MDedge Cardiology

For years, researchers and medical companies have explored low-field MRI systems (those with a magnetic field strength of less than 1 T) — searching for a feasible alternative to the loud, expensive machines requiring special rooms with shielding to block their powerful magnetic field.

Most low-field scanners in development are for brain scans only. In 2022, the US Food and Drug Administration (FDA) cleared the first portable MRI system — Hyperfine’s Swoop, designed for use at a patient’s bedside — for head and brain scans. But the technology has not been applied to whole-body MRI — until now.

In a new study published in Science, researchers from Hong Kong described a whole-body, ultra low–field MRI.

“This is a big breakthrough,” said Kevin Sheth, MD, director of the Yale Center for Brain & Mind Health, who was not involved in the study. “It is one of the first, if not the first, demonstrations of low-field MRI imaging for the entire body.”

The device uses a 0.05 T magnet — one sixtieth the magnetic field strength of the standard 3 T MRI model common in hospitals today, said lead author Ed Wu, PhD, professor of biomedical engineering at The University of Hong Kong.

Because the field strength is so low, no protective shielding is needed. Patients and bystanders can safely use smart phones . And the scanner is safe for patients with implanted devices, like a cochlear implant or pacemaker, or any metal on their body or clothes. No hearing protection is required, either, because the machine is so quiet.

If all goes well, the technology could be commercially available in as little as a few years, Dr. Wu said.

But first, funding and FDA approval would be needed. “A company is going to have to come along and say, ‘This looks fantastic. We’re going to commercialize this, and we’re going to go through this certification process,’ ” said Andrew Webb, PhD, professor of radiology and the founding director of the C.J. Gorter MRI Center at the Leiden University Medical Center, Leiden, the Netherlands. (Dr. Webb was not involved in the study.)
 

Improving Access to MRI

One hope for this technology is to bring MRI to more people worldwide. Africa has less than one MRI scanner per million residents, whereas the United States has about 40.

While a new 3 T machine can cost about $1 million, the low-field version is much cheaper — only about $22,000 in materials cost per scanner, according to Dr. Wu.

A low magnetic field means less electricity, too — the machine can be plugged into a standard wall outlet. And because a fully shielded room isn’t needed, that could save another $100,000 in materials, Dr. Webb said.

Its ease of use could improve accessibility in countries with limited training, Dr. Webb pointed out.

“To be a technician is 2-3 years training for a regular MRI machine, a lot of it to do safety, a lot of it to do very subtle planning,” said Webb. “These [low-field] systems are much simpler.”
 

Challenges and the Future

The prototype weighs about 1.5 tons or 3000 lb. (A 3 T MRI can weigh between 6 and 13 tons or 12,000 and 26,000 lb.) That might sound like a lot, but it’s comparable to a mobile CT scanner, which is designed to be moved from room to room. Plus, “its weight can be substantially reduced if further optimized,” Dr. Wu said.

One challenge with low-field MRIs is image quality, which tends to be not as clear and detailed as those from high-power machines. To address this, the research team used deep learning (artificial intelligence) to enhance the image quality. “Computing power and large-scale data underpin our success, which tackles the physics and math problems that are traditionally considered intractable in existing MRI methodology,” Dr. Wu said.

Dr. Webb said he was impressed by the image quality shown in the study. They “look much higher quality than you would expect from such a low-field system,” he said. Still, only healthy volunteers were scanned. The true test will be using it to view subtle pathologies, Dr. Webb said.

That’s what Dr. Wu and his team are working on now — taking scans to diagnose various medical conditions. His group’s brain-only version of the low-field MRI has been used for diagnosis, he noted.
 

A version of this article appeared on Medscape.com.

For years, researchers and medical companies have explored low-field MRI systems (those with a magnetic field strength of less than 1 T) — searching for a feasible alternative to the loud, expensive machines requiring special rooms with shielding to block their powerful magnetic field.

Most low-field scanners in development are for brain scans only. In 2022, the US Food and Drug Administration (FDA) cleared the first portable MRI system — Hyperfine’s Swoop, designed for use at a patient’s bedside — for head and brain scans. But the technology has not been applied to whole-body MRI — until now.

In a new study published in Science, researchers from Hong Kong described a whole-body, ultra low–field MRI.

“This is a big breakthrough,” said Kevin Sheth, MD, director of the Yale Center for Brain & Mind Health, who was not involved in the study. “It is one of the first, if not the first, demonstrations of low-field MRI imaging for the entire body.”

The device uses a 0.05 T magnet — one sixtieth the magnetic field strength of the standard 3 T MRI model common in hospitals today, said lead author Ed Wu, PhD, professor of biomedical engineering at The University of Hong Kong.

Because the field strength is so low, no protective shielding is needed. Patients and bystanders can safely use smart phones . And the scanner is safe for patients with implanted devices, like a cochlear implant or pacemaker, or any metal on their body or clothes. No hearing protection is required, either, because the machine is so quiet.

If all goes well, the technology could be commercially available in as little as a few years, Dr. Wu said.

But first, funding and FDA approval would be needed. “A company is going to have to come along and say, ‘This looks fantastic. We’re going to commercialize this, and we’re going to go through this certification process,’ ” said Andrew Webb, PhD, professor of radiology and the founding director of the C.J. Gorter MRI Center at the Leiden University Medical Center, Leiden, the Netherlands. (Dr. Webb was not involved in the study.)
 

Improving Access to MRI

One hope for this technology is to bring MRI to more people worldwide. Africa has less than one MRI scanner per million residents, whereas the United States has about 40.

While a new 3 T machine can cost about $1 million, the low-field version is much cheaper — only about $22,000 in materials cost per scanner, according to Dr. Wu.

A low magnetic field means less electricity, too — the machine can be plugged into a standard wall outlet. And because a fully shielded room isn’t needed, that could save another $100,000 in materials, Dr. Webb said.

Its ease of use could improve accessibility in countries with limited training, Dr. Webb pointed out.

“To be a technician is 2-3 years training for a regular MRI machine, a lot of it to do safety, a lot of it to do very subtle planning,” said Webb. “These [low-field] systems are much simpler.”
 

Challenges and the Future

The prototype weighs about 1.5 tons or 3000 lb. (A 3 T MRI can weigh between 6 and 13 tons or 12,000 and 26,000 lb.) That might sound like a lot, but it’s comparable to a mobile CT scanner, which is designed to be moved from room to room. Plus, “its weight can be substantially reduced if further optimized,” Dr. Wu said.

One challenge with low-field MRIs is image quality, which tends to be not as clear and detailed as those from high-power machines. To address this, the research team used deep learning (artificial intelligence) to enhance the image quality. “Computing power and large-scale data underpin our success, which tackles the physics and math problems that are traditionally considered intractable in existing MRI methodology,” Dr. Wu said.

Dr. Webb said he was impressed by the image quality shown in the study. They “look much higher quality than you would expect from such a low-field system,” he said. Still, only healthy volunteers were scanned. The true test will be using it to view subtle pathologies, Dr. Webb said.

That’s what Dr. Wu and his team are working on now — taking scans to diagnose various medical conditions. His group’s brain-only version of the low-field MRI has been used for diagnosis, he noted.
 

A version of this article appeared on Medscape.com.

For years, researchers and medical companies have explored low-field MRI systems (those with a magnetic field strength of less than 1 T) — searching for a feasible alternative to the loud, expensive machines requiring special rooms with shielding to block their powerful magnetic field.

Most low-field scanners in development are for brain scans only. In 2022, the US Food and Drug Administration (FDA) cleared the first portable MRI system — Hyperfine’s Swoop, designed for use at a patient’s bedside — for head and brain scans. But the technology has not been applied to whole-body MRI — until now.

In a new study published in Science, researchers from Hong Kong described a whole-body, ultra low–field MRI.

“This is a big breakthrough,” said Kevin Sheth, MD, director of the Yale Center for Brain & Mind Health, who was not involved in the study. “It is one of the first, if not the first, demonstrations of low-field MRI imaging for the entire body.”

The device uses a 0.05 T magnet — one sixtieth the magnetic field strength of the standard 3 T MRI model common in hospitals today, said lead author Ed Wu, PhD, professor of biomedical engineering at The University of Hong Kong.

Because the field strength is so low, no protective shielding is needed. Patients and bystanders can safely use smart phones . And the scanner is safe for patients with implanted devices, like a cochlear implant or pacemaker, or any metal on their body or clothes. No hearing protection is required, either, because the machine is so quiet.

If all goes well, the technology could be commercially available in as little as a few years, Dr. Wu said.

But first, funding and FDA approval would be needed. “A company is going to have to come along and say, ‘This looks fantastic. We’re going to commercialize this, and we’re going to go through this certification process,’ ” said Andrew Webb, PhD, professor of radiology and the founding director of the C.J. Gorter MRI Center at the Leiden University Medical Center, Leiden, the Netherlands. (Dr. Webb was not involved in the study.)
 

Improving Access to MRI

One hope for this technology is to bring MRI to more people worldwide. Africa has less than one MRI scanner per million residents, whereas the United States has about 40.

While a new 3 T machine can cost about $1 million, the low-field version is much cheaper — only about $22,000 in materials cost per scanner, according to Dr. Wu.

A low magnetic field means less electricity, too — the machine can be plugged into a standard wall outlet. And because a fully shielded room isn’t needed, that could save another $100,000 in materials, Dr. Webb said.

Its ease of use could improve accessibility in countries with limited training, Dr. Webb pointed out.

“To be a technician is 2-3 years training for a regular MRI machine, a lot of it to do safety, a lot of it to do very subtle planning,” said Webb. “These [low-field] systems are much simpler.”
 

Challenges and the Future

The prototype weighs about 1.5 tons or 3000 lb. (A 3 T MRI can weigh between 6 and 13 tons or 12,000 and 26,000 lb.) That might sound like a lot, but it’s comparable to a mobile CT scanner, which is designed to be moved from room to room. Plus, “its weight can be substantially reduced if further optimized,” Dr. Wu said.

One challenge with low-field MRIs is image quality, which tends to be not as clear and detailed as those from high-power machines. To address this, the research team used deep learning (artificial intelligence) to enhance the image quality. “Computing power and large-scale data underpin our success, which tackles the physics and math problems that are traditionally considered intractable in existing MRI methodology,” Dr. Wu said.

Dr. Webb said he was impressed by the image quality shown in the study. They “look much higher quality than you would expect from such a low-field system,” he said. Still, only healthy volunteers were scanned. The true test will be using it to view subtle pathologies, Dr. Webb said.

That’s what Dr. Wu and his team are working on now — taking scans to diagnose various medical conditions. His group’s brain-only version of the low-field MRI has been used for diagnosis, he noted.
 

A version of this article appeared on Medscape.com.

For decades, physicians and nurses who ventured across state lines to practice, particularly in locum tenens roles, have reaped the benefits of medical licensure compacts. Yet, the same courtesy has eluded physician assistants (PAs), until now. The introduction of the PA Licensure Compact (PA Compact) marks a long-awaited and significant step forward for the PA community.

In April, Virginia Governor Glenn Youngkin signed the bill enacting the PA Compact making Virginia the seventh state to join. The legislation opens a cross-state agreement with seven states and finally allows locum tenens PAs to practice across these state’s borders.

How the PA Compact Works

The interstate arrangement recognizes valid, unencumbered PA licenses issued by other states in the compact. PAs working within the seven states won’t need a separate license from any of those states to practice.

The states include Delaware, Nebraska, Utah, Washington, West Virginia, Wisconsin, and Virginia. While the compact has been approved, the American Academy of Physician Associates said it could take an additional 18-24 months for the states to execute it, giving PAs the access they need to work in the compact states.

How the PA Compact Helps

The PA Compact holds the promise of alleviating some of the travel barriers that PAs often encounter, especially when they work locum tenens or in telehealth and must traverse state lines to deliver essential healthcare. This agreement not only enhances healthcare access but also empowers facilities to recruit new PAs, thereby bridging gaps in their healthcare staffing and addressing public health emergencies more effectively.

PAs will also gain increased flexibility and additional opportunities to earn and benefit from the right to practice in more states without requiring a time-consuming and expensive licensure from each state.

One motivating factor behind developing an interstate compact for physician assistants is that the same types of compacts for physicians and nurses are highly successful. The Nurse Licensure Compact and the Interstate Medical Licensure Compact for physicians encompass 37 and 41 states, respectively. While the seven-state PA Compact is in its earliest stages, it will likely be equally beneficial for PAs.

A survey by Barton Associates found that 95% of PAs said they would be more likely to consider working in a different state if the PA Compact made it more accessible.

Other states have begun legislation to enact a PA Compact, including Colorado, New Hampshire, Maine, Michigan New York, Ohio, Oklahoma, Rhode Island, Tennessee, and Vermont. 

If your state still needs to enact a compact or file for compact legislation, let your elected officials know that the PAs in your state want to join a compact. 
 

A version of this article appeared on Medscape.com .

For decades, physicians and nurses who ventured across state lines to practice, particularly in locum tenens roles, have reaped the benefits of medical licensure compacts. Yet, the same courtesy has eluded physician assistants (PAs), until now. The introduction of the PA Licensure Compact (PA Compact) marks a long-awaited and significant step forward for the PA community.

In April, Virginia Governor Glenn Youngkin signed the bill enacting the PA Compact making Virginia the seventh state to join. The legislation opens a cross-state agreement with seven states and finally allows locum tenens PAs to practice across these state’s borders.

How the PA Compact Works

The interstate arrangement recognizes valid, unencumbered PA licenses issued by other states in the compact. PAs working within the seven states won’t need a separate license from any of those states to practice.

