Major finding: There were 37 positive patch-test reactions to combined MCI/MI and another 39 reactions that were negative to combined MCI/MI but positive to MI alone.
Data source: An analysis of 1,056 patch-test results recorded in a database by clinicians during a 1-year period.
Disclosures: The Society for Pediatric Dermatology supported the work. Dr. Goldenberg reported having no relevant financial disclosures; an associate reported serving as a consultant for Johnson & Johnson.
G-CSF safe, but antibiotics are more concerning in SCLC
GENEVA – In patients with limited stage–small cell lung cancer (LS-SCLC) treated with concurrent chemotherapy and radiation, the use of antibiotics to prevent febrile neutropenia was associated with worse outcomes, but granulocyte-colony stimulating factor (G-CSF) prescribed for the same purposes appeared to be safe, reported investigators.
In a subanalysis of data on patients with early SCLC enrolled in the phase III CONVERT trial comparing chemotherapy with concurrent once-daily vs. twice-daily radiation, the use of antibiotic prophylaxis of neutropenia was associated with worse overall survival (OS) and progression-free survival, (PFS) compared with no antibiotics, reported Fabio Gomes, MD, from the Christie NHS Foundation Trust Hospital in Manchester, England.
The use of G-CSF was, however, associated with higher rates of grade 3 or 4 thrombocytopenia and anemia, requiring supportive measures, he acknowledged.
The role of G-CSF with concurrent thoracic radiotherapy is controversial because of safety concerns, but data are scarce, Dr. Gomes said. He noted that the American Society of Clinical Oncology guidelines on the use of white blood cell growth factors recommend against their routine use.
However, some of those concerns arose in the mid-1990s when granulocyt macrophage–stimulating colony factor (GM-CSF) was used, rather than G-CSF, which acts on only a single blood lineage, namely neutrophils. Additionally, modern radiology techniques are more precise than they were 20 years ago, reducing the risk of toxicity, he noted.
In the CONVERT trial, 547 patients with LS-SCLC were randomly assigned to receive four to six cycles of cisplatin and etoposide chemotherapy concurrently with either once daily thoracic radiation for a total dose of 66 Gy divided into 33 fractions delivered over 45 days or to twice-daily radiation at a total dose of 45 Gy divided into 30 fractions delivered over 19 days.
There was no difference between the groups in the primary endpoint of overall survival.
In the subanalysis reported here, Gomes et al. looked at the use of G-CSF, delivered at the investigator’s discretion, in 487 patients. Approximately 40% of patients in the subanalysis received G-CSF during at least one treatment cycle.
Prophylactic antibiotics were recommended by the investigators for use in association with at least one chemotherapy cycle, and 49% of patients in the subanalysis received them during at least one cycle.
Hematological toxicities included grade 3 or 4 thrombocytopenia occurring in 29.9% of patients who received G-CSF, vs. 13.3% of those who did not (P less than .001). The rates were similar between the once-daily and twice-daily radiation groups.
Grade 3 or 4 anemia occurred in 16.9% of patients who received G-CSF, vs. 10.7% of those who didn’t (P = .027). The difference was significant only among patients in the twice-daily radiation arm (20.9% vs. 8.3%, respectively; P = .004).
Patients in the twice-daily radiation arms who received G-CSF also required more platelet transfusion, compared with the once-daily arm (P less than .001), and, in both arms, G-CSF was associated with more red-cell transfusions (P = .007 for once-daily and .001 for twice daily).
G-CSF was not associated with either pneumonitis or esophagitis, and there were no differences in treatment-related deaths with either G-CSF or antibiotics.
Median OS by G-CSF use was 29 months with and 27 months without, a difference that was not significant (P = .08). Median PFS also did not differ by G-CSF use or nonuse.
When it came to antibiotic prophylaxis, however, both median OS and PFS were significant worse with antibiotic use (OS, 24 months with vs. 33 months without; P = .016; PFS, P = .03).
“We are very reassured that there are no significant additional toxicities [with G-CSF] from radiation in the acute setting,” commented Sanjay Popat, FRCP, PhD, from the Royal Marsden Hospital in London, the invited discussant.
“However, we have no data as yet on the impact of G-CSF usage on febrile neutropenia, which is of course the fundamental that we’re aiming to improve in the hope that this will contribute to [lowering] costs,” he added.
The study was sponsored by the Christie Hospital National Health Service Foundation Trust, Cancer Research UK, EORTC, GECP, GFPC, and IFCT. Dr. Gomes reported no relevant disclosures. Dr. Popat reported consultation, honoraria, travel expenses, and institutional research from multiple entities.
GENEVA – In patients with limited stage–small cell lung cancer (LS-SCLC) treated with concurrent chemotherapy and radiation, the use of antibiotics to prevent febrile neutropenia was associated with worse outcomes, but granulocyte-colony stimulating factor (G-CSF) prescribed for the same purposes appeared to be safe, reported investigators.
In a subanalysis of data on patients with early SCLC enrolled in the phase III CONVERT trial comparing chemotherapy with concurrent once-daily vs. twice-daily radiation, the use of antibiotic prophylaxis of neutropenia was associated with worse overall survival (OS) and progression-free survival, (PFS) compared with no antibiotics, reported Fabio Gomes, MD, from the Christie NHS Foundation Trust Hospital in Manchester, England.
The use of G-CSF was, however, associated with higher rates of grade 3 or 4 thrombocytopenia and anemia, requiring supportive measures, he acknowledged.
The role of G-CSF with concurrent thoracic radiotherapy is controversial because of safety concerns, but data are scarce, Dr. Gomes said. He noted that the American Society of Clinical Oncology guidelines on the use of white blood cell growth factors recommend against their routine use.
However, some of those concerns arose in the mid-1990s when granulocyt macrophage–stimulating colony factor (GM-CSF) was used, rather than G-CSF, which acts on only a single blood lineage, namely neutrophils. Additionally, modern radiology techniques are more precise than they were 20 years ago, reducing the risk of toxicity, he noted.
In the CONVERT trial, 547 patients with LS-SCLC were randomly assigned to receive four to six cycles of cisplatin and etoposide chemotherapy concurrently with either once daily thoracic radiation for a total dose of 66 Gy divided into 33 fractions delivered over 45 days or to twice-daily radiation at a total dose of 45 Gy divided into 30 fractions delivered over 19 days.
There was no difference between the groups in the primary endpoint of overall survival.
In the subanalysis reported here, Gomes et al. looked at the use of G-CSF, delivered at the investigator’s discretion, in 487 patients. Approximately 40% of patients in the subanalysis received G-CSF during at least one treatment cycle.
Prophylactic antibiotics were recommended by the investigators for use in association with at least one chemotherapy cycle, and 49% of patients in the subanalysis received them during at least one cycle.
Hematological toxicities included grade 3 or 4 thrombocytopenia occurring in 29.9% of patients who received G-CSF, vs. 13.3% of those who did not (P less than .001). The rates were similar between the once-daily and twice-daily radiation groups.
Grade 3 or 4 anemia occurred in 16.9% of patients who received G-CSF, vs. 10.7% of those who didn’t (P = .027). The difference was significant only among patients in the twice-daily radiation arm (20.9% vs. 8.3%, respectively; P = .004).
Patients in the twice-daily radiation arms who received G-CSF also required more platelet transfusion, compared with the once-daily arm (P less than .001), and, in both arms, G-CSF was associated with more red-cell transfusions (P = .007 for once-daily and .001 for twice daily).
G-CSF was not associated with either pneumonitis or esophagitis, and there were no differences in treatment-related deaths with either G-CSF or antibiotics.
Median OS by G-CSF use was 29 months with and 27 months without, a difference that was not significant (P = .08). Median PFS also did not differ by G-CSF use or nonuse.
When it came to antibiotic prophylaxis, however, both median OS and PFS were significant worse with antibiotic use (OS, 24 months with vs. 33 months without; P = .016; PFS, P = .03).
“We are very reassured that there are no significant additional toxicities [with G-CSF] from radiation in the acute setting,” commented Sanjay Popat, FRCP, PhD, from the Royal Marsden Hospital in London, the invited discussant.
“However, we have no data as yet on the impact of G-CSF usage on febrile neutropenia, which is of course the fundamental that we’re aiming to improve in the hope that this will contribute to [lowering] costs,” he added.
The study was sponsored by the Christie Hospital National Health Service Foundation Trust, Cancer Research UK, EORTC, GECP, GFPC, and IFCT. Dr. Gomes reported no relevant disclosures. Dr. Popat reported consultation, honoraria, travel expenses, and institutional research from multiple entities.
GENEVA – In patients with limited stage–small cell lung cancer (LS-SCLC) treated with concurrent chemotherapy and radiation, the use of antibiotics to prevent febrile neutropenia was associated with worse outcomes, but granulocyte-colony stimulating factor (G-CSF) prescribed for the same purposes appeared to be safe, reported investigators.
In a subanalysis of data on patients with early SCLC enrolled in the phase III CONVERT trial comparing chemotherapy with concurrent once-daily vs. twice-daily radiation, the use of antibiotic prophylaxis of neutropenia was associated with worse overall survival (OS) and progression-free survival, (PFS) compared with no antibiotics, reported Fabio Gomes, MD, from the Christie NHS Foundation Trust Hospital in Manchester, England.
The use of G-CSF was, however, associated with higher rates of grade 3 or 4 thrombocytopenia and anemia, requiring supportive measures, he acknowledged.
The role of G-CSF with concurrent thoracic radiotherapy is controversial because of safety concerns, but data are scarce, Dr. Gomes said. He noted that the American Society of Clinical Oncology guidelines on the use of white blood cell growth factors recommend against their routine use.
However, some of those concerns arose in the mid-1990s when granulocyt macrophage–stimulating colony factor (GM-CSF) was used, rather than G-CSF, which acts on only a single blood lineage, namely neutrophils. Additionally, modern radiology techniques are more precise than they were 20 years ago, reducing the risk of toxicity, he noted.
In the CONVERT trial, 547 patients with LS-SCLC were randomly assigned to receive four to six cycles of cisplatin and etoposide chemotherapy concurrently with either once daily thoracic radiation for a total dose of 66 Gy divided into 33 fractions delivered over 45 days or to twice-daily radiation at a total dose of 45 Gy divided into 30 fractions delivered over 19 days.
There was no difference between the groups in the primary endpoint of overall survival.
In the subanalysis reported here, Gomes et al. looked at the use of G-CSF, delivered at the investigator’s discretion, in 487 patients. Approximately 40% of patients in the subanalysis received G-CSF during at least one treatment cycle.
Prophylactic antibiotics were recommended by the investigators for use in association with at least one chemotherapy cycle, and 49% of patients in the subanalysis received them during at least one cycle.
Hematological toxicities included grade 3 or 4 thrombocytopenia occurring in 29.9% of patients who received G-CSF, vs. 13.3% of those who did not (P less than .001). The rates were similar between the once-daily and twice-daily radiation groups.
Grade 3 or 4 anemia occurred in 16.9% of patients who received G-CSF, vs. 10.7% of those who didn’t (P = .027). The difference was significant only among patients in the twice-daily radiation arm (20.9% vs. 8.3%, respectively; P = .004).
Patients in the twice-daily radiation arms who received G-CSF also required more platelet transfusion, compared with the once-daily arm (P less than .001), and, in both arms, G-CSF was associated with more red-cell transfusions (P = .007 for once-daily and .001 for twice daily).
G-CSF was not associated with either pneumonitis or esophagitis, and there were no differences in treatment-related deaths with either G-CSF or antibiotics.
Median OS by G-CSF use was 29 months with and 27 months without, a difference that was not significant (P = .08). Median PFS also did not differ by G-CSF use or nonuse.
When it came to antibiotic prophylaxis, however, both median OS and PFS were significant worse with antibiotic use (OS, 24 months with vs. 33 months without; P = .016; PFS, P = .03).
“We are very reassured that there are no significant additional toxicities [with G-CSF] from radiation in the acute setting,” commented Sanjay Popat, FRCP, PhD, from the Royal Marsden Hospital in London, the invited discussant.
“However, we have no data as yet on the impact of G-CSF usage on febrile neutropenia, which is of course the fundamental that we’re aiming to improve in the hope that this will contribute to [lowering] costs,” he added.
The study was sponsored by the Christie Hospital National Health Service Foundation Trust, Cancer Research UK, EORTC, GECP, GFPC, and IFCT. Dr. Gomes reported no relevant disclosures. Dr. Popat reported consultation, honoraria, travel expenses, and institutional research from multiple entities.
FROM ELCC
Key clinical point: Febrile neutropenia prophylaxis with G-CSF was safe, but prophylactic antibiotics were associated with worse overall survival in patients with limited stage–small cell lung cancer.
Major finding: Both median overall and progression-free survival were lower among patients who received prophylactic antibiotics. There were no differences in survival by G-CSF use.
Data source: Subanalysis of data on 487 patients in the phase III CONVERT trial comparing once-daily and twice daily radiation concurrent with chemotherapy in LS-SCLC.
Disclosures: The study was sponsored by the Christie Hospital National Health Service Foundation Trust, Cancer Research UK, EORTC, GECP, GFPC, and IFCT. Dr. Gomes reported no relevant disclosures. Dr. Popat reported consultation, honoraria, travel expenses, and institutional research from multiple entities.
Should recent evidence of improved outcomes for neonates born during the periviable period change our approach to these deliveries?
EXPERT COMMENTARY
Pregnancy management when delivery appears to be imminent at 22 to 26 weeks’ gestation—a window defined as the periviable period—is among the most challenging situations that obstetricians face. Expert guidance exists both at a national level in a shared guideline from the American College of Obstetricians and Gynecologists and the Society of Maternal Fetal Medicine and, ideally, at a local level where teams of obstetricians and neonatologists have considered in their facility what represents best care
Among the most important yet often missing data points are outcomes of neonates born in the periviable period. Surveys suggest that obstetric care providers often underestimate the chance of survival following periviable delivery.2 Understanding and weighing anticipated outcomes inform decision making regarding management and planned obstetric and neonatal interventions, including plans for neonatal resuscitation.
Not surprisingly, perhaps, survival of periviable neonates has been linked clearly to willingness to undertake resuscitation.3 Yet decisions are not and should not be all about survival. Patients and providers want to know about short- and long-term morbidity, especially neurologic health, among survivors. Available collections of morbidity and mortality data, however, often are limited by whether all cases are captured or just those from specialized centers with particular management approaches, which outcomes are included and how they are defined, and the inevitable reality that the outcome of death “competes” with the outcome of neurologic development (that is, those neonates who die are not at risk for later abnormal neurologic outcome).
Given the need for more and better information, the data from a recent study by Younge and colleagues is especially welcome. The investigators reported on survival and neurologic outcome among more than 4,000 births between 22 and 24 weeks’ gestation at 11 centers in the United States.
Details of the study
The authors compared outcomes among three 3-year epochs between 2000 and 2011 and reported that the rate of survival without neurodevelopmental impairment increased over this period while the rate of survival with such impairment did not change. This argues that the observed overall increase in survival over these 12 years was not simply a tradeoff for life with significant impairment.
Within that overall message, however, the details of the data are important. Survival without neurodevelopmental impairment did improve from epoch 1 to epoch 3, but just from 16% to 20% (95% confidence interval [CI], 18–23; P = .001). Most neonates in the 2008–2011 epoch died (64%; 95% CI, 61–66; P<.001) or were severely impaired (16%; 95% CI, 14–18; P = .29). This led the authors to conclude that “despite improvements over time, the incidence of death, neurodevelopmental impairment, and other adverse outcomes remains high.” Examined separately, outcomes for infants born at 22 0/7 to 22 6/7 weeks’ gestation were very limited and unchanged over the 3 epochs studied, with death rates of 97% to 98% and survival without neurodevelopmental impairment of just 1%. In my own practice I do not encourage neonatal resuscitation, cesarean delivery, or many other interventions at less than 23 weeks’ gestation.
By contrast, the study showed that at 24 0/7 to 24 6/7 weeks’ gestation in the 2008–2011 epoch, 55% of neonates survived and, overall, 32% of infants survived without evidence of neurodevelopmental impairment at 18 to 22 months of age.
Related Article:
Is expectant management a safe alternative to immediate delivery in patients with PPROM close to term?
Study strengths and weaknesses
It is important to note that the definition of neurodevelopmental impairment used in the Younge study included only what many would classify as severe impairment, and survivors in this cohort “without” neurodevelopmental impairment may still have had important neurologic and other health concerns. In addition, the study did not track outcomes of the children at school age or beyond, when other developmental issues may become evident. As well, the study data may not be generalizable, for it included births from just 11 specialized centers, albeit a consortium accounting for 4% to 5% of periviable births in the United States.
Nevertheless, in supporting findings from other US and European analyses, these new data will help inform counseling conversations in the years to come. Such conversations should consider options for resuscitation, palliative care, and, at less than 24 weeks’ gestation, pregnancy termination. In individual cases these and many other decisions will be informed by both specific clinical circumstances—estimated fetal weight, fetal sex, presence of infection, use of antenatal steroids—and, perhaps most important, individual and family values and preferences. Despite these new data, managing periviable gestations will remain a great and important challenge.
--Jeffrey L. Ecker, MD
Share your thoughts! Send your Letter to the Editor to rbarbieri@frontlinemedcom.com. Please include your name and the city and state in which you practice.
- Obstetric Care Consensus No. 4: Periviable birth. Obstet Gynecol. 2016;127(6):e157-e169.
- Haywood JL, Goldenberg RL, Bronstein J, Nelson KG, Carlo WA. Comparison of perceived and actual rates of survival and freedom from handicap in premature infants. Am J Obstet Gynecol. 1994;171(2):432-439.
- Rysavy MA, Li L, Bell EF, et al; Eunice Kennedy Schriver National Institute of Child Health and Human Development Neonatal Research Unit. Between-hospital variation in treatment and outcomes in extremely preterm infants. N Engl J Med. 2015;372(19):1801-1811.
EXPERT COMMENTARY
Pregnancy management when delivery appears to be imminent at 22 to 26 weeks’ gestation—a window defined as the periviable period—is among the most challenging situations that obstetricians face. Expert guidance exists both at a national level in a shared guideline from the American College of Obstetricians and Gynecologists and the Society of Maternal Fetal Medicine and, ideally, at a local level where teams of obstetricians and neonatologists have considered in their facility what represents best care
Among the most important yet often missing data points are outcomes of neonates born in the periviable period. Surveys suggest that obstetric care providers often underestimate the chance of survival following periviable delivery.2 Understanding and weighing anticipated outcomes inform decision making regarding management and planned obstetric and neonatal interventions, including plans for neonatal resuscitation.
Not surprisingly, perhaps, survival of periviable neonates has been linked clearly to willingness to undertake resuscitation.3 Yet decisions are not and should not be all about survival. Patients and providers want to know about short- and long-term morbidity, especially neurologic health, among survivors. Available collections of morbidity and mortality data, however, often are limited by whether all cases are captured or just those from specialized centers with particular management approaches, which outcomes are included and how they are defined, and the inevitable reality that the outcome of death “competes” with the outcome of neurologic development (that is, those neonates who die are not at risk for later abnormal neurologic outcome).
Given the need for more and better information, the data from a recent study by Younge and colleagues is especially welcome. The investigators reported on survival and neurologic outcome among more than 4,000 births between 22 and 24 weeks’ gestation at 11 centers in the United States.
Details of the study
The authors compared outcomes among three 3-year epochs between 2000 and 2011 and reported that the rate of survival without neurodevelopmental impairment increased over this period while the rate of survival with such impairment did not change. This argues that the observed overall increase in survival over these 12 years was not simply a tradeoff for life with significant impairment.
Within that overall message, however, the details of the data are important. Survival without neurodevelopmental impairment did improve from epoch 1 to epoch 3, but just from 16% to 20% (95% confidence interval [CI], 18–23; P = .001). Most neonates in the 2008–2011 epoch died (64%; 95% CI, 61–66; P<.001) or were severely impaired (16%; 95% CI, 14–18; P = .29). This led the authors to conclude that “despite improvements over time, the incidence of death, neurodevelopmental impairment, and other adverse outcomes remains high.” Examined separately, outcomes for infants born at 22 0/7 to 22 6/7 weeks’ gestation were very limited and unchanged over the 3 epochs studied, with death rates of 97% to 98% and survival without neurodevelopmental impairment of just 1%. In my own practice I do not encourage neonatal resuscitation, cesarean delivery, or many other interventions at less than 23 weeks’ gestation.
By contrast, the study showed that at 24 0/7 to 24 6/7 weeks’ gestation in the 2008–2011 epoch, 55% of neonates survived and, overall, 32% of infants survived without evidence of neurodevelopmental impairment at 18 to 22 months of age.
Related Article:
Is expectant management a safe alternative to immediate delivery in patients with PPROM close to term?
Study strengths and weaknesses
It is important to note that the definition of neurodevelopmental impairment used in the Younge study included only what many would classify as severe impairment, and survivors in this cohort “without” neurodevelopmental impairment may still have had important neurologic and other health concerns. In addition, the study did not track outcomes of the children at school age or beyond, when other developmental issues may become evident. As well, the study data may not be generalizable, for it included births from just 11 specialized centers, albeit a consortium accounting for 4% to 5% of periviable births in the United States.
Nevertheless, in supporting findings from other US and European analyses, these new data will help inform counseling conversations in the years to come. Such conversations should consider options for resuscitation, palliative care, and, at less than 24 weeks’ gestation, pregnancy termination. In individual cases these and many other decisions will be informed by both specific clinical circumstances—estimated fetal weight, fetal sex, presence of infection, use of antenatal steroids—and, perhaps most important, individual and family values and preferences. Despite these new data, managing periviable gestations will remain a great and important challenge.
--Jeffrey L. Ecker, MD
Share your thoughts! Send your Letter to the Editor to rbarbieri@frontlinemedcom.com. Please include your name and the city and state in which you practice.
EXPERT COMMENTARY
Pregnancy management when delivery appears to be imminent at 22 to 26 weeks’ gestation—a window defined as the periviable period—is among the most challenging situations that obstetricians face. Expert guidance exists both at a national level in a shared guideline from the American College of Obstetricians and Gynecologists and the Society of Maternal Fetal Medicine and, ideally, at a local level where teams of obstetricians and neonatologists have considered in their facility what represents best care
Among the most important yet often missing data points are outcomes of neonates born in the periviable period. Surveys suggest that obstetric care providers often underestimate the chance of survival following periviable delivery.2 Understanding and weighing anticipated outcomes inform decision making regarding management and planned obstetric and neonatal interventions, including plans for neonatal resuscitation.
Not surprisingly, perhaps, survival of periviable neonates has been linked clearly to willingness to undertake resuscitation.3 Yet decisions are not and should not be all about survival. Patients and providers want to know about short- and long-term morbidity, especially neurologic health, among survivors. Available collections of morbidity and mortality data, however, often are limited by whether all cases are captured or just those from specialized centers with particular management approaches, which outcomes are included and how they are defined, and the inevitable reality that the outcome of death “competes” with the outcome of neurologic development (that is, those neonates who die are not at risk for later abnormal neurologic outcome).
Given the need for more and better information, the data from a recent study by Younge and colleagues is especially welcome. The investigators reported on survival and neurologic outcome among more than 4,000 births between 22 and 24 weeks’ gestation at 11 centers in the United States.
Details of the study
The authors compared outcomes among three 3-year epochs between 2000 and 2011 and reported that the rate of survival without neurodevelopmental impairment increased over this period while the rate of survival with such impairment did not change. This argues that the observed overall increase in survival over these 12 years was not simply a tradeoff for life with significant impairment.
Within that overall message, however, the details of the data are important. Survival without neurodevelopmental impairment did improve from epoch 1 to epoch 3, but just from 16% to 20% (95% confidence interval [CI], 18–23; P = .001). Most neonates in the 2008–2011 epoch died (64%; 95% CI, 61–66; P<.001) or were severely impaired (16%; 95% CI, 14–18; P = .29). This led the authors to conclude that “despite improvements over time, the incidence of death, neurodevelopmental impairment, and other adverse outcomes remains high.” Examined separately, outcomes for infants born at 22 0/7 to 22 6/7 weeks’ gestation were very limited and unchanged over the 3 epochs studied, with death rates of 97% to 98% and survival without neurodevelopmental impairment of just 1%. In my own practice I do not encourage neonatal resuscitation, cesarean delivery, or many other interventions at less than 23 weeks’ gestation.
By contrast, the study showed that at 24 0/7 to 24 6/7 weeks’ gestation in the 2008–2011 epoch, 55% of neonates survived and, overall, 32% of infants survived without evidence of neurodevelopmental impairment at 18 to 22 months of age.
Related Article:
Is expectant management a safe alternative to immediate delivery in patients with PPROM close to term?
Study strengths and weaknesses
It is important to note that the definition of neurodevelopmental impairment used in the Younge study included only what many would classify as severe impairment, and survivors in this cohort “without” neurodevelopmental impairment may still have had important neurologic and other health concerns. In addition, the study did not track outcomes of the children at school age or beyond, when other developmental issues may become evident. As well, the study data may not be generalizable, for it included births from just 11 specialized centers, albeit a consortium accounting for 4% to 5% of periviable births in the United States.
Nevertheless, in supporting findings from other US and European analyses, these new data will help inform counseling conversations in the years to come. Such conversations should consider options for resuscitation, palliative care, and, at less than 24 weeks’ gestation, pregnancy termination. In individual cases these and many other decisions will be informed by both specific clinical circumstances—estimated fetal weight, fetal sex, presence of infection, use of antenatal steroids—and, perhaps most important, individual and family values and preferences. Despite these new data, managing periviable gestations will remain a great and important challenge.
--Jeffrey L. Ecker, MD
Share your thoughts! Send your Letter to the Editor to rbarbieri@frontlinemedcom.com. Please include your name and the city and state in which you practice.
- Obstetric Care Consensus No. 4: Periviable birth. Obstet Gynecol. 2016;127(6):e157-e169.
- Haywood JL, Goldenberg RL, Bronstein J, Nelson KG, Carlo WA. Comparison of perceived and actual rates of survival and freedom from handicap in premature infants. Am J Obstet Gynecol. 1994;171(2):432-439.
- Rysavy MA, Li L, Bell EF, et al; Eunice Kennedy Schriver National Institute of Child Health and Human Development Neonatal Research Unit. Between-hospital variation in treatment and outcomes in extremely preterm infants. N Engl J Med. 2015;372(19):1801-1811.
- Obstetric Care Consensus No. 4: Periviable birth. Obstet Gynecol. 2016;127(6):e157-e169.
- Haywood JL, Goldenberg RL, Bronstein J, Nelson KG, Carlo WA. Comparison of perceived and actual rates of survival and freedom from handicap in premature infants. Am J Obstet Gynecol. 1994;171(2):432-439.
- Rysavy MA, Li L, Bell EF, et al; Eunice Kennedy Schriver National Institute of Child Health and Human Development Neonatal Research Unit. Between-hospital variation in treatment and outcomes in extremely preterm infants. N Engl J Med. 2015;372(19):1801-1811.
Non-cow’s milk associated with lower childhood height
SAN FRANCISCO – Consumption of non-cow’s milk in early childhood is associated with decreased height, compared with consumption of cow’s milk by children in the same stage of life, a study has shown. The results call into question perceived health benefits of the consumption of non-cow’s milk in childhood.
“These findings are important for health care workers and parents in terms of optimal growth of children and the kind of milk needed to achieve that,” presenter Marie-Elssa Morency explained at the meeting of the Pediatric Academic Societies. Ms. Morency is a master’s student in the department of nutritional sciences at the University of Toronto.
Whether cow’s milk is a better source than non-cow’s milk of nutritional and caloric energy to a growing body has not been studied with rigor. Perceived health benefits of non-cow’s milk have led some parents to substitute cow’s milk with other types of milk for their children, Ms. Morency said.
To gain some clarity, the researchers looked at data from the TARGetKids! longitudinal cohort of children. The cohort is being followed into adolescence to link early life exposures to various physiological and developmental health problems. The present study looked at more than 5,000 healthy children aged 24-72 months. Any conditions that could affect growth were grounds for exclusion.
The primary exposure was the daily consumption of cow’s milk in 4,632 children or non-cow’s milk in 643 children. The typical number of 250-mL glasses of milk consumed per day was gleaned by a questionnaire completed by the parents. The primary outcome was height-for-age z score.
The two groups were similar at baseline in age, sex (slightly more than half were male), body mass index, and maternal height. Those who predominantly consumed cow’s milk averaged 2 cups per day. Some also consumed non-cow’s milk (about one glass per day). Those in the non-cow’s milk group consumed on average 1.4 cups per day, with cow’s milk consumption being rare.
The overall z-score was 0.1 (95% confidence interval [CI], –0.6 to 0.8). The groups differed in z-score, with a score of 0.2 (95% CI, –0.6 to 0.8) in the cow’s milk group and –0.04 (95% CI, –0.8 to 0.7) in the non-cow’s milk group. The resulting shorter height in those consuming non-cow’s milk was 0.42 cm (95% CI, –0.61 to –0.19) in a univariate analysis (P less than .001). A multivariate analysis that adjusted for age, sex, maternal ethnicity, maternal height, z-score, and neighborhood income revealed a significant difference in the same group of 0.31 cm (95% CI, –0.50 to –0.11; P less than .001).
The reduced consumption of cow’s milk in the non-cow’s milk group was identified as a partial mediator of the association between non-cow’s milk consumption and height. Putting the results into context, Ms. Morency explained that a 3-year-old child typically drinking 3 cups of non-cow’s milk each day (about twice the average in this study) would be 1.5 cm shorter than a similar child drinking the same amount of cow’s milk each day.
The literature shows that height children achieve during childhood is an important benchmark of growth and development, adequate nutrition, and pending obesity. Shorter-than average children can often be shorter than average in height as adults, which has been linked with increased risk of type 2 diabetes, gestational diabetes, coronary heart disease, and hypertension.
Diet influences height: Reduced calories and nutrients in an inadequate diet hinder growth, Ms. Morency noted. Cow’s milk delivers more protein, fat, vitamins, minerals, and calories than do non-cow’s milk formulations, such as almond milk and soy milk, she said.
“While non-cow’s milk consumption in childhood may have other health benefits, increased height does not appear to be one of them,” said Ms. Morency.
Study strengths include the relatively large sample size, statistical rigor, and consistent findings with prior studies. Limitations include the cross-sectional design that rules out any conclusions about direct cause, and the use of questionnaire data, which inherently comes with problems of report and recall bias.
A causal connection awaits randomized controlled trials.
The University of Toronto sponsored the study, which was funded by the Canadian Institutes for Health Research. Ms. Morency reported having no financial disclosures.
SAN FRANCISCO – Consumption of non-cow’s milk in early childhood is associated with decreased height, compared with consumption of cow’s milk by children in the same stage of life, a study has shown. The results call into question perceived health benefits of the consumption of non-cow’s milk in childhood.
“These findings are important for health care workers and parents in terms of optimal growth of children and the kind of milk needed to achieve that,” presenter Marie-Elssa Morency explained at the meeting of the Pediatric Academic Societies. Ms. Morency is a master’s student in the department of nutritional sciences at the University of Toronto.
Whether cow’s milk is a better source than non-cow’s milk of nutritional and caloric energy to a growing body has not been studied with rigor. Perceived health benefits of non-cow’s milk have led some parents to substitute cow’s milk with other types of milk for their children, Ms. Morency said.
To gain some clarity, the researchers looked at data from the TARGetKids! longitudinal cohort of children. The cohort is being followed into adolescence to link early life exposures to various physiological and developmental health problems. The present study looked at more than 5,000 healthy children aged 24-72 months. Any conditions that could affect growth were grounds for exclusion.
The primary exposure was the daily consumption of cow’s milk in 4,632 children or non-cow’s milk in 643 children. The typical number of 250-mL glasses of milk consumed per day was gleaned by a questionnaire completed by the parents. The primary outcome was height-for-age z score.
The two groups were similar at baseline in age, sex (slightly more than half were male), body mass index, and maternal height. Those who predominantly consumed cow’s milk averaged 2 cups per day. Some also consumed non-cow’s milk (about one glass per day). Those in the non-cow’s milk group consumed on average 1.4 cups per day, with cow’s milk consumption being rare.
The overall z-score was 0.1 (95% confidence interval [CI], –0.6 to 0.8). The groups differed in z-score, with a score of 0.2 (95% CI, –0.6 to 0.8) in the cow’s milk group and –0.04 (95% CI, –0.8 to 0.7) in the non-cow’s milk group. The resulting shorter height in those consuming non-cow’s milk was 0.42 cm (95% CI, –0.61 to –0.19) in a univariate analysis (P less than .001). A multivariate analysis that adjusted for age, sex, maternal ethnicity, maternal height, z-score, and neighborhood income revealed a significant difference in the same group of 0.31 cm (95% CI, –0.50 to –0.11; P less than .001).
The reduced consumption of cow’s milk in the non-cow’s milk group was identified as a partial mediator of the association between non-cow’s milk consumption and height. Putting the results into context, Ms. Morency explained that a 3-year-old child typically drinking 3 cups of non-cow’s milk each day (about twice the average in this study) would be 1.5 cm shorter than a similar child drinking the same amount of cow’s milk each day.
The literature shows that height children achieve during childhood is an important benchmark of growth and development, adequate nutrition, and pending obesity. Shorter-than average children can often be shorter than average in height as adults, which has been linked with increased risk of type 2 diabetes, gestational diabetes, coronary heart disease, and hypertension.
Diet influences height: Reduced calories and nutrients in an inadequate diet hinder growth, Ms. Morency noted. Cow’s milk delivers more protein, fat, vitamins, minerals, and calories than do non-cow’s milk formulations, such as almond milk and soy milk, she said.
“While non-cow’s milk consumption in childhood may have other health benefits, increased height does not appear to be one of them,” said Ms. Morency.
Study strengths include the relatively large sample size, statistical rigor, and consistent findings with prior studies. Limitations include the cross-sectional design that rules out any conclusions about direct cause, and the use of questionnaire data, which inherently comes with problems of report and recall bias.
A causal connection awaits randomized controlled trials.
The University of Toronto sponsored the study, which was funded by the Canadian Institutes for Health Research. Ms. Morency reported having no financial disclosures.
SAN FRANCISCO – Consumption of non-cow’s milk in early childhood is associated with decreased height, compared with consumption of cow’s milk by children in the same stage of life, a study has shown. The results call into question perceived health benefits of the consumption of non-cow’s milk in childhood.
“These findings are important for health care workers and parents in terms of optimal growth of children and the kind of milk needed to achieve that,” presenter Marie-Elssa Morency explained at the meeting of the Pediatric Academic Societies. Ms. Morency is a master’s student in the department of nutritional sciences at the University of Toronto.
Whether cow’s milk is a better source than non-cow’s milk of nutritional and caloric energy to a growing body has not been studied with rigor. Perceived health benefits of non-cow’s milk have led some parents to substitute cow’s milk with other types of milk for their children, Ms. Morency said.
To gain some clarity, the researchers looked at data from the TARGetKids! longitudinal cohort of children. The cohort is being followed into adolescence to link early life exposures to various physiological and developmental health problems. The present study looked at more than 5,000 healthy children aged 24-72 months. Any conditions that could affect growth were grounds for exclusion.
The primary exposure was the daily consumption of cow’s milk in 4,632 children or non-cow’s milk in 643 children. The typical number of 250-mL glasses of milk consumed per day was gleaned by a questionnaire completed by the parents. The primary outcome was height-for-age z score.
The two groups were similar at baseline in age, sex (slightly more than half were male), body mass index, and maternal height. Those who predominantly consumed cow’s milk averaged 2 cups per day. Some also consumed non-cow’s milk (about one glass per day). Those in the non-cow’s milk group consumed on average 1.4 cups per day, with cow’s milk consumption being rare.