The states include Delaware, Nebraska, Utah, Washington, West Virginia, Wisconsin, and Virginia. While the compact has been approved, the American Academy of Physician Associates said it could take an additional 18-24 months for the states to execute it, giving PAs the access they need to work in the compact states.

How the PA Compact Helps

The PA Compact holds the promise of alleviating some of the travel barriers that PAs often encounter, especially when they work locum tenens or in telehealth and must traverse state lines to deliver essential healthcare. This agreement not only enhances healthcare access but also empowers facilities to recruit new PAs, thereby bridging gaps in their healthcare staffing and addressing public health emergencies more effectively.

PAs will also gain increased flexibility and additional opportunities to earn and benefit from the right to practice in more states without requiring a time-consuming and expensive licensure from each state.

One motivating factor behind developing an interstate compact for physician assistants is that the same types of compacts for physicians and nurses are highly successful. The Nurse Licensure Compact and the Interstate Medical Licensure Compact for physicians encompass 37 and 41 states, respectively. While the seven-state PA Compact is in its earliest stages, it will likely be equally beneficial for PAs.

A survey by Barton Associates found that 95% of PAs said they would be more likely to consider working in a different state if the PA Compact made it more accessible.

Other states have begun legislation to enact a PA Compact, including Colorado, New Hampshire, Maine, Michigan New York, Ohio, Oklahoma, Rhode Island, Tennessee, and Vermont. 

If your state still needs to enact a compact or file for compact legislation, let your elected officials know that the PAs in your state want to join a compact. 
 

A version of this article appeared on Medscape.com .

For decades, physicians and nurses who ventured across state lines to practice, particularly in locum tenens roles, have reaped the benefits of medical licensure compacts. Yet, the same courtesy has eluded physician assistants (PAs), until now. The introduction of the PA Licensure Compact (PA Compact) marks a long-awaited and significant step forward for the PA community.

In April, Virginia Governor Glenn Youngkin signed the bill enacting the PA Compact making Virginia the seventh state to join. The legislation opens a cross-state agreement with seven states and finally allows locum tenens PAs to practice across these state’s borders.

How the PA Compact Works

The interstate arrangement recognizes valid, unencumbered PA licenses issued by other states in the compact. PAs working within the seven states won’t need a separate license from any of those states to practice.

The states include Delaware, Nebraska, Utah, Washington, West Virginia, Wisconsin, and Virginia. While the compact has been approved, the American Academy of Physician Associates said it could take an additional 18-24 months for the states to execute it, giving PAs the access they need to work in the compact states.

How the PA Compact Helps

The PA Compact holds the promise of alleviating some of the travel barriers that PAs often encounter, especially when they work locum tenens or in telehealth and must traverse state lines to deliver essential healthcare. This agreement not only enhances healthcare access but also empowers facilities to recruit new PAs, thereby bridging gaps in their healthcare staffing and addressing public health emergencies more effectively.

PAs will also gain increased flexibility and additional opportunities to earn and benefit from the right to practice in more states without requiring a time-consuming and expensive licensure from each state.

One motivating factor behind developing an interstate compact for physician assistants is that the same types of compacts for physicians and nurses are highly successful. The Nurse Licensure Compact and the Interstate Medical Licensure Compact for physicians encompass 37 and 41 states, respectively. While the seven-state PA Compact is in its earliest stages, it will likely be equally beneficial for PAs.

A survey by Barton Associates found that 95% of PAs said they would be more likely to consider working in a different state if the PA Compact made it more accessible.

Other states have begun legislation to enact a PA Compact, including Colorado, New Hampshire, Maine, Michigan New York, Ohio, Oklahoma, Rhode Island, Tennessee, and Vermont. 

If your state still needs to enact a compact or file for compact legislation, let your elected officials know that the PAs in your state want to join a compact. 
 

A version of this article appeared on Medscape.com .

Over the past few decades, the US Food and Drug Administration (FDA) has increasingly relied on surrogate measures such as blood tests instead of clinical outcomes for medication approvals. But critics say the agency lacks consistent standards to ensure the surrogate aligns with clinical outcomes that matter to patients — things like improvements in symptoms and gains in function.

Sometimes those decisions backfire. Consider: In July 2021, the FDA approved aducanumab for the treatment of Alzheimer’s disease, bucking the advice of an advisory panel for the agency that questioned the effectiveness of the medication. Regulators relied on data from the drugmaker, Biogen, showing the monoclonal antibody could reduce levels of amyloid beta plaques in blood — a surrogate marker officials hoped would translate to clinical benefit.

The FDA’s decision triggered significant controversy, and Biogen in January announced it is pulling it from the market this year, citing disappointing sales.

Although the case of aducanumab might seem extreme, given the stakes — Alzheimer’s remains a disease without an effective treatment — it’s far from unusual.

“When we prescribe a drug, there is an underlying assumption that the FDA has done its due diligence to confirm the drug is safe and of benefit,” said Reshma Ramachandran, MD, MPP, MHS, a researcher at Yale School of Medicine, New Haven, Connecticut, and a coauthor of a recent review of surrogate outcomes. “In fact, we found either no evidence or low-quality evidence.” Such markers are associated with clinical outcomes. “We just don’t know if they work meaningfully to treat the patient’s condition. The results were pretty shocking for us,” she said.

The FDA in 2018 released an Adult Surrogate Endpoint Table listing markers that can be used as substitutes for clinical outcomes to more quickly test, review, and approve new therapies. The analysis found the majority of these endpoints lacked subsequent confirmations, defined as published meta-analyses of clinical studies to validate the association between the marker and a clinical outcome important to patients.

In a paper published in JAMA, Dr. Ramachandran and her colleagues looked at 37 surrogate endpoints for nearly 3 dozen nononcologic diseases in the table.

Approval with surrogate markers implies responsibility for postapproval or validation studies — not just lab measures or imaging findings but mortality, morbidity, or improved quality of life, said Joshua D. Wallach, PhD, MS, assistant professor in the department of epidemiology at the Emory Rollins School of Public Health in Atlanta and lead author of the JAMA review.

Dr. Wallach said surrogate markers are easier to measure and do not require large and long trials. But the FDA has not provided clear rules for what makes a surrogate marker valid in clinical trials.

“They’ve said that at a minimum, it requires meta-analytical evidence from studies that have looked at the correlation or the association between the surrogate and the clinical outcome,” Dr. Wallach said. “Our understanding was that if that’s a minimum expectation, we should be able to find those studies in the literature. And the reality is that we were unable to find evidence from those types of studies supporting the association between the surrogate and the clinical outcome.”

Physicians generally do not receive training about the FDA approval process and the difference between biomarkers, surrogate markers, and clinical endpoints, Dr. Ramachandran said. “Our study shows that things are much more uncertain than we thought when it comes to the prescribing of new drugs,” she said.
 

Surrogate Markers on the Rise

Dr. Wallach’s group looked for published meta-analyses compiling randomized controlled trials reporting surrogate endpoints for more than 3 dozen chronic nononcologic conditions, including type 2 diabetes, Alzheimer’s, kidney disease, HIV, gout, and lupus. They found no meta-analyses at all for 59% of the surrogate markers, while for those that were studied, few reported high-strength evidence of an association with clinical outcomes.

The findings echo previous research. In a 2020 study in JAMA Network Open, researchers tallied primary endpoints for all FDA approvals of new drugs and therapies during three 3-year periods: 1995-1997, 2005-2007, and 2015-2017. The proportion of products whose approvals were based on the use of clinical endpoints decreased from 43.8% in 1995-1997 to 28.4% in 2005-2007 to 23.3% in 2015-2017. The share based on surrogate endpoints rose from 43.3% to roughly 60% over the same interval.

A 2017 study in the Journal of Health Economics found the use of “imperfect” surrogate endpoints helped support the approval of an average of 16 new drugs per year between 2010 and 2014 compared with six per year from 1998 to 2008.

Similar concerns about weak associations between surrogate markers and drugs used to treat cancer have been documented before, including in a 2020 study published in eClinicalMedicine. The researchers found the surrogate endpoints in the FDA table either were not tested or were tested but proven to be weak surrogates.

“And yet the FDA considered these as good enough not only for accelerated approval but also for regular approval,” said Bishal Gyawali, MD, PhD, associate professor in the department of oncology at Queen’s University, Kingston, Ontario, Canada, who led the group.

The use of surrogate endpoints is also increasing in Europe, said Huseyin Naci, MHS, PhD, associate professor of health policy at the London School of Economics and Political Science in England. He cited a cohort study of 298 randomized clinical trials (RCTs) in JAMA Oncology suggesting “contemporary oncology RCTs now largely measure putative surrogate endpoints.” Dr. Wallach called the FDA’s surrogate table “a great first step toward transparency. But a key column is missing from that table, telling us what is the basis for which the FDA allows drug companies to use the recognized surrogate markers. What is the evidence they are considering?”

If the agency allows companies the flexibility to validate surrogate endpoints, postmarketing studies designed to confirm the clinical utility of those endpoints should follow.

“We obviously want physicians to be guided by evidence when they’re selecting treatments, and they need to be able to interpret the clinical benefits of the drug that they’re prescribing,” he said. “This is really about having the research consumer, patients, and physicians, as well as industry, understand why certain markers are considered and not considered.”

Dr. Wallach reported receiving grants from the FDA (through the Yale University — Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr. Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America.
 

A version of this article appeared on Medscape.com.

Over the past few decades, the US Food and Drug Administration (FDA) has increasingly relied on surrogate measures such as blood tests instead of clinical outcomes for medication approvals. But critics say the agency lacks consistent standards to ensure the surrogate aligns with clinical outcomes that matter to patients — things like improvements in symptoms and gains in function.

Sometimes those decisions backfire. Consider: In July 2021, the FDA approved aducanumab for the treatment of Alzheimer’s disease, bucking the advice of an advisory panel for the agency that questioned the effectiveness of the medication. Regulators relied on data from the drugmaker, Biogen, showing the monoclonal antibody could reduce levels of amyloid beta plaques in blood — a surrogate marker officials hoped would translate to clinical benefit.

The FDA’s decision triggered significant controversy, and Biogen in January announced it is pulling it from the market this year, citing disappointing sales.

Although the case of aducanumab might seem extreme, given the stakes — Alzheimer’s remains a disease without an effective treatment — it’s far from unusual.

“When we prescribe a drug, there is an underlying assumption that the FDA has done its due diligence to confirm the drug is safe and of benefit,” said Reshma Ramachandran, MD, MPP, MHS, a researcher at Yale School of Medicine, New Haven, Connecticut, and a coauthor of a recent review of surrogate outcomes. “In fact, we found either no evidence or low-quality evidence.” Such markers are associated with clinical outcomes. “We just don’t know if they work meaningfully to treat the patient’s condition. The results were pretty shocking for us,” she said.

The FDA in 2018 released an Adult Surrogate Endpoint Table listing markers that can be used as substitutes for clinical outcomes to more quickly test, review, and approve new therapies. The analysis found the majority of these endpoints lacked subsequent confirmations, defined as published meta-analyses of clinical studies to validate the association between the marker and a clinical outcome important to patients.

In a paper published in JAMA, Dr. Ramachandran and her colleagues looked at 37 surrogate endpoints for nearly 3 dozen nononcologic diseases in the table.

Approval with surrogate markers implies responsibility for postapproval or validation studies — not just lab measures or imaging findings but mortality, morbidity, or improved quality of life, said Joshua D. Wallach, PhD, MS, assistant professor in the department of epidemiology at the Emory Rollins School of Public Health in Atlanta and lead author of the JAMA review.

Dr. Wallach said surrogate markers are easier to measure and do not require large and long trials. But the FDA has not provided clear rules for what makes a surrogate marker valid in clinical trials.

“They’ve said that at a minimum, it requires meta-analytical evidence from studies that have looked at the correlation or the association between the surrogate and the clinical outcome,” Dr. Wallach said. “Our understanding was that if that’s a minimum expectation, we should be able to find those studies in the literature. And the reality is that we were unable to find evidence from those types of studies supporting the association between the surrogate and the clinical outcome.”

Physicians generally do not receive training about the FDA approval process and the difference between biomarkers, surrogate markers, and clinical endpoints, Dr. Ramachandran said. “Our study shows that things are much more uncertain than we thought when it comes to the prescribing of new drugs,” she said.
 

Surrogate Markers on the Rise

Dr. Wallach’s group looked for published meta-analyses compiling randomized controlled trials reporting surrogate endpoints for more than 3 dozen chronic nononcologic conditions, including type 2 diabetes, Alzheimer’s, kidney disease, HIV, gout, and lupus. They found no meta-analyses at all for 59% of the surrogate markers, while for those that were studied, few reported high-strength evidence of an association with clinical outcomes.

The findings echo previous research. In a 2020 study in JAMA Network Open, researchers tallied primary endpoints for all FDA approvals of new drugs and therapies during three 3-year periods: 1995-1997, 2005-2007, and 2015-2017. The proportion of products whose approvals were based on the use of clinical endpoints decreased from 43.8% in 1995-1997 to 28.4% in 2005-2007 to 23.3% in 2015-2017. The share based on surrogate endpoints rose from 43.3% to roughly 60% over the same interval.

A 2017 study in the Journal of Health Economics found the use of “imperfect” surrogate endpoints helped support the approval of an average of 16 new drugs per year between 2010 and 2014 compared with six per year from 1998 to 2008.

Similar concerns about weak associations between surrogate markers and drugs used to treat cancer have been documented before, including in a 2020 study published in eClinicalMedicine. The researchers found the surrogate endpoints in the FDA table either were not tested or were tested but proven to be weak surrogates.