The overall z-score was 0.1 (95% confidence interval [CI], –0.6 to 0.8). The groups differed in z-score, with a score of 0.2 (95% CI, –0.6 to 0.8) in the cow’s milk group and –0.04 (95% CI, –0.8 to 0.7) in the non-cow’s milk group. The resulting shorter height in those consuming non-cow’s milk was 0.42 cm (95% CI, –0.61 to –0.19) in a univariate analysis (P less than .001). A multivariate analysis that adjusted for age, sex, maternal ethnicity, maternal height, z-score, and neighborhood income revealed a significant difference in the same group of 0.31 cm (95% CI, –0.50 to –0.11; P less than .001).
The reduced consumption of cow’s milk in the non-cow’s milk group was identified as a partial mediator of the association between non-cow’s milk consumption and height. Putting the results into context, Ms. Morency explained that a 3-year-old child typically drinking 3 cups of non-cow’s milk each day (about twice the average in this study) would be 1.5 cm shorter than a similar child drinking the same amount of cow’s milk each day.
The literature shows that height children achieve during childhood is an important benchmark of growth and development, adequate nutrition, and pending obesity. Shorter-than average children can often be shorter than average in height as adults, which has been linked with increased risk of type 2 diabetes, gestational diabetes, coronary heart disease, and hypertension.
Diet influences height: Reduced calories and nutrients in an inadequate diet hinder growth, Ms. Morency noted. Cow’s milk delivers more protein, fat, vitamins, minerals, and calories than do non-cow’s milk formulations, such as almond milk and soy milk, she said.
“While non-cow’s milk consumption in childhood may have other health benefits, increased height does not appear to be one of them,” said Ms. Morency.
Study strengths include the relatively large sample size, statistical rigor, and consistent findings with prior studies. Limitations include the cross-sectional design that rules out any conclusions about direct cause, and the use of questionnaire data, which inherently comes with problems of report and recall bias.
A causal connection awaits randomized controlled trials.
The University of Toronto sponsored the study, which was funded by the Canadian Institutes for Health Research. Ms. Morency reported having no financial disclosures.
Genomic Testing in the Management of Early-Stage Breast Cancer
From the University of Arizona Cancer Center, Tucson, AZ (Dr. Ehsani), and University of Wisconsin Carbone Cancer Center and School of Medicine and Public Health, Madison, WI (Dr. Wisinski).
Abstract
- Objectives: To describe common genomic tests being used clinically to assess prognosis and guide adjuvant chemotherapy and endocrine therapy decisions for early-stage breast cancer.
- Methods: Case presentation and review of the literature.
- Results: Hormone receptor–positive (HR-positive) breast cancers, which express the estrogen and/or progesterone receptor, account for the majority of breast cancers. Endocrine therapy can be highly effective for patients with these HR-positive tumors, and identification of HR-positive breast cancers that do not require the addition of chemotherapy is critical. Clinicopathological features of the breast cancer, including tumor size, nodal involvement, grading, and HR status, are insufficient in predicting the risk for recurrence or the need for chemotherapy. Furthermore, a portion of HR-positive breast cancers have an ongoing risk for late recurrence, and longer durations of endocrine therapy are being used to reduce this risk.
- Conclusion: There is sufficient evidence for use of genomic testing in early-stage HR-positive breast cancer to aid in chemotherapy recommendations. Further confirmation of genomic assays for prediction of benefit from prolonged endocrine therapy is needed.
Key words: molecular testing; decision aids; HR-positive cancer; recurrence risk; adjuvant chemotherapy; endocrine therapy.
Despite the increase in incidence of breast cancer, breast cancer mortality has decreased over the past several decades. This is likely due to both early detection and advances in systemic therapy. However, with more widespread use of screening mammography, there are increasing concerns regarding potential overdiagnosis of cancer [1]. One key challenge is that breast cancer is a heterogeneous disease. Thus, improved tools for determining breast cancer biology can help physicians individualize treatments, with low-risk cancers approached with less aggressive treatments, thus preventing unnecessary toxicities, and higher-risk cancers treated appropriately.
Traditionally, adjuvant chemotherapy was recommended based on tumor features such as stage (tumor size, regional nodal involvement), grade, expression of hormone receptors (estrogen receptor [ER] and progesterone receptor [PR]) and human epidermal growth factor receptor-2 (HER2), and patient features (age, menopausal status). However, this approach is not accurate enough to guide individualized treatment recommendations, which are based on the risk for recurrence and the reduction in this risk that can be achieved with various systemic treatments. In particular, there are individuals with low-risk HR-positive, HER2-negative breast cancers who could be spared the toxicities of cytotoxic chemotherapies without compromising the prognosis.
Beyond chemotherapy, endocrine therapies also have risks, especially when given for extended durations. Recently, extended endocrine therapy has been shown to prevent late recurrences of HR-positive breast cancers. In the MA.17R study, extended endocrine therapy with letrozole for a total of 10 years (beyond 5 years of an aromatase inhibitor [AI]) decreased the risk for breast cancer recurrence or the occurrence of contralateral breast cancer by 34% [2]. However, the overall survival was similar between the 2 groups and the results were not confirmed in other studies [3–5]. Identifying the subgroup of patients who benefit from this extended AI therapy is important in the era of personalized medicine. Several tumor genomic assays have been developed to provide additional prognostic and predictive information with the goal of individualizing adjuvant therapies for breast cancer. Although assays are also being evaluated in HER2-positive and triple negative breast cancer, this review will focus on HR-positive, HER2-negative breast cancer.
Case Study
Initial Presentation
A 54-year-old postmenopausal woman with no significant past medical history presents with an abnormal screening mammogram, which shows a focal asymmetry in the 10 o’clock position at middle depth of the left breast. Further work-up with a diagnostic mammogram and ultrasound of the left breast shows a suspicious hypoechoic solid mass with irregular margins measuring 17 mm. The patient undergoes an ultrasound-guided core needle biopsy of the suspicious mass, the results of which are consistent with an invasive ductal carcinoma, Nottingham grade 2, ER strongly positive (95%), PR weakly positive (5%), HER2 negative, and Ki-67 of 15%. She undergoes a left partial mastectomy and sentinel lymph node biopsy, with final pathology demonstrating a single focus of invasive ductal carcinoma, measuring 2.2 cm in greatest dimension with no evidence of lymphovascular invasion. Margins are clear and 2 sentinel lymph nodes are negative for metastatic disease (final pathologic stage IIA, pT2 pN0 cM0). She is referred to medical oncology to discuss adjuvant systemic therapy.
Can additional testing be used to determine prognosis and guide systemic therapy rec-ommendations for early-stage HR-positive/HER2-negative breast cancer?
After a diagnosis of early-stage breast cancer, the key clinical question faced by the patient and medical oncologist is: what is the individual’s risk for a metastatic breast cancer recurrence and thus the risk for death due to breast cancer? Once the risk for recurrence is established, systemic adjuvant chemotherapy, endocrine therapy, and/or HER2-directed therapy are considered based on the receptor status (ER/PR and HER2) to reduce this risk. Hormone receptor (HR)–positive, HER2-negative breast cancer is the most common type of breast cancer. Although adjuvant endocrine therapy has significantly reduced the risk for recurrence and improved survival for HR-positive breast cancer [6], the role of adjuvant chemotherapy for this subset of breast cancer remains unclear. Prior to genomic testing, the recommendation for adjuvant chemotherapy for HR-positive/HER2-negative tumors was primarily based on patient age and tumor stage and grade. However, chemotherapy overtreatment remained a concern given the potential short- and long-term risks of chemotherapy. Further studies into HR-positive/HER2-negative tumors have shown that these tumors can be divided into 2 main subtypes, luminal A and luminal B [7]. These subtypes represent unique biology and differ in terms of prognosis and response to endocrine therapy and chemotherapy. Luminal A tumors are strongly endocrine responsive and have a good prognosis, while luminal B tumors are less endocrine responsive and are associated with a poorer prognosis; the addition of adjuvant chemotherapy is often considered for luminal B tumors [8]. Several tests, including tumor genomic assays, are now available to help with delineating the tumor subtype and aid in decision-making regarding adjuvant chemotherapy for HR-positive/HER2-negative breast cancers.
Tests for Guiding Adjuvant Chemotherapy Decisions
Ki-67 Assays, Including IHC4 and PEPI
Chronic proliferation is a hallmark of cancer cells [9]. Ki-67, a nuclear nonhistone protein whose expression varies in intensity throughout the cell cycle, has been used as a measurement of tumor cell proliferation [10]. Two large meta-analyses have demonstrated that high Ki-67 expression in breast tumors is independently associated with worse disease-free and overall survival rates [11,12]. Ki-67 expression has also been used to classify HR-positive tumors as luminal A or B. After classifying tumor subtypes based on intrinsic gene expression profiling, Cheang et al determined that a Ki-67 cut point of 13.25% differentiated luminal A and B tumors [13]. However, the ideal cut point for Ki-67 remains unclear, as the sensitivity and specificity in this study was 77% and 78%, respectively. Others have combined Ki-67 with standard ER, PR, and HER2 testing. This IHC4 score, which weighs each of these variables, was validated in postmenopausal patients from the ATAC (Arimidex, Tamoxifen, Alone or in Combination) trial who had ER-positive tumors and did not receive chemotherapy [14]. The prognostic information from the IHC4 was similar to that seen with the 21-gene recurrence score (Oncotype DX), which is discussed later in this article. The key challenge with Ki-67 testing currently is the lack of a validated test methodology, and intraobserver variability in interpreting the Ki-67 results [15]. Recent series have suggested that Ki-67 be considered as a continuous marker rather than a set cut point [16]. These issues continue to impact the clinical utility of Ki-67 for decision making for adjuvant chemotherapy.
Ki-67 and the preoperative endocrine prognostic index (PEPI) score have been explored in the neoadjuvant setting to separate postmenopausal women with endocrine-sensitive versus intrinsically resistant disease and identify patients at risk for recurrent disease [17]. The on-treatment levels of Ki-67 in response to endocrine therapy have been shown to be more prognostic than baseline values, and a decrease in Ki-67 as early as 2 weeks after initiation of neoadjuvant endocrine therapy is associated with endocrine-sensitive tumors and improved outcome. The PEPI score was developed through retrospective analysis of the P024 trial [18] to evaluate the relationship between post-neoadjuvant endocrine therapy tumor characteristics and risk for early relapse. This was subsequently validated in an independent data set from the IMPACT trial [19]. Patients with low pathological stage (0 or 1) and a favorable biomarker profile (PEPI score 0) at surgery had the best prognosis in the absence of chemotherapy. On the other hand, higher pathological stage at surgery and a poor biomarker profile with loss of ER positivity or persistently elevated Ki-67 (PEPI score of 3) identified de novo endocrine-resistant tumors which are at higher risk for early relapse [20]. The ongoing Alliance A011106 ALTERNATE trial (ALTernate approaches for clinical stage II or III Estrogen Receptor positive breast cancer NeoAdjuvant TrEatment in postmenopausal women, NCT01953588) is a phase 3 study to prospectively test this hypothesis.
21-Gene Recurrence Score (Oncotype DX Assay)
The 21-gene Oncotype DX assay is conducted on paraffin-embedded tumor tissue and measures the expression of 16 cancer-related genes and 5 reference genes using quantitative polymerase chain reaction. The genes included in this assay are mainly related to proliferation (including Ki-67), invasion, and HER2 or estrogen signaling [21]. Originally, the 21-gene recurrence score assay was analyzed as a prognostic biomarker tool in a prospective-retrospective biomarker substudy of the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-14 clinical trial in which patients with node-negative, ER-positive tumors were randomly assigned to receive tamoxifen or placebo without chemotherapy [22]. Using the standard reported values of low risk (< 18), intermediate risk (18–30), or high risk (≥ 31) for recurrence, among the tamoxifen-treated patients, cancers with a high-risk recurrence score had a significantly worse rate of distant recurrence and overall survival [21]. Inferior breast cancer survival with a high recurrence score was also confirmed in other series of endocrine-treated patients with node-negative and node-positive disease [23–25].
The predictive utility of the 21-gene recurrence score for endocrine therapy has also been evaluated. A comparison of the placebo- and tamoxifen-treated patients from the NSABP B-14 trial demonstrated that the 21-gene recurrence score predicted benefit from tamoxifen in cancers with low- or intermediate-risk recurrence scores [26]. However, there was no benefit from the use of tamoxifen over placebo in cancers with high-risk recurrence scores. To date, this intriguing data has not been prospectively confirmed, and thus the 21-gene recurrence score is not used to avoid endocrine therapy.
The 21-gene recurrence score is primarily used by oncologists to aid in decision-making regarding adjuvant chemotherapy in patients with node-negative and node-positive (with up to 3 positive lymph nodes), HR-positive/HER2-negative breast cancers. The predictive utility of the 21-gene recurrence score for adjuvant chemotherapy was initially tested using tumor samples from the NSABP B-20 study. This study initially compared adjuvant tamoxifen alone with tamoxifen plus chemotherapy in patients with node-negative, HR-positive tumors. The prospective-retrospective biomarker analysis showed that the patients with high-risk 21-gene recurrence scores benefited from the addition of chemotherapy, whereas those with low- or intermediate-risk did not have an improved freedom from distant recurrence with chemotherapy [27]. Similarly, an analysis from the prospective phase 3 Southwest Oncology Group (SWOG) 8814 trial comparing tamoxifen to tamoxifen with chemotherapy showed that for node-positive tumors, chemotherapy benefit was only seen in those with high 21-gene recurrence scores [24].
Prospective studies are now starting to report results regarding the predictive role of the 21-gene recurrence score. The TAILORx (Trial Assigning Individualized Options for Treatment) trial includes women with node-negative, HR-positive and HER2-negative tumors measuring 0.6 to 5 cm. All patients were treated with standard of care endocrine therapy for at least 5 years. Chemotherapy was determined based on the 21-gene recurrence score results on the primary tumor. The 21-gene recurrence score cutoffs were changed to low (0–10), intermediate (11–25), and high (≥ 26). Patients with scores of 26 or higher were treated with chemotherapy, and those with intermediate scores were randomly assigned to hemotherapy or no chemotherapy; results from this cohort are still pending. However, excellent breast cancer outcomes with endocrine therapy alone were reported from the 1626 (15.9% of total cohort) prospectively followed patients with low-recurrence score tumors. The 5-year invasive disease-free survival was 93.8%, with overall survival of 98% [28]. Given that 5 years is appropriate follow-up to see any chemotherapy benefit, this data supports the recommendation for no chemotherapy in this cohort of patients with very low 21-gene recurrence scores.
The RxPONDER (Rx for Positive Node, Endocrine Responsive Breast Cancer) trial is evaluating women with 1 to 3 node-positive, HR-positive, HER2-negative tumors. In this trial, patients with 21-gene recurrence scores of 0 to 25 were assigned to adjuvant chemotherapy or none. Those with scores of 26 or higher were assigned to chemotherapy. All patients received standard adjuvant endocrine therapy. This study has completed accrual and results are pending. Of note, TAILORx and RxPONDER did not investigate the potential lack of benefit of endocrine therapy in cancers with high recurrence scores. Furthermore, despite data suggesting that chemotherapy may not even benefit women with 4 or more nodes involved but who have a low recurrence score [24], due to the lack of prospective data in this cohort and the quite high risk for distant recurrence, chemotherapy continues to be the standard of care for these patients.
PAM50 (Breast Cancer Prognostic Gene Signature)
Using microarray and quantitative reverse transcriptase PCR (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tissues, the Breast Cancer Prognostic Gene Signature (PAM50) assay was initially developed to identify intrinsic breast cancer subtypes, including luminal A, luminal B, HER2-enriched, and basal-like [7,29]. Based on the prediction analysis of microarray (PAM) method, the assay measures the expression levels of 50 genes, provides a risk category (low, intermediate, and high), and generates a numerical risk of recurrence score (ROR). The intrinsic subtype and ROR have been shown to add significant prognostic value to the clinicopathological characteristics of tumors. Clinical validity of PAM50 was evaluated in postmenopausal women with HR-positive, early-stage breast cancer treated in the prospective ATAC and ABCSG-8 (Austrian Breast and Colorectal Cancer Study Group 8) trials [30,31]. In 1017 patients with ER-positive breast cancer treated with anastrozole or tamoxifen in the ATAC trial, ROR added significant prognostic information beyond the clinical treatment score (integrated prognostic information from nodal status, tumor size, histopathologic grade, age, and anastrozole or tamoxifen treatment) in all patients. Also, compared with the 21-gene recurrence score, ROR provided more prognostic information in ER-positive, node-negative disease and better differentiation of intermediate- and higher-risk groups. Fewer patients were categorized as intermediate risk by ROR and more as high risk, which could reduce the uncertainty in the estimate of clinical benefit from chemotherapy [30]. The clinical utility of PAM50 as a prognostic model was also validated in 1478 postmenopausal women with ER-positive early-stage breast cancer enrolled in the ABCSG-8 trial. In this study, ROR assigned 47% of patients with node-negative disease to the low-risk category. In this low-risk group, the 10-year metastasis risk was less than 3.5 %, indicating lack of benefit from additional chemotherapy [31]. A key limitation of the PAM50 is the lack of any prospective studies with this assay.
PAM50 has been designed to be carried out in any qualified pathology laboratory. Moreover, the ROR score provides additional prognostic information about risk of late recurrence, which will be discussed in the next section.
70-Gene Breast Cancer Recurrence Assay (MammaPrint)
MammaPrint is a 70-gene assay that was initially developed using an unsupervised, hierarchical clustering algorithm on whole-genome expression arrays with early-stage breast cancer. Among 295 consecutive patients who had MammaPrint testing, those classified with a good-prognosis tumor signature (n = 115) had an excellent 10-year survival rate (94.5%) compared to those with a poor-prognosis signature (54.5%), and the signature remained prognostic upon multivariate analysis [32]. Subsequently, a pooled analysis comparing outcomes by MammaPrint score in patients with node-negative or 1 to 3 node-positive breast cancers treated as per discretion of their medical team with either adjuvant chemotherapy plus endocrine therapy or endocrine therapy alone reported that only those patients with a high-risk score benefited from chemotherapy [33]. Recently, a prospective phase 3 study (MINDACT [Microarray In Node negative Disease may Avoid ChemoTherapy]) evaluating the utility of MammaPrint for adjuvant chemotherapy decision-making reported results [34]. In this study, 6693 women with early-stage breast cancer were assessed by clinical risk and genomic risk using MammaPrint. Those with low clinical and genomic risk did not receive chemotherapy, while those with high clinical and genomic risk all received chemotherapy. The primary goal of the study was to assess whether forgoing chemotherapy would be associated with a low rate of recurrence in those patients with a low-risk prognostic MammaPrint signature but high clinical risk. A total of 1550 patients (23.2%) were in the discordant group, and the majority of these patients had HR-positive disease (98.1%). Without chemotherapy, the rate of survival without distant metastasis at 5 years in this group was 94.7% (95% confidence interval [CI] 92.5% to 96.2%), which met the primary endpoint. Of note, initially, MammaPrint was only available for fresh tissue analysis, but recent advances in RNA processing now allow for this analysis on FFPE tissue [35].
Summary
Case Continued
The patient undergoes 21-gene recurrence score testing, which shows a low recurrence score of 10, estimating the 10-year risk of distant recurrence to be approximately 7% with 5 years of tamoxifen. Chemo-therapy is not recommended. The patient completes adjuvant whole breast radiation therapy, and then, based on data supporting AIs over tamoxifen in postmenopausal women, she is started on anastrozole [36]. She initially experiences mild side effects from treatment, including fatigue, arthralgia, and vaginal dryness, but her symptoms are able to be managed. As she approaches 5 years of adjuvant endocrine therapy with anastrozole, she is struggling with rotator cuff injury and is anxious about recurrence, but has no evidence of recurrent cancer. Her bone density scan in the beginning of her fourth year of therapy shows a decrease in bone mineral density, with the lowest T score of –1.5 at the left femoral neck, consistent with osteopenia. She has been treated with calcium and vitamin D supplements.
How long should this patient continue treatment with anastrozole?
The risk for recurrence is highest during the first 5 years after diagnosis for all patients with early breast cancer [37]. Although HR-positive breast cancers have a better prognosis than HR-negative disease, the pattern of recurrence is different between the 2 groups, and it is estimated that approximately half of the recurrences among patients with HR-positive early breast cancer occur after the first 5 years from diagnosis. Annualized hazard of recurrence in HR-positive breast cancer has been shown to remain elevated and fairly stable beyond 10 years, even for those with low tumor burden and node-negative disease [38]. Prospective trials showed that for women with HR-positive early breast cancer, 5 years of adjuvant tamoxifen could substantially reduce recurrence rates and improve survival, and this became the standard of care [39]. AIs are considered the standard of care for adjuvant endocrine therapy in most postmenopausal women, as they result in a significantly lower recurrence rate compared with tamoxifen, either as initial adjuvant therapy or sequentially following 2 to 3 years of tamoxifen [40].
However, extending AI therapy from 5 years to 10 years is not clearly beneficial. In the MA.17R trial, although longer AI therapy resulted in significantly better disease-free survival (95% versus 91%, hazard ratio 0.66; P = 0.01), this was primarily due to a lower incidence of contralateral breast cancer in those taking the AI compared with placebo. The distant recurrence risks were similar and low (4.4% versus 5.5%), and there was no overall survival difference [2]. Also, the NSABP B-42 study, which was presented at the 2016 San Antonio Breast Cancer Symposium, did not meet its predefined endpoint for benefit from extending adjuvant AI therapy with letrozole beyond 5 years [3]. Thus, the absolute benefit from extended endocrine therapy has been modest across these studies. Although endocrine therapy is considered relatively safe and well tolerated, side effects can be significant and even associated with morbidity. Ideally, extended endocrine therapy should be offered to the subset of patients who would benefit the most. Several genomic diagnostic assays, including the EndoPredict test, PAM50, and the Breast Cancer Index (BCI) tests, specifically assess the risk for late recurrence in HR-positive cancers.
Tests for Assessing Risk for Late Recurrence
PAM50
Studies suggest that the ROR score also has value in predicting late recurrences. Analysis of data in patients enrolled in the ABCSG-8 trial showed that ROR could identify patients with endocrine-sensitive disease who are at low risk for late relapse and could be spared from unwanted toxicities of extended endocrine therapies. In 1246 ABCSG-8 patients between years 5 and 15, the PAM50 ROR demonstrated an absolute risk of distant recurrence of 2.4% in the low-risk group, as compared with 17.5% in the high-risk group [44]. Also, a combined analysis of patients from both the ATAC and ABCSG-8 trials demonstrated the utility of ROR in identifying this subgroup of patients with low risk for late relapse [45].
EndoPredict
EndoPredict (EP) is another quantitative RT-PCR–based assay which uses FFPE tissues to calculate a risk score based on 8 cancer-related and 3 reference genes. The score is combined with clinicopathological factors including tumor size and nodal status to make a comprehensive risk score (EPclin). EPclin is used to dichotomize patients into EP low- and EP high-risk groups. EP has been validated in 2 cohorts of patients enrolled in separate randomized studies, ABCSG-6 and ABCSG-8. EP provided prognostic information beyond clinicopathological variables to predict distant recurrence in patients with HR-positive, HER2-negative early breast cancer [46]. More important, EP has been shown to predict early (years 0–5) versus late (> 5 years after diagnosis) recurrences and identify a low-risk subset of patients who would not be expected to benefit from further treatment beyond 5 years of endocrine therapy [47]. Recently, EP and EPclin were compared with the 21-gene (Oncotype DX) recurrence score in a patient population from the TransATAC study. Both EP and EPclin provided more prognostic information compared to the 21-gene recurrence score and identified early and late relapse events [48]. EndoPredict is the first multigene expression assay that could be routinely performed in decentral molecular pathological laboratories with a short turnaround time [49].
Breast Cancer Index
The BCI is a RT-PCR–based gene expression assay that consists of 2 gene expression biomarkers: molecular grade index (MGI) and HOXB13/IL17BR (H/I). The BCI was developed as a prognostic test to assess risk for breast cancer recurrence using a cohort of ER-positive patients (n = 588) treated with adjuvant tamoxifen versus observation from the prospective randomized Stockholm trial [50]. In this blinded retrospective study, H/I and MGI were measured and a continuous risk model (BCI) was developed in the tamoxifen-treated group. More than 50% of the patients in this group were classified as having a low risk of recurrence. The rate of distant recurrence or death in this low-risk group at 10 years was less than 3%. The performance of the BCI model was then tested in the untreated arm of the Stockholm trial. In the untreated arm, BCI classified 53%, 27%, and 20% of patients as low, intermediate, and high risk, respectively. The rate of distant metastasis at 10 years in these risk groups was 8.3% (95% CI 4.7% to 14.4%), 22.9% (95% CI 14.5% to 35.2%), and 28.5% (95% CI 17.9% to 43.6%), respectively, and the rate of breast cancer–specific mortality was 5.1% (95% CI 1.3% to 8.7%), 19.8% (95% CI 10.0% to 28.6%), and 28.8% (95% CI 15.3% to 40.2%) [50].
The prognostic and predictive values of the BCI have been validated in other large, randomized studies and in patients with both node-negative and node-positive disease [51,52]. The predictive value of the endocrine-response biomarker, the H/I ratio, has been demonstrated in randomized studies. In the MA.17 trial, a high H/I ratio was associated with increased risk for late recurrence in the absence of letrozole. However, extended endocrine therapy with letrozole in patients with high H/I ratios predicted benefit from therapy and decreased the probability of late disease recurrence [53]. BCI was also compared to IHC4 and the 21-gene recurrence score in the TransATAC study and was the only test to show prognostic significance for both early (0–5 years) and late (5–10 year) recurrence [54].
The impact of the BCI results on physicians’ recommendations for extended endocrine therapy was assessed by a prospective study. This study showed that the test result had a significant effect on both physician treatment recommendation and patient satisfaction. BCI testing resulted in a change in physician recommendations for extended endocrine therapy, with an overall decrease in recommendations for extended endocrine therapy from 74% to 54%. Knowledge of the test result also led to improved patient satisfaction and decreased anxiety [55].
Summary
Due to the risk for late recurrence, extended endocrine therapy is being recommended for many patients with HR-positive breast cancers. Multiple genomic assays are being developed to better understand an individual’s risk for late recurrence and the potential for benefit from extended endocrine therapies. However, none of the assays have been validated in prospective randomized studies. Further validation is needed prior to routine use of these assays.
Case Continued
A BCI test is done and the result shows 4.3% BCI low-risk category in years 5–10; low likelihood of benefit from extended endocrine therapy. After discussing the results of the BCI test in the context of no survival benefit from extending AIs beyond 5 years, both the patient and her oncologist feel comfortable with discontinuing endocrine therapy at the end of 5 years.
Conclusion
Reduction in breast cancer mortality is mainly the result of improved systemic treatments. With advances in breast cancer screening tools in recent years, the rate of cancer detection has increased. This has raised concerns regarding overdiagnosis. To prevent unwanted toxicities associated with overtreatment, better treatment decision tools are needed. Several genomic assays are currently available and widely used to provide prognostic and predictive information and aid in decisions regarding appropriate use of adjuvant chemotherapy in HR-positive/HER2-negative early-stage breast cancer. Ongoing studies are refining the cutoffs for these assays and expanding the applicability to node-positive breast cancers. Furthermore, with several studies now showing benefit from the use of extended endocrine therapy, some of these assays may be able to identify the subset of patients who are at increased risk for late recurrence and who might benefit from extended endocrine therapy. Advances in molecular testing has enabled clinicians to offer more personalized treatments to their patients, improve patient’s compliance, and decrease anxiety and conflict associated with management decisions. Although small numbers of patients with HER2-positive and triple negative breast cancers were also included in some of these studies, use of genomic assays in this subset of patients is very limited and currently not recommended.
Corresponding author: Kari Braun Wisinski, MD, 1111 Highland Avenue, 6033 Wisconsin Institute for Medical Research, Madison, WI 53705-2275, kbwisinski@medicine.wisc.edu.
Financial disclosures: This work was supported by the NCI Cancer Center Support Grant P30 CA014520.
1. Welch HG, Prorok PC, O'Malley AJ, Kramer BS. Breast-cancer tumor size, overdiagnosis, and mammography screening effectiveness. N Engl J Med 2016;375:1438–47.
2. Goss PE, Ingle JN, Pritchard KI, et al. Extending aromatase-inhibitor adjuvant therapy to 10 years. N Engl J Med 2016;375:209–19.
3. Mamounas E, Bandos H, Lembersky B. A randomized, double-blinded, placebo-controlled clinical trial of extended adjuvant endocrine therapy with letrozole in postmenopausal women with hormone-receptor-positive breast cancer who have completed previous adjuvant treatment with an aromatase inhibitor. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-05.
4. Tjan-Heijnen VC, Van Hellemond IE, Peer PG, et al: First results from the multicenter phase III DATA study comparing 3 versus 6 years of anastrozole after 2-3 years of tamoxifen in postmenopausal women with hormone receptor-positive early breast cancer. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-03.
5. Blok EJ, Van de Velde CJH, Meershoek-Klein Kranenbarg EM, et al: Optimal duration of extended letrozole treatment after 5 years of adjuvant endocrine therapy. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-04.
6. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group. Lancet 2005;365:1687–717.
7. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747–52.
8. Coates AS, Winer EP, Goldhirsch A, et al. Tailoring therapies--improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol 2015;26:1533–46.
9. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000;100:57–70.
10. Urruticoechea A, Smith IE, Dowsett M. Proliferation marker Ki-67 in early breast cancer. J Clin Oncol 2005;23:7212–20.
11. de Azambuja E, Cardoso F, de Castro G Jr, et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer 2007;96:1504–13.
12. Petrelli F, Viale G, Cabiddu M, Barni S. Prognostic value of different cut-off levels of Ki-67 in breast cancer: a systematic review and meta-analysis of 64,196 patients. Breast Cancer Res Treat 2015;153:477–91.
13. Cheang MC, Chia SK, Voduc D, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 2009;101:736–50.
14. Cuzick J, Dowsett M, Pineda S, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and com-parison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol 2011;29:4273–8.
15. Pathmanathan N, Balleine RL. Ki67 and proliferation in breast cancer. J Clin Pathol 2013;66:512–6.
16. Denkert C, Budczies J, von Minckwitz G, et al. Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast 2015; 24 Suppl 2:S67–72.
17. Ma CX, Bose R, Ellis MJ. Prognostic and predictive biomarkers of endocrine responsiveness for estrogen receptor positive breast cancer. Adv Exp Med Biol 2016;882:125–54.
18. Eiermann W, Paepke S, Appfelstaedt J, et al. Preoperative treatment of postmenopausal breast cancer patients with letrozole: a randomized double-blind multicenter study. Ann Oncol 2001;12:1527–32.
19. Smith IE, Dowsett M, Ebbs SR, et al. Neoadjuvant treatment of postmenopausal breast cancer with anastrozole, tamoxifen, or both in combination: the Immediate Preoperative Anas-trozole, Tamoxifen, or Combined with Tamoxifen (IMPACT) multicenter double-blind randomized trial. J Clin Oncol 2005;23:5108–16.
20. Ellis MJ, Tao Y, Luo J, et al. Outcome prediction for estrogen receptor-positive breast cancer based on postneoadjuvant endocrine therapy tumor characteristics. J Natl Cancer Inst 2008;100:1380–8.
21. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351:2817–26.
22. Fisher B, Jeong JH, Bryant J, et al. Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 2004;364:858–68.
23. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 2006;8:R25.
24. Albain KS, Barlow WE, Shak S, et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol 2010;11:55–65.
25. Dowsett M, Cuzick J, Wale C, et al. Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study. J Clin Oncol 2010;28:1829–34.
26. Paik S, Shak S, Tang G, et al. Expression of the 21 genes in the recurrence score assay and tamoxifen clinical benefit in the NSABP study B-14 of node negative, estrogen receptor positive breast cancer. J Clin Oncol 2005;23: suppl:510.
27. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol2006;24:3726–34.
28. Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 2015;373:2005–14.
29. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009;27:1160–7.
30. Dowsett M, Sestak I, Lopez-Knowles E, et al. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 2013;31:2783–90.
31. Gnant M, Filipits M, Greil R, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 post-menopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol 2014;25:339–45.
32. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347:1999–2009.
33. Knauer M, Mook S, Rutgers EJ, et al. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat 2010;120:655–61.
34. Cardoso F, van't Veer LJ, Bogaerts J, et al. 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med 2016;375:717–29.
35. Sapino A, Roepman P, Linn SC, et al. MammaPrint molecular diagnostics on formalin-fixed, paraffin-embedded tissue. J Mol Diagn 2014;16:190–7.
36. Burstein HJ, Griggs JJ, Prestrud AA, Temin S. American society of clinical oncology clinical practice guideline update on adjuvant endocrine therapy for women with hormone receptor-positive breast cancer. J Oncol Pract 2010;6:243–6.
37. Saphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol 1996;14:2738–46.
38. Colleoni M, Sun Z, Price KN, et al. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the International Breast Cancer Study Group Trials I to V. J Clin Oncol 2016;34:927–35.
39. Davies C, Godwin J, Gray R, et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet 2011;378:771–84.
40. Dowsett M, Forbes JF, Bradley R, et al. Aromatase inhibitors versus tamoxifen in early breast cancer: patient-level meta-analysis of the randomised trials. Lancet 2015;386:1341–52.
41. Davies C, Pan H, Godwin J, et al. Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years after diagnosis of oestrogen receptor-positive breast cancer: ATLAS, a randomised trial. Lancet 2013;381:805–16.
42. Gray R, Rea D, Handley K, et al. aTTom: Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years in 6,953 women with early breast cancer. J Clin Oncol 2013;31 (suppl):5.
43. Goss PE, Ingle JN, Martino S, et al. Randomized trial of letrozole following tamoxifen as extended adjuvant therapy in receptor-positive breast cancer: updated findings from NCIC CTG MA.17. J Natl Can-cer Inst 2005;97:1262–71.
44. Filipits M, Nielsen TO, Rudas M, et al. The PAM50 risk-of-recurrence score predicts risk for late distant recurrence after endocrine therapy in postmenopausal women with endocrine-responsive early breast cancer. Clin Cancer Res 2014;20:1298–305.
45. Sestak I, Cuzick J, Dowsett M, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J Clin Oncol 2015;33:916–22.
46. Filipits M, Rudas M, Jakesz R, et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res 2011;17:6012–20.
47. Dubsky P, Brase JC, Jakesz R, et al. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2- breast cancer patients. Br J Cancer 2013;109:2959–64.
48. Buus R, Sestak I, Kronenwett R, et al. Comparison of EndoPredict and EPclin with Oncotype DX Recurrence Score for prediction of risk of distant recurrence after endocrine therapy. J Natl Cancer Inst 2016;108:djw149.
49. Muller BM, Keil E, Lehmann A, et al. The EndoPredict gene-expression assay in clinical practice - performance and impact on clinical decisions. PLoS One 2013;8:e68252.
50. Jerevall PL, Ma XJ, Li H, et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer 2011;104:1762–9.
51. Sgroi DC, Chapman JA, Badovinac-Crnjevic T, et al. Assessment of the prognostic and predictive utility of the Breast Cancer Index (BCI): an NCIC CTG MA.14 study. Breast Cancer Res 2016;18:1.
52. Zhang Y, Schnabel CA, Schroeder BE, et al. Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence. Clin Cancer Res 2013;19:4196–205.
53. Sgroi DC, Carney E, Zarrella E, et al. Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker. J Natl Cancer Inst 2013;105:1036–42.
54. Sgroi DC, Sestak I, Cuzick J, et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: a prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol 2013;14:1067–76.
55. Sanft T, Aktas B, Schroeder B, et al. Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer. Breast Cancer Res Treat 2015;154:533–41.
56. Nielsen TO, Parker JS, Leung S, et al. A comparison of PAM50 Insrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer. Clin Cancer Res 2010;16:5222–32.
57. Mamounas EP, Jeong JH, Wickerham DL, et al. Benefit from exemestane as extended adjuvant therapy after 5 years of adjuvant tamoxifen: intention-to-treat analysis of the National Surgical Adjuvant Breast And Bowel Project B-33 trial. J Clin Oncol 2008;26:1965–71.
From the University of Arizona Cancer Center, Tucson, AZ (Dr. Ehsani), and University of Wisconsin Carbone Cancer Center and School of Medicine and Public Health, Madison, WI (Dr. Wisinski).
Abstract
- Objectives: To describe common genomic tests being used clinically to assess prognosis and guide adjuvant chemotherapy and endocrine therapy decisions for early-stage breast cancer.
- Methods: Case presentation and review of the literature.
- Results: Hormone receptor–positive (HR-positive) breast cancers, which express the estrogen and/or progesterone receptor, account for the majority of breast cancers. Endocrine therapy can be highly effective for patients with these HR-positive tumors, and identification of HR-positive breast cancers that do not require the addition of chemotherapy is critical. Clinicopathological features of the breast cancer, including tumor size, nodal involvement, grading, and HR status, are insufficient in predicting the risk for recurrence or the need for chemotherapy. Furthermore, a portion of HR-positive breast cancers have an ongoing risk for late recurrence, and longer durations of endocrine therapy are being used to reduce this risk.
- Conclusion: There is sufficient evidence for use of genomic testing in early-stage HR-positive breast cancer to aid in chemotherapy recommendations. Further confirmation of genomic assays for prediction of benefit from prolonged endocrine therapy is needed.
Key words: molecular testing; decision aids; HR-positive cancer; recurrence risk; adjuvant chemotherapy; endocrine therapy.
Despite the increase in incidence of breast cancer, breast cancer mortality has decreased over the past several decades. This is likely due to both early detection and advances in systemic therapy. However, with more widespread use of screening mammography, there are increasing concerns regarding potential overdiagnosis of cancer [1]. One key challenge is that breast cancer is a heterogeneous disease. Thus, improved tools for determining breast cancer biology can help physicians individualize treatments, with low-risk cancers approached with less aggressive treatments, thus preventing unnecessary toxicities, and higher-risk cancers treated appropriately.
Traditionally, adjuvant chemotherapy was recommended based on tumor features such as stage (tumor size, regional nodal involvement), grade, expression of hormone receptors (estrogen receptor [ER] and progesterone receptor [PR]) and human epidermal growth factor receptor-2 (HER2), and patient features (age, menopausal status). However, this approach is not accurate enough to guide individualized treatment recommendations, which are based on the risk for recurrence and the reduction in this risk that can be achieved with various systemic treatments. In particular, there are individuals with low-risk HR-positive, HER2-negative breast cancers who could be spared the toxicities of cytotoxic chemotherapies without compromising the prognosis.
Beyond chemotherapy, endocrine therapies also have risks, especially when given for extended durations. Recently, extended endocrine therapy has been shown to prevent late recurrences of HR-positive breast cancers. In the MA.17R study, extended endocrine therapy with letrozole for a total of 10 years (beyond 5 years of an aromatase inhibitor [AI]) decreased the risk for breast cancer recurrence or the occurrence of contralateral breast cancer by 34% [2]. However, the overall survival was similar between the 2 groups and the results were not confirmed in other studies [3–5]. Identifying the subgroup of patients who benefit from this extended AI therapy is important in the era of personalized medicine. Several tumor genomic assays have been developed to provide additional prognostic and predictive information with the goal of individualizing adjuvant therapies for breast cancer. Although assays are also being evaluated in HER2-positive and triple negative breast cancer, this review will focus on HR-positive, HER2-negative breast cancer.
Case Study
Initial Presentation
A 54-year-old postmenopausal woman with no significant past medical history presents with an abnormal screening mammogram, which shows a focal asymmetry in the 10 o’clock position at middle depth of the left breast. Further work-up with a diagnostic mammogram and ultrasound of the left breast shows a suspicious hypoechoic solid mass with irregular margins measuring 17 mm. The patient undergoes an ultrasound-guided core needle biopsy of the suspicious mass, the results of which are consistent with an invasive ductal carcinoma, Nottingham grade 2, ER strongly positive (95%), PR weakly positive (5%), HER2 negative, and Ki-67 of 15%. She undergoes a left partial mastectomy and sentinel lymph node biopsy, with final pathology demonstrating a single focus of invasive ductal carcinoma, measuring 2.2 cm in greatest dimension with no evidence of lymphovascular invasion. Margins are clear and 2 sentinel lymph nodes are negative for metastatic disease (final pathologic stage IIA, pT2 pN0 cM0). She is referred to medical oncology to discuss adjuvant systemic therapy.
Can additional testing be used to determine prognosis and guide systemic therapy rec-ommendations for early-stage HR-positive/HER2-negative breast cancer?
After a diagnosis of early-stage breast cancer, the key clinical question faced by the patient and medical oncologist is: what is the individual’s risk for a metastatic breast cancer recurrence and thus the risk for death due to breast cancer? Once the risk for recurrence is established, systemic adjuvant chemotherapy, endocrine therapy, and/or HER2-directed therapy are considered based on the receptor status (ER/PR and HER2) to reduce this risk. Hormone receptor (HR)–positive, HER2-negative breast cancer is the most common type of breast cancer. Although adjuvant endocrine therapy has significantly reduced the risk for recurrence and improved survival for HR-positive breast cancer [6], the role of adjuvant chemotherapy for this subset of breast cancer remains unclear. Prior to genomic testing, the recommendation for adjuvant chemotherapy for HR-positive/HER2-negative tumors was primarily based on patient age and tumor stage and grade. However, chemotherapy overtreatment remained a concern given the potential short- and long-term risks of chemotherapy. Further studies into HR-positive/HER2-negative tumors have shown that these tumors can be divided into 2 main subtypes, luminal A and luminal B [7]. These subtypes represent unique biology and differ in terms of prognosis and response to endocrine therapy and chemotherapy. Luminal A tumors are strongly endocrine responsive and have a good prognosis, while luminal B tumors are less endocrine responsive and are associated with a poorer prognosis; the addition of adjuvant chemotherapy is often considered for luminal B tumors [8]. Several tests, including tumor genomic assays, are now available to help with delineating the tumor subtype and aid in decision-making regarding adjuvant chemotherapy for HR-positive/HER2-negative breast cancers.
Tests for Guiding Adjuvant Chemotherapy Decisions
Ki-67 Assays, Including IHC4 and PEPI
Chronic proliferation is a hallmark of cancer cells [9]. Ki-67, a nuclear nonhistone protein whose expression varies in intensity throughout the cell cycle, has been used as a measurement of tumor cell proliferation [10]. Two large meta-analyses have demonstrated that high Ki-67 expression in breast tumors is independently associated with worse disease-free and overall survival rates [11,12]. Ki-67 expression has also been used to classify HR-positive tumors as luminal A or B. After classifying tumor subtypes based on intrinsic gene expression profiling, Cheang et al determined that a Ki-67 cut point of 13.25% differentiated luminal A and B tumors [13]. However, the ideal cut point for Ki-67 remains unclear, as the sensitivity and specificity in this study was 77% and 78%, respectively. Others have combined Ki-67 with standard ER, PR, and HER2 testing. This IHC4 score, which weighs each of these variables, was validated in postmenopausal patients from the ATAC (Arimidex, Tamoxifen, Alone or in Combination) trial who had ER-positive tumors and did not receive chemotherapy [14]. The prognostic information from the IHC4 was similar to that seen with the 21-gene recurrence score (Oncotype DX), which is discussed later in this article. The key challenge with Ki-67 testing currently is the lack of a validated test methodology, and intraobserver variability in interpreting the Ki-67 results [15]. Recent series have suggested that Ki-67 be considered as a continuous marker rather than a set cut point [16]. These issues continue to impact the clinical utility of Ki-67 for decision making for adjuvant chemotherapy.
Ki-67 and the preoperative endocrine prognostic index (PEPI) score have been explored in the neoadjuvant setting to separate postmenopausal women with endocrine-sensitive versus intrinsically resistant disease and identify patients at risk for recurrent disease [17]. The on-treatment levels of Ki-67 in response to endocrine therapy have been shown to be more prognostic than baseline values, and a decrease in Ki-67 as early as 2 weeks after initiation of neoadjuvant endocrine therapy is associated with endocrine-sensitive tumors and improved outcome. The PEPI score was developed through retrospective analysis of the P024 trial [18] to evaluate the relationship between post-neoadjuvant endocrine therapy tumor characteristics and risk for early relapse. This was subsequently validated in an independent data set from the IMPACT trial [19]. Patients with low pathological stage (0 or 1) and a favorable biomarker profile (PEPI score 0) at surgery had the best prognosis in the absence of chemotherapy. On the other hand, higher pathological stage at surgery and a poor biomarker profile with loss of ER positivity or persistently elevated Ki-67 (PEPI score of 3) identified de novo endocrine-resistant tumors which are at higher risk for early relapse [20]. The ongoing Alliance A011106 ALTERNATE trial (ALTernate approaches for clinical stage II or III Estrogen Receptor positive breast cancer NeoAdjuvant TrEatment in postmenopausal women, NCT01953588) is a phase 3 study to prospectively test this hypothesis.
21-Gene Recurrence Score (Oncotype DX Assay)
The 21-gene Oncotype DX assay is conducted on paraffin-embedded tumor tissue and measures the expression of 16 cancer-related genes and 5 reference genes using quantitative polymerase chain reaction. The genes included in this assay are mainly related to proliferation (including Ki-67), invasion, and HER2 or estrogen signaling [21]. Originally, the 21-gene recurrence score assay was analyzed as a prognostic biomarker tool in a prospective-retrospective biomarker substudy of the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-14 clinical trial in which patients with node-negative, ER-positive tumors were randomly assigned to receive tamoxifen or placebo without chemotherapy [22]. Using the standard reported values of low risk (< 18), intermediate risk (18–30), or high risk (≥ 31) for recurrence, among the tamoxifen-treated patients, cancers with a high-risk recurrence score had a significantly worse rate of distant recurrence and overall survival [21]. Inferior breast cancer survival with a high recurrence score was also confirmed in other series of endocrine-treated patients with node-negative and node-positive disease [23–25].
The predictive utility of the 21-gene recurrence score for endocrine therapy has also been evaluated. A comparison of the placebo- and tamoxifen-treated patients from the NSABP B-14 trial demonstrated that the 21-gene recurrence score predicted benefit from tamoxifen in cancers with low- or intermediate-risk recurrence scores [26]. However, there was no benefit from the use of tamoxifen over placebo in cancers with high-risk recurrence scores. To date, this intriguing data has not been prospectively confirmed, and thus the 21-gene recurrence score is not used to avoid endocrine therapy.
The 21-gene recurrence score is primarily used by oncologists to aid in decision-making regarding adjuvant chemotherapy in patients with node-negative and node-positive (with up to 3 positive lymph nodes), HR-positive/HER2-negative breast cancers. The predictive utility of the 21-gene recurrence score for adjuvant chemotherapy was initially tested using tumor samples from the NSABP B-20 study. This study initially compared adjuvant tamoxifen alone with tamoxifen plus chemotherapy in patients with node-negative, HR-positive tumors. The prospective-retrospective biomarker analysis showed that the patients with high-risk 21-gene recurrence scores benefited from the addition of chemotherapy, whereas those with low- or intermediate-risk did not have an improved freedom from distant recurrence with chemotherapy [27]. Similarly, an analysis from the prospective phase 3 Southwest Oncology Group (SWOG) 8814 trial comparing tamoxifen to tamoxifen with chemotherapy showed that for node-positive tumors, chemotherapy benefit was only seen in those with high 21-gene recurrence scores [24].
Prospective studies are now starting to report results regarding the predictive role of the 21-gene recurrence score. The TAILORx (Trial Assigning Individualized Options for Treatment) trial includes women with node-negative, HR-positive and HER2-negative tumors measuring 0.6 to 5 cm. All patients were treated with standard of care endocrine therapy for at least 5 years. Chemotherapy was determined based on the 21-gene recurrence score results on the primary tumor. The 21-gene recurrence score cutoffs were changed to low (0–10), intermediate (11–25), and high (≥ 26). Patients with scores of 26 or higher were treated with chemotherapy, and those with intermediate scores were randomly assigned to hemotherapy or no chemotherapy; results from this cohort are still pending. However, excellent breast cancer outcomes with endocrine therapy alone were reported from the 1626 (15.9% of total cohort) prospectively followed patients with low-recurrence score tumors. The 5-year invasive disease-free survival was 93.8%, with overall survival of 98% [28]. Given that 5 years is appropriate follow-up to see any chemotherapy benefit, this data supports the recommendation for no chemotherapy in this cohort of patients with very low 21-gene recurrence scores.
The RxPONDER (Rx for Positive Node, Endocrine Responsive Breast Cancer) trial is evaluating women with 1 to 3 node-positive, HR-positive, HER2-negative tumors. In this trial, patients with 21-gene recurrence scores of 0 to 25 were assigned to adjuvant chemotherapy or none. Those with scores of 26 or higher were assigned to chemotherapy. All patients received standard adjuvant endocrine therapy. This study has completed accrual and results are pending. Of note, TAILORx and RxPONDER did not investigate the potential lack of benefit of endocrine therapy in cancers with high recurrence scores. Furthermore, despite data suggesting that chemotherapy may not even benefit women with 4 or more nodes involved but who have a low recurrence score [24], due to the lack of prospective data in this cohort and the quite high risk for distant recurrence, chemotherapy continues to be the standard of care for these patients.
PAM50 (Breast Cancer Prognostic Gene Signature)
Using microarray and quantitative reverse transcriptase PCR (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tissues, the Breast Cancer Prognostic Gene Signature (PAM50) assay was initially developed to identify intrinsic breast cancer subtypes, including luminal A, luminal B, HER2-enriched, and basal-like [7,29]. Based on the prediction analysis of microarray (PAM) method, the assay measures the expression levels of 50 genes, provides a risk category (low, intermediate, and high), and generates a numerical risk of recurrence score (ROR). The intrinsic subtype and ROR have been shown to add significant prognostic value to the clinicopathological characteristics of tumors. Clinical validity of PAM50 was evaluated in postmenopausal women with HR-positive, early-stage breast cancer treated in the prospective ATAC and ABCSG-8 (Austrian Breast and Colorectal Cancer Study Group 8) trials [30,31]. In 1017 patients with ER-positive breast cancer treated with anastrozole or tamoxifen in the ATAC trial, ROR added significant prognostic information beyond the clinical treatment score (integrated prognostic information from nodal status, tumor size, histopathologic grade, age, and anastrozole or tamoxifen treatment) in all patients. Also, compared with the 21-gene recurrence score, ROR provided more prognostic information in ER-positive, node-negative disease and better differentiation of intermediate- and higher-risk groups. Fewer patients were categorized as intermediate risk by ROR and more as high risk, which could reduce the uncertainty in the estimate of clinical benefit from chemotherapy [30]. The clinical utility of PAM50 as a prognostic model was also validated in 1478 postmenopausal women with ER-positive early-stage breast cancer enrolled in the ABCSG-8 trial. In this study, ROR assigned 47% of patients with node-negative disease to the low-risk category. In this low-risk group, the 10-year metastasis risk was less than 3.5 %, indicating lack of benefit from additional chemotherapy [31]. A key limitation of the PAM50 is the lack of any prospective studies with this assay.
PAM50 has been designed to be carried out in any qualified pathology laboratory. Moreover, the ROR score provides additional prognostic information about risk of late recurrence, which will be discussed in the next section.
70-Gene Breast Cancer Recurrence Assay (MammaPrint)
MammaPrint is a 70-gene assay that was initially developed using an unsupervised, hierarchical clustering algorithm on whole-genome expression arrays with early-stage breast cancer. Among 295 consecutive patients who had MammaPrint testing, those classified with a good-prognosis tumor signature (n = 115) had an excellent 10-year survival rate (94.5%) compared to those with a poor-prognosis signature (54.5%), and the signature remained prognostic upon multivariate analysis [32]. Subsequently, a pooled analysis comparing outcomes by MammaPrint score in patients with node-negative or 1 to 3 node-positive breast cancers treated as per discretion of their medical team with either adjuvant chemotherapy plus endocrine therapy or endocrine therapy alone reported that only those patients with a high-risk score benefited from chemotherapy [33]. Recently, a prospective phase 3 study (MINDACT [Microarray In Node negative Disease may Avoid ChemoTherapy]) evaluating the utility of MammaPrint for adjuvant chemotherapy decision-making reported results [34]. In this study, 6693 women with early-stage breast cancer were assessed by clinical risk and genomic risk using MammaPrint. Those with low clinical and genomic risk did not receive chemotherapy, while those with high clinical and genomic risk all received chemotherapy. The primary goal of the study was to assess whether forgoing chemotherapy would be associated with a low rate of recurrence in those patients with a low-risk prognostic MammaPrint signature but high clinical risk. A total of 1550 patients (23.2%) were in the discordant group, and the majority of these patients had HR-positive disease (98.1%). Without chemotherapy, the rate of survival without distant metastasis at 5 years in this group was 94.7% (95% confidence interval [CI] 92.5% to 96.2%), which met the primary endpoint. Of note, initially, MammaPrint was only available for fresh tissue analysis, but recent advances in RNA processing now allow for this analysis on FFPE tissue [35].
Summary
Case Continued
The patient undergoes 21-gene recurrence score testing, which shows a low recurrence score of 10, estimating the 10-year risk of distant recurrence to be approximately 7% with 5 years of tamoxifen. Chemo-therapy is not recommended. The patient completes adjuvant whole breast radiation therapy, and then, based on data supporting AIs over tamoxifen in postmenopausal women, she is started on anastrozole [36]. She initially experiences mild side effects from treatment, including fatigue, arthralgia, and vaginal dryness, but her symptoms are able to be managed. As she approaches 5 years of adjuvant endocrine therapy with anastrozole, she is struggling with rotator cuff injury and is anxious about recurrence, but has no evidence of recurrent cancer. Her bone density scan in the beginning of her fourth year of therapy shows a decrease in bone mineral density, with the lowest T score of –1.5 at the left femoral neck, consistent with osteopenia. She has been treated with calcium and vitamin D supplements.
How long should this patient continue treatment with anastrozole?
The risk for recurrence is highest during the first 5 years after diagnosis for all patients with early breast cancer [37]. Although HR-positive breast cancers have a better prognosis than HR-negative disease, the pattern of recurrence is different between the 2 groups, and it is estimated that approximately half of the recurrences among patients with HR-positive early breast cancer occur after the first 5 years from diagnosis. Annualized hazard of recurrence in HR-positive breast cancer has been shown to remain elevated and fairly stable beyond 10 years, even for those with low tumor burden and node-negative disease [38]. Prospective trials showed that for women with HR-positive early breast cancer, 5 years of adjuvant tamoxifen could substantially reduce recurrence rates and improve survival, and this became the standard of care [39]. AIs are considered the standard of care for adjuvant endocrine therapy in most postmenopausal women, as they result in a significantly lower recurrence rate compared with tamoxifen, either as initial adjuvant therapy or sequentially following 2 to 3 years of tamoxifen [40].
However, extending AI therapy from 5 years to 10 years is not clearly beneficial. In the MA.17R trial, although longer AI therapy resulted in significantly better disease-free survival (95% versus 91%, hazard ratio 0.66; P = 0.01), this was primarily due to a lower incidence of contralateral breast cancer in those taking the AI compared with placebo. The distant recurrence risks were similar and low (4.4% versus 5.5%), and there was no overall survival difference [2]. Also, the NSABP B-42 study, which was presented at the 2016 San Antonio Breast Cancer Symposium, did not meet its predefined endpoint for benefit from extending adjuvant AI therapy with letrozole beyond 5 years [3]. Thus, the absolute benefit from extended endocrine therapy has been modest across these studies. Although endocrine therapy is considered relatively safe and well tolerated, side effects can be significant and even associated with morbidity. Ideally, extended endocrine therapy should be offered to the subset of patients who would benefit the most. Several genomic diagnostic assays, including the EndoPredict test, PAM50, and the Breast Cancer Index (BCI) tests, specifically assess the risk for late recurrence in HR-positive cancers.
Tests for Assessing Risk for Late Recurrence
PAM50
Studies suggest that the ROR score also has value in predicting late recurrences. Analysis of data in patients enrolled in the ABCSG-8 trial showed that ROR could identify patients with endocrine-sensitive disease who are at low risk for late relapse and could be spared from unwanted toxicities of extended endocrine therapies. In 1246 ABCSG-8 patients between years 5 and 15, the PAM50 ROR demonstrated an absolute risk of distant recurrence of 2.4% in the low-risk group, as compared with 17.5% in the high-risk group [44]. Also, a combined analysis of patients from both the ATAC and ABCSG-8 trials demonstrated the utility of ROR in identifying this subgroup of patients with low risk for late relapse [45].
EndoPredict
EndoPredict (EP) is another quantitative RT-PCR–based assay which uses FFPE tissues to calculate a risk score based on 8 cancer-related and 3 reference genes. The score is combined with clinicopathological factors including tumor size and nodal status to make a comprehensive risk score (EPclin). EPclin is used to dichotomize patients into EP low- and EP high-risk groups. EP has been validated in 2 cohorts of patients enrolled in separate randomized studies, ABCSG-6 and ABCSG-8. EP provided prognostic information beyond clinicopathological variables to predict distant recurrence in patients with HR-positive, HER2-negative early breast cancer [46]. More important, EP has been shown to predict early (years 0–5) versus late (> 5 years after diagnosis) recurrences and identify a low-risk subset of patients who would not be expected to benefit from further treatment beyond 5 years of endocrine therapy [47]. Recently, EP and EPclin were compared with the 21-gene (Oncotype DX) recurrence score in a patient population from the TransATAC study. Both EP and EPclin provided more prognostic information compared to the 21-gene recurrence score and identified early and late relapse events [48]. EndoPredict is the first multigene expression assay that could be routinely performed in decentral molecular pathological laboratories with a short turnaround time [49].
Breast Cancer Index
The BCI is a RT-PCR–based gene expression assay that consists of 2 gene expression biomarkers: molecular grade index (MGI) and HOXB13/IL17BR (H/I). The BCI was developed as a prognostic test to assess risk for breast cancer recurrence using a cohort of ER-positive patients (n = 588) treated with adjuvant tamoxifen versus observation from the prospective randomized Stockholm trial [50]. In this blinded retrospective study, H/I and MGI were measured and a continuous risk model (BCI) was developed in the tamoxifen-treated group. More than 50% of the patients in this group were classified as having a low risk of recurrence. The rate of distant recurrence or death in this low-risk group at 10 years was less than 3%. The performance of the BCI model was then tested in the untreated arm of the Stockholm trial. In the untreated arm, BCI classified 53%, 27%, and 20% of patients as low, intermediate, and high risk, respectively. The rate of distant metastasis at 10 years in these risk groups was 8.3% (95% CI 4.7% to 14.4%), 22.9% (95% CI 14.5% to 35.2%), and 28.5% (95% CI 17.9% to 43.6%), respectively, and the rate of breast cancer–specific mortality was 5.1% (95% CI 1.3% to 8.7%), 19.8% (95% CI 10.0% to 28.6%), and 28.8% (95% CI 15.3% to 40.2%) [50].
The prognostic and predictive values of the BCI have been validated in other large, randomized studies and in patients with both node-negative and node-positive disease [51,52]. The predictive value of the endocrine-response biomarker, the H/I ratio, has been demonstrated in randomized studies. In the MA.17 trial, a high H/I ratio was associated with increased risk for late recurrence in the absence of letrozole. However, extended endocrine therapy with letrozole in patients with high H/I ratios predicted benefit from therapy and decreased the probability of late disease recurrence [53]. BCI was also compared to IHC4 and the 21-gene recurrence score in the TransATAC study and was the only test to show prognostic significance for both early (0–5 years) and late (5–10 year) recurrence [54].
The impact of the BCI results on physicians’ recommendations for extended endocrine therapy was assessed by a prospective study. This study showed that the test result had a significant effect on both physician treatment recommendation and patient satisfaction. BCI testing resulted in a change in physician recommendations for extended endocrine therapy, with an overall decrease in recommendations for extended endocrine therapy from 74% to 54%. Knowledge of the test result also led to improved patient satisfaction and decreased anxiety [55].
Summary
Due to the risk for late recurrence, extended endocrine therapy is being recommended for many patients with HR-positive breast cancers. Multiple genomic assays are being developed to better understand an individual’s risk for late recurrence and the potential for benefit from extended endocrine therapies. However, none of the assays have been validated in prospective randomized studies. Further validation is needed prior to routine use of these assays.
Case Continued
A BCI test is done and the result shows 4.3% BCI low-risk category in years 5–10; low likelihood of benefit from extended endocrine therapy. After discussing the results of the BCI test in the context of no survival benefit from extending AIs beyond 5 years, both the patient and her oncologist feel comfortable with discontinuing endocrine therapy at the end of 5 years.
Conclusion
Reduction in breast cancer mortality is mainly the result of improved systemic treatments. With advances in breast cancer screening tools in recent years, the rate of cancer detection has increased. This has raised concerns regarding overdiagnosis. To prevent unwanted toxicities associated with overtreatment, better treatment decision tools are needed. Several genomic assays are currently available and widely used to provide prognostic and predictive information and aid in decisions regarding appropriate use of adjuvant chemotherapy in HR-positive/HER2-negative early-stage breast cancer. Ongoing studies are refining the cutoffs for these assays and expanding the applicability to node-positive breast cancers. Furthermore, with several studies now showing benefit from the use of extended endocrine therapy, some of these assays may be able to identify the subset of patients who are at increased risk for late recurrence and who might benefit from extended endocrine therapy. Advances in molecular testing has enabled clinicians to offer more personalized treatments to their patients, improve patient’s compliance, and decrease anxiety and conflict associated with management decisions. Although small numbers of patients with HER2-positive and triple negative breast cancers were also included in some of these studies, use of genomic assays in this subset of patients is very limited and currently not recommended.
Corresponding author: Kari Braun Wisinski, MD, 1111 Highland Avenue, 6033 Wisconsin Institute for Medical Research, Madison, WI 53705-2275, kbwisinski@medicine.wisc.edu.
Financial disclosures: This work was supported by the NCI Cancer Center Support Grant P30 CA014520.
From the University of Arizona Cancer Center, Tucson, AZ (Dr. Ehsani), and University of Wisconsin Carbone Cancer Center and School of Medicine and Public Health, Madison, WI (Dr. Wisinski).
Abstract
- Objectives: To describe common genomic tests being used clinically to assess prognosis and guide adjuvant chemotherapy and endocrine therapy decisions for early-stage breast cancer.
- Methods: Case presentation and review of the literature.
- Results: Hormone receptor–positive (HR-positive) breast cancers, which express the estrogen and/or progesterone receptor, account for the majority of breast cancers. Endocrine therapy can be highly effective for patients with these HR-positive tumors, and identification of HR-positive breast cancers that do not require the addition of chemotherapy is critical. Clinicopathological features of the breast cancer, including tumor size, nodal involvement, grading, and HR status, are insufficient in predicting the risk for recurrence or the need for chemotherapy. Furthermore, a portion of HR-positive breast cancers have an ongoing risk for late recurrence, and longer durations of endocrine therapy are being used to reduce this risk.
- Conclusion: There is sufficient evidence for use of genomic testing in early-stage HR-positive breast cancer to aid in chemotherapy recommendations. Further confirmation of genomic assays for prediction of benefit from prolonged endocrine therapy is needed.
Key words: molecular testing; decision aids; HR-positive cancer; recurrence risk; adjuvant chemotherapy; endocrine therapy.
Despite the increase in incidence of breast cancer, breast cancer mortality has decreased over the past several decades. This is likely due to both early detection and advances in systemic therapy. However, with more widespread use of screening mammography, there are increasing concerns regarding potential overdiagnosis of cancer [1]. One key challenge is that breast cancer is a heterogeneous disease. Thus, improved tools for determining breast cancer biology can help physicians individualize treatments, with low-risk cancers approached with less aggressive treatments, thus preventing unnecessary toxicities, and higher-risk cancers treated appropriately.
Traditionally, adjuvant chemotherapy was recommended based on tumor features such as stage (tumor size, regional nodal involvement), grade, expression of hormone receptors (estrogen receptor [ER] and progesterone receptor [PR]) and human epidermal growth factor receptor-2 (HER2), and patient features (age, menopausal status). However, this approach is not accurate enough to guide individualized treatment recommendations, which are based on the risk for recurrence and the reduction in this risk that can be achieved with various systemic treatments. In particular, there are individuals with low-risk HR-positive, HER2-negative breast cancers who could be spared the toxicities of cytotoxic chemotherapies without compromising the prognosis.
Beyond chemotherapy, endocrine therapies also have risks, especially when given for extended durations. Recently, extended endocrine therapy has been shown to prevent late recurrences of HR-positive breast cancers. In the MA.17R study, extended endocrine therapy with letrozole for a total of 10 years (beyond 5 years of an aromatase inhibitor [AI]) decreased the risk for breast cancer recurrence or the occurrence of contralateral breast cancer by 34% [2]. However, the overall survival was similar between the 2 groups and the results were not confirmed in other studies [3–5]. Identifying the subgroup of patients who benefit from this extended AI therapy is important in the era of personalized medicine. Several tumor genomic assays have been developed to provide additional prognostic and predictive information with the goal of individualizing adjuvant therapies for breast cancer. Although assays are also being evaluated in HER2-positive and triple negative breast cancer, this review will focus on HR-positive, HER2-negative breast cancer.
Case Study
Initial Presentation
A 54-year-old postmenopausal woman with no significant past medical history presents with an abnormal screening mammogram, which shows a focal asymmetry in the 10 o’clock position at middle depth of the left breast. Further work-up with a diagnostic mammogram and ultrasound of the left breast shows a suspicious hypoechoic solid mass with irregular margins measuring 17 mm. The patient undergoes an ultrasound-guided core needle biopsy of the suspicious mass, the results of which are consistent with an invasive ductal carcinoma, Nottingham grade 2, ER strongly positive (95%), PR weakly positive (5%), HER2 negative, and Ki-67 of 15%. She undergoes a left partial mastectomy and sentinel lymph node biopsy, with final pathology demonstrating a single focus of invasive ductal carcinoma, measuring 2.2 cm in greatest dimension with no evidence of lymphovascular invasion. Margins are clear and 2 sentinel lymph nodes are negative for metastatic disease (final pathologic stage IIA, pT2 pN0 cM0). She is referred to medical oncology to discuss adjuvant systemic therapy.
Can additional testing be used to determine prognosis and guide systemic therapy rec-ommendations for early-stage HR-positive/HER2-negative breast cancer?
After a diagnosis of early-stage breast cancer, the key clinical question faced by the patient and medical oncologist is: what is the individual’s risk for a metastatic breast cancer recurrence and thus the risk for death due to breast cancer? Once the risk for recurrence is established, systemic adjuvant chemotherapy, endocrine therapy, and/or HER2-directed therapy are considered based on the receptor status (ER/PR and HER2) to reduce this risk. Hormone receptor (HR)–positive, HER2-negative breast cancer is the most common type of breast cancer. Although adjuvant endocrine therapy has significantly reduced the risk for recurrence and improved survival for HR-positive breast cancer [6], the role of adjuvant chemotherapy for this subset of breast cancer remains unclear. Prior to genomic testing, the recommendation for adjuvant chemotherapy for HR-positive/HER2-negative tumors was primarily based on patient age and tumor stage and grade. However, chemotherapy overtreatment remained a concern given the potential short- and long-term risks of chemotherapy. Further studies into HR-positive/HER2-negative tumors have shown that these tumors can be divided into 2 main subtypes, luminal A and luminal B [7]. These subtypes represent unique biology and differ in terms of prognosis and response to endocrine therapy and chemotherapy. Luminal A tumors are strongly endocrine responsive and have a good prognosis, while luminal B tumors are less endocrine responsive and are associated with a poorer prognosis; the addition of adjuvant chemotherapy is often considered for luminal B tumors [8]. Several tests, including tumor genomic assays, are now available to help with delineating the tumor subtype and aid in decision-making regarding adjuvant chemotherapy for HR-positive/HER2-negative breast cancers.
Tests for Guiding Adjuvant Chemotherapy Decisions
Ki-67 Assays, Including IHC4 and PEPI
Chronic proliferation is a hallmark of cancer cells [9]. Ki-67, a nuclear nonhistone protein whose expression varies in intensity throughout the cell cycle, has been used as a measurement of tumor cell proliferation [10]. Two large meta-analyses have demonstrated that high Ki-67 expression in breast tumors is independently associated with worse disease-free and overall survival rates [11,12]. Ki-67 expression has also been used to classify HR-positive tumors as luminal A or B. After classifying tumor subtypes based on intrinsic gene expression profiling, Cheang et al determined that a Ki-67 cut point of 13.25% differentiated luminal A and B tumors [13]. However, the ideal cut point for Ki-67 remains unclear, as the sensitivity and specificity in this study was 77% and 78%, respectively. Others have combined Ki-67 with standard ER, PR, and HER2 testing. This IHC4 score, which weighs each of these variables, was validated in postmenopausal patients from the ATAC (Arimidex, Tamoxifen, Alone or in Combination) trial who had ER-positive tumors and did not receive chemotherapy [14]. The prognostic information from the IHC4 was similar to that seen with the 21-gene recurrence score (Oncotype DX), which is discussed later in this article. The key challenge with Ki-67 testing currently is the lack of a validated test methodology, and intraobserver variability in interpreting the Ki-67 results [15]. Recent series have suggested that Ki-67 be considered as a continuous marker rather than a set cut point [16]. These issues continue to impact the clinical utility of Ki-67 for decision making for adjuvant chemotherapy.
Ki-67 and the preoperative endocrine prognostic index (PEPI) score have been explored in the neoadjuvant setting to separate postmenopausal women with endocrine-sensitive versus intrinsically resistant disease and identify patients at risk for recurrent disease [17]. The on-treatment levels of Ki-67 in response to endocrine therapy have been shown to be more prognostic than baseline values, and a decrease in Ki-67 as early as 2 weeks after initiation of neoadjuvant endocrine therapy is associated with endocrine-sensitive tumors and improved outcome. The PEPI score was developed through retrospective analysis of the P024 trial [18] to evaluate the relationship between post-neoadjuvant endocrine therapy tumor characteristics and risk for early relapse. This was subsequently validated in an independent data set from the IMPACT trial [19]. Patients with low pathological stage (0 or 1) and a favorable biomarker profile (PEPI score 0) at surgery had the best prognosis in the absence of chemotherapy. On the other hand, higher pathological stage at surgery and a poor biomarker profile with loss of ER positivity or persistently elevated Ki-67 (PEPI score of 3) identified de novo endocrine-resistant tumors which are at higher risk for early relapse [20]. The ongoing Alliance A011106 ALTERNATE trial (ALTernate approaches for clinical stage II or III Estrogen Receptor positive breast cancer NeoAdjuvant TrEatment in postmenopausal women, NCT01953588) is a phase 3 study to prospectively test this hypothesis.