“And yet the FDA considered these as good enough not only for accelerated approval but also for regular approval,” said Bishal Gyawali, MD, PhD, associate professor in the department of oncology at Queen’s University, Kingston, Ontario, Canada, who led the group.

The use of surrogate endpoints is also increasing in Europe, said Huseyin Naci, MHS, PhD, associate professor of health policy at the London School of Economics and Political Science in England. He cited a cohort study of 298 randomized clinical trials (RCTs) in JAMA Oncology suggesting “contemporary oncology RCTs now largely measure putative surrogate endpoints.” Dr. Wallach called the FDA’s surrogate table “a great first step toward transparency. But a key column is missing from that table, telling us what is the basis for which the FDA allows drug companies to use the recognized surrogate markers. What is the evidence they are considering?”

If the agency allows companies the flexibility to validate surrogate endpoints, postmarketing studies designed to confirm the clinical utility of those endpoints should follow.

“We obviously want physicians to be guided by evidence when they’re selecting treatments, and they need to be able to interpret the clinical benefits of the drug that they’re prescribing,” he said. “This is really about having the research consumer, patients, and physicians, as well as industry, understand why certain markers are considered and not considered.”

Dr. Wallach reported receiving grants from the FDA (through the Yale University — Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr. Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America.
 

A version of this article appeared on Medscape.com.

Over the past few decades, the US Food and Drug Administration (FDA) has increasingly relied on surrogate measures such as blood tests instead of clinical outcomes for medication approvals. But critics say the agency lacks consistent standards to ensure the surrogate aligns with clinical outcomes that matter to patients — things like improvements in symptoms and gains in function.

Sometimes those decisions backfire. Consider: In July 2021, the FDA approved aducanumab for the treatment of Alzheimer’s disease, bucking the advice of an advisory panel for the agency that questioned the effectiveness of the medication. Regulators relied on data from the drugmaker, Biogen, showing the monoclonal antibody could reduce levels of amyloid beta plaques in blood — a surrogate marker officials hoped would translate to clinical benefit.

The FDA’s decision triggered significant controversy, and Biogen in January announced it is pulling it from the market this year, citing disappointing sales.

Although the case of aducanumab might seem extreme, given the stakes — Alzheimer’s remains a disease without an effective treatment — it’s far from unusual.

“When we prescribe a drug, there is an underlying assumption that the FDA has done its due diligence to confirm the drug is safe and of benefit,” said Reshma Ramachandran, MD, MPP, MHS, a researcher at Yale School of Medicine, New Haven, Connecticut, and a coauthor of a recent review of surrogate outcomes. “In fact, we found either no evidence or low-quality evidence.” Such markers are associated with clinical outcomes. “We just don’t know if they work meaningfully to treat the patient’s condition. The results were pretty shocking for us,” she said.

The FDA in 2018 released an Adult Surrogate Endpoint Table listing markers that can be used as substitutes for clinical outcomes to more quickly test, review, and approve new therapies. The analysis found the majority of these endpoints lacked subsequent confirmations, defined as published meta-analyses of clinical studies to validate the association between the marker and a clinical outcome important to patients.

In a paper published in JAMA, Dr. Ramachandran and her colleagues looked at 37 surrogate endpoints for nearly 3 dozen nononcologic diseases in the table.

Approval with surrogate markers implies responsibility for postapproval or validation studies — not just lab measures or imaging findings but mortality, morbidity, or improved quality of life, said Joshua D. Wallach, PhD, MS, assistant professor in the department of epidemiology at the Emory Rollins School of Public Health in Atlanta and lead author of the JAMA review.

Dr. Wallach said surrogate markers are easier to measure and do not require large and long trials. But the FDA has not provided clear rules for what makes a surrogate marker valid in clinical trials.

“They’ve said that at a minimum, it requires meta-analytical evidence from studies that have looked at the correlation or the association between the surrogate and the clinical outcome,” Dr. Wallach said. “Our understanding was that if that’s a minimum expectation, we should be able to find those studies in the literature. And the reality is that we were unable to find evidence from those types of studies supporting the association between the surrogate and the clinical outcome.”

Physicians generally do not receive training about the FDA approval process and the difference between biomarkers, surrogate markers, and clinical endpoints, Dr. Ramachandran said. “Our study shows that things are much more uncertain than we thought when it comes to the prescribing of new drugs,” she said.
 

Surrogate Markers on the Rise

Dr. Wallach’s group looked for published meta-analyses compiling randomized controlled trials reporting surrogate endpoints for more than 3 dozen chronic nononcologic conditions, including type 2 diabetes, Alzheimer’s, kidney disease, HIV, gout, and lupus. They found no meta-analyses at all for 59% of the surrogate markers, while for those that were studied, few reported high-strength evidence of an association with clinical outcomes.

The findings echo previous research. In a 2020 study in JAMA Network Open, researchers tallied primary endpoints for all FDA approvals of new drugs and therapies during three 3-year periods: 1995-1997, 2005-2007, and 2015-2017. The proportion of products whose approvals were based on the use of clinical endpoints decreased from 43.8% in 1995-1997 to 28.4% in 2005-2007 to 23.3% in 2015-2017. The share based on surrogate endpoints rose from 43.3% to roughly 60% over the same interval.

A 2017 study in the Journal of Health Economics found the use of “imperfect” surrogate endpoints helped support the approval of an average of 16 new drugs per year between 2010 and 2014 compared with six per year from 1998 to 2008.

Similar concerns about weak associations between surrogate markers and drugs used to treat cancer have been documented before, including in a 2020 study published in eClinicalMedicine. The researchers found the surrogate endpoints in the FDA table either were not tested or were tested but proven to be weak surrogates.

“And yet the FDA considered these as good enough not only for accelerated approval but also for regular approval,” said Bishal Gyawali, MD, PhD, associate professor in the department of oncology at Queen’s University, Kingston, Ontario, Canada, who led the group.

The use of surrogate endpoints is also increasing in Europe, said Huseyin Naci, MHS, PhD, associate professor of health policy at the London School of Economics and Political Science in England. He cited a cohort study of 298 randomized clinical trials (RCTs) in JAMA Oncology suggesting “contemporary oncology RCTs now largely measure putative surrogate endpoints.” Dr. Wallach called the FDA’s surrogate table “a great first step toward transparency. But a key column is missing from that table, telling us what is the basis for which the FDA allows drug companies to use the recognized surrogate markers. What is the evidence they are considering?”

If the agency allows companies the flexibility to validate surrogate endpoints, postmarketing studies designed to confirm the clinical utility of those endpoints should follow.

“We obviously want physicians to be guided by evidence when they’re selecting treatments, and they need to be able to interpret the clinical benefits of the drug that they’re prescribing,” he said. “This is really about having the research consumer, patients, and physicians, as well as industry, understand why certain markers are considered and not considered.”

Dr. Wallach reported receiving grants from the FDA (through the Yale University — Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr. Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America.
 

A version of this article appeared on Medscape.com.

The annual production of plastic worldwide has increased exponentially from about 2 million tons in 1950 to 460 million tons in 2019, and current levels are expected to triple by 2060.

Plastic contains more than 10,000 chemicals, including carcinogenic substances and endocrine disruptors. Plastic and associated chemicals are responsible for widespread pollution, contaminating aquatic (marine and freshwater), terrestrial, and atmospheric environments globally.

Atmospheric concentrations of plastic particles are on the rise, to the extent that in a remote station in the Eastern Alps in Austria, the contribution of micro- and nanoplastics (MNPs) to organic matter was comparable to data collected at an urban site.

The ocean is the ultimate destination for much of the plastic. All oceans, on the surface and in the depths, contain plastic, which is even found in polar sea ice. Many plastics seem to resist decomposition in the ocean and could persist in the environment for decades. Macro- and microplastic (MP) particles have been identified in hundreds of marine species, including species consumed by humans.

The quantity and fate of MP particles (> 10 µm) and smaller nanoplastics (< 10 µm) in aquatic environments are poorly understood, but what is most concerning is their ability to cross biologic barriers and the potential harm associated with their mobility in biologic systems.
 

MNP Exposure

MNPs can originate from a wide variety of sources, including food, beverages, and food product packaging. Water bottles represent a significant source of ingestible MNPs for people in their daily lives. Recent estimates, using stimulated Raman scattering imaging, documented a concentration of MNP of approximately 2.4 ± 1.3 × 10⁵ particles per liter of bottled water. Around 90% are nanoplastics, which is two to three orders of magnitude higher than previously reported results for larger MPs.

MNPs enter the body primarily through ingestion or inhalation. For example, MNPs can be ingested by drinking liquids or eating food that has been stored or heated in plastic containers from which they have leaked or by using toothpaste that contains them. Infants are exposed to MPs from artificial milk preparation in polypropylene baby bottles, with higher levels than previously detected and ranging from 14,600 to 4,550,000 particles per capita per day.
 

MNP and Biologic Systems

The possible formation of hetero-aggregates between nanoplastics and natural organic matter has long been recognized as a potential challenge in the analysis of nanoplastics and can influence toxicologic results in biologic exposure. The direct visualization of such hetero-aggregates in real-world samples supports these concerns, but the analysis of MNPs with traditional techniques remains challenging. Unlike engineered nanoparticles (prepared in the laboratory as model systems), the nanoplastics in the environment are label-free and exhibit significant heterogeneity in chemical composition and morphology.

A systematic analysis of evidence on the toxic effects of MNPs on murine models, however, showed that 52.78% of biologic endpoints (related to glucose metabolism, reproduction, oxidative stress, and lipid metabolism) were significantly affected by MNP exposure.
 

Between Risk and Toxicity

MNP can enter the body in vivo through the digestive tract, respiratory tract, and skin contact. On average, humans could ingest from 0.1 to 5 g of MNP per week through various exposure routes.

MNPs are a potential risk factor for cardiovascular diseases, as suggested by a recent study on 257 patients with carotid atheromatous plaques. In 58.4% of cases, polyvinyl chloride was detected in the carotid artery plaque, with an average level of 5.2 ± 2.4 μg/mg of plaque. Patients with MNPs inside the atheroma had a higher risk (relative risk, 4.53) for a composite cardiovascular event of myocardial infarction, stroke, or death from any cause at 34 months of follow-up than participants where MNPs were not detectable inside the atheromatous plaque.

The potential link between inflammatory bowel disease (IBD) and MPs has been hypothesized by a study that reported a higher fecal MP concentration in patients with IBD than in healthy individuals. Fecal MP level was correlated with disease severity.

However, these studies have not demonstrated a causal relationship between MNPs and disease, and the way MNPs may influence cellular functions and induce stress responses is not yet well understood.
 

Future Scenarios

Current evidence confirms the fragmentation of plastic beyond the micrometer level and has unequivocally detected nanoplastics in real samples. As with many other particle distributions of the same size in the natural world, there are substantially more nanoplastics, despite their invisibility with conventional imaging techniques, than particles larger than the micron size.

The initial results of studies on MNPs in humans will stimulate future research on the amounts of MNPs that accumulate in tissue over a person’s lifetime. Researchers also will examine how the particles’ characteristics, including their chemical composition, size, and shape, can influence organs and tissues.

The way MNPs can cause harm, including through effects on the immune system and microbiome, will need to be clarified by investigating possible direct cytotoxic effects, consistent with the introductory statement of the Organization for Economic Cooperation and Development global policy forum on plastics, which states, “Plastic pollution is one of the great environmental challenges of the 21st century, causing wide-ranging damage to ecosystems and human health.”

This story was translated from Univadis Italy, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

The annual production of plastic worldwide has increased exponentially from about 2 million tons in 1950 to 460 million tons in 2019, and current levels are expected to triple by 2060.

Plastic contains more than 10,000 chemicals, including carcinogenic substances and endocrine disruptors. Plastic and associated chemicals are responsible for widespread pollution, contaminating aquatic (marine and freshwater), terrestrial, and atmospheric environments globally.

Atmospheric concentrations of plastic particles are on the rise, to the extent that in a remote station in the Eastern Alps in Austria, the contribution of micro- and nanoplastics (MNPs) to organic matter was comparable to data collected at an urban site.

The ocean is the ultimate destination for much of the plastic. All oceans, on the surface and in the depths, contain plastic, which is even found in polar sea ice. Many plastics seem to resist decomposition in the ocean and could persist in the environment for decades. Macro- and microplastic (MP) particles have been identified in hundreds of marine species, including species consumed by humans.

The quantity and fate of MP particles (> 10 µm) and smaller nanoplastics (< 10 µm) in aquatic environments are poorly understood, but what is most concerning is their ability to cross biologic barriers and the potential harm associated with their mobility in biologic systems.
 

MNP Exposure

MNPs can originate from a wide variety of sources, including food, beverages, and food product packaging. Water bottles represent a significant source of ingestible MNPs for people in their daily lives. Recent estimates, using stimulated Raman scattering imaging, documented a concentration of MNP of approximately 2.4 ± 1.3 × 10⁵ particles per liter of bottled water. Around 90% are nanoplastics, which is two to three orders of magnitude higher than previously reported results for larger MPs.

MNPs enter the body primarily through ingestion or inhalation. For example, MNPs can be ingested by drinking liquids or eating food that has been stored or heated in plastic containers from which they have leaked or by using toothpaste that contains them. Infants are exposed to MPs from artificial milk preparation in polypropylene baby bottles, with higher levels than previously detected and ranging from 14,600 to 4,550,000 particles per capita per day.
 