21-Gene Recurrence Score (Oncotype DX Assay)
The 21-gene Oncotype DX assay is conducted on paraffin-embedded tumor tissue and measures the expression of 16 cancer-related genes and 5 reference genes using quantitative polymerase chain reaction. The genes included in this assay are mainly related to proliferation (including Ki-67), invasion, and HER2 or estrogen signaling [21]. Originally, the 21-gene recurrence score assay was analyzed as a prognostic biomarker tool in a prospective-retrospective biomarker substudy of the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-14 clinical trial in which patients with node-negative, ER-positive tumors were randomly assigned to receive tamoxifen or placebo without chemotherapy [22]. Using the standard reported values of low risk (< 18), intermediate risk (18–30), or high risk (≥ 31) for recurrence, among the tamoxifen-treated patients, cancers with a high-risk recurrence score had a significantly worse rate of distant recurrence and overall survival [21]. Inferior breast cancer survival with a high recurrence score was also confirmed in other series of endocrine-treated patients with node-negative and node-positive disease [23–25].
The predictive utility of the 21-gene recurrence score for endocrine therapy has also been evaluated. A comparison of the placebo- and tamoxifen-treated patients from the NSABP B-14 trial demonstrated that the 21-gene recurrence score predicted benefit from tamoxifen in cancers with low- or intermediate-risk recurrence scores [26]. However, there was no benefit from the use of tamoxifen over placebo in cancers with high-risk recurrence scores. To date, this intriguing data has not been prospectively confirmed, and thus the 21-gene recurrence score is not used to avoid endocrine therapy.
The 21-gene recurrence score is primarily used by oncologists to aid in decision-making regarding adjuvant chemotherapy in patients with node-negative and node-positive (with up to 3 positive lymph nodes), HR-positive/HER2-negative breast cancers. The predictive utility of the 21-gene recurrence score for adjuvant chemotherapy was initially tested using tumor samples from the NSABP B-20 study. This study initially compared adjuvant tamoxifen alone with tamoxifen plus chemotherapy in patients with node-negative, HR-positive tumors. The prospective-retrospective biomarker analysis showed that the patients with high-risk 21-gene recurrence scores benefited from the addition of chemotherapy, whereas those with low- or intermediate-risk did not have an improved freedom from distant recurrence with chemotherapy [27]. Similarly, an analysis from the prospective phase 3 Southwest Oncology Group (SWOG) 8814 trial comparing tamoxifen to tamoxifen with chemotherapy showed that for node-positive tumors, chemotherapy benefit was only seen in those with high 21-gene recurrence scores [24].
Prospective studies are now starting to report results regarding the predictive role of the 21-gene recurrence score. The TAILORx (Trial Assigning Individualized Options for Treatment) trial includes women with node-negative, HR-positive and HER2-negative tumors measuring 0.6 to 5 cm. All patients were treated with standard of care endocrine therapy for at least 5 years. Chemotherapy was determined based on the 21-gene recurrence score results on the primary tumor. The 21-gene recurrence score cutoffs were changed to low (0–10), intermediate (11–25), and high (≥ 26). Patients with scores of 26 or higher were treated with chemotherapy, and those with intermediate scores were randomly assigned to hemotherapy or no chemotherapy; results from this cohort are still pending. However, excellent breast cancer outcomes with endocrine therapy alone were reported from the 1626 (15.9% of total cohort) prospectively followed patients with low-recurrence score tumors. The 5-year invasive disease-free survival was 93.8%, with overall survival of 98% [28]. Given that 5 years is appropriate follow-up to see any chemotherapy benefit, this data supports the recommendation for no chemotherapy in this cohort of patients with very low 21-gene recurrence scores.
The RxPONDER (Rx for Positive Node, Endocrine Responsive Breast Cancer) trial is evaluating women with 1 to 3 node-positive, HR-positive, HER2-negative tumors. In this trial, patients with 21-gene recurrence scores of 0 to 25 were assigned to adjuvant chemotherapy or none. Those with scores of 26 or higher were assigned to chemotherapy. All patients received standard adjuvant endocrine therapy. This study has completed accrual and results are pending. Of note, TAILORx and RxPONDER did not investigate the potential lack of benefit of endocrine therapy in cancers with high recurrence scores. Furthermore, despite data suggesting that chemotherapy may not even benefit women with 4 or more nodes involved but who have a low recurrence score [24], due to the lack of prospective data in this cohort and the quite high risk for distant recurrence, chemotherapy continues to be the standard of care for these patients.
PAM50 (Breast Cancer Prognostic Gene Signature)
Using microarray and quantitative reverse transcriptase PCR (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tissues, the Breast Cancer Prognostic Gene Signature (PAM50) assay was initially developed to identify intrinsic breast cancer subtypes, including luminal A, luminal B, HER2-enriched, and basal-like [7,29]. Based on the prediction analysis of microarray (PAM) method, the assay measures the expression levels of 50 genes, provides a risk category (low, intermediate, and high), and generates a numerical risk of recurrence score (ROR). The intrinsic subtype and ROR have been shown to add significant prognostic value to the clinicopathological characteristics of tumors. Clinical validity of PAM50 was evaluated in postmenopausal women with HR-positive, early-stage breast cancer treated in the prospective ATAC and ABCSG-8 (Austrian Breast and Colorectal Cancer Study Group 8) trials [30,31]. In 1017 patients with ER-positive breast cancer treated with anastrozole or tamoxifen in the ATAC trial, ROR added significant prognostic information beyond the clinical treatment score (integrated prognostic information from nodal status, tumor size, histopathologic grade, age, and anastrozole or tamoxifen treatment) in all patients. Also, compared with the 21-gene recurrence score, ROR provided more prognostic information in ER-positive, node-negative disease and better differentiation of intermediate- and higher-risk groups. Fewer patients were categorized as intermediate risk by ROR and more as high risk, which could reduce the uncertainty in the estimate of clinical benefit from chemotherapy [30]. The clinical utility of PAM50 as a prognostic model was also validated in 1478 postmenopausal women with ER-positive early-stage breast cancer enrolled in the ABCSG-8 trial. In this study, ROR assigned 47% of patients with node-negative disease to the low-risk category. In this low-risk group, the 10-year metastasis risk was less than 3.5 %, indicating lack of benefit from additional chemotherapy [31]. A key limitation of the PAM50 is the lack of any prospective studies with this assay.
PAM50 has been designed to be carried out in any qualified pathology laboratory. Moreover, the ROR score provides additional prognostic information about risk of late recurrence, which will be discussed in the next section.
70-Gene Breast Cancer Recurrence Assay (MammaPrint)
MammaPrint is a 70-gene assay that was initially developed using an unsupervised, hierarchical clustering algorithm on whole-genome expression arrays with early-stage breast cancer. Among 295 consecutive patients who had MammaPrint testing, those classified with a good-prognosis tumor signature (n = 115) had an excellent 10-year survival rate (94.5%) compared to those with a poor-prognosis signature (54.5%), and the signature remained prognostic upon multivariate analysis [32]. Subsequently, a pooled analysis comparing outcomes by MammaPrint score in patients with node-negative or 1 to 3 node-positive breast cancers treated as per discretion of their medical team with either adjuvant chemotherapy plus endocrine therapy or endocrine therapy alone reported that only those patients with a high-risk score benefited from chemotherapy [33]. Recently, a prospective phase 3 study (MINDACT [Microarray In Node negative Disease may Avoid ChemoTherapy]) evaluating the utility of MammaPrint for adjuvant chemotherapy decision-making reported results [34]. In this study, 6693 women with early-stage breast cancer were assessed by clinical risk and genomic risk using MammaPrint. Those with low clinical and genomic risk did not receive chemotherapy, while those with high clinical and genomic risk all received chemotherapy. The primary goal of the study was to assess whether forgoing chemotherapy would be associated with a low rate of recurrence in those patients with a low-risk prognostic MammaPrint signature but high clinical risk. A total of 1550 patients (23.2%) were in the discordant group, and the majority of these patients had HR-positive disease (98.1%). Without chemotherapy, the rate of survival without distant metastasis at 5 years in this group was 94.7% (95% confidence interval [CI] 92.5% to 96.2%), which met the primary endpoint. Of note, initially, MammaPrint was only available for fresh tissue analysis, but recent advances in RNA processing now allow for this analysis on FFPE tissue [35].
Summary
Case Continued
The patient undergoes 21-gene recurrence score testing, which shows a low recurrence score of 10, estimating the 10-year risk of distant recurrence to be approximately 7% with 5 years of tamoxifen. Chemo-therapy is not recommended. The patient completes adjuvant whole breast radiation therapy, and then, based on data supporting AIs over tamoxifen in postmenopausal women, she is started on anastrozole [36]. She initially experiences mild side effects from treatment, including fatigue, arthralgia, and vaginal dryness, but her symptoms are able to be managed. As she approaches 5 years of adjuvant endocrine therapy with anastrozole, she is struggling with rotator cuff injury and is anxious about recurrence, but has no evidence of recurrent cancer. Her bone density scan in the beginning of her fourth year of therapy shows a decrease in bone mineral density, with the lowest T score of –1.5 at the left femoral neck, consistent with osteopenia. She has been treated with calcium and vitamin D supplements.
How long should this patient continue treatment with anastrozole?
The risk for recurrence is highest during the first 5 years after diagnosis for all patients with early breast cancer [37]. Although HR-positive breast cancers have a better prognosis than HR-negative disease, the pattern of recurrence is different between the 2 groups, and it is estimated that approximately half of the recurrences among patients with HR-positive early breast cancer occur after the first 5 years from diagnosis. Annualized hazard of recurrence in HR-positive breast cancer has been shown to remain elevated and fairly stable beyond 10 years, even for those with low tumor burden and node-negative disease [38]. Prospective trials showed that for women with HR-positive early breast cancer, 5 years of adjuvant tamoxifen could substantially reduce recurrence rates and improve survival, and this became the standard of care [39]. AIs are considered the standard of care for adjuvant endocrine therapy in most postmenopausal women, as they result in a significantly lower recurrence rate compared with tamoxifen, either as initial adjuvant therapy or sequentially following 2 to 3 years of tamoxifen [40].
However, extending AI therapy from 5 years to 10 years is not clearly beneficial. In the MA.17R trial, although longer AI therapy resulted in significantly better disease-free survival (95% versus 91%, hazard ratio 0.66; P = 0.01), this was primarily due to a lower incidence of contralateral breast cancer in those taking the AI compared with placebo. The distant recurrence risks were similar and low (4.4% versus 5.5%), and there was no overall survival difference [2]. Also, the NSABP B-42 study, which was presented at the 2016 San Antonio Breast Cancer Symposium, did not meet its predefined endpoint for benefit from extending adjuvant AI therapy with letrozole beyond 5 years [3]. Thus, the absolute benefit from extended endocrine therapy has been modest across these studies. Although endocrine therapy is considered relatively safe and well tolerated, side effects can be significant and even associated with morbidity. Ideally, extended endocrine therapy should be offered to the subset of patients who would benefit the most. Several genomic diagnostic assays, including the EndoPredict test, PAM50, and the Breast Cancer Index (BCI) tests, specifically assess the risk for late recurrence in HR-positive cancers.
Tests for Assessing Risk for Late Recurrence
PAM50
Studies suggest that the ROR score also has value in predicting late recurrences. Analysis of data in patients enrolled in the ABCSG-8 trial showed that ROR could identify patients with endocrine-sensitive disease who are at low risk for late relapse and could be spared from unwanted toxicities of extended endocrine therapies. In 1246 ABCSG-8 patients between years 5 and 15, the PAM50 ROR demonstrated an absolute risk of distant recurrence of 2.4% in the low-risk group, as compared with 17.5% in the high-risk group [44]. Also, a combined analysis of patients from both the ATAC and ABCSG-8 trials demonstrated the utility of ROR in identifying this subgroup of patients with low risk for late relapse [45].
EndoPredict
EndoPredict (EP) is another quantitative RT-PCR–based assay which uses FFPE tissues to calculate a risk score based on 8 cancer-related and 3 reference genes. The score is combined with clinicopathological factors including tumor size and nodal status to make a comprehensive risk score (EPclin). EPclin is used to dichotomize patients into EP low- and EP high-risk groups. EP has been validated in 2 cohorts of patients enrolled in separate randomized studies, ABCSG-6 and ABCSG-8. EP provided prognostic information beyond clinicopathological variables to predict distant recurrence in patients with HR-positive, HER2-negative early breast cancer [46]. More important, EP has been shown to predict early (years 0–5) versus late (> 5 years after diagnosis) recurrences and identify a low-risk subset of patients who would not be expected to benefit from further treatment beyond 5 years of endocrine therapy [47]. Recently, EP and EPclin were compared with the 21-gene (Oncotype DX) recurrence score in a patient population from the TransATAC study. Both EP and EPclin provided more prognostic information compared to the 21-gene recurrence score and identified early and late relapse events [48]. EndoPredict is the first multigene expression assay that could be routinely performed in decentral molecular pathological laboratories with a short turnaround time [49].
Breast Cancer Index
The BCI is a RT-PCR–based gene expression assay that consists of 2 gene expression biomarkers: molecular grade index (MGI) and HOXB13/IL17BR (H/I). The BCI was developed as a prognostic test to assess risk for breast cancer recurrence using a cohort of ER-positive patients (n = 588) treated with adjuvant tamoxifen versus observation from the prospective randomized Stockholm trial [50]. In this blinded retrospective study, H/I and MGI were measured and a continuous risk model (BCI) was developed in the tamoxifen-treated group. More than 50% of the patients in this group were classified as having a low risk of recurrence. The rate of distant recurrence or death in this low-risk group at 10 years was less than 3%. The performance of the BCI model was then tested in the untreated arm of the Stockholm trial. In the untreated arm, BCI classified 53%, 27%, and 20% of patients as low, intermediate, and high risk, respectively. The rate of distant metastasis at 10 years in these risk groups was 8.3% (95% CI 4.7% to 14.4%), 22.9% (95% CI 14.5% to 35.2%), and 28.5% (95% CI 17.9% to 43.6%), respectively, and the rate of breast cancer–specific mortality was 5.1% (95% CI 1.3% to 8.7%), 19.8% (95% CI 10.0% to 28.6%), and 28.8% (95% CI 15.3% to 40.2%) [50].
The prognostic and predictive values of the BCI have been validated in other large, randomized studies and in patients with both node-negative and node-positive disease [51,52]. The predictive value of the endocrine-response biomarker, the H/I ratio, has been demonstrated in randomized studies. In the MA.17 trial, a high H/I ratio was associated with increased risk for late recurrence in the absence of letrozole. However, extended endocrine therapy with letrozole in patients with high H/I ratios predicted benefit from therapy and decreased the probability of late disease recurrence [53]. BCI was also compared to IHC4 and the 21-gene recurrence score in the TransATAC study and was the only test to show prognostic significance for both early (0–5 years) and late (5–10 year) recurrence [54].
The impact of the BCI results on physicians’ recommendations for extended endocrine therapy was assessed by a prospective study. This study showed that the test result had a significant effect on both physician treatment recommendation and patient satisfaction. BCI testing resulted in a change in physician recommendations for extended endocrine therapy, with an overall decrease in recommendations for extended endocrine therapy from 74% to 54%. Knowledge of the test result also led to improved patient satisfaction and decreased anxiety [55].
Summary
Due to the risk for late recurrence, extended endocrine therapy is being recommended for many patients with HR-positive breast cancers. Multiple genomic assays are being developed to better understand an individual’s risk for late recurrence and the potential for benefit from extended endocrine therapies. However, none of the assays have been validated in prospective randomized studies. Further validation is needed prior to routine use of these assays.
Case Continued
A BCI test is done and the result shows 4.3% BCI low-risk category in years 5–10; low likelihood of benefit from extended endocrine therapy. After discussing the results of the BCI test in the context of no survival benefit from extending AIs beyond 5 years, both the patient and her oncologist feel comfortable with discontinuing endocrine therapy at the end of 5 years.
Conclusion
Reduction in breast cancer mortality is mainly the result of improved systemic treatments. With advances in breast cancer screening tools in recent years, the rate of cancer detection has increased. This has raised concerns regarding overdiagnosis. To prevent unwanted toxicities associated with overtreatment, better treatment decision tools are needed. Several genomic assays are currently available and widely used to provide prognostic and predictive information and aid in decisions regarding appropriate use of adjuvant chemotherapy in HR-positive/HER2-negative early-stage breast cancer. Ongoing studies are refining the cutoffs for these assays and expanding the applicability to node-positive breast cancers. Furthermore, with several studies now showing benefit from the use of extended endocrine therapy, some of these assays may be able to identify the subset of patients who are at increased risk for late recurrence and who might benefit from extended endocrine therapy. Advances in molecular testing has enabled clinicians to offer more personalized treatments to their patients, improve patient’s compliance, and decrease anxiety and conflict associated with management decisions. Although small numbers of patients with HER2-positive and triple negative breast cancers were also included in some of these studies, use of genomic assays in this subset of patients is very limited and currently not recommended.
Corresponding author: Kari Braun Wisinski, MD, 1111 Highland Avenue, 6033 Wisconsin Institute for Medical Research, Madison, WI 53705-2275, kbwisinski@medicine.wisc.edu.
Financial disclosures: This work was supported by the NCI Cancer Center Support Grant P30 CA014520.
1. Welch HG, Prorok PC, O'Malley AJ, Kramer BS. Breast-cancer tumor size, overdiagnosis, and mammography screening effectiveness. N Engl J Med 2016;375:1438–47.
2. Goss PE, Ingle JN, Pritchard KI, et al. Extending aromatase-inhibitor adjuvant therapy to 10 years. N Engl J Med 2016;375:209–19.
3. Mamounas E, Bandos H, Lembersky B. A randomized, double-blinded, placebo-controlled clinical trial of extended adjuvant endocrine therapy with letrozole in postmenopausal women with hormone-receptor-positive breast cancer who have completed previous adjuvant treatment with an aromatase inhibitor. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-05.
4. Tjan-Heijnen VC, Van Hellemond IE, Peer PG, et al: First results from the multicenter phase III DATA study comparing 3 versus 6 years of anastrozole after 2-3 years of tamoxifen in postmenopausal women with hormone receptor-positive early breast cancer. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-03.
5. Blok EJ, Van de Velde CJH, Meershoek-Klein Kranenbarg EM, et al: Optimal duration of extended letrozole treatment after 5 years of adjuvant endocrine therapy. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-04.
6. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group. Lancet 2005;365:1687–717.
7. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747–52.
8. Coates AS, Winer EP, Goldhirsch A, et al. Tailoring therapies--improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol 2015;26:1533–46.
9. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000;100:57–70.
10. Urruticoechea A, Smith IE, Dowsett M. Proliferation marker Ki-67 in early breast cancer. J Clin Oncol 2005;23:7212–20.
11. de Azambuja E, Cardoso F, de Castro G Jr, et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer 2007;96:1504–13.
12. Petrelli F, Viale G, Cabiddu M, Barni S. Prognostic value of different cut-off levels of Ki-67 in breast cancer: a systematic review and meta-analysis of 64,196 patients. Breast Cancer Res Treat 2015;153:477–91.
13. Cheang MC, Chia SK, Voduc D, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 2009;101:736–50.
14. Cuzick J, Dowsett M, Pineda S, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and com-parison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol 2011;29:4273–8.
15. Pathmanathan N, Balleine RL. Ki67 and proliferation in breast cancer. J Clin Pathol 2013;66:512–6.
16. Denkert C, Budczies J, von Minckwitz G, et al. Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast 2015; 24 Suppl 2:S67–72.
17. Ma CX, Bose R, Ellis MJ. Prognostic and predictive biomarkers of endocrine responsiveness for estrogen receptor positive breast cancer. Adv Exp Med Biol 2016;882:125–54.
18. Eiermann W, Paepke S, Appfelstaedt J, et al. Preoperative treatment of postmenopausal breast cancer patients with letrozole: a randomized double-blind multicenter study. Ann Oncol 2001;12:1527–32.
19. Smith IE, Dowsett M, Ebbs SR, et al. Neoadjuvant treatment of postmenopausal breast cancer with anastrozole, tamoxifen, or both in combination: the Immediate Preoperative Anas-trozole, Tamoxifen, or Combined with Tamoxifen (IMPACT) multicenter double-blind randomized trial. J Clin Oncol 2005;23:5108–16.
20. Ellis MJ, Tao Y, Luo J, et al. Outcome prediction for estrogen receptor-positive breast cancer based on postneoadjuvant endocrine therapy tumor characteristics. J Natl Cancer Inst 2008;100:1380–8.
21. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351:2817–26.
22. Fisher B, Jeong JH, Bryant J, et al. Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 2004;364:858–68.
23. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 2006;8:R25.
24. Albain KS, Barlow WE, Shak S, et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol 2010;11:55–65.
25. Dowsett M, Cuzick J, Wale C, et al. Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study. J Clin Oncol 2010;28:1829–34.
26. Paik S, Shak S, Tang G, et al. Expression of the 21 genes in the recurrence score assay and tamoxifen clinical benefit in the NSABP study B-14 of node negative, estrogen receptor positive breast cancer. J Clin Oncol 2005;23: suppl:510.
27. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol2006;24:3726–34.
28. Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 2015;373:2005–14.
29. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009;27:1160–7.
30. Dowsett M, Sestak I, Lopez-Knowles E, et al. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 2013;31:2783–90.
31. Gnant M, Filipits M, Greil R, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 post-menopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol 2014;25:339–45.
32. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347:1999–2009.
33. Knauer M, Mook S, Rutgers EJ, et al. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat 2010;120:655–61.
34. Cardoso F, van't Veer LJ, Bogaerts J, et al. 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med 2016;375:717–29.
35. Sapino A, Roepman P, Linn SC, et al. MammaPrint molecular diagnostics on formalin-fixed, paraffin-embedded tissue. J Mol Diagn 2014;16:190–7.
36. Burstein HJ, Griggs JJ, Prestrud AA, Temin S. American society of clinical oncology clinical practice guideline update on adjuvant endocrine therapy for women with hormone receptor-positive breast cancer. J Oncol Pract 2010;6:243–6.
37. Saphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol 1996;14:2738–46.
38. Colleoni M, Sun Z, Price KN, et al. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the International Breast Cancer Study Group Trials I to V. J Clin Oncol 2016;34:927–35.
39. Davies C, Godwin J, Gray R, et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet 2011;378:771–84.
40. Dowsett M, Forbes JF, Bradley R, et al. Aromatase inhibitors versus tamoxifen in early breast cancer: patient-level meta-analysis of the randomised trials. Lancet 2015;386:1341–52.
41. Davies C, Pan H, Godwin J, et al. Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years after diagnosis of oestrogen receptor-positive breast cancer: ATLAS, a randomised trial. Lancet 2013;381:805–16.
42. Gray R, Rea D, Handley K, et al. aTTom: Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years in 6,953 women with early breast cancer. J Clin Oncol 2013;31 (suppl):5.
43. Goss PE, Ingle JN, Martino S, et al. Randomized trial of letrozole following tamoxifen as extended adjuvant therapy in receptor-positive breast cancer: updated findings from NCIC CTG MA.17. J Natl Can-cer Inst 2005;97:1262–71.
44. Filipits M, Nielsen TO, Rudas M, et al. The PAM50 risk-of-recurrence score predicts risk for late distant recurrence after endocrine therapy in postmenopausal women with endocrine-responsive early breast cancer. Clin Cancer Res 2014;20:1298–305.
45. Sestak I, Cuzick J, Dowsett M, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J Clin Oncol 2015;33:916–22.
46. Filipits M, Rudas M, Jakesz R, et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res 2011;17:6012–20.
47. Dubsky P, Brase JC, Jakesz R, et al. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2- breast cancer patients. Br J Cancer 2013;109:2959–64.
48. Buus R, Sestak I, Kronenwett R, et al. Comparison of EndoPredict and EPclin with Oncotype DX Recurrence Score for prediction of risk of distant recurrence after endocrine therapy. J Natl Cancer Inst 2016;108:djw149.
49. Muller BM, Keil E, Lehmann A, et al. The EndoPredict gene-expression assay in clinical practice - performance and impact on clinical decisions. PLoS One 2013;8:e68252.
50. Jerevall PL, Ma XJ, Li H, et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer 2011;104:1762–9.
51. Sgroi DC, Chapman JA, Badovinac-Crnjevic T, et al. Assessment of the prognostic and predictive utility of the Breast Cancer Index (BCI): an NCIC CTG MA.14 study. Breast Cancer Res 2016;18:1.
52. Zhang Y, Schnabel CA, Schroeder BE, et al. Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence. Clin Cancer Res 2013;19:4196–205.
53. Sgroi DC, Carney E, Zarrella E, et al. Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker. J Natl Cancer Inst 2013;105:1036–42.
54. Sgroi DC, Sestak I, Cuzick J, et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: a prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol 2013;14:1067–76.
55. Sanft T, Aktas B, Schroeder B, et al. Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer. Breast Cancer Res Treat 2015;154:533–41.
56. Nielsen TO, Parker JS, Leung S, et al. A comparison of PAM50 Insrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer. Clin Cancer Res 2010;16:5222–32.
57. Mamounas EP, Jeong JH, Wickerham DL, et al. Benefit from exemestane as extended adjuvant therapy after 5 years of adjuvant tamoxifen: intention-to-treat analysis of the National Surgical Adjuvant Breast And Bowel Project B-33 trial. J Clin Oncol 2008;26:1965–71.
1. Welch HG, Prorok PC, O'Malley AJ, Kramer BS. Breast-cancer tumor size, overdiagnosis, and mammography screening effectiveness. N Engl J Med 2016;375:1438–47.
2. Goss PE, Ingle JN, Pritchard KI, et al. Extending aromatase-inhibitor adjuvant therapy to 10 years. N Engl J Med 2016;375:209–19.
3. Mamounas E, Bandos H, Lembersky B. A randomized, double-blinded, placebo-controlled clinical trial of extended adjuvant endocrine therapy with letrozole in postmenopausal women with hormone-receptor-positive breast cancer who have completed previous adjuvant treatment with an aromatase inhibitor. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-05.
4. Tjan-Heijnen VC, Van Hellemond IE, Peer PG, et al: First results from the multicenter phase III DATA study comparing 3 versus 6 years of anastrozole after 2-3 years of tamoxifen in postmenopausal women with hormone receptor-positive early breast cancer. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-03.
5. Blok EJ, Van de Velde CJH, Meershoek-Klein Kranenbarg EM, et al: Optimal duration of extended letrozole treatment after 5 years of adjuvant endocrine therapy. In: Proceedings from the San Antonio Breast Cancer Symposium; December 6–10, 2016; San Antonio, TX. Abstract S1-04.
6. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group. Lancet 2005;365:1687–717.
7. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747–52.
8. Coates AS, Winer EP, Goldhirsch A, et al. Tailoring therapies--improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol 2015;26:1533–46.
9. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000;100:57–70.
10. Urruticoechea A, Smith IE, Dowsett M. Proliferation marker Ki-67 in early breast cancer. J Clin Oncol 2005;23:7212–20.
11. de Azambuja E, Cardoso F, de Castro G Jr, et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer 2007;96:1504–13.
12. Petrelli F, Viale G, Cabiddu M, Barni S. Prognostic value of different cut-off levels of Ki-67 in breast cancer: a systematic review and meta-analysis of 64,196 patients. Breast Cancer Res Treat 2015;153:477–91.
13. Cheang MC, Chia SK, Voduc D, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 2009;101:736–50.
14. Cuzick J, Dowsett M, Pineda S, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and com-parison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol 2011;29:4273–8.
15. Pathmanathan N, Balleine RL. Ki67 and proliferation in breast cancer. J Clin Pathol 2013;66:512–6.
16. Denkert C, Budczies J, von Minckwitz G, et al. Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast 2015; 24 Suppl 2:S67–72.
17. Ma CX, Bose R, Ellis MJ. Prognostic and predictive biomarkers of endocrine responsiveness for estrogen receptor positive breast cancer. Adv Exp Med Biol 2016;882:125–54.
18. Eiermann W, Paepke S, Appfelstaedt J, et al. Preoperative treatment of postmenopausal breast cancer patients with letrozole: a randomized double-blind multicenter study. Ann Oncol 2001;12:1527–32.
19. Smith IE, Dowsett M, Ebbs SR, et al. Neoadjuvant treatment of postmenopausal breast cancer with anastrozole, tamoxifen, or both in combination: the Immediate Preoperative Anas-trozole, Tamoxifen, or Combined with Tamoxifen (IMPACT) multicenter double-blind randomized trial. J Clin Oncol 2005;23:5108–16.
20. Ellis MJ, Tao Y, Luo J, et al. Outcome prediction for estrogen receptor-positive breast cancer based on postneoadjuvant endocrine therapy tumor characteristics. J Natl Cancer Inst 2008;100:1380–8.
21. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351:2817–26.
22. Fisher B, Jeong JH, Bryant J, et al. Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 2004;364:858–68.
23. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 2006;8:R25.
24. Albain KS, Barlow WE, Shak S, et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol 2010;11:55–65.
25. Dowsett M, Cuzick J, Wale C, et al. Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study. J Clin Oncol 2010;28:1829–34.
26. Paik S, Shak S, Tang G, et al. Expression of the 21 genes in the recurrence score assay and tamoxifen clinical benefit in the NSABP study B-14 of node negative, estrogen receptor positive breast cancer. J Clin Oncol 2005;23: suppl:510.
27. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol2006;24:3726–34.
28. Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 2015;373:2005–14.
29. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009;27:1160–7.
30. Dowsett M, Sestak I, Lopez-Knowles E, et al. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 2013;31:2783–90.
31. Gnant M, Filipits M, Greil R, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 post-menopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol 2014;25:339–45.
32. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347:1999–2009.
33. Knauer M, Mook S, Rutgers EJ, et al. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat 2010;120:655–61.
34. Cardoso F, van't Veer LJ, Bogaerts J, et al. 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med 2016;375:717–29.
35. Sapino A, Roepman P, Linn SC, et al. MammaPrint molecular diagnostics on formalin-fixed, paraffin-embedded tissue. J Mol Diagn 2014;16:190–7.
36. Burstein HJ, Griggs JJ, Prestrud AA, Temin S. American society of clinical oncology clinical practice guideline update on adjuvant endocrine therapy for women with hormone receptor-positive breast cancer. J Oncol Pract 2010;6:243–6.
37. Saphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol 1996;14:2738–46.
38. Colleoni M, Sun Z, Price KN, et al. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the International Breast Cancer Study Group Trials I to V. J Clin Oncol 2016;34:927–35.
39. Davies C, Godwin J, Gray R, et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet 2011;378:771–84.
40. Dowsett M, Forbes JF, Bradley R, et al. Aromatase inhibitors versus tamoxifen in early breast cancer: patient-level meta-analysis of the randomised trials. Lancet 2015;386:1341–52.
41. Davies C, Pan H, Godwin J, et al. Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years after diagnosis of oestrogen receptor-positive breast cancer: ATLAS, a randomised trial. Lancet 2013;381:805–16.
42. Gray R, Rea D, Handley K, et al. aTTom: Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years in 6,953 women with early breast cancer. J Clin Oncol 2013;31 (suppl):5.
43. Goss PE, Ingle JN, Martino S, et al. Randomized trial of letrozole following tamoxifen as extended adjuvant therapy in receptor-positive breast cancer: updated findings from NCIC CTG MA.17. J Natl Can-cer Inst 2005;97:1262–71.
44. Filipits M, Nielsen TO, Rudas M, et al. The PAM50 risk-of-recurrence score predicts risk for late distant recurrence after endocrine therapy in postmenopausal women with endocrine-responsive early breast cancer. Clin Cancer Res 2014;20:1298–305.
45. Sestak I, Cuzick J, Dowsett M, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J Clin Oncol 2015;33:916–22.
46. Filipits M, Rudas M, Jakesz R, et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res 2011;17:6012–20.
47. Dubsky P, Brase JC, Jakesz R, et al. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2- breast cancer patients. Br J Cancer 2013;109:2959–64.
48. Buus R, Sestak I, Kronenwett R, et al. Comparison of EndoPredict and EPclin with Oncotype DX Recurrence Score for prediction of risk of distant recurrence after endocrine therapy. J Natl Cancer Inst 2016;108:djw149.
49. Muller BM, Keil E, Lehmann A, et al. The EndoPredict gene-expression assay in clinical practice - performance and impact on clinical decisions. PLoS One 2013;8:e68252.
50. Jerevall PL, Ma XJ, Li H, et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer 2011;104:1762–9.
51. Sgroi DC, Chapman JA, Badovinac-Crnjevic T, et al. Assessment of the prognostic and predictive utility of the Breast Cancer Index (BCI): an NCIC CTG MA.14 study. Breast Cancer Res 2016;18:1.
52. Zhang Y, Schnabel CA, Schroeder BE, et al. Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence. Clin Cancer Res 2013;19:4196–205.
53. Sgroi DC, Carney E, Zarrella E, et al. Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker. J Natl Cancer Inst 2013;105:1036–42.
54. Sgroi DC, Sestak I, Cuzick J, et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: a prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol 2013;14:1067–76.
55. Sanft T, Aktas B, Schroeder B, et al. Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer. Breast Cancer Res Treat 2015;154:533–41.
56. Nielsen TO, Parker JS, Leung S, et al. A comparison of PAM50 Insrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer. Clin Cancer Res 2010;16:5222–32.
57. Mamounas EP, Jeong JH, Wickerham DL, et al. Benefit from exemestane as extended adjuvant therapy after 5 years of adjuvant tamoxifen: intention-to-treat analysis of the National Surgical Adjuvant Breast And Bowel Project B-33 trial. J Clin Oncol 2008;26:1965–71.
Clinical Assessment and Management of Cancer-Related Fatigue
From the University of Texas MD Anderson Cancer Center, Houston, TX.
Abstract
- Objective: To review the evidence on interventions for managing cancer-related fatigue (CRF) and provide evidence-based guidance on approaches to its management.
- Methods: Nonsystematic review of the literature.
- Results: Several theories have been proposed to explain the biology of CRF, but there is no single clear mechanism that can be targeted for therapy. The approach to patients begins with screening for fatigue and assessing its intensity, followed by a thorough history and examination to determine whether any reversible medical conditions are contributing to fatigue. Management of underlying medical comorbidities may help some patients. For patients whose fatigue persists, pharmacologic and nonpharmacologic treatment options are available. Pharmacologic options include psychostimulants, such as methylphenidate and modafinil, and corticosteroids. Nonpharmacologic approaches include exercise, cognitive behavior therapy, yoga, acupuncture, and tai chi.
- Conclusion: We recommend an individualized approach, often with a combination of the available options. Patients need to be evaluated periodically to assess their fatigue, and since cancer-related fatigue affects survivors, long-term follow-up is needed.
Key words: fatigue; cancer; pro-inflammatory cytokines; nonpharmacologic; psychostimulants.
Fatigue is a common distressing effect of cancer [1].It impairs the quality of life of patients undergoing active cancer treatment and of post-treatment survivors. The National Comprehensive Cancer Network (NCCN) defines cancer-related fatigue (CRF) as “a distressing, persistent, subjective sense of physical, emotional and/or cognitive tiredness related to cancer or cancer treatment that is not proportional to recent activity and interferes with usual functioning [2].” Differences between CRF and fatigue reported by individuals without cancer are that CRF is more severe and is not relieved by rest. The prevalence of CRF in cancer patients and survivors is highly variable, ranging between 25% and 99% [2,3]. This variability may be secondary to methods used for screening fatigue and characteristics of the patient groups. In this article, we discuss recognition of CRF and approaches to its management.
Pathophysiology
The specific pathophysiologic mechanism underlying CRF is unknown, making targeted treatment a challenge. The multidimensional and subjective nature of CRF has limited the development of research methodologies to explain this condition. However, research has been done in both human and animal models, and several theories have been proposed to explain the pathophysiology of CRF. While pro-inflammatory cytokines remain the central factor playing a significant role at multiple levels in CRF, there may be a complex interplay of more than 1 mechanism contributing to fatigue in an individual patient.
Central Nervous System Disturbances
The basal ganglia are known to influence motivation. Lack of motivation and drive may cause failure to complete physical and mental tasks, even with preserved cognitive ability and motor function. In a study of melanoma patients receiving interferon, increased activity of the basal ganglia and the cerebellum resulted in higher fatigue scores [4]. Higher levels of cytokines may alter blood flow to the cerebellum and lead to the perception of fatigue. In a study of 12 patients and matched controls, when patients were asked to perform sustained elbow flexion until they perceived exhaustion, CRF patients perceived physical exhaustion sooner than controls. In CRF patients in this study, muscle fatigue measured by electromyogram was less than that in healthy individuals at the time of exhaustion, suggesting the role of the central nervous system in CRF [5]. However, there is not enough evidence at this time to support central nervous system disturbance as the main contributing factor to fatigue in cancer patients.
Circadian Rhythm Dysregulation
Circadian rhythm is regulated by the suprachiasmatic nucleus in the hypothalamus through cortisol and melatonin. Sleep disturbances occur with disruption of the circadian rhythm. Tumor-related peptides such as epidermal growth factor or alterations in serotonin and cortisol can influence the suprachiasmatic nucleus and the complex signaling pathways [2]. Positive feedback loops that are activated by cortisol under the influence of cytokines may lead to continuous cytokine production and altered circadian rhythm. Bower et al showed that changes in the cortisol curve influence fatigue in breast cancer survivors [6]. These patients had a late evening peak in cortisol levels, compared with an early morning peak in individuals without cancer.
Inhibition of Hypothalamic–Pituitary–Adrenal Axis
The hypothalamic–pituitary–adrenal (HPA) axis regulates the release of the stress hormone cortisol. One of several hypotheses advanced to explain the effect of serotonin and the HPA axis on CRF suggests that lower serotonin levels cause decreased activation of 5-hydroxytrytophan 1-a (5-HT1-a) receptors in the hypothalamus, leading to decreased activity of the HPA axis [6]. The inhibition of the HPA axis may occur with higher levels of serotonin as well [7]. The 5-HT1-a receptors are also triggered by cytokines. However, the correction of serotonin levels by antidepressants was not shown to improve fatigue [8]. Inhibition of the HPA axis can also lead to lower testosterone, progesterone, or estrogen levels, which may indirectly contribute to fatigue [2].
Skeletal Muscle Effect
Chemotherapy- and tumor-related cachexia have a direct effect on the metabolism of skeletal muscles. This effect may lead to impaired adenosine triphosphate (ATP) generation during muscle contraction [9]. ATP infusion improved muscle strength in one trial, but this was not confirmed in another trial [10,11]. Muscle contraction studies showed no differences in the contractile properties of muscles in fatigued patients who failed earlier in motor tasks and healthy controls [12]. This finding suggests that there could be a failure of skeletal muscle activation by the central nervous system or inhibition of skeletal muscle activity. Cytokines and other neurotransmitters activate vagal efferent nerve fibers, which may lead to reflex inhibition in skeletal muscles [13,14].
Pro-inflammatory Cytokines
Tumors or treatment of them may cause tissue injury, which triggers immune cells to release cytokines, signaling the brain to manifest the symptom fatigue. Inflammatory pathways are influenced by psychological, behavioral, and biological factors, which play a role as risk factors in CRF. Interleukin 6 (IL-6), interleukin-1 receptor antagonist, interleukin-1, and tumor necrosis factor (TNF) have been shown to be elevated in fatigued patients being treated for leukemia and non-Hodgkin lymphoma [15]. IL-6 was also associated with increased fatigue in breast cancer survivors [16]. Similar findings were reported in patients undergoing stem cell transplantation and high-dose chemotherapy [17]. Elevated levels of IL-6 and C-reactive protein were also linked to fatigue in terminally ill cancer patients [18,19]. Furthermore, TNF-α signaling was associated with post-chemotherapy fatigue in breast cancer patients [20]. Leukocytes in breast cancer survivors with fatigue also have increased gene expression of pro-inflammatory cytokines, emphasizing the role of cytokines and inflammation in the pathogenesis of CRF [21].
Other Hypotheses
Several other hypotheses for CRF pathogenesis have been proposed. Activation of latent viruses such as Epstein-Barr virus, lack of social support [22], genetic alterations in immune pathway [23], epigenetic changes [24], accumulation of neurotoxic metabolites and depletion of serotonin by indoleamine 2,3-dioxygenase pathway activation [25], elevated vascular endothelial growth factor levels [26], and hypoxia-related organ dysfunction due to anemia or hemoglobin dysfunction [13] all have been postulated to cause CRF.
Approach to Evaluation and Treatment
Screening
Because patients and health care professionals may be unaware of the treatment options available for CRF, patients may not report fatigue levels to their clinicians, and clinicians may not understand the impact of fatigue on their patients’ quality of life. This leads to underrecognition of the problem. The NCCN recommends screening every cancer patient and post-treatment survivor for fatigue [2]. Patients should be screened at their first visit and then at periodic intervals during and after cancer treatment.
Many scales are available to screen patients for CRF in clinical practice and clinical trials [27]. A single item that asks patients to rate their fatigue on a scale from 0 to 10—in which 0 indicates no fatigue, 1 to 3 indicates mild fatigue, 4 to 6 indicates moderate fatigue, 7 to 9 indicates severe fatigue, and 10 indicates the worst fatigue imaginable—is commonly used to screen for CRF [2]. This scale was adapted from the MD Anderson Symptom Inventory scale and is based on a large nationwide study of cancer patients and survivors [28]. The statistically derived cutoff points in this study are consistent with other scales such as the Brief Fatigue Inventory (BFI) and support the cutoff points (4–6 for moderate and ≥ 7 for severe fatigue) used in various fatigue management guidelines. Furthermore, studies of fatigue in cancer patients have revealed a marked decrease in physical function at levels of 7 or higher, suggesting 7 as an optimal cutoff to identify severe fatigue [29,30]. The Visual Analog Scale is another simple-to-use tool that helps in understanding variations in fatigue throughout the course of the day [31]. The 9-item BFI is often used in clinical trials [29]. It measures the severity of fatigue over the previous 24 hours and has been validated in non-English speaking patients [32].
CRF affects not only the somatic domain, but also the cognitive, behavioral, and affective domains; therefore, multidimensional scales have been developed for screening. One such tool is the Multidimensional Fatigue Inventory, which measures general, physical, mental, and emotional fatigue domains as well as activity and compares them with those of individuals without cancer [33,34]. The Functional Assessment of Cancer Therapy for Fatigue (FACT-F) is a 13-item questionnaire that has been used to measure CRF in clinical trials as well as in patients receiving various treatments [35].
Although many scales are available, the validity of self-reporting on simple fatigue-rating scales is equal to or better than most complex, lengthy scales [36]. Therefore, unidimensional tools such as the numeric rating scale of 0–10 are commonly used in clinical practice. Mild fatigue (0–3) requires periodic re-evaluation, and moderate and severe fatigue need further evaluation and management [37].
Primary Evaluation
This phase involves a focused history and physical examination and assessment of concurrent symptoms and contributing factors.
History and Physical Examination
A detailed history of the patient’s malignancy and type of previous and current treatment may help reveal the cause of fatigue. New-onset fatigue or increase in fatigue may be related to the progression of disease in patients with active malignancy or recurrence of cancer in survivors. These patients may require appropriate testing to assess the underlying disease pattern. A detailed review of systems may help identify some of the contributing factors, which are discussed below. A detailed history regarding medications, including over-the-counter drugs, complementary agents, and past and prior cancer therapies, is helpful as medications can contribute to fatigue. For example, opioids may cause drowsiness and fatigue, which could be improved by dose adjustments. A focused history of fatigue should be obtained in all patients with moderate to severe CRF, which includes the onset, pattern, duration, associated or alleviating factors, and interference with functioning, including activities of daily living [37]. Physical examination should focus on identifying signs of organ dysfunction and features of substance or alcohol abuse which may cause poor sleep and fatigue.
Assessment of Contributing Factors
The management of fatigue should be multifactorial, with a comprehensive assessment and treatment plan to address all modifiable fatigue etiologies. The Table lists potential contributing factors to fatigue that should be considered when evaluating patients for CRF; several common conditions are discussed below.
Anemia. Anemia has been correlated with fatigue and quality of life. In a study of 4382 cancer patients receiving chemotherapy, quality-of-life measures using FACT-Anemia scores improved with increased hemoglobin levels [38]. Cancer patients may have anemia due to marrow-suppressing effects of chemotherapy and may also have iron deficiency anemia due to blood loss or autoimmune hemolytic anemia. Therefore, a detailed work-up is required to identify the etiology of anemia. Patients with CRF whose anemia is related to chemotherapy or anemia of chronic disease may benefit from red blood cell transfusion or erythropoiesis-stimulating agents (ESAs). ESAs have been studied extensively; however, their use is controversial because of concerns about thromboembolic side effects leading to adverse outcomes [39]. Also, ESA therapy is not recommended in patients with hematologic malignancies. ESA use should be restricted to patients with chemotherapy-related anemia with hemoglobin below 10 mg/dL and should be discontinued in 6 to 8 weeks if patients do not respond [40]. Other patients may benefit from blood transfusions, which were shown to help in patients with hemoglobin levels between 7.5 and 8.5 g/dL [41].
Sleep disturbance. Poor sleep is common in fatigued cancer survivors [42]. Pro-inflammatory cytokines can disrupt the sleep–wake cycle, causing changes in the HPA axis and neuroendocrine system, which in turn may lead to increasing fatigue. Heckler et al showed that improvement in nighttime sleep leads to improvement of fatigue [43]. Cognitive behavioral therapy and sleep hygiene are important in caring for patients with CRF and poor sleep [44]. Taking a warm bath and/or drinking a glass of milk before bedtime, avoiding caffeinated drinks, and avoiding frequent napping in the day might help. Some patients may require medications such as benzodiazepines or non-benzodiazepine hypnotics (eg, zolpidem) to promote sleep [45]. Melatonin agonists are approved for insomnia in the United states, but not in Europe [46].
Malnutrition. Patients with advanced-stage cancer and with cancers affecting the gastrointestinal tract frequently develop mechanical bowel obstructions, especially at the end of their life, which cause malnutrition. Chemotherapy-related nausea and vomiting may also cause poor oral intake and malnutrition, causing fatigue from muscle weakness. Dehydration and electrolyte imbalances frequently occur as a result of poor oral intake, which might worsen fatigue. In our experience, modifying dietary intake with appropriate caloric exchanges with the help of a nutrition expert has lessened fatigue in some patients. However, terminally ill patients are advised to eat based on their comfort.
Medical comorbidities. Congestive heart failure from anthracycline chemotherapy, hypothyroidism after radiation therapy for head and neck cancers, renal failure, or hepatic failure from chemotherapy may indirectly lead to fatigue. Chemotherapy, opioids, and steroids may cause hypogonadism, which can contribute to fatigue in men [47].
Assessment of Concurrent Symptoms
Depression is common in cancer patients and coexists with pain, insomnia, fatigue, and anxiety as a symptom cluster [48]. A symptom cluster is defined as 2 or more concurrent and interrelated symptoms occurring together; treating of one of these symptoms without addressing other symptoms is not effective [49]. Therefore, screening for and management of depression, anxiety, and insomnia play an important role in the management of CRF.
Physical symptoms due to the tumor or to therapy—such as pain, dyspnea, nausea, and decreased physical activity—may also contribute to fatigue both directly and indirectly. Patients with lung cancer may have hypoxemia, which can contribute to dyspnea with activity and a perception of fatigue. Optimal management of pain and other physical symptoms in patients with cancer may significantly alleviate fatigue [50].
Management
Management of CRF is individualized based on the patient’s clinical status: active cancer treatment, survivor, or end of life. Education and counselling of patients and their caregivers play an important role in CRF. NCCN guidelines recommend focusing on pain control, distress management, energy conservation, physical activity, nutrition, and sleep hygiene.
Nonpharmacologic Interventions
Energy conservation. Energy conservation strategies, in which patients are advised to set priorities and realistic expectations, are highly recommended. Some energy-conserving strategies are to pace oneself, delegate and schedule activities at times of peak energy, postpone nonessential activities, attend to 1 activity at a time, structure daily routines, and maintain a diary to identify their peak energy period and structure activities around that time [51,52]. When patients approach the end of life, increasing fatigue may limit their activity level, and they may depend on caregivers for assistance with activities of daily living, monitoring treatment-related adverse effects, and taking medications, especially elderly patients [53].
Cognitive behavioral therapy. Cognitive behavioral therapy (CBT) has been shown to improve CRF during active treatment, and the benefits persist for a minimum of 2 years after therapy [54]. CBT interventions that optimize sleep quality may improve fatigue [55]. More studies are needed to understand whether referral to a psychologist for formal CBT is required. Randomized clinical trials (RCTs) showed patient fatigue education, learned self-care, coping techniques, and balancing rest and activity benefit patients with CRF [56].
Exercise. Physical activity is highly encouraged in patients with CRF. Exercise increases muscle protein synthesis, improves cytokine response, and decreases the rate of sarcopenia in healthy populations [57]. Studies have shown that exercise helps CRF at all phases of the cancer journey, including radiation therapy, chemotherapy, and survivorship [58]. Some patients may feel less motivated to exercise and may not believe that exercise is possible or could potentially help them. Counselling is needed for such patients.
Older cancer survivors have a decline in their functional capacity and reduced muscle mass. Exercise can improve cardiorespiratory fitness, muscle strength, and body composition [57]. Exercise not only helps at the cellular level but also has psychosocial benefits from improved self-esteem. Therefore, exercise may be recommended not only for younger patients, but also in the older population, who may have comorbidities and less motivation than younger patients.
In a meta-analysis of 56 randomized controlled trials involving 4068 participants, aerobic exercise was found to have beneficial effects on CRF for patients during and after chemotherapy, specifically for patients with solid tumors [59]. In another meta-analysis of breast and prostate cancer survivors, a combination of aerobic exercise with resistance training (3–6 metabolic equivalents, 60%–80% range of motion) was shown to reduce CRF more than aerobic exercise alone [60]. This effect was also shown in an RCT of 160 patients with stage 0 to III breast cancer undergoing radiation therapy [61]. The control group in this study had a group-based non-exercise intervention/relaxation; therefore, the study showed that the effect of resistance training extends beyond the psychosocial benefits of group-based interventions. The intervention comprised 8 progressive machine-based resistance exercises (3 sets, 8–12 repetitions at 60%–80% of 1 repetition maximum) for 60 minutes twice weekly for 12 weeks. However, fatigue assessment questionnaire scores showed benefits in the physical fatigue but not the affective and cognitive components.
The American Society of Clinical Oncology’s guidelines for cancer survivors with fatigue recommends 150 minutes of moderate aerobic exercise (eg, fast walking, cycling, or swimming) per week, with 2 or 3 sessions of strength training per week [62]. An individualized approach to exercise is recommended, as patients’ ability to perform certain types of exercises may be limited by thrombocytopenia, neutropenia, or lytic bone metastasis. Routine use of pre-exercise cardiovascular testing is not recommended but may be considered in high-risk populations, especially patients with risk factors for coronary heart disease and diabetes [63]. Patients withcomorbidities, substantial deconditioning, functional and anatomic defects, or recent major surgery may benefit from referral to physical therapy [37]. Patients near end of life may also benefit from an exercise program, as demonstrated in several studies that showed benefit in CRF and quality of life [64,65]. We recommend that physicians use their best clinical judgement in suggesting the type and intensity of exercise program, as it may not be feasible in some patients.
Mind-body interventions. Mindfulness-based stress reduction (MBSR) has shown promise in breast cancer survivors, who reported immediate improvements in fatigue severity that continued up to 6 weeks after cessation of the training [66]. Prior studies had similar findings, suggesting that MBSR modestly decreases fatigue and sleep disturbances and has a greater effect on the degree to which symptoms interfere with many facets of life [67].
Yoga. A study of a yoga intervention showed a benefit in older cancer survivors [68]. In breast cancer patients undergoing chemotherapy, yoga was shown to benefit not only physical fatigue, but also cognitive fatigue [69]. DVD-based yoga had benefits similar to strengthening exercises in a study of 34 early-stage breast cancer survivors with CRF [70]. More studies are needed in men and patients and survivors of other cancers, as most studies of yoga were conducted in women with breast cancer.
Tai chi/qigong. Like yoga, tai chi and qigong are practices of meditative movement. These practices use postures or movements with a focus on breath and a meditative state to bring about deep states of relaxation. Qigong is a series of simple, repeated practices including body posture/movement, breath practice, and meditation performed in synchrony. Tai chi easy (TCE) is a simplified set of common, repetitive tai chi movements. In a trial, qigong/TCE was compared with sham qigong, which had physical movements but no breathing or meditative practice. Breast cancer survivors in the qigong/TCE group had improved fatigue scores, and the effect persisted for 3 months [71]. Additional research is needed in this area.
Acupuncture. An RCT in breast cancer patients with CRF showed an improvement in the mean general fatigue score (per the Multidimensional Fatigue Inventory) in patients who received acupuncture versus those who did not (−3.11 [95% confidence interval −3.97 to −2.25]; P < 0.001) at 6 weeks. Improvements were seen in both the mental and physical aspects of fatigue [72]. However, Deng et al noted that true acupuncture was no more effective than sham acupuncture for reducing post-chemotherapy chronic fatigue [73]. Presently, there is not sufficient evidence to evaluate the benefits of acupuncture in CRF.
Other modalities. Massage therapy, music therapy, hypnosis, therapeutic touch, biofield therapies, relaxation, and reiki are other therapies for which few studies have been done, with mixed results, and additional research is needed [74]. Currently, there are not sufficient data to recommend any of these modalities.
Pharmacologic Interventions
Psychostimulants. Methylphenidate and modafinil are psychostimulants or wakefulness-promoting agents. Pilot studies showed benefit from methylphenidate and modafinil in CRF [75–77], but RCTs have yielded mixed results. Therefore, in patients with severe fatigue during cancer therapy, the initial management strategy involves evaluation and treatment of medical conditions such as anemia and a trial of non-pharmacological strategies as discussed above. If symptoms persist, then a therapeutic trial of a psychostimulant may be considered per NCCN guidelines for patients undergoing active cancer treatment [37].
Methylphenidate directly stimulates adrenergic receptors and indirectly releases dopamine and norepinephrine from presynaptic terminals, which may explain why the drug benefits patients receiving opioid-induced sedation. It is a commonly studied psychostimulant, though its mechanism of action in CRF is unclear. RCTs of methylphenidate have resulted in a wide range of findings due to the heterogeneity of study populations and variations in the dosage of methylphenidate. A meta-analysis of 7 studies indicates that methylphenidate benefitted the subgroup of patients with CRF [78]. Likewise, in an analysis of 5 RCTs, Minton et al showed a benefit of psychostimulants in fatigue compared with placebo [79]. However, another study of methylphenidate in patients with CRF showed a benefit only in patients with severe fatigue or advanced disease [80]. Methylphenidate was found to benefit cancer patients receiving opioid-induced sedation, as methylphenidate promotes wakefulness, though fatigue was not studied specifically [81]. In a trial with 30 hospice patients in which the methylphenidate dose was titrated based on response and adverse effects, Kerr at al found that the drug improved fatigue in a dose-dependent manner [82]. However, a study in patients with CRF at the University of Texas MD Anderson Cancer Center found no significant difference in BFI scores between patients receiving methylphenidate and those receiving placebo at the end of 2 weeks of treatment [83]. Also, other RCTs in patients undergoing adjuvant chemotherapy for breast cancer [84] and patients receiving radiation therapy for brain tumors [85] failed to demonstrate the efficacy of methylphenidate in CRF. It should be used cautiously after ruling out other causes of fatigue. The drug is overall well tolerated and side effects include headache and nausea.
Modafinil is a non-amphetamine psychostimulant that has been approved for the treatment of narcolepsy. In a trial studying the effect of modafinil on patients receiving docetaxel-based chemotherapy for metastatic breast or prostate cancer, there was a modest but not statistically significant improvement in fatigue scores on the MD Anderson Symptom Inventory compared with placebo. Nausea and vomiting were higher in the modafinil arm than in the placebo arm [86]. Similarly, modafinil was not superior to placebo for CRF in 208 patients with non-squamous cell lung cancer not undergoing chemotherapy or radiation [87]. A placebo effect was also noted in patients with multiple myeloma [88] and patients with primary brain tumors [89]. In a phase 3, multicenter, randomized, placebo-controlled, double-blind clinical trial of modafinil for CRF in 867 patients undergoing chemotherapy, there was a reduction in fatigue only for patients with severe baseline fatigue, with no significant effect on mild to moderate fatigue [90]. In another recent study, modafinil was shown to reduce depressive symptoms only in patients with severe fatigue (BFI item 3 score ≥ 7) [91]. This finding is consistent with previous studies showing benefit in patients with high baseline fatigue, but additional RCTs are needed to provide clarity. NCCN guidelines do not recommend the use of modafinil to treat CRF [37].
Other pharmacologic interventions. Corticosteroids are often used for symptom control in cancer patients. These drugs have anti-inflammatory effects through their modulation of pro-inflammatory cytokines [92]. In a RCT evaluating the efficacy of corticosteroids, patients receiving dexamethasone (4 mg twice daily) experienced significant improvement in their FACT-F scores compared with patients receiving placebo [93]. A similar benefit in fatigue was demonstrated in another study of methylprednisolone (32 mg daily) versus placebo [94]. Despite the benefits of steroids, their adverse effects, such as mood swings, gastritis, hyperglycemia, and immune suppression, limit their long-term use. Therefore, the use of steroids should be restricted to terminally ill fatigued patients with other symptoms such as anorexia, brain metastasis, or pain related to bone metastasis [37].
Testosterone replacement has been shown to diminish fatigue in non-cancer patients. Many men with advanced cancer have hypogonadism leading to low serum testosterone, which may cause fatigue. In a small trial in which cancer patients with hypogonadism received intramuscular testosterone every 14 days or placebo, the group receiving testosterone showed improvement in FACT-F scores, but there was no significant difference in FACT-F scores between the 2 groups [95].
Antidepressants have failed to demonstrate benefit in CRF without depression [8]. However, if a patient has both fatigue and depression, antidepressants may help [96]. A selective serotonin receptor inhibitor is recommended as a first-line antidepressant [97]. Patients with cancer are often receiving multiple medications, and medication interactions should be considered to prevent adverse events such as serotonin syndrome.
Complementary and Alternative Supplements
Studies using vitamin supplementation have been inconclusive in patients with CRF [74]. The use of other dietary supplements has yielded mixed results, and coenzyme Q has shown no benefit for patients with CRF [98].
The benefit of ginseng was studied in a RCT involving 364 patients with CRF. There was an improvement in Multidimensional Fatigue Symptom Inventory-short form (MFSI-SF) scores at 8 weeks in patients receiving 2000 mg of Wisconsin ginseng compared with patients receiving placebo [99]. Patients on active treatment had greater improvement as compared to the post-treatment group in this trial. In another study of high-dose panax ginseng (ginseng root) at 800 mg daily for 29 days, patients had improvement of CRF as well as overall quality of life, appetite, and sleep at night. It was also well tolerated with few adverse effects [100]. Interaction with warfarin, calcium channel blockers, antiplatelet agents, thrombolytic agents, imatinib, and other agents may occur; therefore, ginseng must be used with careful monitoring in selected patients. There is not enough evidence at this time to support the routine use of ginseng in CRF.
The seed extract of the guarana plant (Paullinia cupana) traditionally has been used as a stimulant. An improvement in fatigue scores was seen with the use of oral guarana (100 mg daily) at the end of 21 days in breast cancer patients receiving chemotherapy [101]. Further studies are needed for these results to be generalized and to understand the adverse effects and interaction profile of guarana.
Re-evaluation
Patients who have completed cancer treatment must be monitored for fatigue over the long term, as fatigue may exist beyond the period of active treatment. Many studies have shown fatigue in breast cancer survivors, and fatigue has been demonstrated in survivors of colorectal, lung, and prostate cancers as well as myeloproliferative neoplasms [28]. Therefore, it is important to screen patients for fatigue during follow-up visits. There are currently no studies evaluating the long-term treatment of fatigue. In our experience, the timing of follow-up depends on the level of fatigue and interventions prescribed. Once fatigue is stabilized to a level with which the patient is able to cope, the time interval for follow up may be lengthened. Annual visits may suffice in patients with mild fatigue. Follow-up of patients with moderate to severe fatigue depends on the level of fatigue, the ability to cope, choice of treatment, and presence of contributing factors.
Conclusion
CRF is a complex condition that places a significant burden on patients and caregivers, resulting in emotional distress, poor functioning, and suffering. Fatigue can occur before, during, and long after cancer treatment. The approach to CRF begins with screening for and educating patients and their caregivers about the symptoms. Many screening scales are available that may be used to follow patients’ progress over time. The evaluation and management of contributing conditions may help improve fatigue. If the fatigue persists, an individualized approach with a combination of nonpharmacologic and pharmacologic approaches should be considered. More research is needed to understand brain signaling pathways, cytokine changes, and genomic changes in cancer patients with fatigue. Though many hypotheses have been proposed, to date there is no biological marker to assess this condition. Biomarker research needs to be advanced to help to identify patients at risk for fatigue. As cytokines have a major role in CRF, targeted therapy to block cytokine pathways may also be explored in the future.
Acknowledgment: Bryan Tutt provided editorial assistance.
Corresponding author: Carmelita P. Escalante, MD, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX 77030, cescalan@mdanderson.org.
Financial disclosures: None.
1. Scherber RM, Kosiorek HE, Senyak Z, et al. Comprehensively understanding fatigue in patients with myeloproliferative neoplasms. Cancer 2016;122:477–85.
2. Neefjes EC, van der Vorst MJ, Blauwhoff-Buskermolen S, Verheul HM. Aiming for a better understanding and management of cancer-related fatigue. Oncologist 2013;18:1135–43.
3. Radbruch L, Strasser F, Elsner F, et al. Fatigue in palliative care patients -- an EAPC approach. Palliat Med 2008;22:13–32.
4. Capuron L, Pagnoni G, Demetrashvili MF, et al. Basal ganglia hypermetabolism and symptoms of fatigue during interferon-alpha therapy. Neuropsychopharmacology 2007;32:2384–92.
5. Kisiel-Sajewicz K, Siemionow V, Seyidova-Khoshknabi D, et al. Myoelectrical manifestation of fatigue less prominent in patients with cancer related fatigue. PLoS One 2013;8:e83636.
6. Bower JE, Ganz PA, Aziz N. Altered cortisol response to psychologic stress in breast cancer survivors with persistent fatigue. Psychosom Med 2005;67:277–80.
7. Barsevick A, Frost M, Zwinderman A, et al. I’m so tired: biological and genetic mechanisms of cancer-related fatigue. Qual Life Res 2010;19:1419–27.
8. Morrow GR, Hickok JT, Roscoe JA, et al. Differential effects of paroxetine on fatigue and depression: a randomized, double-blind trial from the University of Rochester Cancer Center Community Clinical Oncology Program. J Clin Oncol 2003;21:4635–41.
9. Fontes-Oliveira CC, Busquets S, Toledo M, et al. Mitochondrial and sarcoplasmic reticulum abnormalities in cancer cachexia: altered energetic efficiency? Biochim Biophys Acta 2013;1830:2770–8.
10. Agteresch HJ, Dagnelie PC, van der Gaast A, et al. Randomized clinical trial of adenosine 5’-triphosphate in patients with advanced non-small-cell lung cancer. J Natl Cancer Inst 2000;92:321–8.
11. Beijer S, Hupperets PS, van den Borne BE, et al. Randomized clinical trial on the effects of adenosine 5’-triphosphate infusions on quality of life, functional status, and fatigue in preterminal cancer patients. J Pain Symptom Manage 2010;40:520–30.
12. Kisiel-Sajewicz K, Davis MP, Siemionow V, et al. Lack of muscle contractile property changes at the time of perceived physical exhaustion suggests central mechanisms contributing to early motor task failure in patients with cancer-related fatigue. J Pain Symptom Manage 2012;44:351–61.
13. Ryan JL, Carroll JK, Ryan EP, et al. Mechanisms of cancer-related fatigue. Oncologist 2007;12 Suppl 1:22–34.
14. Seruga B, Zhang H, Bernstein LJ, Tannock IF. Cytokines and their relationship to the symptoms and outcome of cancer. Nat Rev Cancer 2008;8:887–99.
15. Wang XS, Giralt SA, Mendoza TR, et al. Clinical factors associated with cancer-related fatigue in patients being treated for leukemia and non-Hodgkin’s lymphoma. J Clin Oncol 2002;20:1319–28.
16. Collado-Hidalgo A, Bower JE, Ganz PA, et al. Inflammatory biomarkers for persistent fatigue in breast cancer survivors. Clin Cancer Res 2006;12:2759–66.
17. Wang XS, Shi Q, Williams LA, et al. Serum interleukin-6 predicts the development of multiple symptoms at nadir of allogeneic hematopoietic stem cell transplantation. Cancer 2008;113:2102–9.
18. Inagaki M, Isono M, Okuyama T, et al. Plasma interleukin-6 and fatigue in terminally ill cancer patients. J Pain Symptom Manage 2008;35:153–61.
19. Laird BJ, McMillan DC, Fayers P, et al. The systemic inflammatory response and its relationship to pain and other symptoms in advanced cancer. Oncologist 2013;18:1050–5.
20. Bower JE, Ganz PA, Irwin MR, et al. Inflammation and behavioral symptoms after breast cancer treatment: do fatigue, depression, and sleep disturbance share a common underlying mechanism? J Clin Oncol 2011;29:3517–22.
21. Whistler T, Taylor R, Craddock RC, et al. Gene expression correlates of unexplained fatigue. Pharmacogenomics 2006;7:395–405.
22. Fagundes CP, Bennett JM, Alfano CM, et al. Social support and socioeconomic status interact to predict Epstein-Barr virus latency in women awaiting diagnosis or newly diagnosed with breast cancer. Health Psychol 2012;31:11–19.
23. Landmark-Hoyvik H, Reinertsen KV, Loge JH, et al. Alterations of gene expression in blood cells associated with chronic fatigue in breast cancer survivors. Pharmacogenomics J 2009;9:333–40.
24. Smith AK, Conneely KN, Pace TW, et al. Epigenetic changes associated with inflammation in breast cancer patients treated with chemotherapy. Brain Behav Immun 2014;38:227–36.
25. Kim S, Miller BJ, Stefanek ME, Miller AH. Inflammation-induced activation of the indoleamine 2,3-dioxygenase pathway: Relevance to cancer-related fatigue. Cancer 2015;121:2129–36.
26. Mills PJ, Parker B, Dimsdale JE, et al. The relationship between fatigue and quality of life and inflammation during anthracycline-based chemotherapy in breast cancer. Biol Psychol 2005;69:85–96.
27. Jean-Pierre P, Figueroa-Moseley CD, Kohli S, et al. Assessment of cancer-related fatigue: implications for clinical diagnosis and treatment. Oncologist 2007;12 Suppl 1:11–21.
28. Wang XS, Zhao F, Fisch MJ, et al. Prevalence and characteristics of moderate to severe fatigue: a multicenter study in cancer patients and survivors. Cancer 2014;120:425–32.
29. Mendoza TR, Wang XS, Cleeland CS, et al. The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer 1999;85:1186–96.
30. Mendoza ME, Capafons A, Gralow JR, et al. Randomized controlled trial of the Valencia model of waking hypnosis plus CBT for pain, fatigue, and sleep management in patients with cancer and cancer survivors. Psychooncology 2016 Jul 28.
31. Glaus A. Assessment of fatigue in cancer and non-cancer patients and in healthy individuals. Support Care Cancer 1993;1:305–15.
32. Seyidova-Khoshknabi D, Davis MP, Walsh D. A systematic review of cancer-related fatigue measurement questionnaires. Am J Hosp Palliat Care 2011;28:119–29.
33. Holzner B, Kemmler G, Greil R, et al. The impact of hemoglobin levels on fatigue and quality of life in cancer patients. Ann Oncol 2002;13:965–73.
34. Stein KD, Jacobsen PB, Blanchard CM, Thors C. Further validation of the multidimensional fatigue symptom inventory-short form. J Pain Symptom Manage 2004;27:14–23.
35. Hwang SS, Chang VT, Rue M, Kasimis B. Multidimensional independent predictors of cancer-related fatigue. J Pain Symptom Manage 2003;26:604–14.
36. Peterspm DR. Scope and generality of verbally defined personality factors. Psychol Rev 1965;72:48–59.
37. Berger AM, Abernethy AP, Atkinson A, et al. NCCN Clinical Practice Guidelines Cancer-related fatigue. J Natl Compr Canc Netw 2010;8:904–31.
38. Crawford J, Cella D, Cleeland CS, et al. Relationship between changes in hemoglobin level and quality of life during chemotherapy in anemic cancer patients receiving epoetin alfa therapy. Cancer 2002;95:888–95.
39. Tonia T, Mettler A, Robert N, et al. Erythropoietin or darbepoetin for patients with cancer. Cochrane Database Syst Rev 2012;12:CD003407.
40. Rizzo JD, Brouwers M, Hurley P, et al. American Society of Hematology/American Society of Clinical Oncology clinical practice guideline update on the use of epoetin and darbepoetin in adult patients with cancer. Blood 2010;116:4045–59.
41. Preston NJ, Hurlow A, Brine J, Bennett MI. Blood transfusions for anaemia in patients with advanced cancer. Cochrane Database Syst Rev 2012(2):CD009007.
42. Minton O, Stone PC. A comparison of cognitive function, sleep and activity levels in disease-free breast cancer patients with or without cancer-related fatigue syndrome. BMJ Support Palliat Care 2012;2:231–8.
43. Heckler CE, Garland SN, Peoples AR, et al. Cognitive behavioral therapy for insomnia, but not armodafinil, improves fatigue in cancer survivors with insomnia: a randomized placebo-controlled trial. Support Care Cancer 2016;24:2059–66.
44. Howell D, Oliver TK, Keller-Olaman S, et al. Sleep disturbance in adults with cancer: a systematic review of evidence for best practices in assessment and management for clinical practice. Ann Oncol 2014;25:791–800.
45. Wilt TJ, MacDonald R, Brasure M, et al. Pharmacologic treatment of insomnia disorder: an evidence report for a clinical practice guideline by the American College of Physicians. Ann Intern Med 2016;165:103–12.
46. Kuriyama A, Honda M, Hayashino Y. Ramelteon for the treatment of insomnia in adults: a systematic review and meta-analysis. Sleep Med 2014;15:385–92.
47. Strasser F, Palmer JL, Schover LR, et al. The impact of hypogonadism and autonomic dysfunction on fatigue, emotional function, and sexual desire in male patients with advanced cancer: a pilot study. Cancer 2006;107:2949–57.
48. Agasi-Idenburg SC, Thong MS, Punt CJ, et al. Comparison of symptom clusters associated with fatigue in older and younger survivors of colorectal cancer. Support Care Cancer 2017;25:625–32.
49. Miaskowski C, Aouizerat BE. Is there a biological basis for the clustering of symptoms? Semin Oncol Nurs 2007;23:99–105.
50. de Raaf PJ, de Klerk C, Timman R, et al. Systematic monitoring and treatment of physical symptoms to alleviate fatigue in patients with advanced cancer: a randomized controlled trial. J Clin Oncol 2013;31:716–23.
51. Barsevick AM, Whitmer K, Sweeney C, Nail LM. A pilot study examining energy conservation for cancer treatment-related fatigue. Cancer Nurs 2002;25:333–41.
52. Barsevick AM, Dudley W, Beck S, et a;. A randomized clinical trial of energy conservation for patients with cancer-related fatigue. Cancer 2004;100:1302–10.
53. Luciani A, Jacobsen PB, Extermann M, et al. Fatigue and functional dependence in older cancer patients. Am J Clin Oncol 2008;31:424–30.