MNP and Biologic Systems

The possible formation of hetero-aggregates between nanoplastics and natural organic matter has long been recognized as a potential challenge in the analysis of nanoplastics and can influence toxicologic results in biologic exposure. The direct visualization of such hetero-aggregates in real-world samples supports these concerns, but the analysis of MNPs with traditional techniques remains challenging. Unlike engineered nanoparticles (prepared in the laboratory as model systems), the nanoplastics in the environment are label-free and exhibit significant heterogeneity in chemical composition and morphology.

A systematic analysis of evidence on the toxic effects of MNPs on murine models, however, showed that 52.78% of biologic endpoints (related to glucose metabolism, reproduction, oxidative stress, and lipid metabolism) were significantly affected by MNP exposure.
 

Between Risk and Toxicity

MNP can enter the body in vivo through the digestive tract, respiratory tract, and skin contact. On average, humans could ingest from 0.1 to 5 g of MNP per week through various exposure routes.

MNPs are a potential risk factor for cardiovascular diseases, as suggested by a recent study on 257 patients with carotid atheromatous plaques. In 58.4% of cases, polyvinyl chloride was detected in the carotid artery plaque, with an average level of 5.2 ± 2.4 μg/mg of plaque. Patients with MNPs inside the atheroma had a higher risk (relative risk, 4.53) for a composite cardiovascular event of myocardial infarction, stroke, or death from any cause at 34 months of follow-up than participants where MNPs were not detectable inside the atheromatous plaque.

The potential link between inflammatory bowel disease (IBD) and MPs has been hypothesized by a study that reported a higher fecal MP concentration in patients with IBD than in healthy individuals. Fecal MP level was correlated with disease severity.

However, these studies have not demonstrated a causal relationship between MNPs and disease, and the way MNPs may influence cellular functions and induce stress responses is not yet well understood.
 

Future Scenarios

Current evidence confirms the fragmentation of plastic beyond the micrometer level and has unequivocally detected nanoplastics in real samples. As with many other particle distributions of the same size in the natural world, there are substantially more nanoplastics, despite their invisibility with conventional imaging techniques, than particles larger than the micron size.

The initial results of studies on MNPs in humans will stimulate future research on the amounts of MNPs that accumulate in tissue over a person’s lifetime. Researchers also will examine how the particles’ characteristics, including their chemical composition, size, and shape, can influence organs and tissues.

The way MNPs can cause harm, including through effects on the immune system and microbiome, will need to be clarified by investigating possible direct cytotoxic effects, consistent with the introductory statement of the Organization for Economic Cooperation and Development global policy forum on plastics, which states, “Plastic pollution is one of the great environmental challenges of the 21st century, causing wide-ranging damage to ecosystems and human health.”

This story was translated from Univadis Italy, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

The annual production of plastic worldwide has increased exponentially from about 2 million tons in 1950 to 460 million tons in 2019, and current levels are expected to triple by 2060.

Plastic contains more than 10,000 chemicals, including carcinogenic substances and endocrine disruptors. Plastic and associated chemicals are responsible for widespread pollution, contaminating aquatic (marine and freshwater), terrestrial, and atmospheric environments globally.

Atmospheric concentrations of plastic particles are on the rise, to the extent that in a remote station in the Eastern Alps in Austria, the contribution of micro- and nanoplastics (MNPs) to organic matter was comparable to data collected at an urban site.

The ocean is the ultimate destination for much of the plastic. All oceans, on the surface and in the depths, contain plastic, which is even found in polar sea ice. Many plastics seem to resist decomposition in the ocean and could persist in the environment for decades. Macro- and microplastic (MP) particles have been identified in hundreds of marine species, including species consumed by humans.

The quantity and fate of MP particles (> 10 µm) and smaller nanoplastics (< 10 µm) in aquatic environments are poorly understood, but what is most concerning is their ability to cross biologic barriers and the potential harm associated with their mobility in biologic systems.
 

MNP Exposure

MNPs can originate from a wide variety of sources, including food, beverages, and food product packaging. Water bottles represent a significant source of ingestible MNPs for people in their daily lives. Recent estimates, using stimulated Raman scattering imaging, documented a concentration of MNP of approximately 2.4 ± 1.3 × 10⁵ particles per liter of bottled water. Around 90% are nanoplastics, which is two to three orders of magnitude higher than previously reported results for larger MPs.

MNPs enter the body primarily through ingestion or inhalation. For example, MNPs can be ingested by drinking liquids or eating food that has been stored or heated in plastic containers from which they have leaked or by using toothpaste that contains them. Infants are exposed to MPs from artificial milk preparation in polypropylene baby bottles, with higher levels than previously detected and ranging from 14,600 to 4,550,000 particles per capita per day.
 

MNP and Biologic Systems

The possible formation of hetero-aggregates between nanoplastics and natural organic matter has long been recognized as a potential challenge in the analysis of nanoplastics and can influence toxicologic results in biologic exposure. The direct visualization of such hetero-aggregates in real-world samples supports these concerns, but the analysis of MNPs with traditional techniques remains challenging. Unlike engineered nanoparticles (prepared in the laboratory as model systems), the nanoplastics in the environment are label-free and exhibit significant heterogeneity in chemical composition and morphology.

A systematic analysis of evidence on the toxic effects of MNPs on murine models, however, showed that 52.78% of biologic endpoints (related to glucose metabolism, reproduction, oxidative stress, and lipid metabolism) were significantly affected by MNP exposure.
 

Between Risk and Toxicity

MNP can enter the body in vivo through the digestive tract, respiratory tract, and skin contact. On average, humans could ingest from 0.1 to 5 g of MNP per week through various exposure routes.

MNPs are a potential risk factor for cardiovascular diseases, as suggested by a recent study on 257 patients with carotid atheromatous plaques. In 58.4% of cases, polyvinyl chloride was detected in the carotid artery plaque, with an average level of 5.2 ± 2.4 μg/mg of plaque. Patients with MNPs inside the atheroma had a higher risk (relative risk, 4.53) for a composite cardiovascular event of myocardial infarction, stroke, or death from any cause at 34 months of follow-up than participants where MNPs were not detectable inside the atheromatous plaque.

The potential link between inflammatory bowel disease (IBD) and MPs has been hypothesized by a study that reported a higher fecal MP concentration in patients with IBD than in healthy individuals. Fecal MP level was correlated with disease severity.

However, these studies have not demonstrated a causal relationship between MNPs and disease, and the way MNPs may influence cellular functions and induce stress responses is not yet well understood.
 

Future Scenarios

Current evidence confirms the fragmentation of plastic beyond the micrometer level and has unequivocally detected nanoplastics in real samples. As with many other particle distributions of the same size in the natural world, there are substantially more nanoplastics, despite their invisibility with conventional imaging techniques, than particles larger than the micron size.

The initial results of studies on MNPs in humans will stimulate future research on the amounts of MNPs that accumulate in tissue over a person’s lifetime. Researchers also will examine how the particles’ characteristics, including their chemical composition, size, and shape, can influence organs and tissues.

The way MNPs can cause harm, including through effects on the immune system and microbiome, will need to be clarified by investigating possible direct cytotoxic effects, consistent with the introductory statement of the Organization for Economic Cooperation and Development global policy forum on plastics, which states, “Plastic pollution is one of the great environmental challenges of the 21st century, causing wide-ranging damage to ecosystems and human health.”

This story was translated from Univadis Italy, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

Serious mental illness (SMI), including bipolar disorder or schizophrenia spectrum disorders, is associated with a twofold increased risk for comorbid physical illness, results of a new meta-analysis showed.

“Although treatment of physical and mental health remains siloed in many health services globally, the high prevalence of physical multimorbidity attests to the urgent need for integrated care models that address both physical and mental health outcomes in people with severe mental illness,” the authors, led by Sean Halstead, MD, of The University of Queensland Medical School in Brisbane, Australia, wrote.

The findings were published online in The Lancet Psychiatry.
 

Shorter Lifespan?

SMI is associated with reduced life expectancy, and experts speculate that additional chronic illnesses — whether physical or psychiatric — may underlie this association.

While previous research has paired SMI with comorbid physical illnesses, the researchers noted that this study is the first to focus on both physical and psychiatric multimorbidity in individuals with SMI.

The investigators conducted a meta-analysis of 82 observational studies comprising 1.6 million individuals with SMI and 13.2 million control subjects to determine the risk for physical or psychiatric multimorbidity.

Studies were included if participants were diagnosed with either a schizophrenia spectrum disorder or bipolar disorder, and the study assessed either physical multimorbidity (at least two physical health conditions) or psychiatric multimorbidity (at least three psychiatric conditions), including the initial SMI.

Investigators found that individuals with SMI had more than a twofold increased risk for physical multimorbidity than those without SMI (odds ratio [OR], 2.40; 95% CI, 1.57-3.65; P = .0009).

Physical multimorbidity, which included cardiovascular, endocrine, neurological rental, gastrointestinal, musculoskeletal, and infectious disorders, was prevalent at similar rates in both schizophrenia spectrum disorder and bipolar disorder.

The ratio of physical multimorbidity was about four times higher in younger populations with SMI (mean age ≤ 40; OR, 3.99; 95% CI, 1.43-11.10) than in older populations (mean age > 40; OR, 1.55; 95% CI, 0.96-2.51; subgroup differences, P = .0013).

In terms of absolute prevalence, 25% of those with SMI had a physical multimorbidity, and 14% had a psychiatric multimorbidity, which were primarily anxiety and substance use disorders.

Investigators speculated that physical multimorbidity in SMI could stem from side effects of psychotropic medications, which are known to cause rapid cardiometabolic changes, including weight gain. In addition, lifestyle factors or nonmodifiable risk factors could also contribute to physical multimorbidity.

The study’s limitations included its small sample sizes for subgroup analyses and insufficient analysis for significant covariates, including smoking rates and symptom severity.

“While health services and treatment guidelines often operate on the assumption that individuals have a single principal diagnosis, these results attest to the clinical complexity many people with severe mental illness face in relation to burden of chronic disease,” the investigators wrote. They added that a greater understanding of the epidemiological manifestations of multimorbidity in SMI is “imperative.”

There was no source of funding for this study. Dr. Halstead is supported by the Australian Research Training Program scholarship. Other disclosures were noted in the original article.

A version of this article appeared on Medscape.com .

Serious mental illness (SMI), including bipolar disorder or schizophrenia spectrum disorders, is associated with a twofold increased risk for comorbid physical illness, results of a new meta-analysis showed.

“Although treatment of physical and mental health remains siloed in many health services globally, the high prevalence of physical multimorbidity attests to the urgent need for integrated care models that address both physical and mental health outcomes in people with severe mental illness,” the authors, led by Sean Halstead, MD, of The University of Queensland Medical School in Brisbane, Australia, wrote.

The findings were published online in The Lancet Psychiatry.
 

Shorter Lifespan?

SMI is associated with reduced life expectancy, and experts speculate that additional chronic illnesses — whether physical or psychiatric — may underlie this association.

While previous research has paired SMI with comorbid physical illnesses, the researchers noted that this study is the first to focus on both physical and psychiatric multimorbidity in individuals with SMI.

The investigators conducted a meta-analysis of 82 observational studies comprising 1.6 million individuals with SMI and 13.2 million control subjects to determine the risk for physical or psychiatric multimorbidity.

Studies were included if participants were diagnosed with either a schizophrenia spectrum disorder or bipolar disorder, and the study assessed either physical multimorbidity (at least two physical health conditions) or psychiatric multimorbidity (at least three psychiatric conditions), including the initial SMI.

Investigators found that individuals with SMI had more than a twofold increased risk for physical multimorbidity than those without SMI (odds ratio [OR], 2.40; 95% CI, 1.57-3.65; P = .0009).

Physical multimorbidity, which included cardiovascular, endocrine, neurological rental, gastrointestinal, musculoskeletal, and infectious disorders, was prevalent at similar rates in both schizophrenia spectrum disorder and bipolar disorder.

The ratio of physical multimorbidity was about four times higher in younger populations with SMI (mean age ≤ 40; OR, 3.99; 95% CI, 1.43-11.10) than in older populations (mean age > 40; OR, 1.55; 95% CI, 0.96-2.51; subgroup differences, P = .0013).

In terms of absolute prevalence, 25% of those with SMI had a physical multimorbidity, and 14% had a psychiatric multimorbidity, which were primarily anxiety and substance use disorders.

Investigators speculated that physical multimorbidity in SMI could stem from side effects of psychotropic medications, which are known to cause rapid cardiometabolic changes, including weight gain. In addition, lifestyle factors or nonmodifiable risk factors could also contribute to physical multimorbidity.

The study’s limitations included its small sample sizes for subgroup analyses and insufficient analysis for significant covariates, including smoking rates and symptom severity.

“While health services and treatment guidelines often operate on the assumption that individuals have a single principal diagnosis, these results attest to the clinical complexity many people with severe mental illness face in relation to burden of chronic disease,” the investigators wrote. They added that a greater understanding of the epidemiological manifestations of multimorbidity in SMI is “imperative.”

There was no source of funding for this study. Dr. Halstead is supported by the Australian Research Training Program scholarship. Other disclosures were noted in the original article.

A version of this article appeared on Medscape.com .

Serious mental illness (SMI), including bipolar disorder or schizophrenia spectrum disorders, is associated with a twofold increased risk for comorbid physical illness, results of a new meta-analysis showed.

“Although treatment of physical and mental health remains siloed in many health services globally, the high prevalence of physical multimorbidity attests to the urgent need for integrated care models that address both physical and mental health outcomes in people with severe mental illness,” the authors, led by Sean Halstead, MD, of The University of Queensland Medical School in Brisbane, Australia, wrote.

The findings were published online in The Lancet Psychiatry.
 

Shorter Lifespan?

SMI is associated with reduced life expectancy, and experts speculate that additional chronic illnesses — whether physical or psychiatric — may underlie this association.