54. Abrahams HJ, Gielissen MF, Goedendorp MM, et al. A randomized controlled trial of web-based cognitive behavioral therapy for severely fatigued breast cancer survivors (CHANGE-study): study protocol. BMC Cancer 2015;15:765.
55. Quesnel C, Savard J, Simard S, et al. Efficacy of cognitive-behavioral therapy for insomnia in women treated for nonmetastatic breast cancer. J Consult Clin Psychol 2003;71:189–200.
56. Goedendorp MM, Gielissen MF, Verhagen CA, Bleijenberg G. Psychosocial interventions for reducing fatigue during cancer treatment in adults. Cochrane Database Syst Rev 2009(1):CD006953.
57. Greiwe JS, Cheng B, Rubin DC, et al. Resistance exercise decreases skeletal muscle tumor necrosis factor alpha in frail elderly humans. FASEB J 2001;15:475–82.
58. Furmaniak AC, Menig M, Markes MH. Exercise for women receiving adjuvant therapy for breast cancer. Cochrane Database Syst Rev 2016;(9):CD005001.
59. Cramp F, Byron-Daniel J. Exercise for the management of cancer-related fatigue in adults. Cochrane Database Syst Rev 2012;(11):CD006145.
60. Brown JC, Huedo-Medina TB, Pescatello LS, et al. Efficacy of exercise interventions in modulating cancer-related fatigue among adult cancer survivors: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2011;20:123–33.
61. Steindorf K, Schmidt ME, Klassen O, et al. Randomized, controlled trial of resistance training in breast cancer patients receiving adjuvant radiotherapy: results on cancer-related fatigue and quality of life. Ann Oncol 2014;25:2237–43.
62. Bower JE, Bak K, Berger A, et al. Screening, assessment, and management of fatigue in adult survivors of cancer: an American Society of Clinical oncology clinical practice guideline adaptation. J Clin Oncol 2014;32:1840–50.
63. Kenjale AA, Hornsby WE, Crowgey T, et al. Pre-exercise participation cardiovascular screening in a heterogeneous cohort of adult cancer patients. Oncologist 2014;19:999–1005.
64. Oldervoll LM, Loge JH, Paltiel H, et al. The effect of a physical exercise program in palliative care: A phase II study. J Pain Symptom Manage 2006;31:421–30.
65. Porock D, Kristjanson LJ, Tinnelly K, et al. An exercise intervention for advanced cancer patients experiencing fatigue: a pilot study. J Palliat Care 2000;16:30–6.
66. Lengacher CA, Kip KE, Reich RR, et al. A cost-effective mindfulness stress reduction program: a randomized control trial for breast cancer survivors. Nursing Econ 2015;33:210–8, 32.
67. Lengacher CA, Reich RR, Post-White J, et al. Mindfulness based stress reduction in post-treatment breast cancer patients: an examination of symptoms and symptom clusters. J Behav Med 2012;35:86–94.
68. Sprod LK, Fernandez ID, Janelsins MC, et al. Effects of yoga on cancer-related fatigue and global side-effect burden in older cancer survivors. J Geriatr Oncol 2015;6:8–14.
69. Wang G, Wang S, Jiang P, Zeng C. [Effect of Yoga on cancer related fatigue in breast cancer patients with chemotherapy]. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2014;39:1077–82.
70. Stan DL, Croghan KA, Croghan IT, et al. Randomized pilot trial of yoga versus strengthening exercises in breast cancer survivors with cancer-related fatigue. Support Care Cancer 2016;24:4005–15.
71. Larkey LK, Roe DJ, Weihs KL, et al. Randomized controlled trial of Qigong/Tai Chi Easy on cancer-related fatigue in breast cancer survivors. Ann Behav Med 2015;49:165–76.
72. Molassiotis A, Bardy J, Finnegan-John J, et al. Acupuncture for cancer-related fatigue in patients with breast cancer: a pragmatic randomized controlled trial. J Clin Oncol 2012;30:4470–6.
73. Deng G, Chan Y, Sjoberg D, et al. Acupuncture for the treatment of post-chemotherapy chronic fatigue: a randomized, blinded, sham-controlled trial. Support Care Cancer 2013;21:1735–41.
74. Finnegan-John J, Molassiotis A, Richardson A, Ream E. A systematic review of complementary and alternative medicine interventions for the management of cancer-related fatigue. Integr Cancer Ther 2013;12:276–90.
75. Schwartz AL, Thompson JA, Masood N. Interferon-induced fatigue in patients with melanoma: a pilot study of exercise and methylphenidate. Oncol Nurs Forum 2002;29:E85–90.
76. Spathis A, Dhillan R, Booden D, et al. Modafinil for the treatment of fatigue in lung cancer: a pilot study. Palliat Med 2009;23:325–31.
77. Blackhall L, Petroni G, Shu J, et al. A pilot study evaluating the safety and efficacy of modafinal for cancer-related fatigue. J Palliat Med 2009;12:433–9.
78. Qu D, Zhang Z, Yu X, et al. Psychotropic drugs for the management of cancer-related fatigue: a systematic review and meta-analysis. Eur J Cancer Care (Engl) 2015;25:970–9.
79. Minton O, Richardson A, Sharpe M, et al. Drug therapy for the management of cancer-related fatigue. Cochrane Database Syst Rev 2010(7):CD006704.
80. Moraska AR, Sood A, Dakhil SR, et al. Phase III, randomized, double-blind, placebo-controlled study of long-acting methylphenidate for cancer-related fatigue: North Central Cancer Treatment Group NCCTG-N05C7 trial. J Clin Oncol 2010;28:3673–9.
81. Bruera E, Driver L, Barnes EA, et al. Patient-controlled methylphenidate for the management of fatigue in patients with advanced cancer: a preliminary report. J Clin Oncol 2003;21:4439–43.
82. Kerr CW, Drake J, Milch RA, et al. Effects of methylphenidate on fatigue and depression: a randomized, double-blind, placebo-controlled trial. J Pain Symptom Manage 2012;43:68–77.
83. Escalante CP, Meyers C, Reuben JM, et al. A randomized, double-blind, 2-period, placebo-controlled crossover trial of a sustained-release methylphenidate in the treatment of fatigue in cancer patients. Cancer J 2014;20:8–14.
84. Mar Fan HG, Clemons M, Xu W, et al. A randomised, placebo-controlled, double-blind trial of the effects of d-methylphenidate on fatigue and cognitive dysfunction in women undergoing adjuvant chemotherapy for breast cancer. Support Care Cancer 2008;16:577–83.
85. Butler JM Jr, Case LD, Atkins J, et al. A phase III, double-blind, placebo-controlled prospective randomized clinical trial of d-threo-methylphenidate HCl in brain tumor patients receiving radiation therapy. Int J Radiat Oncol Biol Phys 2007;69:1496–501.
86. Hovey E, de Souza P, Marx G, et al. Phase III, randomized, double-blind, placebo-controlled study of modafinil for fatigue in patients treated with docetaxel-based chemotherapy. Support Care Cancer 2014;22:1233–42.
87. Spathis A, Fife K, Blackhall F, et al. Modafinil for the treatment of fatigue in lung cancer: results of a placebo-controlled, double-blind, randomized trial. J Clin Oncol 2014;32:1882–8.
88. Berenson JR, Yellin O, Shamasunder HK, et al. A phase 3 trial of armodafinil for the treatment of cancer-related fatigue for patients with multiple myeloma. Support Care Cancer 2015;23:1503–12.
89. Boele FW, Douw L, de Groot M, et al. The effect of modafinil on fatigue, cognitive functioning, and mood in primary brain tumor patients: a multicenter randomized controlled trial. Neuro Oncol 2013;15:1420–8.
90. Jean-Pierre P, Morrow GR, Roscoe JA, et al. A phase 3 randomized, placebo-controlled, double-blind, clinical trial of the effect of modafinil on cancer-related fatigue among 631 patients receiving chemotherapy: a University of Rochester Cancer Center Community Clinical Oncology Program Research base study. Cancer 2010;116:3513–20.
91. Conley CC, Kamen CS, Heckler CE, et al. Modafinil moderates the relationship between cancer-related fatigue and depression in 541 patients receiving chemotherapy. J Clin Psychopharmacol 2016;36:82–5.
92. Brattsand R, Linden M. Cytokine modulation by glucocorticoids: mechanisms and actions in cellular studies. Aliment Pharmacol Ther 1996;10 Suppl 2:81–90.
93. Yennurajalingam S, Frisbee-Hume S, Palmer JL, et al. Reduction of cancer-related fatigue with dexamethasone: a double-blind, randomized, placebo-controlled trial in patients with advanced cancer. J Clin Oncol 2013;31:3076–82.
94. Bruera E, Roca E, Cedaro L, et al. Action of oral methylprednisolone in terminal cancer patients: a prospective randomized double-blind study. Cancer Treat Rep 1985;69:751–4.
95. Pulivarthi K, Dev R, Garcia J, et al. Testosterone replacement for fatigue in male hypogonadic patients with advanced cancer: A preliminary double-blind placebo-controlled trial. J Clin Oncol 2012;30 (suppl). Abstract e19643.
96. Palesh OG, Mustian KM, Peppone LJ, et al. Impact of paroxetine on sleep problems in 426 cancer patients receiving chemotherapy: a trial from the University of Rochester Cancer Center Community Clinical Oncology Program. Sleep Med 2012;13:1184–90.
97. Thekdi SM, Trinidad A, Roth A. Psychopharmacology in Cancer. Curr Psychiatry Rep 2014;17:529.
98. Lesser GJ. Case D, Stark N, et al. A randomized, double-blind, placebo-controlled study of oral coenzyme Q10 to relieve self-reported treatment-related fatigue in newly diagnosed patients with breast cancer. J Support Oncol 2013;11:31–42.
99. Barton DL, Liu H, Dakhil SR, et al. Wisconsin Ginseng (Panax quinquefolius) to improve cancer-related fatigue: a randomized, double-blind trial, N07C2. J Natl Cancer Inst 2013;105:1230–8.
100. Yennurajalingam S, Reddy A, Tannir NM, et al. High-dose Asian ginseng (panax ginseng) for cancer-related fatigue: a preliminary report. Integr Cancer Ther 2015;14:419–27.
101. Howell D, Keller-Olaman S, Oliver TK, et al. A pan-Canadian practice guideline and algorithm: screening, assessment, and supportive care of adults with cancer-related fatigue. Curr Oncol 2013;20:e233–46.
From the University of Texas MD Anderson Cancer Center, Houston, TX.
Abstract
- Objective: To review the evidence on interventions for managing cancer-related fatigue (CRF) and provide evidence-based guidance on approaches to its management.
- Methods: Nonsystematic review of the literature.
- Results: Several theories have been proposed to explain the biology of CRF, but there is no single clear mechanism that can be targeted for therapy. The approach to patients begins with screening for fatigue and assessing its intensity, followed by a thorough history and examination to determine whether any reversible medical conditions are contributing to fatigue. Management of underlying medical comorbidities may help some patients. For patients whose fatigue persists, pharmacologic and nonpharmacologic treatment options are available. Pharmacologic options include psychostimulants, such as methylphenidate and modafinil, and corticosteroids. Nonpharmacologic approaches include exercise, cognitive behavior therapy, yoga, acupuncture, and tai chi.
- Conclusion: We recommend an individualized approach, often with a combination of the available options. Patients need to be evaluated periodically to assess their fatigue, and since cancer-related fatigue affects survivors, long-term follow-up is needed.
Key words: fatigue; cancer; pro-inflammatory cytokines; nonpharmacologic; psychostimulants.
Fatigue is a common distressing effect of cancer [1].It impairs the quality of life of patients undergoing active cancer treatment and of post-treatment survivors. The National Comprehensive Cancer Network (NCCN) defines cancer-related fatigue (CRF) as “a distressing, persistent, subjective sense of physical, emotional and/or cognitive tiredness related to cancer or cancer treatment that is not proportional to recent activity and interferes with usual functioning [2].” Differences between CRF and fatigue reported by individuals without cancer are that CRF is more severe and is not relieved by rest. The prevalence of CRF in cancer patients and survivors is highly variable, ranging between 25% and 99% [2,3]. This variability may be secondary to methods used for screening fatigue and characteristics of the patient groups. In this article, we discuss recognition of CRF and approaches to its management.
Pathophysiology
The specific pathophysiologic mechanism underlying CRF is unknown, making targeted treatment a challenge. The multidimensional and subjective nature of CRF has limited the development of research methodologies to explain this condition. However, research has been done in both human and animal models, and several theories have been proposed to explain the pathophysiology of CRF. While pro-inflammatory cytokines remain the central factor playing a significant role at multiple levels in CRF, there may be a complex interplay of more than 1 mechanism contributing to fatigue in an individual patient.
Central Nervous System Disturbances
The basal ganglia are known to influence motivation. Lack of motivation and drive may cause failure to complete physical and mental tasks, even with preserved cognitive ability and motor function. In a study of melanoma patients receiving interferon, increased activity of the basal ganglia and the cerebellum resulted in higher fatigue scores [4]. Higher levels of cytokines may alter blood flow to the cerebellum and lead to the perception of fatigue. In a study of 12 patients and matched controls, when patients were asked to perform sustained elbow flexion until they perceived exhaustion, CRF patients perceived physical exhaustion sooner than controls. In CRF patients in this study, muscle fatigue measured by electromyogram was less than that in healthy individuals at the time of exhaustion, suggesting the role of the central nervous system in CRF [5]. However, there is not enough evidence at this time to support central nervous system disturbance as the main contributing factor to fatigue in cancer patients.
Circadian Rhythm Dysregulation
Circadian rhythm is regulated by the suprachiasmatic nucleus in the hypothalamus through cortisol and melatonin. Sleep disturbances occur with disruption of the circadian rhythm. Tumor-related peptides such as epidermal growth factor or alterations in serotonin and cortisol can influence the suprachiasmatic nucleus and the complex signaling pathways [2]. Positive feedback loops that are activated by cortisol under the influence of cytokines may lead to continuous cytokine production and altered circadian rhythm. Bower et al showed that changes in the cortisol curve influence fatigue in breast cancer survivors [6]. These patients had a late evening peak in cortisol levels, compared with an early morning peak in individuals without cancer.
Inhibition of Hypothalamic–Pituitary–Adrenal Axis
The hypothalamic–pituitary–adrenal (HPA) axis regulates the release of the stress hormone cortisol. One of several hypotheses advanced to explain the effect of serotonin and the HPA axis on CRF suggests that lower serotonin levels cause decreased activation of 5-hydroxytrytophan 1-a (5-HT1-a) receptors in the hypothalamus, leading to decreased activity of the HPA axis [6]. The inhibition of the HPA axis may occur with higher levels of serotonin as well [7]. The 5-HT1-a receptors are also triggered by cytokines. However, the correction of serotonin levels by antidepressants was not shown to improve fatigue [8]. Inhibition of the HPA axis can also lead to lower testosterone, progesterone, or estrogen levels, which may indirectly contribute to fatigue [2].
Skeletal Muscle Effect
Chemotherapy- and tumor-related cachexia have a direct effect on the metabolism of skeletal muscles. This effect may lead to impaired adenosine triphosphate (ATP) generation during muscle contraction [9]. ATP infusion improved muscle strength in one trial, but this was not confirmed in another trial [10,11]. Muscle contraction studies showed no differences in the contractile properties of muscles in fatigued patients who failed earlier in motor tasks and healthy controls [12]. This finding suggests that there could be a failure of skeletal muscle activation by the central nervous system or inhibition of skeletal muscle activity. Cytokines and other neurotransmitters activate vagal efferent nerve fibers, which may lead to reflex inhibition in skeletal muscles [13,14].
Pro-inflammatory Cytokines
Tumors or treatment of them may cause tissue injury, which triggers immune cells to release cytokines, signaling the brain to manifest the symptom fatigue. Inflammatory pathways are influenced by psychological, behavioral, and biological factors, which play a role as risk factors in CRF. Interleukin 6 (IL-6), interleukin-1 receptor antagonist, interleukin-1, and tumor necrosis factor (TNF) have been shown to be elevated in fatigued patients being treated for leukemia and non-Hodgkin lymphoma [15]. IL-6 was also associated with increased fatigue in breast cancer survivors [16]. Similar findings were reported in patients undergoing stem cell transplantation and high-dose chemotherapy [17]. Elevated levels of IL-6 and C-reactive protein were also linked to fatigue in terminally ill cancer patients [18,19]. Furthermore, TNF-α signaling was associated with post-chemotherapy fatigue in breast cancer patients [20]. Leukocytes in breast cancer survivors with fatigue also have increased gene expression of pro-inflammatory cytokines, emphasizing the role of cytokines and inflammation in the pathogenesis of CRF [21].
Other Hypotheses
Several other hypotheses for CRF pathogenesis have been proposed. Activation of latent viruses such as Epstein-Barr virus, lack of social support [22], genetic alterations in immune pathway [23], epigenetic changes [24], accumulation of neurotoxic metabolites and depletion of serotonin by indoleamine 2,3-dioxygenase pathway activation [25], elevated vascular endothelial growth factor levels [26], and hypoxia-related organ dysfunction due to anemia or hemoglobin dysfunction [13] all have been postulated to cause CRF.
Approach to Evaluation and Treatment
Screening
Because patients and health care professionals may be unaware of the treatment options available for CRF, patients may not report fatigue levels to their clinicians, and clinicians may not understand the impact of fatigue on their patients’ quality of life. This leads to underrecognition of the problem. The NCCN recommends screening every cancer patient and post-treatment survivor for fatigue [2]. Patients should be screened at their first visit and then at periodic intervals during and after cancer treatment.
Many scales are available to screen patients for CRF in clinical practice and clinical trials [27]. A single item that asks patients to rate their fatigue on a scale from 0 to 10—in which 0 indicates no fatigue, 1 to 3 indicates mild fatigue, 4 to 6 indicates moderate fatigue, 7 to 9 indicates severe fatigue, and 10 indicates the worst fatigue imaginable—is commonly used to screen for CRF [2]. This scale was adapted from the MD Anderson Symptom Inventory scale and is based on a large nationwide study of cancer patients and survivors [28]. The statistically derived cutoff points in this study are consistent with other scales such as the Brief Fatigue Inventory (BFI) and support the cutoff points (4–6 for moderate and ≥ 7 for severe fatigue) used in various fatigue management guidelines. Furthermore, studies of fatigue in cancer patients have revealed a marked decrease in physical function at levels of 7 or higher, suggesting 7 as an optimal cutoff to identify severe fatigue [29,30]. The Visual Analog Scale is another simple-to-use tool that helps in understanding variations in fatigue throughout the course of the day [31]. The 9-item BFI is often used in clinical trials [29]. It measures the severity of fatigue over the previous 24 hours and has been validated in non-English speaking patients [32].
CRF affects not only the somatic domain, but also the cognitive, behavioral, and affective domains; therefore, multidimensional scales have been developed for screening. One such tool is the Multidimensional Fatigue Inventory, which measures general, physical, mental, and emotional fatigue domains as well as activity and compares them with those of individuals without cancer [33,34]. The Functional Assessment of Cancer Therapy for Fatigue (FACT-F) is a 13-item questionnaire that has been used to measure CRF in clinical trials as well as in patients receiving various treatments [35].
Although many scales are available, the validity of self-reporting on simple fatigue-rating scales is equal to or better than most complex, lengthy scales [36]. Therefore, unidimensional tools such as the numeric rating scale of 0–10 are commonly used in clinical practice. Mild fatigue (0–3) requires periodic re-evaluation, and moderate and severe fatigue need further evaluation and management [37].
Primary Evaluation
This phase involves a focused history and physical examination and assessment of concurrent symptoms and contributing factors.
History and Physical Examination
A detailed history of the patient’s malignancy and type of previous and current treatment may help reveal the cause of fatigue. New-onset fatigue or increase in fatigue may be related to the progression of disease in patients with active malignancy or recurrence of cancer in survivors. These patients may require appropriate testing to assess the underlying disease pattern. A detailed review of systems may help identify some of the contributing factors, which are discussed below. A detailed history regarding medications, including over-the-counter drugs, complementary agents, and past and prior cancer therapies, is helpful as medications can contribute to fatigue. For example, opioids may cause drowsiness and fatigue, which could be improved by dose adjustments. A focused history of fatigue should be obtained in all patients with moderate to severe CRF, which includes the onset, pattern, duration, associated or alleviating factors, and interference with functioning, including activities of daily living [37]. Physical examination should focus on identifying signs of organ dysfunction and features of substance or alcohol abuse which may cause poor sleep and fatigue.
Assessment of Contributing Factors
The management of fatigue should be multifactorial, with a comprehensive assessment and treatment plan to address all modifiable fatigue etiologies. The Table lists potential contributing factors to fatigue that should be considered when evaluating patients for CRF; several common conditions are discussed below.
Anemia. Anemia has been correlated with fatigue and quality of life. In a study of 4382 cancer patients receiving chemotherapy, quality-of-life measures using FACT-Anemia scores improved with increased hemoglobin levels [38]. Cancer patients may have anemia due to marrow-suppressing effects of chemotherapy and may also have iron deficiency anemia due to blood loss or autoimmune hemolytic anemia. Therefore, a detailed work-up is required to identify the etiology of anemia. Patients with CRF whose anemia is related to chemotherapy or anemia of chronic disease may benefit from red blood cell transfusion or erythropoiesis-stimulating agents (ESAs). ESAs have been studied extensively; however, their use is controversial because of concerns about thromboembolic side effects leading to adverse outcomes [39]. Also, ESA therapy is not recommended in patients with hematologic malignancies. ESA use should be restricted to patients with chemotherapy-related anemia with hemoglobin below 10 mg/dL and should be discontinued in 6 to 8 weeks if patients do not respond [40]. Other patients may benefit from blood transfusions, which were shown to help in patients with hemoglobin levels between 7.5 and 8.5 g/dL [41].
Sleep disturbance. Poor sleep is common in fatigued cancer survivors [42]. Pro-inflammatory cytokines can disrupt the sleep–wake cycle, causing changes in the HPA axis and neuroendocrine system, which in turn may lead to increasing fatigue. Heckler et al showed that improvement in nighttime sleep leads to improvement of fatigue [43]. Cognitive behavioral therapy and sleep hygiene are important in caring for patients with CRF and poor sleep [44]. Taking a warm bath and/or drinking a glass of milk before bedtime, avoiding caffeinated drinks, and avoiding frequent napping in the day might help. Some patients may require medications such as benzodiazepines or non-benzodiazepine hypnotics (eg, zolpidem) to promote sleep [45]. Melatonin agonists are approved for insomnia in the United states, but not in Europe [46].
Malnutrition. Patients with advanced-stage cancer and with cancers affecting the gastrointestinal tract frequently develop mechanical bowel obstructions, especially at the end of their life, which cause malnutrition. Chemotherapy-related nausea and vomiting may also cause poor oral intake and malnutrition, causing fatigue from muscle weakness. Dehydration and electrolyte imbalances frequently occur as a result of poor oral intake, which might worsen fatigue. In our experience, modifying dietary intake with appropriate caloric exchanges with the help of a nutrition expert has lessened fatigue in some patients. However, terminally ill patients are advised to eat based on their comfort.
Medical comorbidities. Congestive heart failure from anthracycline chemotherapy, hypothyroidism after radiation therapy for head and neck cancers, renal failure, or hepatic failure from chemotherapy may indirectly lead to fatigue. Chemotherapy, opioids, and steroids may cause hypogonadism, which can contribute to fatigue in men [47].
Assessment of Concurrent Symptoms
Depression is common in cancer patients and coexists with pain, insomnia, fatigue, and anxiety as a symptom cluster [48]. A symptom cluster is defined as 2 or more concurrent and interrelated symptoms occurring together; treating of one of these symptoms without addressing other symptoms is not effective [49]. Therefore, screening for and management of depression, anxiety, and insomnia play an important role in the management of CRF.
Physical symptoms due to the tumor or to therapy—such as pain, dyspnea, nausea, and decreased physical activity—may also contribute to fatigue both directly and indirectly. Patients with lung cancer may have hypoxemia, which can contribute to dyspnea with activity and a perception of fatigue. Optimal management of pain and other physical symptoms in patients with cancer may significantly alleviate fatigue [50].
Management
Management of CRF is individualized based on the patient’s clinical status: active cancer treatment, survivor, or end of life. Education and counselling of patients and their caregivers play an important role in CRF. NCCN guidelines recommend focusing on pain control, distress management, energy conservation, physical activity, nutrition, and sleep hygiene.
Nonpharmacologic Interventions
Energy conservation. Energy conservation strategies, in which patients are advised to set priorities and realistic expectations, are highly recommended. Some energy-conserving strategies are to pace oneself, delegate and schedule activities at times of peak energy, postpone nonessential activities, attend to 1 activity at a time, structure daily routines, and maintain a diary to identify their peak energy period and structure activities around that time [51,52]. When patients approach the end of life, increasing fatigue may limit their activity level, and they may depend on caregivers for assistance with activities of daily living, monitoring treatment-related adverse effects, and taking medications, especially elderly patients [53].
Cognitive behavioral therapy. Cognitive behavioral therapy (CBT) has been shown to improve CRF during active treatment, and the benefits persist for a minimum of 2 years after therapy [54]. CBT interventions that optimize sleep quality may improve fatigue [55]. More studies are needed to understand whether referral to a psychologist for formal CBT is required. Randomized clinical trials (RCTs) showed patient fatigue education, learned self-care, coping techniques, and balancing rest and activity benefit patients with CRF [56].
Exercise. Physical activity is highly encouraged in patients with CRF. Exercise increases muscle protein synthesis, improves cytokine response, and decreases the rate of sarcopenia in healthy populations [57]. Studies have shown that exercise helps CRF at all phases of the cancer journey, including radiation therapy, chemotherapy, and survivorship [58]. Some patients may feel less motivated to exercise and may not believe that exercise is possible or could potentially help them. Counselling is needed for such patients.
Older cancer survivors have a decline in their functional capacity and reduced muscle mass. Exercise can improve cardiorespiratory fitness, muscle strength, and body composition [57]. Exercise not only helps at the cellular level but also has psychosocial benefits from improved self-esteem. Therefore, exercise may be recommended not only for younger patients, but also in the older population, who may have comorbidities and less motivation than younger patients.
In a meta-analysis of 56 randomized controlled trials involving 4068 participants, aerobic exercise was found to have beneficial effects on CRF for patients during and after chemotherapy, specifically for patients with solid tumors [59]. In another meta-analysis of breast and prostate cancer survivors, a combination of aerobic exercise with resistance training (3–6 metabolic equivalents, 60%–80% range of motion) was shown to reduce CRF more than aerobic exercise alone [60]. This effect was also shown in an RCT of 160 patients with stage 0 to III breast cancer undergoing radiation therapy [61]. The control group in this study had a group-based non-exercise intervention/relaxation; therefore, the study showed that the effect of resistance training extends beyond the psychosocial benefits of group-based interventions. The intervention comprised 8 progressive machine-based resistance exercises (3 sets, 8–12 repetitions at 60%–80% of 1 repetition maximum) for 60 minutes twice weekly for 12 weeks. However, fatigue assessment questionnaire scores showed benefits in the physical fatigue but not the affective and cognitive components.
The American Society of Clinical Oncology’s guidelines for cancer survivors with fatigue recommends 150 minutes of moderate aerobic exercise (eg, fast walking, cycling, or swimming) per week, with 2 or 3 sessions of strength training per week [62]. An individualized approach to exercise is recommended, as patients’ ability to perform certain types of exercises may be limited by thrombocytopenia, neutropenia, or lytic bone metastasis. Routine use of pre-exercise cardiovascular testing is not recommended but may be considered in high-risk populations, especially patients with risk factors for coronary heart disease and diabetes [63]. Patients withcomorbidities, substantial deconditioning, functional and anatomic defects, or recent major surgery may benefit from referral to physical therapy [37]. Patients near end of life may also benefit from an exercise program, as demonstrated in several studies that showed benefit in CRF and quality of life [64,65]. We recommend that physicians use their best clinical judgement in suggesting the type and intensity of exercise program, as it may not be feasible in some patients.
Mind-body interventions. Mindfulness-based stress reduction (MBSR) has shown promise in breast cancer survivors, who reported immediate improvements in fatigue severity that continued up to 6 weeks after cessation of the training [66]. Prior studies had similar findings, suggesting that MBSR modestly decreases fatigue and sleep disturbances and has a greater effect on the degree to which symptoms interfere with many facets of life [67].
Yoga. A study of a yoga intervention showed a benefit in older cancer survivors [68]. In breast cancer patients undergoing chemotherapy, yoga was shown to benefit not only physical fatigue, but also cognitive fatigue [69]. DVD-based yoga had benefits similar to strengthening exercises in a study of 34 early-stage breast cancer survivors with CRF [70]. More studies are needed in men and patients and survivors of other cancers, as most studies of yoga were conducted in women with breast cancer.
Tai chi/qigong. Like yoga, tai chi and qigong are practices of meditative movement. These practices use postures or movements with a focus on breath and a meditative state to bring about deep states of relaxation. Qigong is a series of simple, repeated practices including body posture/movement, breath practice, and meditation performed in synchrony. Tai chi easy (TCE) is a simplified set of common, repetitive tai chi movements. In a trial, qigong/TCE was compared with sham qigong, which had physical movements but no breathing or meditative practice. Breast cancer survivors in the qigong/TCE group had improved fatigue scores, and the effect persisted for 3 months [71]. Additional research is needed in this area.
Acupuncture. An RCT in breast cancer patients with CRF showed an improvement in the mean general fatigue score (per the Multidimensional Fatigue Inventory) in patients who received acupuncture versus those who did not (−3.11 [95% confidence interval −3.97 to −2.25]; P < 0.001) at 6 weeks. Improvements were seen in both the mental and physical aspects of fatigue [72]. However, Deng et al noted that true acupuncture was no more effective than sham acupuncture for reducing post-chemotherapy chronic fatigue [73]. Presently, there is not sufficient evidence to evaluate the benefits of acupuncture in CRF.
Other modalities. Massage therapy, music therapy, hypnosis, therapeutic touch, biofield therapies, relaxation, and reiki are other therapies for which few studies have been done, with mixed results, and additional research is needed [74]. Currently, there are not sufficient data to recommend any of these modalities.
Pharmacologic Interventions
Psychostimulants. Methylphenidate and modafinil are psychostimulants or wakefulness-promoting agents. Pilot studies showed benefit from methylphenidate and modafinil in CRF [75–77], but RCTs have yielded mixed results. Therefore, in patients with severe fatigue during cancer therapy, the initial management strategy involves evaluation and treatment of medical conditions such as anemia and a trial of non-pharmacological strategies as discussed above. If symptoms persist, then a therapeutic trial of a psychostimulant may be considered per NCCN guidelines for patients undergoing active cancer treatment [37].
Methylphenidate directly stimulates adrenergic receptors and indirectly releases dopamine and norepinephrine from presynaptic terminals, which may explain why the drug benefits patients receiving opioid-induced sedation. It is a commonly studied psychostimulant, though its mechanism of action in CRF is unclear. RCTs of methylphenidate have resulted in a wide range of findings due to the heterogeneity of study populations and variations in the dosage of methylphenidate. A meta-analysis of 7 studies indicates that methylphenidate benefitted the subgroup of patients with CRF [78]. Likewise, in an analysis of 5 RCTs, Minton et al showed a benefit of psychostimulants in fatigue compared with placebo [79]. However, another study of methylphenidate in patients with CRF showed a benefit only in patients with severe fatigue or advanced disease [80]. Methylphenidate was found to benefit cancer patients receiving opioid-induced sedation, as methylphenidate promotes wakefulness, though fatigue was not studied specifically [81]. In a trial with 30 hospice patients in which the methylphenidate dose was titrated based on response and adverse effects, Kerr at al found that the drug improved fatigue in a dose-dependent manner [82]. However, a study in patients with CRF at the University of Texas MD Anderson Cancer Center found no significant difference in BFI scores between patients receiving methylphenidate and those receiving placebo at the end of 2 weeks of treatment [83]. Also, other RCTs in patients undergoing adjuvant chemotherapy for breast cancer [84] and patients receiving radiation therapy for brain tumors [85] failed to demonstrate the efficacy of methylphenidate in CRF. It should be used cautiously after ruling out other causes of fatigue. The drug is overall well tolerated and side effects include headache and nausea.
Modafinil is a non-amphetamine psychostimulant that has been approved for the treatment of narcolepsy. In a trial studying the effect of modafinil on patients receiving docetaxel-based chemotherapy for metastatic breast or prostate cancer, there was a modest but not statistically significant improvement in fatigue scores on the MD Anderson Symptom Inventory compared with placebo. Nausea and vomiting were higher in the modafinil arm than in the placebo arm [86]. Similarly, modafinil was not superior to placebo for CRF in 208 patients with non-squamous cell lung cancer not undergoing chemotherapy or radiation [87]. A placebo effect was also noted in patients with multiple myeloma [88] and patients with primary brain tumors [89]. In a phase 3, multicenter, randomized, placebo-controlled, double-blind clinical trial of modafinil for CRF in 867 patients undergoing chemotherapy, there was a reduction in fatigue only for patients with severe baseline fatigue, with no significant effect on mild to moderate fatigue [90]. In another recent study, modafinil was shown to reduce depressive symptoms only in patients with severe fatigue (BFI item 3 score ≥ 7) [91]. This finding is consistent with previous studies showing benefit in patients with high baseline fatigue, but additional RCTs are needed to provide clarity. NCCN guidelines do not recommend the use of modafinil to treat CRF [37].
Other pharmacologic interventions. Corticosteroids are often used for symptom control in cancer patients. These drugs have anti-inflammatory effects through their modulation of pro-inflammatory cytokines [92]. In a RCT evaluating the efficacy of corticosteroids, patients receiving dexamethasone (4 mg twice daily) experienced significant improvement in their FACT-F scores compared with patients receiving placebo [93]. A similar benefit in fatigue was demonstrated in another study of methylprednisolone (32 mg daily) versus placebo [94]. Despite the benefits of steroids, their adverse effects, such as mood swings, gastritis, hyperglycemia, and immune suppression, limit their long-term use. Therefore, the use of steroids should be restricted to terminally ill fatigued patients with other symptoms such as anorexia, brain metastasis, or pain related to bone metastasis [37].
Testosterone replacement has been shown to diminish fatigue in non-cancer patients. Many men with advanced cancer have hypogonadism leading to low serum testosterone, which may cause fatigue. In a small trial in which cancer patients with hypogonadism received intramuscular testosterone every 14 days or placebo, the group receiving testosterone showed improvement in FACT-F scores, but there was no significant difference in FACT-F scores between the 2 groups [95].
Antidepressants have failed to demonstrate benefit in CRF without depression [8]. However, if a patient has both fatigue and depression, antidepressants may help [96]. A selective serotonin receptor inhibitor is recommended as a first-line antidepressant [97]. Patients with cancer are often receiving multiple medications, and medication interactions should be considered to prevent adverse events such as serotonin syndrome.
Complementary and Alternative Supplements
Studies using vitamin supplementation have been inconclusive in patients with CRF [74]. The use of other dietary supplements has yielded mixed results, and coenzyme Q has shown no benefit for patients with CRF [98].
The benefit of ginseng was studied in a RCT involving 364 patients with CRF. There was an improvement in Multidimensional Fatigue Symptom Inventory-short form (MFSI-SF) scores at 8 weeks in patients receiving 2000 mg of Wisconsin ginseng compared with patients receiving placebo [99]. Patients on active treatment had greater improvement as compared to the post-treatment group in this trial. In another study of high-dose panax ginseng (ginseng root) at 800 mg daily for 29 days, patients had improvement of CRF as well as overall quality of life, appetite, and sleep at night. It was also well tolerated with few adverse effects [100]. Interaction with warfarin, calcium channel blockers, antiplatelet agents, thrombolytic agents, imatinib, and other agents may occur; therefore, ginseng must be used with careful monitoring in selected patients. There is not enough evidence at this time to support the routine use of ginseng in CRF.