While previous research has paired SMI with comorbid physical illnesses, the researchers noted that this study is the first to focus on both physical and psychiatric multimorbidity in individuals with SMI.

The investigators conducted a meta-analysis of 82 observational studies comprising 1.6 million individuals with SMI and 13.2 million control subjects to determine the risk for physical or psychiatric multimorbidity.

Studies were included if participants were diagnosed with either a schizophrenia spectrum disorder or bipolar disorder, and the study assessed either physical multimorbidity (at least two physical health conditions) or psychiatric multimorbidity (at least three psychiatric conditions), including the initial SMI.

Investigators found that individuals with SMI had more than a twofold increased risk for physical multimorbidity than those without SMI (odds ratio [OR], 2.40; 95% CI, 1.57-3.65; P = .0009).

Physical multimorbidity, which included cardiovascular, endocrine, neurological rental, gastrointestinal, musculoskeletal, and infectious disorders, was prevalent at similar rates in both schizophrenia spectrum disorder and bipolar disorder.

The ratio of physical multimorbidity was about four times higher in younger populations with SMI (mean age ≤ 40; OR, 3.99; 95% CI, 1.43-11.10) than in older populations (mean age > 40; OR, 1.55; 95% CI, 0.96-2.51; subgroup differences, P = .0013).

In terms of absolute prevalence, 25% of those with SMI had a physical multimorbidity, and 14% had a psychiatric multimorbidity, which were primarily anxiety and substance use disorders.

Investigators speculated that physical multimorbidity in SMI could stem from side effects of psychotropic medications, which are known to cause rapid cardiometabolic changes, including weight gain. In addition, lifestyle factors or nonmodifiable risk factors could also contribute to physical multimorbidity.

The study’s limitations included its small sample sizes for subgroup analyses and insufficient analysis for significant covariates, including smoking rates and symptom severity.

“While health services and treatment guidelines often operate on the assumption that individuals have a single principal diagnosis, these results attest to the clinical complexity many people with severe mental illness face in relation to burden of chronic disease,” the investigators wrote. They added that a greater understanding of the epidemiological manifestations of multimorbidity in SMI is “imperative.”

There was no source of funding for this study. Dr. Halstead is supported by the Australian Research Training Program scholarship. Other disclosures were noted in the original article.

A version of this article appeared on Medscape.com .

A few months ago, I posted a column on continuous positive airway pressure (CPAP) with the title, “CPAP Oversells and Underperforms.” To date, it has 299 likes and 90 comments, which are almost all negative. I’m glad to see that it’s generated interest, and I’d like to address some of the themes expressed in the posts.

Most comments were personal testimonies to the miracles of CPAP. These are important, and the point deserves emphasis. CPAP can provide significant improvements in daytime sleepiness and quality of life. I closed the original piece by acknowledging this important fact. Readers can be forgiven for missing it given that the title and text were otherwise disparaging of CPAP.

But several comments warrant a more in-depth discussion. The original piece focuses on CPAP and cardiovascular (CV) outcomes but made no mention of atrial fibrillation (AF) or ejection fraction (EF). The effects of CPAP on each are touted by cardiologists and PAP-pushers alike and are drivers of frequent referrals. It›s my fault for omitting them from the discussion.

AF is easy. The data is identical to all other things CPAP and CV. Based on biologic plausibility alone, the likelihood of a relationship between AF and obstructive sleep apnea (OSA) is similar to the odds that the Celtics raise an 18th banner come June. There’s hypoxia, intrathoracic pressure swings, sympathetic surges, and sleep state disruptions. It’s easy to get from there to arrhythmogenesis. There’s lots of observational noise, too, but no randomized proof that CPAP alters this relationship.

I found four randomized controlled trials (RCTs) that tested CPAP’s effect on AF. I’ll save you the suspense; they were all negative. One even found a signal for more adverse events in the CPAP group. These studies have several positive qualities: They enrolled patients with moderate to severe sleep apnea and high oxygen desaturation indices, adherence averaged more than 4 hours across all groups in all trials, and the methods for assessing the AF outcomes differed slightly. There’s also a lot not to like: The sample sizes were small, only one trial enrolled “sleepy” patients (as assessed by the Epworth Sleepiness Score), and follow-up was short.

To paraphrase Carl Sagan, “absence of evidence does not equal evidence of absence.” As a statistician would say, type II error cannot be excluded by these RCTs. In medicine, however, the burden of proof falls on demonstrating efficacy. If we treat before concluding that a therapy works, we risk wasting time, money, medical resources, and the most precious of patient commodities: the energy required for behavior change. In their response to letters to the editor, the authors of the third RCT summarize the CPAP, AF, and CV disease data far better than I ever could. They sound the same words of caution and come out against screening patients with AF for OSA. 

The story for CPAP’s effects on EF is similar though muddier. The American College of Cardiology (ACC)/American Heart Association (AHA) guidelines for heart failure cite a meta-analysis showing that CPAP improves left ventricular EF. In 2019, the American Academy of Sleep Medicine (AASM) CPAP guidelines included a systematic review and meta-analysis that found that CPAP has no effect on left ventricular EF in patients with or without heart failure.

There are a million reasons why two systematic reviews on the same topic might come to different conclusions. In this case, the included studies only partially overlap, and broadly speaking, it appears the authors made trade-offs. The review cited by the ACC/AHA had broader inclusion and significantly more patients and paid for it in heterogeneity (I2 in the 80%-90% range). The AASM analysis achieved 0% heterogeneity but limited inclusion to fewer than 100 patients. Across both, the improvement in EF was 2%- 5% at a minimally clinically important difference of 4%. Hardly convincing.

In summary, the road to negative trials and patient harm has always been paved with observational signal and biologic plausibility. Throw in some intellectual and academic bias, and you’ve created the perfect storm of therapeutic overconfidence. The cemetery for discarded medical therapies is crowded, but there’s room for CPAP, at least when it comes to using it to improve CV outcomes. 
 

Dr. Holley is a professor in the department of medicine, Uniformed Services University, Bethesda, Maryland, and a physician at Pulmonary/Sleep and Critical Care Medicine, MedStar Washington Hospital Center, Washington. He disclosed ties to Metapharm Inc., CHEST College, and WebMD.

A version of this article appeared on Medscape.com .

A few months ago, I posted a column on continuous positive airway pressure (CPAP) with the title, “CPAP Oversells and Underperforms.” To date, it has 299 likes and 90 comments, which are almost all negative. I’m glad to see that it’s generated interest, and I’d like to address some of the themes expressed in the posts.

Most comments were personal testimonies to the miracles of CPAP. These are important, and the point deserves emphasis. CPAP can provide significant improvements in daytime sleepiness and quality of life. I closed the original piece by acknowledging this important fact. Readers can be forgiven for missing it given that the title and text were otherwise disparaging of CPAP.

But several comments warrant a more in-depth discussion. The original piece focuses on CPAP and cardiovascular (CV) outcomes but made no mention of atrial fibrillation (AF) or ejection fraction (EF). The effects of CPAP on each are touted by cardiologists and PAP-pushers alike and are drivers of frequent referrals. It›s my fault for omitting them from the discussion.

AF is easy. The data is identical to all other things CPAP and CV. Based on biologic plausibility alone, the likelihood of a relationship between AF and obstructive sleep apnea (OSA) is similar to the odds that the Celtics raise an 18th banner come June. There’s hypoxia, intrathoracic pressure swings, sympathetic surges, and sleep state disruptions. It’s easy to get from there to arrhythmogenesis. There’s lots of observational noise, too, but no randomized proof that CPAP alters this relationship.

I found four randomized controlled trials (RCTs) that tested CPAP’s effect on AF. I’ll save you the suspense; they were all negative. One even found a signal for more adverse events in the CPAP group. These studies have several positive qualities: They enrolled patients with moderate to severe sleep apnea and high oxygen desaturation indices, adherence averaged more than 4 hours across all groups in all trials, and the methods for assessing the AF outcomes differed slightly. There’s also a lot not to like: The sample sizes were small, only one trial enrolled “sleepy” patients (as assessed by the Epworth Sleepiness Score), and follow-up was short.

To paraphrase Carl Sagan, “absence of evidence does not equal evidence of absence.” As a statistician would say, type II error cannot be excluded by these RCTs. In medicine, however, the burden of proof falls on demonstrating efficacy. If we treat before concluding that a therapy works, we risk wasting time, money, medical resources, and the most precious of patient commodities: the energy required for behavior change. In their response to letters to the editor, the authors of the third RCT summarize the CPAP, AF, and CV disease data far better than I ever could. They sound the same words of caution and come out against screening patients with AF for OSA. 

The story for CPAP’s effects on EF is similar though muddier. The American College of Cardiology (ACC)/American Heart Association (AHA) guidelines for heart failure cite a meta-analysis showing that CPAP improves left ventricular EF. In 2019, the American Academy of Sleep Medicine (AASM) CPAP guidelines included a systematic review and meta-analysis that found that CPAP has no effect on left ventricular EF in patients with or without heart failure.

There are a million reasons why two systematic reviews on the same topic might come to different conclusions. In this case, the included studies only partially overlap, and broadly speaking, it appears the authors made trade-offs. The review cited by the ACC/AHA had broader inclusion and significantly more patients and paid for it in heterogeneity (I2 in the 80%-90% range). The AASM analysis achieved 0% heterogeneity but limited inclusion to fewer than 100 patients. Across both, the improvement in EF was 2%- 5% at a minimally clinically important difference of 4%. Hardly convincing.

In summary, the road to negative trials and patient harm has always been paved with observational signal and biologic plausibility. Throw in some intellectual and academic bias, and you’ve created the perfect storm of therapeutic overconfidence. The cemetery for discarded medical therapies is crowded, but there’s room for CPAP, at least when it comes to using it to improve CV outcomes. 
 

Dr. Holley is a professor in the department of medicine, Uniformed Services University, Bethesda, Maryland, and a physician at Pulmonary/Sleep and Critical Care Medicine, MedStar Washington Hospital Center, Washington. He disclosed ties to Metapharm Inc., CHEST College, and WebMD.

A version of this article appeared on Medscape.com .

A few months ago, I posted a column on continuous positive airway pressure (CPAP) with the title, “CPAP Oversells and Underperforms.” To date, it has 299 likes and 90 comments, which are almost all negative. I’m glad to see that it’s generated interest, and I’d like to address some of the themes expressed in the posts.

Most comments were personal testimonies to the miracles of CPAP. These are important, and the point deserves emphasis. CPAP can provide significant improvements in daytime sleepiness and quality of life. I closed the original piece by acknowledging this important fact. Readers can be forgiven for missing it given that the title and text were otherwise disparaging of CPAP.

But several comments warrant a more in-depth discussion. The original piece focuses on CPAP and cardiovascular (CV) outcomes but made no mention of atrial fibrillation (AF) or ejection fraction (EF). The effects of CPAP on each are touted by cardiologists and PAP-pushers alike and are drivers of frequent referrals. It›s my fault for omitting them from the discussion.

AF is easy. The data is identical to all other things CPAP and CV. Based on biologic plausibility alone, the likelihood of a relationship between AF and obstructive sleep apnea (OSA) is similar to the odds that the Celtics raise an 18th banner come June. There’s hypoxia, intrathoracic pressure swings, sympathetic surges, and sleep state disruptions. It’s easy to get from there to arrhythmogenesis. There’s lots of observational noise, too, but no randomized proof that CPAP alters this relationship.

I found four randomized controlled trials (RCTs) that tested CPAP’s effect on AF. I’ll save you the suspense; they were all negative. One even found a signal for more adverse events in the CPAP group. These studies have several positive qualities: They enrolled patients with moderate to severe sleep apnea and high oxygen desaturation indices, adherence averaged more than 4 hours across all groups in all trials, and the methods for assessing the AF outcomes differed slightly. There’s also a lot not to like: The sample sizes were small, only one trial enrolled “sleepy” patients (as assessed by the Epworth Sleepiness Score), and follow-up was short.

To paraphrase Carl Sagan, “absence of evidence does not equal evidence of absence.” As a statistician would say, type II error cannot be excluded by these RCTs. In medicine, however, the burden of proof falls on demonstrating efficacy. If we treat before concluding that a therapy works, we risk wasting time, money, medical resources, and the most precious of patient commodities: the energy required for behavior change. In their response to letters to the editor, the authors of the third RCT summarize the CPAP, AF, and CV disease data far better than I ever could. They sound the same words of caution and come out against screening patients with AF for OSA. 

The story for CPAP’s effects on EF is similar though muddier. The American College of Cardiology (ACC)/American Heart Association (AHA) guidelines for heart failure cite a meta-analysis showing that CPAP improves left ventricular EF. In 2019, the American Academy of Sleep Medicine (AASM) CPAP guidelines included a systematic review and meta-analysis that found that CPAP has no effect on left ventricular EF in patients with or without heart failure.

There are a million reasons why two systematic reviews on the same topic might come to different conclusions. In this case, the included studies only partially overlap, and broadly speaking, it appears the authors made trade-offs. The review cited by the ACC/AHA had broader inclusion and significantly more patients and paid for it in heterogeneity (I2 in the 80%-90% range). The AASM analysis achieved 0% heterogeneity but limited inclusion to fewer than 100 patients. Across both, the improvement in EF was 2%- 5% at a minimally clinically important difference of 4%. Hardly convincing.

In summary, the road to negative trials and patient harm has always been paved with observational signal and biologic plausibility. Throw in some intellectual and academic bias, and you’ve created the perfect storm of therapeutic overconfidence. The cemetery for discarded medical therapies is crowded, but there’s room for CPAP, at least when it comes to using it to improve CV outcomes. 
 

Dr. Holley is a professor in the department of medicine, Uniformed Services University, Bethesda, Maryland, and a physician at Pulmonary/Sleep and Critical Care Medicine, MedStar Washington Hospital Center, Washington. He disclosed ties to Metapharm Inc., CHEST College, and WebMD.

A version of this article appeared on Medscape.com .

This transcript has been edited for clarity. 

It’s the counterintuitive stuff in epidemiology that always really interests me. One intuition many of us have is that if a risk factor is significantly associated with an outcome, knowledge of that risk factor would help to predict that outcome. Makes sense. Feels right.

But it’s not right. Not always.

Here’s a fake example to illustrate my point. Let’s say we have 10,000 individuals who we follow for 10 years and 2000 of them die. (It’s been a rough decade.) At baseline, I measured a novel biomarker, the Perry Factor, in everyone. To keep it simple, the Perry Factor has only two values: 0 or 1. 

I then do a standard associational analysis and find that individuals who are positive for the Perry Factor have a 40-fold higher odds of death than those who are negative for it. I am beginning to reconsider ascribing my good name to this biomarker. This is a highly statistically significant result — a P value <.001. 

Clearly, knowledge of the Perry Factor should help me predict who will die in the cohort. I evaluate predictive power using a metric called the area under the receiver operating characteristic curve (AUC, referred to as the C-statistic in time-to-event studies). It tells you, given two people — one who dies and one who doesn’t — how frequently you “pick” the right person, given the knowledge of their Perry Factor.

A C-statistic of 0.5, or 50%, would mean the Perry Factor gives you no better results than a coin flip; it’s chance. A C-statistic of 1 is perfect prediction. So, what will the C-statistic be, given the incredibly strong association of the Perry Factor with outcomes? 0.9? 0.95?

0.5024. Almost useless.

Dr. WIlson

Dr. Wilson

Dr. Wilson

Dr. Wilson

Dr. Wilson

Dr. WIlson

Dr. Wilson

Why does this happen? Why do these promising biomarkers, clearly associated with bad outcomes, fail to improve our ability to predict the future? I already gave one example, which has to do with how the markers are distributed in the population. But even more relevant here is that the new markers will only improve prediction insofar as they are not already represented in the old predictive model. 

Of course, BNP, for example, wasn’t in the old model. But smoking was. Diabetes was. Blood pressure was. All of that data might actually tell you something about the patient’s BNP through their mutual correlation. And improvement in prediction requires new information. 

This is actually why I consider this a really successful study. We need to do studies like this to help us find what those new sources of information might be. It doesn’t seem like these biomarkers will help us in our effort to risk-stratify people. So, we move on to other domains. Perhaps social determinants of health would improve risk prediction. Perhaps insurance status. Perhaps environmental exposures. Perhaps markers of stress.

We will never get to a C-statistic of 1. Perfect prediction is the domain of palm readers and astrophysicists. But better prediction is always possible through data. The big question, of course, is which data?
 

Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Conn. He has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity. 

It’s the counterintuitive stuff in epidemiology that always really interests me. One intuition many of us have is that if a risk factor is significantly associated with an outcome, knowledge of that risk factor would help to predict that outcome. Makes sense. Feels right.

But it’s not right. Not always.

Here’s a fake example to illustrate my point. Let’s say we have 10,000 individuals who we follow for 10 years and 2000 of them die. (It’s been a rough decade.) At baseline, I measured a novel biomarker, the Perry Factor, in everyone. To keep it simple, the Perry Factor has only two values: 0 or 1. 

I then do a standard associational analysis and find that individuals who are positive for the Perry Factor have a 40-fold higher odds of death than those who are negative for it. I am beginning to reconsider ascribing my good name to this biomarker. This is a highly statistically significant result — a P value <.001. 

Clearly, knowledge of the Perry Factor should help me predict who will die in the cohort. I evaluate predictive power using a metric called the area under the receiver operating characteristic curve (AUC, referred to as the C-statistic in time-to-event studies). It tells you, given two people — one who dies and one who doesn’t — how frequently you “pick” the right person, given the knowledge of their Perry Factor.

A C-statistic of 0.5, or 50%, would mean the Perry Factor gives you no better results than a coin flip; it’s chance. A C-statistic of 1 is perfect prediction. So, what will the C-statistic be, given the incredibly strong association of the Perry Factor with outcomes? 0.9? 0.95?

0.5024. Almost useless.

Dr. WIlson

Dr. Wilson

Dr. Wilson

Dr. Wilson

Dr. Wilson

Dr. WIlson

Dr. Wilson

Why does this happen? Why do these promising biomarkers, clearly associated with bad outcomes, fail to improve our ability to predict the future? I already gave one example, which has to do with how the markers are distributed in the population. But even more relevant here is that the new markers will only improve prediction insofar as they are not already represented in the old predictive model. 

Of course, BNP, for example, wasn’t in the old model. But smoking was. Diabetes was. Blood pressure was. All of that data might actually tell you something about the patient’s BNP through their mutual correlation. And improvement in prediction requires new information. 

This is actually why I consider this a really successful study. We need to do studies like this to help us find what those new sources of information might be. It doesn’t seem like these biomarkers will help us in our effort to risk-stratify people. So, we move on to other domains. Perhaps social determinants of health would improve risk prediction. Perhaps insurance status. Perhaps environmental exposures. Perhaps markers of stress.

We will never get to a C-statistic of 1. Perfect prediction is the domain of palm readers and astrophysicists. But better prediction is always possible through data. The big question, of course, is which data?
 

Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Conn. He has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity. 

It’s the counterintuitive stuff in epidemiology that always really interests me. One intuition many of us have is that if a risk factor is significantly associated with an outcome, knowledge of that risk factor would help to predict that outcome. Makes sense. Feels right.

But it’s not right. Not always.

Here’s a fake example to illustrate my point. Let’s say we have 10,000 individuals who we follow for 10 years and 2000 of them die. (It’s been a rough decade.) At baseline, I measured a novel biomarker, the Perry Factor, in everyone. To keep it simple, the Perry Factor has only two values: 0 or 1. 

I then do a standard associational analysis and find that individuals who are positive for the Perry Factor have a 40-fold higher odds of death than those who are negative for it. I am beginning to reconsider ascribing my good name to this biomarker. This is a highly statistically significant result — a P value <.001. 

Clearly, knowledge of the Perry Factor should help me predict who will die in the cohort. I evaluate predictive power using a metric called the area under the receiver operating characteristic curve (AUC, referred to as the C-statistic in time-to-event studies). It tells you, given two people — one who dies and one who doesn’t — how frequently you “pick” the right person, given the knowledge of their Perry Factor.

A C-statistic of 0.5, or 50%, would mean the Perry Factor gives you no better results than a coin flip; it’s chance. A C-statistic of 1 is perfect prediction. So, what will the C-statistic be, given the incredibly strong association of the Perry Factor with outcomes? 0.9? 0.95?

0.5024. Almost useless.

Dr. WIlson

Dr. Wilson

Dr. Wilson

Dr. Wilson

Dr. Wilson

Dr. WIlson

Dr. Wilson

Why does this happen? Why do these promising biomarkers, clearly associated with bad outcomes, fail to improve our ability to predict the future? I already gave one example, which has to do with how the markers are distributed in the population. But even more relevant here is that the new markers will only improve prediction insofar as they are not already represented in the old predictive model. 

Of course, BNP, for example, wasn’t in the old model. But smoking was. Diabetes was. Blood pressure was. All of that data might actually tell you something about the patient’s BNP through their mutual correlation. And improvement in prediction requires new information. 

This is actually why I consider this a really successful study. We need to do studies like this to help us find what those new sources of information might be. It doesn’t seem like these biomarkers will help us in our effort to risk-stratify people. So, we move on to other domains. Perhaps social determinants of health would improve risk prediction. Perhaps insurance status. Perhaps environmental exposures. Perhaps markers of stress.

We will never get to a C-statistic of 1. Perfect prediction is the domain of palm readers and astrophysicists. But better prediction is always possible through data. The big question, of course, is which data?
 

Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Conn. He has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

NEW YORK — Systemic autoimmune disease is well-recognized as a major risk factor for cardiovascular disease (CVD), but less recognized as a cardiovascular risk factor is a history of pregnancy complications, including preeclampsia, and cardiologists and rheumatologists need to include an obstetric history when managing patients with autoimmune diseases, a specialist in reproductive health in rheumatology told attendees at the 4th Annual Cardiometabolic Risk in Inflammatory Conditions conference.

“Autoimmune diseases, lupus in particular, increase the risk for both cardiovascular disease and maternal placental syndromes,” Lisa R. Sammaritano, MD, a professor at Hospital for Special Surgery in New York City and a specialist in reproductive health issues in rheumatology patients, told attendees. “For those patients who have complications during pregnancy, it further increases their already increased risk for later cardiovascular disease.”
 

CVD Risk Double Whammy

A history of systemic lupus erythematosus (SLE) and problematic pregnancy can be a double whammy for CVD risk. Dr. Sammaritano cited a 2022 meta-analysis that showed patients with SLE had a 2.5 times greater risk for stroke and almost three times greater risk for myocardial infarction than people without SLE.

Maternal placental syndromes include pregnancy loss, restricted fetal growth, preeclampsia, premature membrane rupture, placental abruption, and intrauterine fetal demise, Dr. Sammaritano said. Hypertensive disorders of pregnancy, formerly called adverse pregnancy outcomes, she noted, include gestational hypertension, preeclampsia, and eclampsia.

Pregnancy complications can have an adverse effect on the mother’s postpartum cardiovascular health, Dr. Sammaritano noted, a fact borne out by the cardiovascular health after maternal placental syndromes population-based retrospective cohort study and a 2007 meta-analysis that found a history of preeclampsia doubles the risk for venous thromboembolism, stroke, and ischemic heart disease up to 15 years after pregnancy.

“It is always important to obtain a reproductive health history from patients with autoimmune diseases,” Dr. Sammaritano told this news organization in an interview. “This is an integral part of any medical history. In the usual setting, this includes not only pregnancy history but also use of contraception in reproductive-aged women. Unplanned pregnancy can lead to adverse outcomes in the setting of active or severe autoimmune disease or when teratogenic medications are used.”

Pregnancy history can be a factor in a woman’s cardiovascular health more than 15 years postpartum, even if a woman is no longer planning a pregnancy or is menopausal. “As such, this history is important in assessing every woman’s risk profile for CVD in addition to usual traditional risk factors,” Dr. Sammaritano said.

“It is even more important for women with autoimmune disorders, who have been shown to have an already increased risk for CVD independent of their pregnancy history, likely related to a chronic inflammatory state and other autoimmune-related factors such as presence of antiphospholipid antibodies [aPL] or use of corticosteroids.”

Timing of disease onset is also an issue, she said. “In patients with SLE, for example, onset of CVD is much earlier than in the general population,” Dr. Sammaritano said. “As a result, these patients should likely be assessed for risk — both traditional and other risk factors — earlier than the general population, especially if an adverse obstetric history is present.”

At the younger end of the age continuum, women with autoimmune disease, including SLE and antiphospholipid syndrome, who are pregnant should be put on guideline-directed low-dose aspirin preeclampsia prophylaxis, Dr. Sammaritano said. “Whether every patient with SLE needs this is still uncertain, but certainly, those with a history of renal disease, hypertension, or aPL antibody clearly do,” she added.

The evidence supporting hydroxychloroquine (HCQ) in these patients is controversial, but Dr. Sammaritano noted two meta-analyses, one in 2022 and the other in 2023, that showed that HCQ lowered the risk for preeclampsia in women.

“The clear benefit of HCQ in preventing maternal disease complications, including flare, means we recommend it regardless for all patients with SLE at baseline and during pregnancy [if tolerated],” Dr. Sammaritano said. “The benefit or optimal use of these medications in other autoimmune diseases is less studied and less certain.”

Dr. Sammaritano added in her presentation, “We really need better therapies and, hopefully, those will be on the way, but I think the takeaway message, particularly for practicing rheumatologists and cardiologists, is to ask the question about obstetric history. Many of us don’t. It doesn’t seem relevant in the moment, but it really is in terms of the patient’s long-term risk for cardiovascular disease.”
 

The Case for Treatment During Pregnancy

Prophylaxis against pregnancy complications in patients with autoimmune disease may be achievable, Taryn Youngstein, MBBS, consultant rheumatologist and codirector of the Centre of Excellence in Vasculitis Research, Imperial College London, London, England, told this news organization after Dr. Sammaritano’s presentation. At the 2023 American College of Rheumatology Annual Meeting, her group reported the safety and effectiveness of continuing tocilizumab in pregnant women with Takayasu arteritis, a large-vessel vasculitis predominantly affecting women of reproductive age.

“What traditionally happens is you would stop the biologic particularly before the third trimester because of safety and concerns that the monoclonal antibody is actively transported across the placenta, which means the baby gets much more concentration of the drug than the mum,” Dr. Youngstein said.

It’s a situation physicians must monitor closely, she said. “The mum is donating their immune system to the baby, but they’re also donating drug.”

“In high-risk patients, we would share decision-making with the patient,” Dr. Youngstein continued. “We have decided it’s too high of a risk for us to stop the drug, so we have been continuing the interleukin-6 [IL-6] inhibitor throughout the entire pregnancy.”

The data from Dr. Youngstein’s group showed that pregnant women with Takayasu arteritis who continued IL-6 inhibition therapy all carried to term with healthy births.

“We’ve shown that it’s relatively safe to do that, but you have to be very careful in monitoring the baby,” she said. This includes not giving the infant any live vaccines at birth because it will have the high levels of IL-6 inhibition, she said.