The seed extract of the guarana plant (Paullinia cupana) traditionally has been used as a stimulant. An improvement in fatigue scores was seen with the use of oral guarana (100 mg daily) at the end of 21 days in breast cancer patients receiving chemotherapy [101]. Further studies are needed for these results to be generalized and to understand the adverse effects and interaction profile of guarana.
Re-evaluation
Patients who have completed cancer treatment must be monitored for fatigue over the long term, as fatigue may exist beyond the period of active treatment. Many studies have shown fatigue in breast cancer survivors, and fatigue has been demonstrated in survivors of colorectal, lung, and prostate cancers as well as myeloproliferative neoplasms [28]. Therefore, it is important to screen patients for fatigue during follow-up visits. There are currently no studies evaluating the long-term treatment of fatigue. In our experience, the timing of follow-up depends on the level of fatigue and interventions prescribed. Once fatigue is stabilized to a level with which the patient is able to cope, the time interval for follow up may be lengthened. Annual visits may suffice in patients with mild fatigue. Follow-up of patients with moderate to severe fatigue depends on the level of fatigue, the ability to cope, choice of treatment, and presence of contributing factors.
Conclusion
CRF is a complex condition that places a significant burden on patients and caregivers, resulting in emotional distress, poor functioning, and suffering. Fatigue can occur before, during, and long after cancer treatment. The approach to CRF begins with screening for and educating patients and their caregivers about the symptoms. Many screening scales are available that may be used to follow patients’ progress over time. The evaluation and management of contributing conditions may help improve fatigue. If the fatigue persists, an individualized approach with a combination of nonpharmacologic and pharmacologic approaches should be considered. More research is needed to understand brain signaling pathways, cytokine changes, and genomic changes in cancer patients with fatigue. Though many hypotheses have been proposed, to date there is no biological marker to assess this condition. Biomarker research needs to be advanced to help to identify patients at risk for fatigue. As cytokines have a major role in CRF, targeted therapy to block cytokine pathways may also be explored in the future.
Acknowledgment: Bryan Tutt provided editorial assistance.
Corresponding author: Carmelita P. Escalante, MD, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX 77030, cescalan@mdanderson.org.
Financial disclosures: None.
From the University of Texas MD Anderson Cancer Center, Houston, TX.
Abstract
- Objective: To review the evidence on interventions for managing cancer-related fatigue (CRF) and provide evidence-based guidance on approaches to its management.
- Methods: Nonsystematic review of the literature.
- Results: Several theories have been proposed to explain the biology of CRF, but there is no single clear mechanism that can be targeted for therapy. The approach to patients begins with screening for fatigue and assessing its intensity, followed by a thorough history and examination to determine whether any reversible medical conditions are contributing to fatigue. Management of underlying medical comorbidities may help some patients. For patients whose fatigue persists, pharmacologic and nonpharmacologic treatment options are available. Pharmacologic options include psychostimulants, such as methylphenidate and modafinil, and corticosteroids. Nonpharmacologic approaches include exercise, cognitive behavior therapy, yoga, acupuncture, and tai chi.
- Conclusion: We recommend an individualized approach, often with a combination of the available options. Patients need to be evaluated periodically to assess their fatigue, and since cancer-related fatigue affects survivors, long-term follow-up is needed.
Key words: fatigue; cancer; pro-inflammatory cytokines; nonpharmacologic; psychostimulants.
Fatigue is a common distressing effect of cancer [1].It impairs the quality of life of patients undergoing active cancer treatment and of post-treatment survivors. The National Comprehensive Cancer Network (NCCN) defines cancer-related fatigue (CRF) as “a distressing, persistent, subjective sense of physical, emotional and/or cognitive tiredness related to cancer or cancer treatment that is not proportional to recent activity and interferes with usual functioning [2].” Differences between CRF and fatigue reported by individuals without cancer are that CRF is more severe and is not relieved by rest. The prevalence of CRF in cancer patients and survivors is highly variable, ranging between 25% and 99% [2,3]. This variability may be secondary to methods used for screening fatigue and characteristics of the patient groups. In this article, we discuss recognition of CRF and approaches to its management.
Pathophysiology
The specific pathophysiologic mechanism underlying CRF is unknown, making targeted treatment a challenge. The multidimensional and subjective nature of CRF has limited the development of research methodologies to explain this condition. However, research has been done in both human and animal models, and several theories have been proposed to explain the pathophysiology of CRF. While pro-inflammatory cytokines remain the central factor playing a significant role at multiple levels in CRF, there may be a complex interplay of more than 1 mechanism contributing to fatigue in an individual patient.
Central Nervous System Disturbances
The basal ganglia are known to influence motivation. Lack of motivation and drive may cause failure to complete physical and mental tasks, even with preserved cognitive ability and motor function. In a study of melanoma patients receiving interferon, increased activity of the basal ganglia and the cerebellum resulted in higher fatigue scores [4]. Higher levels of cytokines may alter blood flow to the cerebellum and lead to the perception of fatigue. In a study of 12 patients and matched controls, when patients were asked to perform sustained elbow flexion until they perceived exhaustion, CRF patients perceived physical exhaustion sooner than controls. In CRF patients in this study, muscle fatigue measured by electromyogram was less than that in healthy individuals at the time of exhaustion, suggesting the role of the central nervous system in CRF [5]. However, there is not enough evidence at this time to support central nervous system disturbance as the main contributing factor to fatigue in cancer patients.
Circadian Rhythm Dysregulation
Circadian rhythm is regulated by the suprachiasmatic nucleus in the hypothalamus through cortisol and melatonin. Sleep disturbances occur with disruption of the circadian rhythm. Tumor-related peptides such as epidermal growth factor or alterations in serotonin and cortisol can influence the suprachiasmatic nucleus and the complex signaling pathways [2]. Positive feedback loops that are activated by cortisol under the influence of cytokines may lead to continuous cytokine production and altered circadian rhythm. Bower et al showed that changes in the cortisol curve influence fatigue in breast cancer survivors [6]. These patients had a late evening peak in cortisol levels, compared with an early morning peak in individuals without cancer.
Inhibition of Hypothalamic–Pituitary–Adrenal Axis
The hypothalamic–pituitary–adrenal (HPA) axis regulates the release of the stress hormone cortisol. One of several hypotheses advanced to explain the effect of serotonin and the HPA axis on CRF suggests that lower serotonin levels cause decreased activation of 5-hydroxytrytophan 1-a (5-HT1-a) receptors in the hypothalamus, leading to decreased activity of the HPA axis [6]. The inhibition of the HPA axis may occur with higher levels of serotonin as well [7]. The 5-HT1-a receptors are also triggered by cytokines. However, the correction of serotonin levels by antidepressants was not shown to improve fatigue [8]. Inhibition of the HPA axis can also lead to lower testosterone, progesterone, or estrogen levels, which may indirectly contribute to fatigue [2].
Skeletal Muscle Effect
Chemotherapy- and tumor-related cachexia have a direct effect on the metabolism of skeletal muscles. This effect may lead to impaired adenosine triphosphate (ATP) generation during muscle contraction [9]. ATP infusion improved muscle strength in one trial, but this was not confirmed in another trial [10,11]. Muscle contraction studies showed no differences in the contractile properties of muscles in fatigued patients who failed earlier in motor tasks and healthy controls [12]. This finding suggests that there could be a failure of skeletal muscle activation by the central nervous system or inhibition of skeletal muscle activity. Cytokines and other neurotransmitters activate vagal efferent nerve fibers, which may lead to reflex inhibition in skeletal muscles [13,14].
Pro-inflammatory Cytokines
Tumors or treatment of them may cause tissue injury, which triggers immune cells to release cytokines, signaling the brain to manifest the symptom fatigue. Inflammatory pathways are influenced by psychological, behavioral, and biological factors, which play a role as risk factors in CRF. Interleukin 6 (IL-6), interleukin-1 receptor antagonist, interleukin-1, and tumor necrosis factor (TNF) have been shown to be elevated in fatigued patients being treated for leukemia and non-Hodgkin lymphoma [15]. IL-6 was also associated with increased fatigue in breast cancer survivors [16]. Similar findings were reported in patients undergoing stem cell transplantation and high-dose chemotherapy [17]. Elevated levels of IL-6 and C-reactive protein were also linked to fatigue in terminally ill cancer patients [18,19]. Furthermore, TNF-α signaling was associated with post-chemotherapy fatigue in breast cancer patients [20]. Leukocytes in breast cancer survivors with fatigue also have increased gene expression of pro-inflammatory cytokines, emphasizing the role of cytokines and inflammation in the pathogenesis of CRF [21].
Other Hypotheses
Several other hypotheses for CRF pathogenesis have been proposed. Activation of latent viruses such as Epstein-Barr virus, lack of social support [22], genetic alterations in immune pathway [23], epigenetic changes [24], accumulation of neurotoxic metabolites and depletion of serotonin by indoleamine 2,3-dioxygenase pathway activation [25], elevated vascular endothelial growth factor levels [26], and hypoxia-related organ dysfunction due to anemia or hemoglobin dysfunction [13] all have been postulated to cause CRF.
Approach to Evaluation and Treatment
Screening
Because patients and health care professionals may be unaware of the treatment options available for CRF, patients may not report fatigue levels to their clinicians, and clinicians may not understand the impact of fatigue on their patients’ quality of life. This leads to underrecognition of the problem. The NCCN recommends screening every cancer patient and post-treatment survivor for fatigue [2]. Patients should be screened at their first visit and then at periodic intervals during and after cancer treatment.
Many scales are available to screen patients for CRF in clinical practice and clinical trials [27]. A single item that asks patients to rate their fatigue on a scale from 0 to 10—in which 0 indicates no fatigue, 1 to 3 indicates mild fatigue, 4 to 6 indicates moderate fatigue, 7 to 9 indicates severe fatigue, and 10 indicates the worst fatigue imaginable—is commonly used to screen for CRF [2]. This scale was adapted from the MD Anderson Symptom Inventory scale and is based on a large nationwide study of cancer patients and survivors [28]. The statistically derived cutoff points in this study are consistent with other scales such as the Brief Fatigue Inventory (BFI) and support the cutoff points (4–6 for moderate and ≥ 7 for severe fatigue) used in various fatigue management guidelines. Furthermore, studies of fatigue in cancer patients have revealed a marked decrease in physical function at levels of 7 or higher, suggesting 7 as an optimal cutoff to identify severe fatigue [29,30]. The Visual Analog Scale is another simple-to-use tool that helps in understanding variations in fatigue throughout the course of the day [31]. The 9-item BFI is often used in clinical trials [29]. It measures the severity of fatigue over the previous 24 hours and has been validated in non-English speaking patients [32].
CRF affects not only the somatic domain, but also the cognitive, behavioral, and affective domains; therefore, multidimensional scales have been developed for screening. One such tool is the Multidimensional Fatigue Inventory, which measures general, physical, mental, and emotional fatigue domains as well as activity and compares them with those of individuals without cancer [33,34]. The Functional Assessment of Cancer Therapy for Fatigue (FACT-F) is a 13-item questionnaire that has been used to measure CRF in clinical trials as well as in patients receiving various treatments [35].
Although many scales are available, the validity of self-reporting on simple fatigue-rating scales is equal to or better than most complex, lengthy scales [36]. Therefore, unidimensional tools such as the numeric rating scale of 0–10 are commonly used in clinical practice. Mild fatigue (0–3) requires periodic re-evaluation, and moderate and severe fatigue need further evaluation and management [37].
Primary Evaluation
This phase involves a focused history and physical examination and assessment of concurrent symptoms and contributing factors.
History and Physical Examination
A detailed history of the patient’s malignancy and type of previous and current treatment may help reveal the cause of fatigue. New-onset fatigue or increase in fatigue may be related to the progression of disease in patients with active malignancy or recurrence of cancer in survivors. These patients may require appropriate testing to assess the underlying disease pattern. A detailed review of systems may help identify some of the contributing factors, which are discussed below. A detailed history regarding medications, including over-the-counter drugs, complementary agents, and past and prior cancer therapies, is helpful as medications can contribute to fatigue. For example, opioids may cause drowsiness and fatigue, which could be improved by dose adjustments. A focused history of fatigue should be obtained in all patients with moderate to severe CRF, which includes the onset, pattern, duration, associated or alleviating factors, and interference with functioning, including activities of daily living [37]. Physical examination should focus on identifying signs of organ dysfunction and features of substance or alcohol abuse which may cause poor sleep and fatigue.
Assessment of Contributing Factors
The management of fatigue should be multifactorial, with a comprehensive assessment and treatment plan to address all modifiable fatigue etiologies. The Table lists potential contributing factors to fatigue that should be considered when evaluating patients for CRF; several common conditions are discussed below.
Anemia. Anemia has been correlated with fatigue and quality of life. In a study of 4382 cancer patients receiving chemotherapy, quality-of-life measures using FACT-Anemia scores improved with increased hemoglobin levels [38]. Cancer patients may have anemia due to marrow-suppressing effects of chemotherapy and may also have iron deficiency anemia due to blood loss or autoimmune hemolytic anemia. Therefore, a detailed work-up is required to identify the etiology of anemia. Patients with CRF whose anemia is related to chemotherapy or anemia of chronic disease may benefit from red blood cell transfusion or erythropoiesis-stimulating agents (ESAs). ESAs have been studied extensively; however, their use is controversial because of concerns about thromboembolic side effects leading to adverse outcomes [39]. Also, ESA therapy is not recommended in patients with hematologic malignancies. ESA use should be restricted to patients with chemotherapy-related anemia with hemoglobin below 10 mg/dL and should be discontinued in 6 to 8 weeks if patients do not respond [40]. Other patients may benefit from blood transfusions, which were shown to help in patients with hemoglobin levels between 7.5 and 8.5 g/dL [41].
Sleep disturbance. Poor sleep is common in fatigued cancer survivors [42]. Pro-inflammatory cytokines can disrupt the sleep–wake cycle, causing changes in the HPA axis and neuroendocrine system, which in turn may lead to increasing fatigue. Heckler et al showed that improvement in nighttime sleep leads to improvement of fatigue [43]. Cognitive behavioral therapy and sleep hygiene are important in caring for patients with CRF and poor sleep [44]. Taking a warm bath and/or drinking a glass of milk before bedtime, avoiding caffeinated drinks, and avoiding frequent napping in the day might help. Some patients may require medications such as benzodiazepines or non-benzodiazepine hypnotics (eg, zolpidem) to promote sleep [45]. Melatonin agonists are approved for insomnia in the United states, but not in Europe [46].
Malnutrition. Patients with advanced-stage cancer and with cancers affecting the gastrointestinal tract frequently develop mechanical bowel obstructions, especially at the end of their life, which cause malnutrition. Chemotherapy-related nausea and vomiting may also cause poor oral intake and malnutrition, causing fatigue from muscle weakness. Dehydration and electrolyte imbalances frequently occur as a result of poor oral intake, which might worsen fatigue. In our experience, modifying dietary intake with appropriate caloric exchanges with the help of a nutrition expert has lessened fatigue in some patients. However, terminally ill patients are advised to eat based on their comfort.
Medical comorbidities. Congestive heart failure from anthracycline chemotherapy, hypothyroidism after radiation therapy for head and neck cancers, renal failure, or hepatic failure from chemotherapy may indirectly lead to fatigue. Chemotherapy, opioids, and steroids may cause hypogonadism, which can contribute to fatigue in men [47].
Assessment of Concurrent Symptoms
Depression is common in cancer patients and coexists with pain, insomnia, fatigue, and anxiety as a symptom cluster [48]. A symptom cluster is defined as 2 or more concurrent and interrelated symptoms occurring together; treating of one of these symptoms without addressing other symptoms is not effective [49]. Therefore, screening for and management of depression, anxiety, and insomnia play an important role in the management of CRF.
Physical symptoms due to the tumor or to therapy—such as pain, dyspnea, nausea, and decreased physical activity—may also contribute to fatigue both directly and indirectly. Patients with lung cancer may have hypoxemia, which can contribute to dyspnea with activity and a perception of fatigue. Optimal management of pain and other physical symptoms in patients with cancer may significantly alleviate fatigue [50].
Management
Management of CRF is individualized based on the patient’s clinical status: active cancer treatment, survivor, or end of life. Education and counselling of patients and their caregivers play an important role in CRF. NCCN guidelines recommend focusing on pain control, distress management, energy conservation, physical activity, nutrition, and sleep hygiene.
Nonpharmacologic Interventions
Energy conservation. Energy conservation strategies, in which patients are advised to set priorities and realistic expectations, are highly recommended. Some energy-conserving strategies are to pace oneself, delegate and schedule activities at times of peak energy, postpone nonessential activities, attend to 1 activity at a time, structure daily routines, and maintain a diary to identify their peak energy period and structure activities around that time [51,52]. When patients approach the end of life, increasing fatigue may limit their activity level, and they may depend on caregivers for assistance with activities of daily living, monitoring treatment-related adverse effects, and taking medications, especially elderly patients [53].
Cognitive behavioral therapy. Cognitive behavioral therapy (CBT) has been shown to improve CRF during active treatment, and the benefits persist for a minimum of 2 years after therapy [54]. CBT interventions that optimize sleep quality may improve fatigue [55]. More studies are needed to understand whether referral to a psychologist for formal CBT is required. Randomized clinical trials (RCTs) showed patient fatigue education, learned self-care, coping techniques, and balancing rest and activity benefit patients with CRF [56].
Exercise. Physical activity is highly encouraged in patients with CRF. Exercise increases muscle protein synthesis, improves cytokine response, and decreases the rate of sarcopenia in healthy populations [57]. Studies have shown that exercise helps CRF at all phases of the cancer journey, including radiation therapy, chemotherapy, and survivorship [58]. Some patients may feel less motivated to exercise and may not believe that exercise is possible or could potentially help them. Counselling is needed for such patients.
Older cancer survivors have a decline in their functional capacity and reduced muscle mass. Exercise can improve cardiorespiratory fitness, muscle strength, and body composition [57]. Exercise not only helps at the cellular level but also has psychosocial benefits from improved self-esteem. Therefore, exercise may be recommended not only for younger patients, but also in the older population, who may have comorbidities and less motivation than younger patients.
In a meta-analysis of 56 randomized controlled trials involving 4068 participants, aerobic exercise was found to have beneficial effects on CRF for patients during and after chemotherapy, specifically for patients with solid tumors [59]. In another meta-analysis of breast and prostate cancer survivors, a combination of aerobic exercise with resistance training (3–6 metabolic equivalents, 60%–80% range of motion) was shown to reduce CRF more than aerobic exercise alone [60]. This effect was also shown in an RCT of 160 patients with stage 0 to III breast cancer undergoing radiation therapy [61]. The control group in this study had a group-based non-exercise intervention/relaxation; therefore, the study showed that the effect of resistance training extends beyond the psychosocial benefits of group-based interventions. The intervention comprised 8 progressive machine-based resistance exercises (3 sets, 8–12 repetitions at 60%–80% of 1 repetition maximum) for 60 minutes twice weekly for 12 weeks. However, fatigue assessment questionnaire scores showed benefits in the physical fatigue but not the affective and cognitive components.
The American Society of Clinical Oncology’s guidelines for cancer survivors with fatigue recommends 150 minutes of moderate aerobic exercise (eg, fast walking, cycling, or swimming) per week, with 2 or 3 sessions of strength training per week [62]. An individualized approach to exercise is recommended, as patients’ ability to perform certain types of exercises may be limited by thrombocytopenia, neutropenia, or lytic bone metastasis. Routine use of pre-exercise cardiovascular testing is not recommended but may be considered in high-risk populations, especially patients with risk factors for coronary heart disease and diabetes [63]. Patients withcomorbidities, substantial deconditioning, functional and anatomic defects, or recent major surgery may benefit from referral to physical therapy [37]. Patients near end of life may also benefit from an exercise program, as demonstrated in several studies that showed benefit in CRF and quality of life [64,65]. We recommend that physicians use their best clinical judgement in suggesting the type and intensity of exercise program, as it may not be feasible in some patients.
Mind-body interventions. Mindfulness-based stress reduction (MBSR) has shown promise in breast cancer survivors, who reported immediate improvements in fatigue severity that continued up to 6 weeks after cessation of the training [66]. Prior studies had similar findings, suggesting that MBSR modestly decreases fatigue and sleep disturbances and has a greater effect on the degree to which symptoms interfere with many facets of life [67].
Yoga. A study of a yoga intervention showed a benefit in older cancer survivors [68]. In breast cancer patients undergoing chemotherapy, yoga was shown to benefit not only physical fatigue, but also cognitive fatigue [69]. DVD-based yoga had benefits similar to strengthening exercises in a study of 34 early-stage breast cancer survivors with CRF [70]. More studies are needed in men and patients and survivors of other cancers, as most studies of yoga were conducted in women with breast cancer.
Tai chi/qigong. Like yoga, tai chi and qigong are practices of meditative movement. These practices use postures or movements with a focus on breath and a meditative state to bring about deep states of relaxation. Qigong is a series of simple, repeated practices including body posture/movement, breath practice, and meditation performed in synchrony. Tai chi easy (TCE) is a simplified set of common, repetitive tai chi movements. In a trial, qigong/TCE was compared with sham qigong, which had physical movements but no breathing or meditative practice. Breast cancer survivors in the qigong/TCE group had improved fatigue scores, and the effect persisted for 3 months [71]. Additional research is needed in this area.
Acupuncture. An RCT in breast cancer patients with CRF showed an improvement in the mean general fatigue score (per the Multidimensional Fatigue Inventory) in patients who received acupuncture versus those who did not (−3.11 [95% confidence interval −3.97 to −2.25]; P < 0.001) at 6 weeks. Improvements were seen in both the mental and physical aspects of fatigue [72]. However, Deng et al noted that true acupuncture was no more effective than sham acupuncture for reducing post-chemotherapy chronic fatigue [73]. Presently, there is not sufficient evidence to evaluate the benefits of acupuncture in CRF.
Other modalities. Massage therapy, music therapy, hypnosis, therapeutic touch, biofield therapies, relaxation, and reiki are other therapies for which few studies have been done, with mixed results, and additional research is needed [74]. Currently, there are not sufficient data to recommend any of these modalities.
Pharmacologic Interventions
Psychostimulants. Methylphenidate and modafinil are psychostimulants or wakefulness-promoting agents. Pilot studies showed benefit from methylphenidate and modafinil in CRF [75–77], but RCTs have yielded mixed results. Therefore, in patients with severe fatigue during cancer therapy, the initial management strategy involves evaluation and treatment of medical conditions such as anemia and a trial of non-pharmacological strategies as discussed above. If symptoms persist, then a therapeutic trial of a psychostimulant may be considered per NCCN guidelines for patients undergoing active cancer treatment [37].
Methylphenidate directly stimulates adrenergic receptors and indirectly releases dopamine and norepinephrine from presynaptic terminals, which may explain why the drug benefits patients receiving opioid-induced sedation. It is a commonly studied psychostimulant, though its mechanism of action in CRF is unclear. RCTs of methylphenidate have resulted in a wide range of findings due to the heterogeneity of study populations and variations in the dosage of methylphenidate. A meta-analysis of 7 studies indicates that methylphenidate benefitted the subgroup of patients with CRF [78]. Likewise, in an analysis of 5 RCTs, Minton et al showed a benefit of psychostimulants in fatigue compared with placebo [79]. However, another study of methylphenidate in patients with CRF showed a benefit only in patients with severe fatigue or advanced disease [80]. Methylphenidate was found to benefit cancer patients receiving opioid-induced sedation, as methylphenidate promotes wakefulness, though fatigue was not studied specifically [81]. In a trial with 30 hospice patients in which the methylphenidate dose was titrated based on response and adverse effects, Kerr at al found that the drug improved fatigue in a dose-dependent manner [82]. However, a study in patients with CRF at the University of Texas MD Anderson Cancer Center found no significant difference in BFI scores between patients receiving methylphenidate and those receiving placebo at the end of 2 weeks of treatment [83]. Also, other RCTs in patients undergoing adjuvant chemotherapy for breast cancer [84] and patients receiving radiation therapy for brain tumors [85] failed to demonstrate the efficacy of methylphenidate in CRF. It should be used cautiously after ruling out other causes of fatigue. The drug is overall well tolerated and side effects include headache and nausea.
Modafinil is a non-amphetamine psychostimulant that has been approved for the treatment of narcolepsy. In a trial studying the effect of modafinil on patients receiving docetaxel-based chemotherapy for metastatic breast or prostate cancer, there was a modest but not statistically significant improvement in fatigue scores on the MD Anderson Symptom Inventory compared with placebo. Nausea and vomiting were higher in the modafinil arm than in the placebo arm [86]. Similarly, modafinil was not superior to placebo for CRF in 208 patients with non-squamous cell lung cancer not undergoing chemotherapy or radiation [87]. A placebo effect was also noted in patients with multiple myeloma [88] and patients with primary brain tumors [89]. In a phase 3, multicenter, randomized, placebo-controlled, double-blind clinical trial of modafinil for CRF in 867 patients undergoing chemotherapy, there was a reduction in fatigue only for patients with severe baseline fatigue, with no significant effect on mild to moderate fatigue [90]. In another recent study, modafinil was shown to reduce depressive symptoms only in patients with severe fatigue (BFI item 3 score ≥ 7) [91]. This finding is consistent with previous studies showing benefit in patients with high baseline fatigue, but additional RCTs are needed to provide clarity. NCCN guidelines do not recommend the use of modafinil to treat CRF [37].
Other pharmacologic interventions. Corticosteroids are often used for symptom control in cancer patients. These drugs have anti-inflammatory effects through their modulation of pro-inflammatory cytokines [92]. In a RCT evaluating the efficacy of corticosteroids, patients receiving dexamethasone (4 mg twice daily) experienced significant improvement in their FACT-F scores compared with patients receiving placebo [93]. A similar benefit in fatigue was demonstrated in another study of methylprednisolone (32 mg daily) versus placebo [94]. Despite the benefits of steroids, their adverse effects, such as mood swings, gastritis, hyperglycemia, and immune suppression, limit their long-term use. Therefore, the use of steroids should be restricted to terminally ill fatigued patients with other symptoms such as anorexia, brain metastasis, or pain related to bone metastasis [37].
Testosterone replacement has been shown to diminish fatigue in non-cancer patients. Many men with advanced cancer have hypogonadism leading to low serum testosterone, which may cause fatigue. In a small trial in which cancer patients with hypogonadism received intramuscular testosterone every 14 days or placebo, the group receiving testosterone showed improvement in FACT-F scores, but there was no significant difference in FACT-F scores between the 2 groups [95].
Antidepressants have failed to demonstrate benefit in CRF without depression [8]. However, if a patient has both fatigue and depression, antidepressants may help [96]. A selective serotonin receptor inhibitor is recommended as a first-line antidepressant [97]. Patients with cancer are often receiving multiple medications, and medication interactions should be considered to prevent adverse events such as serotonin syndrome.
Complementary and Alternative Supplements
Studies using vitamin supplementation have been inconclusive in patients with CRF [74]. The use of other dietary supplements has yielded mixed results, and coenzyme Q has shown no benefit for patients with CRF [98].
The benefit of ginseng was studied in a RCT involving 364 patients with CRF. There was an improvement in Multidimensional Fatigue Symptom Inventory-short form (MFSI-SF) scores at 8 weeks in patients receiving 2000 mg of Wisconsin ginseng compared with patients receiving placebo [99]. Patients on active treatment had greater improvement as compared to the post-treatment group in this trial. In another study of high-dose panax ginseng (ginseng root) at 800 mg daily for 29 days, patients had improvement of CRF as well as overall quality of life, appetite, and sleep at night. It was also well tolerated with few adverse effects [100]. Interaction with warfarin, calcium channel blockers, antiplatelet agents, thrombolytic agents, imatinib, and other agents may occur; therefore, ginseng must be used with careful monitoring in selected patients. There is not enough evidence at this time to support the routine use of ginseng in CRF.
The seed extract of the guarana plant (Paullinia cupana) traditionally has been used as a stimulant. An improvement in fatigue scores was seen with the use of oral guarana (100 mg daily) at the end of 21 days in breast cancer patients receiving chemotherapy [101]. Further studies are needed for these results to be generalized and to understand the adverse effects and interaction profile of guarana.
Re-evaluation
Patients who have completed cancer treatment must be monitored for fatigue over the long term, as fatigue may exist beyond the period of active treatment. Many studies have shown fatigue in breast cancer survivors, and fatigue has been demonstrated in survivors of colorectal, lung, and prostate cancers as well as myeloproliferative neoplasms [28]. Therefore, it is important to screen patients for fatigue during follow-up visits. There are currently no studies evaluating the long-term treatment of fatigue. In our experience, the timing of follow-up depends on the level of fatigue and interventions prescribed. Once fatigue is stabilized to a level with which the patient is able to cope, the time interval for follow up may be lengthened. Annual visits may suffice in patients with mild fatigue. Follow-up of patients with moderate to severe fatigue depends on the level of fatigue, the ability to cope, choice of treatment, and presence of contributing factors.
Conclusion
CRF is a complex condition that places a significant burden on patients and caregivers, resulting in emotional distress, poor functioning, and suffering. Fatigue can occur before, during, and long after cancer treatment. The approach to CRF begins with screening for and educating patients and their caregivers about the symptoms. Many screening scales are available that may be used to follow patients’ progress over time. The evaluation and management of contributing conditions may help improve fatigue. If the fatigue persists, an individualized approach with a combination of nonpharmacologic and pharmacologic approaches should be considered. More research is needed to understand brain signaling pathways, cytokine changes, and genomic changes in cancer patients with fatigue. Though many hypotheses have been proposed, to date there is no biological marker to assess this condition. Biomarker research needs to be advanced to help to identify patients at risk for fatigue. As cytokines have a major role in CRF, targeted therapy to block cytokine pathways may also be explored in the future.
Acknowledgment: Bryan Tutt provided editorial assistance.
Corresponding author: Carmelita P. Escalante, MD, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX 77030, cescalan@mdanderson.org.
Financial disclosures: None.
1. Scherber RM, Kosiorek HE, Senyak Z, et al. Comprehensively understanding fatigue in patients with myeloproliferative neoplasms. Cancer 2016;122:477–85.
2. Neefjes EC, van der Vorst MJ, Blauwhoff-Buskermolen S, Verheul HM. Aiming for a better understanding and management of cancer-related fatigue. Oncologist 2013;18:1135–43.
3. Radbruch L, Strasser F, Elsner F, et al. Fatigue in palliative care patients -- an EAPC approach. Palliat Med 2008;22:13–32.
4. Capuron L, Pagnoni G, Demetrashvili MF, et al. Basal ganglia hypermetabolism and symptoms of fatigue during interferon-alpha therapy. Neuropsychopharmacology 2007;32:2384–92.
5. Kisiel-Sajewicz K, Siemionow V, Seyidova-Khoshknabi D, et al. Myoelectrical manifestation of fatigue less prominent in patients with cancer related fatigue. PLoS One 2013;8:e83636.
6. Bower JE, Ganz PA, Aziz N. Altered cortisol response to psychologic stress in breast cancer survivors with persistent fatigue. Psychosom Med 2005;67:277–80.
7. Barsevick A, Frost M, Zwinderman A, et al. I’m so tired: biological and genetic mechanisms of cancer-related fatigue. Qual Life Res 2010;19:1419–27.
8. Morrow GR, Hickok JT, Roscoe JA, et al. Differential effects of paroxetine on fatigue and depression: a randomized, double-blind trial from the University of Rochester Cancer Center Community Clinical Oncology Program. J Clin Oncol 2003;21:4635–41.
9. Fontes-Oliveira CC, Busquets S, Toledo M, et al. Mitochondrial and sarcoplasmic reticulum abnormalities in cancer cachexia: altered energetic efficiency? Biochim Biophys Acta 2013;1830:2770–8.
10. Agteresch HJ, Dagnelie PC, van der Gaast A, et al. Randomized clinical trial of adenosine 5’-triphosphate in patients with advanced non-small-cell lung cancer. J Natl Cancer Inst 2000;92:321–8.
11. Beijer S, Hupperets PS, van den Borne BE, et al. Randomized clinical trial on the effects of adenosine 5’-triphosphate infusions on quality of life, functional status, and fatigue in preterminal cancer patients. J Pain Symptom Manage 2010;40:520–30.
12. Kisiel-Sajewicz K, Davis MP, Siemionow V, et al. Lack of muscle contractile property changes at the time of perceived physical exhaustion suggests central mechanisms contributing to early motor task failure in patients with cancer-related fatigue. J Pain Symptom Manage 2012;44:351–61.
13. Ryan JL, Carroll JK, Ryan EP, et al. Mechanisms of cancer-related fatigue. Oncologist 2007;12 Suppl 1:22–34.
14. Seruga B, Zhang H, Bernstein LJ, Tannock IF. Cytokines and their relationship to the symptoms and outcome of cancer. Nat Rev Cancer 2008;8:887–99.
15. Wang XS, Giralt SA, Mendoza TR, et al. Clinical factors associated with cancer-related fatigue in patients being treated for leukemia and non-Hodgkin’s lymphoma. J Clin Oncol 2002;20:1319–28.
16. Collado-Hidalgo A, Bower JE, Ganz PA, et al. Inflammatory biomarkers for persistent fatigue in breast cancer survivors. Clin Cancer Res 2006;12:2759–66.
17. Wang XS, Shi Q, Williams LA, et al. Serum interleukin-6 predicts the development of multiple symptoms at nadir of allogeneic hematopoietic stem cell transplantation. Cancer 2008;113:2102–9.
18. Inagaki M, Isono M, Okuyama T, et al. Plasma interleukin-6 and fatigue in terminally ill cancer patients. J Pain Symptom Manage 2008;35:153–61.
19. Laird BJ, McMillan DC, Fayers P, et al. The systemic inflammatory response and its relationship to pain and other symptoms in advanced cancer. Oncologist 2013;18:1050–5.
20. Bower JE, Ganz PA, Irwin MR, et al. Inflammation and behavioral symptoms after breast cancer treatment: do fatigue, depression, and sleep disturbance share a common underlying mechanism? J Clin Oncol 2011;29:3517–22.
21. Whistler T, Taylor R, Craddock RC, et al. Gene expression correlates of unexplained fatigue. Pharmacogenomics 2006;7:395–405.
22. Fagundes CP, Bennett JM, Alfano CM, et al. Social support and socioeconomic status interact to predict Epstein-Barr virus latency in women awaiting diagnosis or newly diagnosed with breast cancer. Health Psychol 2012;31:11–19.
23. Landmark-Hoyvik H, Reinertsen KV, Loge JH, et al. Alterations of gene expression in blood cells associated with chronic fatigue in breast cancer survivors. Pharmacogenomics J 2009;9:333–40.
24. Smith AK, Conneely KN, Pace TW, et al. Epigenetic changes associated with inflammation in breast cancer patients treated with chemotherapy. Brain Behav Immun 2014;38:227–36.
25. Kim S, Miller BJ, Stefanek ME, Miller AH. Inflammation-induced activation of the indoleamine 2,3-dioxygenase pathway: Relevance to cancer-related fatigue. Cancer 2015;121:2129–36.
26. Mills PJ, Parker B, Dimsdale JE, et al. The relationship between fatigue and quality of life and inflammation during anthracycline-based chemotherapy in breast cancer. Biol Psychol 2005;69:85–96.
27. Jean-Pierre P, Figueroa-Moseley CD, Kohli S, et al. Assessment of cancer-related fatigue: implications for clinical diagnosis and treatment. Oncologist 2007;12 Suppl 1:11–21.