Dr. Sammaritano and Dr. Youngstein had no relevant financial relationships to disclose.

A version of this article appeared on Medscape.com.

NEW YORK — Systemic autoimmune disease is well-recognized as a major risk factor for cardiovascular disease (CVD), but less recognized as a cardiovascular risk factor is a history of pregnancy complications, including preeclampsia, and cardiologists and rheumatologists need to include an obstetric history when managing patients with autoimmune diseases, a specialist in reproductive health in rheumatology told attendees at the 4th Annual Cardiometabolic Risk in Inflammatory Conditions conference.

“Autoimmune diseases, lupus in particular, increase the risk for both cardiovascular disease and maternal placental syndromes,” Lisa R. Sammaritano, MD, a professor at Hospital for Special Surgery in New York City and a specialist in reproductive health issues in rheumatology patients, told attendees. “For those patients who have complications during pregnancy, it further increases their already increased risk for later cardiovascular disease.”
 

CVD Risk Double Whammy

A history of systemic lupus erythematosus (SLE) and problematic pregnancy can be a double whammy for CVD risk. Dr. Sammaritano cited a 2022 meta-analysis that showed patients with SLE had a 2.5 times greater risk for stroke and almost three times greater risk for myocardial infarction than people without SLE.

Maternal placental syndromes include pregnancy loss, restricted fetal growth, preeclampsia, premature membrane rupture, placental abruption, and intrauterine fetal demise, Dr. Sammaritano said. Hypertensive disorders of pregnancy, formerly called adverse pregnancy outcomes, she noted, include gestational hypertension, preeclampsia, and eclampsia.

Pregnancy complications can have an adverse effect on the mother’s postpartum cardiovascular health, Dr. Sammaritano noted, a fact borne out by the cardiovascular health after maternal placental syndromes population-based retrospective cohort study and a 2007 meta-analysis that found a history of preeclampsia doubles the risk for venous thromboembolism, stroke, and ischemic heart disease up to 15 years after pregnancy.

“It is always important to obtain a reproductive health history from patients with autoimmune diseases,” Dr. Sammaritano told this news organization in an interview. “This is an integral part of any medical history. In the usual setting, this includes not only pregnancy history but also use of contraception in reproductive-aged women. Unplanned pregnancy can lead to adverse outcomes in the setting of active or severe autoimmune disease or when teratogenic medications are used.”

Pregnancy history can be a factor in a woman’s cardiovascular health more than 15 years postpartum, even if a woman is no longer planning a pregnancy or is menopausal. “As such, this history is important in assessing every woman’s risk profile for CVD in addition to usual traditional risk factors,” Dr. Sammaritano said.

“It is even more important for women with autoimmune disorders, who have been shown to have an already increased risk for CVD independent of their pregnancy history, likely related to a chronic inflammatory state and other autoimmune-related factors such as presence of antiphospholipid antibodies [aPL] or use of corticosteroids.”

Timing of disease onset is also an issue, she said. “In patients with SLE, for example, onset of CVD is much earlier than in the general population,” Dr. Sammaritano said. “As a result, these patients should likely be assessed for risk — both traditional and other risk factors — earlier than the general population, especially if an adverse obstetric history is present.”

At the younger end of the age continuum, women with autoimmune disease, including SLE and antiphospholipid syndrome, who are pregnant should be put on guideline-directed low-dose aspirin preeclampsia prophylaxis, Dr. Sammaritano said. “Whether every patient with SLE needs this is still uncertain, but certainly, those with a history of renal disease, hypertension, or aPL antibody clearly do,” she added.

The evidence supporting hydroxychloroquine (HCQ) in these patients is controversial, but Dr. Sammaritano noted two meta-analyses, one in 2022 and the other in 2023, that showed that HCQ lowered the risk for preeclampsia in women.

“The clear benefit of HCQ in preventing maternal disease complications, including flare, means we recommend it regardless for all patients with SLE at baseline and during pregnancy [if tolerated],” Dr. Sammaritano said. “The benefit or optimal use of these medications in other autoimmune diseases is less studied and less certain.”

Dr. Sammaritano added in her presentation, “We really need better therapies and, hopefully, those will be on the way, but I think the takeaway message, particularly for practicing rheumatologists and cardiologists, is to ask the question about obstetric history. Many of us don’t. It doesn’t seem relevant in the moment, but it really is in terms of the patient’s long-term risk for cardiovascular disease.”
 

The Case for Treatment During Pregnancy

Prophylaxis against pregnancy complications in patients with autoimmune disease may be achievable, Taryn Youngstein, MBBS, consultant rheumatologist and codirector of the Centre of Excellence in Vasculitis Research, Imperial College London, London, England, told this news organization after Dr. Sammaritano’s presentation. At the 2023 American College of Rheumatology Annual Meeting, her group reported the safety and effectiveness of continuing tocilizumab in pregnant women with Takayasu arteritis, a large-vessel vasculitis predominantly affecting women of reproductive age.

“What traditionally happens is you would stop the biologic particularly before the third trimester because of safety and concerns that the monoclonal antibody is actively transported across the placenta, which means the baby gets much more concentration of the drug than the mum,” Dr. Youngstein said.

It’s a situation physicians must monitor closely, she said. “The mum is donating their immune system to the baby, but they’re also donating drug.”

“In high-risk patients, we would share decision-making with the patient,” Dr. Youngstein continued. “We have decided it’s too high of a risk for us to stop the drug, so we have been continuing the interleukin-6 [IL-6] inhibitor throughout the entire pregnancy.”

The data from Dr. Youngstein’s group showed that pregnant women with Takayasu arteritis who continued IL-6 inhibition therapy all carried to term with healthy births.

“We’ve shown that it’s relatively safe to do that, but you have to be very careful in monitoring the baby,” she said. This includes not giving the infant any live vaccines at birth because it will have the high levels of IL-6 inhibition, she said.

Dr. Sammaritano and Dr. Youngstein had no relevant financial relationships to disclose.

A version of this article appeared on Medscape.com.

NEW YORK — Systemic autoimmune disease is well-recognized as a major risk factor for cardiovascular disease (CVD), but less recognized as a cardiovascular risk factor is a history of pregnancy complications, including preeclampsia, and cardiologists and rheumatologists need to include an obstetric history when managing patients with autoimmune diseases, a specialist in reproductive health in rheumatology told attendees at the 4th Annual Cardiometabolic Risk in Inflammatory Conditions conference.

“Autoimmune diseases, lupus in particular, increase the risk for both cardiovascular disease and maternal placental syndromes,” Lisa R. Sammaritano, MD, a professor at Hospital for Special Surgery in New York City and a specialist in reproductive health issues in rheumatology patients, told attendees. “For those patients who have complications during pregnancy, it further increases their already increased risk for later cardiovascular disease.”
 

CVD Risk Double Whammy

A history of systemic lupus erythematosus (SLE) and problematic pregnancy can be a double whammy for CVD risk. Dr. Sammaritano cited a 2022 meta-analysis that showed patients with SLE had a 2.5 times greater risk for stroke and almost three times greater risk for myocardial infarction than people without SLE.

Maternal placental syndromes include pregnancy loss, restricted fetal growth, preeclampsia, premature membrane rupture, placental abruption, and intrauterine fetal demise, Dr. Sammaritano said. Hypertensive disorders of pregnancy, formerly called adverse pregnancy outcomes, she noted, include gestational hypertension, preeclampsia, and eclampsia.

Pregnancy complications can have an adverse effect on the mother’s postpartum cardiovascular health, Dr. Sammaritano noted, a fact borne out by the cardiovascular health after maternal placental syndromes population-based retrospective cohort study and a 2007 meta-analysis that found a history of preeclampsia doubles the risk for venous thromboembolism, stroke, and ischemic heart disease up to 15 years after pregnancy.

“It is always important to obtain a reproductive health history from patients with autoimmune diseases,” Dr. Sammaritano told this news organization in an interview. “This is an integral part of any medical history. In the usual setting, this includes not only pregnancy history but also use of contraception in reproductive-aged women. Unplanned pregnancy can lead to adverse outcomes in the setting of active or severe autoimmune disease or when teratogenic medications are used.”

Pregnancy history can be a factor in a woman’s cardiovascular health more than 15 years postpartum, even if a woman is no longer planning a pregnancy or is menopausal. “As such, this history is important in assessing every woman’s risk profile for CVD in addition to usual traditional risk factors,” Dr. Sammaritano said.

“It is even more important for women with autoimmune disorders, who have been shown to have an already increased risk for CVD independent of their pregnancy history, likely related to a chronic inflammatory state and other autoimmune-related factors such as presence of antiphospholipid antibodies [aPL] or use of corticosteroids.”

Timing of disease onset is also an issue, she said. “In patients with SLE, for example, onset of CVD is much earlier than in the general population,” Dr. Sammaritano said. “As a result, these patients should likely be assessed for risk — both traditional and other risk factors — earlier than the general population, especially if an adverse obstetric history is present.”

At the younger end of the age continuum, women with autoimmune disease, including SLE and antiphospholipid syndrome, who are pregnant should be put on guideline-directed low-dose aspirin preeclampsia prophylaxis, Dr. Sammaritano said. “Whether every patient with SLE needs this is still uncertain, but certainly, those with a history of renal disease, hypertension, or aPL antibody clearly do,” she added.

The evidence supporting hydroxychloroquine (HCQ) in these patients is controversial, but Dr. Sammaritano noted two meta-analyses, one in 2022 and the other in 2023, that showed that HCQ lowered the risk for preeclampsia in women.

“The clear benefit of HCQ in preventing maternal disease complications, including flare, means we recommend it regardless for all patients with SLE at baseline and during pregnancy [if tolerated],” Dr. Sammaritano said. “The benefit or optimal use of these medications in other autoimmune diseases is less studied and less certain.”

Dr. Sammaritano added in her presentation, “We really need better therapies and, hopefully, those will be on the way, but I think the takeaway message, particularly for practicing rheumatologists and cardiologists, is to ask the question about obstetric history. Many of us don’t. It doesn’t seem relevant in the moment, but it really is in terms of the patient’s long-term risk for cardiovascular disease.”
 

The Case for Treatment During Pregnancy

Prophylaxis against pregnancy complications in patients with autoimmune disease may be achievable, Taryn Youngstein, MBBS, consultant rheumatologist and codirector of the Centre of Excellence in Vasculitis Research, Imperial College London, London, England, told this news organization after Dr. Sammaritano’s presentation. At the 2023 American College of Rheumatology Annual Meeting, her group reported the safety and effectiveness of continuing tocilizumab in pregnant women with Takayasu arteritis, a large-vessel vasculitis predominantly affecting women of reproductive age.

“What traditionally happens is you would stop the biologic particularly before the third trimester because of safety and concerns that the monoclonal antibody is actively transported across the placenta, which means the baby gets much more concentration of the drug than the mum,” Dr. Youngstein said.

It’s a situation physicians must monitor closely, she said. “The mum is donating their immune system to the baby, but they’re also donating drug.”

“In high-risk patients, we would share decision-making with the patient,” Dr. Youngstein continued. “We have decided it’s too high of a risk for us to stop the drug, so we have been continuing the interleukin-6 [IL-6] inhibitor throughout the entire pregnancy.”

The data from Dr. Youngstein’s group showed that pregnant women with Takayasu arteritis who continued IL-6 inhibition therapy all carried to term with healthy births.

“We’ve shown that it’s relatively safe to do that, but you have to be very careful in monitoring the baby,” she said. This includes not giving the infant any live vaccines at birth because it will have the high levels of IL-6 inhibition, she said.

Dr. Sammaritano and Dr. Youngstein had no relevant financial relationships to disclose.

A version of this article appeared on Medscape.com.

TOPLINE:

Higher doses of nonsteroidal anti-inflammatory drugs (NSAIDs) increase the risk for cardiovascular diseases (CVDs) such as ischemic heart disease, stroke, and congestive heart failure in patients with ankylosing spondylitis (AS) compared with lower doses.

METHODOLOGY:

• NSAIDs can suppress inflammation and relieve pain in patients with AS, but long-term treatment with NSAIDs poses concerns regarding gastrointestinal and renal toxicities and increased CVD risk.
• This nationwide cohort study used data from the Korean National Health Insurance database to investigate the risk for CVD associated with an increasing NSAID dosage in a real-world AS cohort.
• Investigators recruited 19,775 patients (mean age, 36.1 years; 75% men) with newly diagnosed AS and without any prior CVD between January 2010 and December 2018, among whom 99.7% received NSAID treatment and 30.2% received tumor necrosis factor inhibitor treatment.
• A time-varying approach was used to assess the NSAID exposure, wherein periods of NSAID use were defined as “NSAID-exposed” and periods longer than 1 month without NSAID use were defined as “NSAID-unexposed.”
• The primary outcome was the composite outcome of ischemic heart disease, stroke, or congestive heart failure.

TAKEAWAY:

• During the follow-up period of 98,290 person-years, 1663 cases of CVD were identified, which included 1157 cases of ischemic heart disease, 301 cases of stroke, and 613 cases of congestive heart failure.
• After adjusting for confounders, each defined daily dose increase in NSAIDs raised the risk for incident CVD by 10% (adjusted hazard ratio [aHR], 1.10; 95% CI, 1.08-1.13).
• Similarly, increasing the dose of NSAIDs was associated with an increased risk for ischemic heart disease (aHR, 1.08; 95% CI, 1.05-1.11), stroke (aHR, 1.09; 95% CI, 1.04-1.15), and congestive heart failure (aHR, 1.12; 95% CI, 1.08-1.16).
• The association between increasing NSAID dose and increased CVD risk was consistent across various subgroups, with NSAIDs posing a greater threat to cardiovascular health in women than in men.

IN PRACTICE:

The authors wrote, “Taken together, these results suggest that increasing the dose of NSAIDs is associated with a higher cardiovascular risk in AS, but that the increased risk might be lower than that in the general population.”

SOURCE:

First author Ji-Won Kim, MD, PhD, of the Division of Rheumatology, Department of Internal Medicine, Daegu Catholic University School of Medicine, Daegu, the Republic of Korea, and colleagues had their work published online on April 9 in Annals of the Rheumatic Diseases.

LIMITATIONS:

The study was of retrospective nature. The levels of acute phase reactants and AS disease activity could not be determined owing to a lack of data in the National Health Insurance database. The accuracy of the diagnosis of cardiovascular outcomes on the basis of the International Classification of Disease codes was also questionable.

DISCLOSURES:

The study was supported by the National Research Foundation of Korea. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Higher doses of nonsteroidal anti-inflammatory drugs (NSAIDs) increase the risk for cardiovascular diseases (CVDs) such as ischemic heart disease, stroke, and congestive heart failure in patients with ankylosing spondylitis (AS) compared with lower doses.

METHODOLOGY:

• NSAIDs can suppress inflammation and relieve pain in patients with AS, but long-term treatment with NSAIDs poses concerns regarding gastrointestinal and renal toxicities and increased CVD risk.
• This nationwide cohort study used data from the Korean National Health Insurance database to investigate the risk for CVD associated with an increasing NSAID dosage in a real-world AS cohort.
• Investigators recruited 19,775 patients (mean age, 36.1 years; 75% men) with newly diagnosed AS and without any prior CVD between January 2010 and December 2018, among whom 99.7% received NSAID treatment and 30.2% received tumor necrosis factor inhibitor treatment.
• A time-varying approach was used to assess the NSAID exposure, wherein periods of NSAID use were defined as “NSAID-exposed” and periods longer than 1 month without NSAID use were defined as “NSAID-unexposed.”
• The primary outcome was the composite outcome of ischemic heart disease, stroke, or congestive heart failure.

TAKEAWAY:

• During the follow-up period of 98,290 person-years, 1663 cases of CVD were identified, which included 1157 cases of ischemic heart disease, 301 cases of stroke, and 613 cases of congestive heart failure.
• After adjusting for confounders, each defined daily dose increase in NSAIDs raised the risk for incident CVD by 10% (adjusted hazard ratio [aHR], 1.10; 95% CI, 1.08-1.13).
• Similarly, increasing the dose of NSAIDs was associated with an increased risk for ischemic heart disease (aHR, 1.08; 95% CI, 1.05-1.11), stroke (aHR, 1.09; 95% CI, 1.04-1.15), and congestive heart failure (aHR, 1.12; 95% CI, 1.08-1.16).
• The association between increasing NSAID dose and increased CVD risk was consistent across various subgroups, with NSAIDs posing a greater threat to cardiovascular health in women than in men.

IN PRACTICE:

The authors wrote, “Taken together, these results suggest that increasing the dose of NSAIDs is associated with a higher cardiovascular risk in AS, but that the increased risk might be lower than that in the general population.”

SOURCE:

First author Ji-Won Kim, MD, PhD, of the Division of Rheumatology, Department of Internal Medicine, Daegu Catholic University School of Medicine, Daegu, the Republic of Korea, and colleagues had their work published online on April 9 in Annals of the Rheumatic Diseases.

LIMITATIONS:

The study was of retrospective nature. The levels of acute phase reactants and AS disease activity could not be determined owing to a lack of data in the National Health Insurance database. The accuracy of the diagnosis of cardiovascular outcomes on the basis of the International Classification of Disease codes was also questionable.

DISCLOSURES:

The study was supported by the National Research Foundation of Korea. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Higher doses of nonsteroidal anti-inflammatory drugs (NSAIDs) increase the risk for cardiovascular diseases (CVDs) such as ischemic heart disease, stroke, and congestive heart failure in patients with ankylosing spondylitis (AS) compared with lower doses.

METHODOLOGY:

• NSAIDs can suppress inflammation and relieve pain in patients with AS, but long-term treatment with NSAIDs poses concerns regarding gastrointestinal and renal toxicities and increased CVD risk.
• This nationwide cohort study used data from the Korean National Health Insurance database to investigate the risk for CVD associated with an increasing NSAID dosage in a real-world AS cohort.
• Investigators recruited 19,775 patients (mean age, 36.1 years; 75% men) with newly diagnosed AS and without any prior CVD between January 2010 and December 2018, among whom 99.7% received NSAID treatment and 30.2% received tumor necrosis factor inhibitor treatment.
• A time-varying approach was used to assess the NSAID exposure, wherein periods of NSAID use were defined as “NSAID-exposed” and periods longer than 1 month without NSAID use were defined as “NSAID-unexposed.”
• The primary outcome was the composite outcome of ischemic heart disease, stroke, or congestive heart failure.

TAKEAWAY:

• During the follow-up period of 98,290 person-years, 1663 cases of CVD were identified, which included 1157 cases of ischemic heart disease, 301 cases of stroke, and 613 cases of congestive heart failure.
• After adjusting for confounders, each defined daily dose increase in NSAIDs raised the risk for incident CVD by 10% (adjusted hazard ratio [aHR], 1.10; 95% CI, 1.08-1.13).
• Similarly, increasing the dose of NSAIDs was associated with an increased risk for ischemic heart disease (aHR, 1.08; 95% CI, 1.05-1.11), stroke (aHR, 1.09; 95% CI, 1.04-1.15), and congestive heart failure (aHR, 1.12; 95% CI, 1.08-1.16).
• The association between increasing NSAID dose and increased CVD risk was consistent across various subgroups, with NSAIDs posing a greater threat to cardiovascular health in women than in men.

IN PRACTICE:

The authors wrote, “Taken together, these results suggest that increasing the dose of NSAIDs is associated with a higher cardiovascular risk in AS, but that the increased risk might be lower than that in the general population.”

SOURCE:

First author Ji-Won Kim, MD, PhD, of the Division of Rheumatology, Department of Internal Medicine, Daegu Catholic University School of Medicine, Daegu, the Republic of Korea, and colleagues had their work published online on April 9 in Annals of the Rheumatic Diseases.

LIMITATIONS:

The study was of retrospective nature. The levels of acute phase reactants and AS disease activity could not be determined owing to a lack of data in the National Health Insurance database. The accuracy of the diagnosis of cardiovascular outcomes on the basis of the International Classification of Disease codes was also questionable.

DISCLOSURES:

The study was supported by the National Research Foundation of Korea. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Blood pressure (BP) self-monitoring and medication management may be better than usual care for controlling hypertension, a new study published in JAMA Network Open suggested. 

METHODOLOGY:

• The secondary analysis of a randomized, unblinded clinical trial included patients aged ≥ 40 years with uncontrolled hypertension in Valencia, Spain, between 2017 and 2020.
• The 111 patients in the intervention group received educational materials and instructions for self-monitoring of BP with a home monitor and medication adjustment as needed without contacting their healthcare clinicians.
• The 108 patients in the control group received usual care, including education on BP control.
• After 24 months, researchers recorded BP levels, the number of people who achieved a target BP (systolic BP < 140 mm Hg and diastolic BP < 90 mm Hg), adverse events, quality of life, behavioral changes, and health service use.

TAKEAWAY:

• Patients in the intervention group had a lower average systolic BP reading at 24 months than patients who received usual care (adjusted mean difference, -3.4 mm Hg).
• Patients in the intervention group also had a lower average diastolic BP reading than usual care (adjusted mean difference, -2.5 mm Hg).
• The percentage of people who achieved the target BP was similar in both groups (64% in the intervention group compared with 54% in the control group).
• Researchers found no difference between groups in terms of adverse events, use of health services, behavioral changes such as smoking status or body weight, or quality of life.

IN PRACTICE:

“These results suggest that simple, inexpensive, and easy-to-implement self-management interventions have the potential to improve the long-term control of hypertension in routine clinical practice.” 

SOURCE:

The study was led by Gabriel Sanfélix-Gimeno, PhD, Pharm D, head of the Health Services Research & Pharmacoepidemiology Unit at Fisabio Research Institute in Valencia, Spain.

LIMITATIONS:

Some study participants were lost to follow-up due to COVID-19 restrictions. The trial was unblinded, which may have led to biases among patients and clinicians. Clinicians treated both the control and intervention groups. The results may not be extrapolated to those with controlled hypertension, very high BP, or people who are pregnant because they were not included in the study.

DISCLOSURES:

Various authors reported receiving grants from RTI Health Solutions or personal fees from GSK and MSD outside the submitted work. No other disclosures were reported. The study was funded by the Instituto de Salud Carlos III at the Spanish Ministry of Research, Innovation and Universities, the European Regional Development Fund, and Spanish Clinical Research Network.

A version of this article appeared on Medscape.com.

TOPLINE:

Blood pressure (BP) self-monitoring and medication management may be better than usual care for controlling hypertension, a new study published in JAMA Network Open suggested. 

METHODOLOGY:

• The secondary analysis of a randomized, unblinded clinical trial included patients aged ≥ 40 years with uncontrolled hypertension in Valencia, Spain, between 2017 and 2020.
• The 111 patients in the intervention group received educational materials and instructions for self-monitoring of BP with a home monitor and medication adjustment as needed without contacting their healthcare clinicians.
• The 108 patients in the control group received usual care, including education on BP control.
• After 24 months, researchers recorded BP levels, the number of people who achieved a target BP (systolic BP < 140 mm Hg and diastolic BP < 90 mm Hg), adverse events, quality of life, behavioral changes, and health service use.

TAKEAWAY:

• Patients in the intervention group had a lower average systolic BP reading at 24 months than patients who received usual care (adjusted mean difference, -3.4 mm Hg).
• Patients in the intervention group also had a lower average diastolic BP reading than usual care (adjusted mean difference, -2.5 mm Hg).
• The percentage of people who achieved the target BP was similar in both groups (64% in the intervention group compared with 54% in the control group).
• Researchers found no difference between groups in terms of adverse events, use of health services, behavioral changes such as smoking status or body weight, or quality of life.

IN PRACTICE:

“These results suggest that simple, inexpensive, and easy-to-implement self-management interventions have the potential to improve the long-term control of hypertension in routine clinical practice.” 

SOURCE:

The study was led by Gabriel Sanfélix-Gimeno, PhD, Pharm D, head of the Health Services Research & Pharmacoepidemiology Unit at Fisabio Research Institute in Valencia, Spain.

LIMITATIONS:

Some study participants were lost to follow-up due to COVID-19 restrictions. The trial was unblinded, which may have led to biases among patients and clinicians. Clinicians treated both the control and intervention groups. The results may not be extrapolated to those with controlled hypertension, very high BP, or people who are pregnant because they were not included in the study.

DISCLOSURES:

Various authors reported receiving grants from RTI Health Solutions or personal fees from GSK and MSD outside the submitted work. No other disclosures were reported. The study was funded by the Instituto de Salud Carlos III at the Spanish Ministry of Research, Innovation and Universities, the European Regional Development Fund, and Spanish Clinical Research Network.

A version of this article appeared on Medscape.com.

TOPLINE:

Blood pressure (BP) self-monitoring and medication management may be better than usual care for controlling hypertension, a new study published in JAMA Network Open suggested. 

METHODOLOGY:

• The secondary analysis of a randomized, unblinded clinical trial included patients aged ≥ 40 years with uncontrolled hypertension in Valencia, Spain, between 2017 and 2020.
• The 111 patients in the intervention group received educational materials and instructions for self-monitoring of BP with a home monitor and medication adjustment as needed without contacting their healthcare clinicians.
• The 108 patients in the control group received usual care, including education on BP control.
• After 24 months, researchers recorded BP levels, the number of people who achieved a target BP (systolic BP < 140 mm Hg and diastolic BP < 90 mm Hg), adverse events, quality of life, behavioral changes, and health service use.

TAKEAWAY:

• Patients in the intervention group had a lower average systolic BP reading at 24 months than patients who received usual care (adjusted mean difference, -3.4 mm Hg).
• Patients in the intervention group also had a lower average diastolic BP reading than usual care (adjusted mean difference, -2.5 mm Hg).
• The percentage of people who achieved the target BP was similar in both groups (64% in the intervention group compared with 54% in the control group).
• Researchers found no difference between groups in terms of adverse events, use of health services, behavioral changes such as smoking status or body weight, or quality of life.

IN PRACTICE:

“These results suggest that simple, inexpensive, and easy-to-implement self-management interventions have the potential to improve the long-term control of hypertension in routine clinical practice.” 

SOURCE:

The study was led by Gabriel Sanfélix-Gimeno, PhD, Pharm D, head of the Health Services Research & Pharmacoepidemiology Unit at Fisabio Research Institute in Valencia, Spain.

LIMITATIONS:

Some study participants were lost to follow-up due to COVID-19 restrictions. The trial was unblinded, which may have led to biases among patients and clinicians. Clinicians treated both the control and intervention groups. The results may not be extrapolated to those with controlled hypertension, very high BP, or people who are pregnant because they were not included in the study.

DISCLOSURES:

Various authors reported receiving grants from RTI Health Solutions or personal fees from GSK and MSD outside the submitted work. No other disclosures were reported. The study was funded by the Instituto de Salud Carlos III at the Spanish Ministry of Research, Innovation and Universities, the European Regional Development Fund, and Spanish Clinical Research Network.

A version of this article appeared on Medscape.com.