28. Wang XS, Zhao F, Fisch MJ, et al. Prevalence and characteristics of moderate to severe fatigue: a multicenter study in cancer patients and survivors. Cancer 2014;120:425–32.
29. Mendoza TR, Wang XS, Cleeland CS, et al. The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer 1999;85:1186–96.
30. Mendoza ME, Capafons A, Gralow JR, et al. Randomized controlled trial of the Valencia model of waking hypnosis plus CBT for pain, fatigue, and sleep management in patients with cancer and cancer survivors. Psychooncology 2016 Jul 28.
31. Glaus A. Assessment of fatigue in cancer and non-cancer patients and in healthy individuals. Support Care Cancer 1993;1:305–15.
32. Seyidova-Khoshknabi D, Davis MP, Walsh D. A systematic review of cancer-related fatigue measurement questionnaires. Am J Hosp Palliat Care 2011;28:119–29.
33. Holzner B, Kemmler G, Greil R, et al. The impact of hemoglobin levels on fatigue and quality of life in cancer patients. Ann Oncol 2002;13:965–73.
34. Stein KD, Jacobsen PB, Blanchard CM, Thors C. Further validation of the multidimensional fatigue symptom inventory-short form. J Pain Symptom Manage 2004;27:14–23.
35. Hwang SS, Chang VT, Rue M, Kasimis B. Multidimensional independent predictors of cancer-related fatigue. J Pain Symptom Manage 2003;26:604–14.
36. Peterspm DR. Scope and generality of verbally defined personality factors. Psychol Rev 1965;72:48–59.
37. Berger AM, Abernethy AP, Atkinson A, et al. NCCN Clinical Practice Guidelines Cancer-related fatigue. J Natl Compr Canc Netw 2010;8:904–31.
38. Crawford J, Cella D, Cleeland CS, et al. Relationship between changes in hemoglobin level and quality of life during chemotherapy in anemic cancer patients receiving epoetin alfa therapy. Cancer 2002;95:888–95.
39. Tonia T, Mettler A, Robert N, et al. Erythropoietin or darbepoetin for patients with cancer. Cochrane Database Syst Rev 2012;12:CD003407.
40. Rizzo JD, Brouwers M, Hurley P, et al. American Society of Hematology/American Society of Clinical Oncology clinical practice guideline update on the use of epoetin and darbepoetin in adult patients with cancer. Blood 2010;116:4045–59.
41. Preston NJ, Hurlow A, Brine J, Bennett MI. Blood transfusions for anaemia in patients with advanced cancer. Cochrane Database Syst Rev 2012(2):CD009007.
42. Minton O, Stone PC. A comparison of cognitive function, sleep and activity levels in disease-free breast cancer patients with or without cancer-related fatigue syndrome. BMJ Support Palliat Care 2012;2:231–8.
43. Heckler CE, Garland SN, Peoples AR, et al. Cognitive behavioral therapy for insomnia, but not armodafinil, improves fatigue in cancer survivors with insomnia: a randomized placebo-controlled trial. Support Care Cancer 2016;24:2059–66.
44. Howell D, Oliver TK, Keller-Olaman S, et al. Sleep disturbance in adults with cancer: a systematic review of evidence for best practices in assessment and management for clinical practice. Ann Oncol 2014;25:791–800.
45. Wilt TJ, MacDonald R, Brasure M, et al. Pharmacologic treatment of insomnia disorder: an evidence report for a clinical practice guideline by the American College of Physicians. Ann Intern Med 2016;165:103–12.
46. Kuriyama A, Honda M, Hayashino Y. Ramelteon for the treatment of insomnia in adults: a systematic review and meta-analysis. Sleep Med 2014;15:385–92.
47. Strasser F, Palmer JL, Schover LR, et al. The impact of hypogonadism and autonomic dysfunction on fatigue, emotional function, and sexual desire in male patients with advanced cancer: a pilot study. Cancer 2006;107:2949–57.
48. Agasi-Idenburg SC, Thong MS, Punt CJ, et al. Comparison of symptom clusters associated with fatigue in older and younger survivors of colorectal cancer. Support Care Cancer 2017;25:625–32.
49. Miaskowski C, Aouizerat BE. Is there a biological basis for the clustering of symptoms? Semin Oncol Nurs 2007;23:99–105.
50. de Raaf PJ, de Klerk C, Timman R, et al. Systematic monitoring and treatment of physical symptoms to alleviate fatigue in patients with advanced cancer: a randomized controlled trial. J Clin Oncol 2013;31:716–23.
51. Barsevick AM, Whitmer K, Sweeney C, Nail LM. A pilot study examining energy conservation for cancer treatment-related fatigue. Cancer Nurs 2002;25:333–41.
52. Barsevick AM, Dudley W, Beck S, et a;. A randomized clinical trial of energy conservation for patients with cancer-related fatigue. Cancer 2004;100:1302–10.
53. Luciani A, Jacobsen PB, Extermann M, et al. Fatigue and functional dependence in older cancer patients. Am J Clin Oncol 2008;31:424–30.
54. Abrahams HJ, Gielissen MF, Goedendorp MM, et al. A randomized controlled trial of web-based cognitive behavioral therapy for severely fatigued breast cancer survivors (CHANGE-study): study protocol. BMC Cancer 2015;15:765.
55. Quesnel C, Savard J, Simard S, et al. Efficacy of cognitive-behavioral therapy for insomnia in women treated for nonmetastatic breast cancer. J Consult Clin Psychol 2003;71:189–200.
56. Goedendorp MM, Gielissen MF, Verhagen CA, Bleijenberg G. Psychosocial interventions for reducing fatigue during cancer treatment in adults. Cochrane Database Syst Rev 2009(1):CD006953.
57. Greiwe JS, Cheng B, Rubin DC, et al. Resistance exercise decreases skeletal muscle tumor necrosis factor alpha in frail elderly humans. FASEB J 2001;15:475–82.
58. Furmaniak AC, Menig M, Markes MH. Exercise for women receiving adjuvant therapy for breast cancer. Cochrane Database Syst Rev 2016;(9):CD005001.
59. Cramp F, Byron-Daniel J. Exercise for the management of cancer-related fatigue in adults. Cochrane Database Syst Rev 2012;(11):CD006145.
60. Brown JC, Huedo-Medina TB, Pescatello LS, et al. Efficacy of exercise interventions in modulating cancer-related fatigue among adult cancer survivors: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2011;20:123–33.
61. Steindorf K, Schmidt ME, Klassen O, et al. Randomized, controlled trial of resistance training in breast cancer patients receiving adjuvant radiotherapy: results on cancer-related fatigue and quality of life. Ann Oncol 2014;25:2237–43.
62. Bower JE, Bak K, Berger A, et al. Screening, assessment, and management of fatigue in adult survivors of cancer: an American Society of Clinical oncology clinical practice guideline adaptation. J Clin Oncol 2014;32:1840–50.
63. Kenjale AA, Hornsby WE, Crowgey T, et al. Pre-exercise participation cardiovascular screening in a heterogeneous cohort of adult cancer patients. Oncologist 2014;19:999–1005.
64. Oldervoll LM, Loge JH, Paltiel H, et al. The effect of a physical exercise program in palliative care: A phase II study. J Pain Symptom Manage 2006;31:421–30.
65. Porock D, Kristjanson LJ, Tinnelly K, et al. An exercise intervention for advanced cancer patients experiencing fatigue: a pilot study. J Palliat Care 2000;16:30–6.
66. Lengacher CA, Kip KE, Reich RR, et al. A cost-effective mindfulness stress reduction program: a randomized control trial for breast cancer survivors. Nursing Econ 2015;33:210–8, 32.
67. Lengacher CA, Reich RR, Post-White J, et al. Mindfulness based stress reduction in post-treatment breast cancer patients: an examination of symptoms and symptom clusters. J Behav Med 2012;35:86–94.
68. Sprod LK, Fernandez ID, Janelsins MC, et al. Effects of yoga on cancer-related fatigue and global side-effect burden in older cancer survivors. J Geriatr Oncol 2015;6:8–14.
69. Wang G, Wang S, Jiang P, Zeng C. [Effect of Yoga on cancer related fatigue in breast cancer patients with chemotherapy]. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2014;39:1077–82.
70. Stan DL, Croghan KA, Croghan IT, et al. Randomized pilot trial of yoga versus strengthening exercises in breast cancer survivors with cancer-related fatigue. Support Care Cancer 2016;24:4005–15.
71. Larkey LK, Roe DJ, Weihs KL, et al. Randomized controlled trial of Qigong/Tai Chi Easy on cancer-related fatigue in breast cancer survivors. Ann Behav Med 2015;49:165–76.
72. Molassiotis A, Bardy J, Finnegan-John J, et al. Acupuncture for cancer-related fatigue in patients with breast cancer: a pragmatic randomized controlled trial. J Clin Oncol 2012;30:4470–6.
73. Deng G, Chan Y, Sjoberg D, et al. Acupuncture for the treatment of post-chemotherapy chronic fatigue: a randomized, blinded, sham-controlled trial. Support Care Cancer 2013;21:1735–41.
74. Finnegan-John J, Molassiotis A, Richardson A, Ream E. A systematic review of complementary and alternative medicine interventions for the management of cancer-related fatigue. Integr Cancer Ther 2013;12:276–90.
75. Schwartz AL, Thompson JA, Masood N. Interferon-induced fatigue in patients with melanoma: a pilot study of exercise and methylphenidate. Oncol Nurs Forum 2002;29:E85–90.
76. Spathis A, Dhillan R, Booden D, et al. Modafinil for the treatment of fatigue in lung cancer: a pilot study. Palliat Med 2009;23:325–31.
77. Blackhall L, Petroni G, Shu J, et al. A pilot study evaluating the safety and efficacy of modafinal for cancer-related fatigue. J Palliat Med 2009;12:433–9.
78. Qu D, Zhang Z, Yu X, et al. Psychotropic drugs for the management of cancer-related fatigue: a systematic review and meta-analysis. Eur J Cancer Care (Engl) 2015;25:970–9.
79. Minton O, Richardson A, Sharpe M, et al. Drug therapy for the management of cancer-related fatigue. Cochrane Database Syst Rev 2010(7):CD006704.
80. Moraska AR, Sood A, Dakhil SR, et al. Phase III, randomized, double-blind, placebo-controlled study of long-acting methylphenidate for cancer-related fatigue: North Central Cancer Treatment Group NCCTG-N05C7 trial. J Clin Oncol 2010;28:3673–9.
81. Bruera E, Driver L, Barnes EA, et al. Patient-controlled methylphenidate for the management of fatigue in patients with advanced cancer: a preliminary report. J Clin Oncol 2003;21:4439–43.
82. Kerr CW, Drake J, Milch RA, et al. Effects of methylphenidate on fatigue and depression: a randomized, double-blind, placebo-controlled trial. J Pain Symptom Manage 2012;43:68–77.
83. Escalante CP, Meyers C, Reuben JM, et al. A randomized, double-blind, 2-period, placebo-controlled crossover trial of a sustained-release methylphenidate in the treatment of fatigue in cancer patients. Cancer J 2014;20:8–14.
84. Mar Fan HG, Clemons M, Xu W, et al. A randomised, placebo-controlled, double-blind trial of the effects of d-methylphenidate on fatigue and cognitive dysfunction in women undergoing adjuvant chemotherapy for breast cancer. Support Care Cancer 2008;16:577–83.
85. Butler JM Jr, Case LD, Atkins J, et al. A phase III, double-blind, placebo-controlled prospective randomized clinical trial of d-threo-methylphenidate HCl in brain tumor patients receiving radiation therapy. Int J Radiat Oncol Biol Phys 2007;69:1496–501.
86. Hovey E, de Souza P, Marx G, et al. Phase III, randomized, double-blind, placebo-controlled study of modafinil for fatigue in patients treated with docetaxel-based chemotherapy. Support Care Cancer 2014;22:1233–42.
87. Spathis A, Fife K, Blackhall F, et al. Modafinil for the treatment of fatigue in lung cancer: results of a placebo-controlled, double-blind, randomized trial. J Clin Oncol 2014;32:1882–8.
88. Berenson JR, Yellin O, Shamasunder HK, et al. A phase 3 trial of armodafinil for the treatment of cancer-related fatigue for patients with multiple myeloma. Support Care Cancer 2015;23:1503–12.
89. Boele FW, Douw L, de Groot M, et al. The effect of modafinil on fatigue, cognitive functioning, and mood in primary brain tumor patients: a multicenter randomized controlled trial. Neuro Oncol 2013;15:1420–8.
90. Jean-Pierre P, Morrow GR, Roscoe JA, et al. A phase 3 randomized, placebo-controlled, double-blind, clinical trial of the effect of modafinil on cancer-related fatigue among 631 patients receiving chemotherapy: a University of Rochester Cancer Center Community Clinical Oncology Program Research base study. Cancer 2010;116:3513–20.
91. Conley CC, Kamen CS, Heckler CE, et al. Modafinil moderates the relationship between cancer-related fatigue and depression in 541 patients receiving chemotherapy. J Clin Psychopharmacol 2016;36:82–5.
92. Brattsand R, Linden M. Cytokine modulation by glucocorticoids: mechanisms and actions in cellular studies. Aliment Pharmacol Ther 1996;10 Suppl 2:81–90.
93. Yennurajalingam S, Frisbee-Hume S, Palmer JL, et al. Reduction of cancer-related fatigue with dexamethasone: a double-blind, randomized, placebo-controlled trial in patients with advanced cancer. J Clin Oncol 2013;31:3076–82.
94. Bruera E, Roca E, Cedaro L, et al. Action of oral methylprednisolone in terminal cancer patients: a prospective randomized double-blind study. Cancer Treat Rep 1985;69:751–4.
95. Pulivarthi K, Dev R, Garcia J, et al. Testosterone replacement for fatigue in male hypogonadic patients with advanced cancer: A preliminary double-blind placebo-controlled trial. J Clin Oncol 2012;30 (suppl). Abstract e19643.
96. Palesh OG, Mustian KM, Peppone LJ, et al. Impact of paroxetine on sleep problems in 426 cancer patients receiving chemotherapy: a trial from the University of Rochester Cancer Center Community Clinical Oncology Program. Sleep Med 2012;13:1184–90.
97. Thekdi SM, Trinidad A, Roth A. Psychopharmacology in Cancer. Curr Psychiatry Rep 2014;17:529.
98. Lesser GJ. Case D, Stark N, et al. A randomized, double-blind, placebo-controlled study of oral coenzyme Q10 to relieve self-reported treatment-related fatigue in newly diagnosed patients with breast cancer. J Support Oncol 2013;11:31–42.
99. Barton DL, Liu H, Dakhil SR, et al. Wisconsin Ginseng (Panax quinquefolius) to improve cancer-related fatigue: a randomized, double-blind trial, N07C2. J Natl Cancer Inst 2013;105:1230–8.
100. Yennurajalingam S, Reddy A, Tannir NM, et al. High-dose Asian ginseng (panax ginseng) for cancer-related fatigue: a preliminary report. Integr Cancer Ther 2015;14:419–27.
101. Howell D, Keller-Olaman S, Oliver TK, et al. A pan-Canadian practice guideline and algorithm: screening, assessment, and supportive care of adults with cancer-related fatigue. Curr Oncol 2013;20:e233–46.
1. Scherber RM, Kosiorek HE, Senyak Z, et al. Comprehensively understanding fatigue in patients with myeloproliferative neoplasms. Cancer 2016;122:477–85.
2. Neefjes EC, van der Vorst MJ, Blauwhoff-Buskermolen S, Verheul HM. Aiming for a better understanding and management of cancer-related fatigue. Oncologist 2013;18:1135–43.
3. Radbruch L, Strasser F, Elsner F, et al. Fatigue in palliative care patients -- an EAPC approach. Palliat Med 2008;22:13–32.
4. Capuron L, Pagnoni G, Demetrashvili MF, et al. Basal ganglia hypermetabolism and symptoms of fatigue during interferon-alpha therapy. Neuropsychopharmacology 2007;32:2384–92.
5. Kisiel-Sajewicz K, Siemionow V, Seyidova-Khoshknabi D, et al. Myoelectrical manifestation of fatigue less prominent in patients with cancer related fatigue. PLoS One 2013;8:e83636.
6. Bower JE, Ganz PA, Aziz N. Altered cortisol response to psychologic stress in breast cancer survivors with persistent fatigue. Psychosom Med 2005;67:277–80.
7. Barsevick A, Frost M, Zwinderman A, et al. I’m so tired: biological and genetic mechanisms of cancer-related fatigue. Qual Life Res 2010;19:1419–27.
8. Morrow GR, Hickok JT, Roscoe JA, et al. Differential effects of paroxetine on fatigue and depression: a randomized, double-blind trial from the University of Rochester Cancer Center Community Clinical Oncology Program. J Clin Oncol 2003;21:4635–41.
9. Fontes-Oliveira CC, Busquets S, Toledo M, et al. Mitochondrial and sarcoplasmic reticulum abnormalities in cancer cachexia: altered energetic efficiency? Biochim Biophys Acta 2013;1830:2770–8.
10. Agteresch HJ, Dagnelie PC, van der Gaast A, et al. Randomized clinical trial of adenosine 5’-triphosphate in patients with advanced non-small-cell lung cancer. J Natl Cancer Inst 2000;92:321–8.
11. Beijer S, Hupperets PS, van den Borne BE, et al. Randomized clinical trial on the effects of adenosine 5’-triphosphate infusions on quality of life, functional status, and fatigue in preterminal cancer patients. J Pain Symptom Manage 2010;40:520–30.
12. Kisiel-Sajewicz K, Davis MP, Siemionow V, et al. Lack of muscle contractile property changes at the time of perceived physical exhaustion suggests central mechanisms contributing to early motor task failure in patients with cancer-related fatigue. J Pain Symptom Manage 2012;44:351–61.
13. Ryan JL, Carroll JK, Ryan EP, et al. Mechanisms of cancer-related fatigue. Oncologist 2007;12 Suppl 1:22–34.
14. Seruga B, Zhang H, Bernstein LJ, Tannock IF. Cytokines and their relationship to the symptoms and outcome of cancer. Nat Rev Cancer 2008;8:887–99.
15. Wang XS, Giralt SA, Mendoza TR, et al. Clinical factors associated with cancer-related fatigue in patients being treated for leukemia and non-Hodgkin’s lymphoma. J Clin Oncol 2002;20:1319–28.
16. Collado-Hidalgo A, Bower JE, Ganz PA, et al. Inflammatory biomarkers for persistent fatigue in breast cancer survivors. Clin Cancer Res 2006;12:2759–66.
17. Wang XS, Shi Q, Williams LA, et al. Serum interleukin-6 predicts the development of multiple symptoms at nadir of allogeneic hematopoietic stem cell transplantation. Cancer 2008;113:2102–9.
18. Inagaki M, Isono M, Okuyama T, et al. Plasma interleukin-6 and fatigue in terminally ill cancer patients. J Pain Symptom Manage 2008;35:153–61.
19. Laird BJ, McMillan DC, Fayers P, et al. The systemic inflammatory response and its relationship to pain and other symptoms in advanced cancer. Oncologist 2013;18:1050–5.
20. Bower JE, Ganz PA, Irwin MR, et al. Inflammation and behavioral symptoms after breast cancer treatment: do fatigue, depression, and sleep disturbance share a common underlying mechanism? J Clin Oncol 2011;29:3517–22.
21. Whistler T, Taylor R, Craddock RC, et al. Gene expression correlates of unexplained fatigue. Pharmacogenomics 2006;7:395–405.
22. Fagundes CP, Bennett JM, Alfano CM, et al. Social support and socioeconomic status interact to predict Epstein-Barr virus latency in women awaiting diagnosis or newly diagnosed with breast cancer. Health Psychol 2012;31:11–19.
23. Landmark-Hoyvik H, Reinertsen KV, Loge JH, et al. Alterations of gene expression in blood cells associated with chronic fatigue in breast cancer survivors. Pharmacogenomics J 2009;9:333–40.
24. Smith AK, Conneely KN, Pace TW, et al. Epigenetic changes associated with inflammation in breast cancer patients treated with chemotherapy. Brain Behav Immun 2014;38:227–36.
25. Kim S, Miller BJ, Stefanek ME, Miller AH. Inflammation-induced activation of the indoleamine 2,3-dioxygenase pathway: Relevance to cancer-related fatigue. Cancer 2015;121:2129–36.
26. Mills PJ, Parker B, Dimsdale JE, et al. The relationship between fatigue and quality of life and inflammation during anthracycline-based chemotherapy in breast cancer. Biol Psychol 2005;69:85–96.
27. Jean-Pierre P, Figueroa-Moseley CD, Kohli S, et al. Assessment of cancer-related fatigue: implications for clinical diagnosis and treatment. Oncologist 2007;12 Suppl 1:11–21.
28. Wang XS, Zhao F, Fisch MJ, et al. Prevalence and characteristics of moderate to severe fatigue: a multicenter study in cancer patients and survivors. Cancer 2014;120:425–32.
29. Mendoza TR, Wang XS, Cleeland CS, et al. The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer 1999;85:1186–96.
30. Mendoza ME, Capafons A, Gralow JR, et al. Randomized controlled trial of the Valencia model of waking hypnosis plus CBT for pain, fatigue, and sleep management in patients with cancer and cancer survivors. Psychooncology 2016 Jul 28.
31. Glaus A. Assessment of fatigue in cancer and non-cancer patients and in healthy individuals. Support Care Cancer 1993;1:305–15.
32. Seyidova-Khoshknabi D, Davis MP, Walsh D. A systematic review of cancer-related fatigue measurement questionnaires. Am J Hosp Palliat Care 2011;28:119–29.
33. Holzner B, Kemmler G, Greil R, et al. The impact of hemoglobin levels on fatigue and quality of life in cancer patients. Ann Oncol 2002;13:965–73.
34. Stein KD, Jacobsen PB, Blanchard CM, Thors C. Further validation of the multidimensional fatigue symptom inventory-short form. J Pain Symptom Manage 2004;27:14–23.
35. Hwang SS, Chang VT, Rue M, Kasimis B. Multidimensional independent predictors of cancer-related fatigue. J Pain Symptom Manage 2003;26:604–14.
36. Peterspm DR. Scope and generality of verbally defined personality factors. Psychol Rev 1965;72:48–59.
37. Berger AM, Abernethy AP, Atkinson A, et al. NCCN Clinical Practice Guidelines Cancer-related fatigue. J Natl Compr Canc Netw 2010;8:904–31.
38. Crawford J, Cella D, Cleeland CS, et al. Relationship between changes in hemoglobin level and quality of life during chemotherapy in anemic cancer patients receiving epoetin alfa therapy. Cancer 2002;95:888–95.
39. Tonia T, Mettler A, Robert N, et al. Erythropoietin or darbepoetin for patients with cancer. Cochrane Database Syst Rev 2012;12:CD003407.
40. Rizzo JD, Brouwers M, Hurley P, et al. American Society of Hematology/American Society of Clinical Oncology clinical practice guideline update on the use of epoetin and darbepoetin in adult patients with cancer. Blood 2010;116:4045–59.
41. Preston NJ, Hurlow A, Brine J, Bennett MI. Blood transfusions for anaemia in patients with advanced cancer. Cochrane Database Syst Rev 2012(2):CD009007.
42. Minton O, Stone PC. A comparison of cognitive function, sleep and activity levels in disease-free breast cancer patients with or without cancer-related fatigue syndrome. BMJ Support Palliat Care 2012;2:231–8.
43. Heckler CE, Garland SN, Peoples AR, et al. Cognitive behavioral therapy for insomnia, but not armodafinil, improves fatigue in cancer survivors with insomnia: a randomized placebo-controlled trial. Support Care Cancer 2016;24:2059–66.
44. Howell D, Oliver TK, Keller-Olaman S, et al. Sleep disturbance in adults with cancer: a systematic review of evidence for best practices in assessment and management for clinical practice. Ann Oncol 2014;25:791–800.
45. Wilt TJ, MacDonald R, Brasure M, et al. Pharmacologic treatment of insomnia disorder: an evidence report for a clinical practice guideline by the American College of Physicians. Ann Intern Med 2016;165:103–12.
46. Kuriyama A, Honda M, Hayashino Y. Ramelteon for the treatment of insomnia in adults: a systematic review and meta-analysis. Sleep Med 2014;15:385–92.
47. Strasser F, Palmer JL, Schover LR, et al. The impact of hypogonadism and autonomic dysfunction on fatigue, emotional function, and sexual desire in male patients with advanced cancer: a pilot study. Cancer 2006;107:2949–57.
48. Agasi-Idenburg SC, Thong MS, Punt CJ, et al. Comparison of symptom clusters associated with fatigue in older and younger survivors of colorectal cancer. Support Care Cancer 2017;25:625–32.
49. Miaskowski C, Aouizerat BE. Is there a biological basis for the clustering of symptoms? Semin Oncol Nurs 2007;23:99–105.
50. de Raaf PJ, de Klerk C, Timman R, et al. Systematic monitoring and treatment of physical symptoms to alleviate fatigue in patients with advanced cancer: a randomized controlled trial. J Clin Oncol 2013;31:716–23.
51. Barsevick AM, Whitmer K, Sweeney C, Nail LM. A pilot study examining energy conservation for cancer treatment-related fatigue. Cancer Nurs 2002;25:333–41.
52. Barsevick AM, Dudley W, Beck S, et a;. A randomized clinical trial of energy conservation for patients with cancer-related fatigue. Cancer 2004;100:1302–10.
53. Luciani A, Jacobsen PB, Extermann M, et al. Fatigue and functional dependence in older cancer patients. Am J Clin Oncol 2008;31:424–30.
54. Abrahams HJ, Gielissen MF, Goedendorp MM, et al. A randomized controlled trial of web-based cognitive behavioral therapy for severely fatigued breast cancer survivors (CHANGE-study): study protocol. BMC Cancer 2015;15:765.
55. Quesnel C, Savard J, Simard S, et al. Efficacy of cognitive-behavioral therapy for insomnia in women treated for nonmetastatic breast cancer. J Consult Clin Psychol 2003;71:189–200.
56. Goedendorp MM, Gielissen MF, Verhagen CA, Bleijenberg G. Psychosocial interventions for reducing fatigue during cancer treatment in adults. Cochrane Database Syst Rev 2009(1):CD006953.
57. Greiwe JS, Cheng B, Rubin DC, et al. Resistance exercise decreases skeletal muscle tumor necrosis factor alpha in frail elderly humans. FASEB J 2001;15:475–82.
58. Furmaniak AC, Menig M, Markes MH. Exercise for women receiving adjuvant therapy for breast cancer. Cochrane Database Syst Rev 2016;(9):CD005001.
59. Cramp F, Byron-Daniel J. Exercise for the management of cancer-related fatigue in adults. Cochrane Database Syst Rev 2012;(11):CD006145.
60. Brown JC, Huedo-Medina TB, Pescatello LS, et al. Efficacy of exercise interventions in modulating cancer-related fatigue among adult cancer survivors: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2011;20:123–33.
61. Steindorf K, Schmidt ME, Klassen O, et al. Randomized, controlled trial of resistance training in breast cancer patients receiving adjuvant radiotherapy: results on cancer-related fatigue and quality of life. Ann Oncol 2014;25:2237–43.
62. Bower JE, Bak K, Berger A, et al. Screening, assessment, and management of fatigue in adult survivors of cancer: an American Society of Clinical oncology clinical practice guideline adaptation. J Clin Oncol 2014;32:1840–50.
63. Kenjale AA, Hornsby WE, Crowgey T, et al. Pre-exercise participation cardiovascular screening in a heterogeneous cohort of adult cancer patients. Oncologist 2014;19:999–1005.
64. Oldervoll LM, Loge JH, Paltiel H, et al. The effect of a physical exercise program in palliative care: A phase II study. J Pain Symptom Manage 2006;31:421–30.
65. Porock D, Kristjanson LJ, Tinnelly K, et al. An exercise intervention for advanced cancer patients experiencing fatigue: a pilot study. J Palliat Care 2000;16:30–6.
66. Lengacher CA, Kip KE, Reich RR, et al. A cost-effective mindfulness stress reduction program: a randomized control trial for breast cancer survivors. Nursing Econ 2015;33:210–8, 32.
67. Lengacher CA, Reich RR, Post-White J, et al. Mindfulness based stress reduction in post-treatment breast cancer patients: an examination of symptoms and symptom clusters. J Behav Med 2012;35:86–94.
68. Sprod LK, Fernandez ID, Janelsins MC, et al. Effects of yoga on cancer-related fatigue and global side-effect burden in older cancer survivors. J Geriatr Oncol 2015;6:8–14.
69. Wang G, Wang S, Jiang P, Zeng C. [Effect of Yoga on cancer related fatigue in breast cancer patients with chemotherapy]. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2014;39:1077–82.
70. Stan DL, Croghan KA, Croghan IT, et al. Randomized pilot trial of yoga versus strengthening exercises in breast cancer survivors with cancer-related fatigue. Support Care Cancer 2016;24:4005–15.
71. Larkey LK, Roe DJ, Weihs KL, et al. Randomized controlled trial of Qigong/Tai Chi Easy on cancer-related fatigue in breast cancer survivors. Ann Behav Med 2015;49:165–76.
72. Molassiotis A, Bardy J, Finnegan-John J, et al. Acupuncture for cancer-related fatigue in patients with breast cancer: a pragmatic randomized controlled trial. J Clin Oncol 2012;30:4470–6.
73. Deng G, Chan Y, Sjoberg D, et al. Acupuncture for the treatment of post-chemotherapy chronic fatigue: a randomized, blinded, sham-controlled trial. Support Care Cancer 2013;21:1735–41.
74. Finnegan-John J, Molassiotis A, Richardson A, Ream E. A systematic review of complementary and alternative medicine interventions for the management of cancer-related fatigue. Integr Cancer Ther 2013;12:276–90.
75. Schwartz AL, Thompson JA, Masood N. Interferon-induced fatigue in patients with melanoma: a pilot study of exercise and methylphenidate. Oncol Nurs Forum 2002;29:E85–90.
76. Spathis A, Dhillan R, Booden D, et al. Modafinil for the treatment of fatigue in lung cancer: a pilot study. Palliat Med 2009;23:325–31.
77. Blackhall L, Petroni G, Shu J, et al. A pilot study evaluating the safety and efficacy of modafinal for cancer-related fatigue. J Palliat Med 2009;12:433–9.
78. Qu D, Zhang Z, Yu X, et al. Psychotropic drugs for the management of cancer-related fatigue: a systematic review and meta-analysis. Eur J Cancer Care (Engl) 2015;25:970–9.
79. Minton O, Richardson A, Sharpe M, et al. Drug therapy for the management of cancer-related fatigue. Cochrane Database Syst Rev 2010(7):CD006704.
80. Moraska AR, Sood A, Dakhil SR, et al. Phase III, randomized, double-blind, placebo-controlled study of long-acting methylphenidate for cancer-related fatigue: North Central Cancer Treatment Group NCCTG-N05C7 trial. J Clin Oncol 2010;28:3673–9.
81. Bruera E, Driver L, Barnes EA, et al. Patient-controlled methylphenidate for the management of fatigue in patients with advanced cancer: a preliminary report. J Clin Oncol 2003;21:4439–43.
82. Kerr CW, Drake J, Milch RA, et al. Effects of methylphenidate on fatigue and depression: a randomized, double-blind, placebo-controlled trial. J Pain Symptom Manage 2012;43:68–77.
83. Escalante CP, Meyers C, Reuben JM, et al. A randomized, double-blind, 2-period, placebo-controlled crossover trial of a sustained-release methylphenidate in the treatment of fatigue in cancer patients. Cancer J 2014;20:8–14.
84. Mar Fan HG, Clemons M, Xu W, et al. A randomised, placebo-controlled, double-blind trial of the effects of d-methylphenidate on fatigue and cognitive dysfunction in women undergoing adjuvant chemotherapy for breast cancer. Support Care Cancer 2008;16:577–83.
85. Butler JM Jr, Case LD, Atkins J, et al. A phase III, double-blind, placebo-controlled prospective randomized clinical trial of d-threo-methylphenidate HCl in brain tumor patients receiving radiation therapy. Int J Radiat Oncol Biol Phys 2007;69:1496–501.
86. Hovey E, de Souza P, Marx G, et al. Phase III, randomized, double-blind, placebo-controlled study of modafinil for fatigue in patients treated with docetaxel-based chemotherapy. Support Care Cancer 2014;22:1233–42.
87. Spathis A, Fife K, Blackhall F, et al. Modafinil for the treatment of fatigue in lung cancer: results of a placebo-controlled, double-blind, randomized trial. J Clin Oncol 2014;32:1882–8.
88. Berenson JR, Yellin O, Shamasunder HK, et al. A phase 3 trial of armodafinil for the treatment of cancer-related fatigue for patients with multiple myeloma. Support Care Cancer 2015;23:1503–12.
89. Boele FW, Douw L, de Groot M, et al. The effect of modafinil on fatigue, cognitive functioning, and mood in primary brain tumor patients: a multicenter randomized controlled trial. Neuro Oncol 2013;15:1420–8.
90. Jean-Pierre P, Morrow GR, Roscoe JA, et al. A phase 3 randomized, placebo-controlled, double-blind, clinical trial of the effect of modafinil on cancer-related fatigue among 631 patients receiving chemotherapy: a University of Rochester Cancer Center Community Clinical Oncology Program Research base study. Cancer 2010;116:3513–20.
91. Conley CC, Kamen CS, Heckler CE, et al. Modafinil moderates the relationship between cancer-related fatigue and depression in 541 patients receiving chemotherapy. J Clin Psychopharmacol 2016;36:82–5.
92. Brattsand R, Linden M. Cytokine modulation by glucocorticoids: mechanisms and actions in cellular studies. Aliment Pharmacol Ther 1996;10 Suppl 2:81–90.
93. Yennurajalingam S, Frisbee-Hume S, Palmer JL, et al. Reduction of cancer-related fatigue with dexamethasone: a double-blind, randomized, placebo-controlled trial in patients with advanced cancer. J Clin Oncol 2013;31:3076–82.
94. Bruera E, Roca E, Cedaro L, et al. Action of oral methylprednisolone in terminal cancer patients: a prospective randomized double-blind study. Cancer Treat Rep 1985;69:751–4.
95. Pulivarthi K, Dev R, Garcia J, et al. Testosterone replacement for fatigue in male hypogonadic patients with advanced cancer: A preliminary double-blind placebo-controlled trial. J Clin Oncol 2012;30 (suppl). Abstract e19643.
96. Palesh OG, Mustian KM, Peppone LJ, et al. Impact of paroxetine on sleep problems in 426 cancer patients receiving chemotherapy: a trial from the University of Rochester Cancer Center Community Clinical Oncology Program. Sleep Med 2012;13:1184–90.
97. Thekdi SM, Trinidad A, Roth A. Psychopharmacology in Cancer. Curr Psychiatry Rep 2014;17:529.
98. Lesser GJ. Case D, Stark N, et al. A randomized, double-blind, placebo-controlled study of oral coenzyme Q10 to relieve self-reported treatment-related fatigue in newly diagnosed patients with breast cancer. J Support Oncol 2013;11:31–42.
99. Barton DL, Liu H, Dakhil SR, et al. Wisconsin Ginseng (Panax quinquefolius) to improve cancer-related fatigue: a randomized, double-blind trial, N07C2. J Natl Cancer Inst 2013;105:1230–8.
100. Yennurajalingam S, Reddy A, Tannir NM, et al. High-dose Asian ginseng (panax ginseng) for cancer-related fatigue: a preliminary report. Integr Cancer Ther 2015;14:419–27.
101. Howell D, Keller-Olaman S, Oliver TK, et al. A pan-Canadian practice guideline and algorithm: screening, assessment, and supportive care of adults with cancer-related fatigue. Curr Oncol 2013;20:e233–46.