And it didn’t just sparkle because of the sequined Taylor Swift fans clogging the nearby streets during the meeting.
Arif Kamal, MD, MBA, MHS, who is also an oncologist at Duke University, Durham, N.C., said he was impressed by a pair of landmark studies released at the meeting that show hidden cancer can be targeted with “really remarkable outcomes.” He also highlighted sessions that examined the role of artificial intelligence (AI) in oncology, during an interview.
Below are lightly edited excerpts from a conversation with Dr. Kamal:
Question: What are some of most groundbreaking studies released at ASCO?
Answer: One is an interim analysis of the, which involved patients with early-stage hormone receptor-positive, HER2-negative (HR+/HER2–) breast tumors. This phase 3 randomized trial compared maintenance therapy with the cyclin-dependent kinase 4/6 (CDK4/6) inhibitor ribociclib (Kisqali) plus endocrine therapy with an aromatase inhibitor to endocrine therapy alone in patients with node-positive or node-negative and stage II or III HR+/HER– breast cancer.
For a long time, the standard care in these patients has been to use endocrine therapy alone. This is the first big trial to show that upstream usage of additional therapy in early stages is also beneficial for disease-free survival. The 3-year invasive disease-free survival rate was 90.4% in the rebociclib-endocrine therapy group vs. 87.1% for patients who received only endocrine therapy (P = .0014).
Q: How do these findings add to current knowledge?
A: Typically, we let people get metastatic disease before we use CDK4/6 inhibitors. These findings show that systemic treatment beyond endocrine therapy will be helpful in cases where you’ve got smaller disease that has not spread yet.
Even in patients with node-negative breast cancer, micrometastatic disease is clearly there, because the medication killed the negative lymph nodes.
Q: What else struck you as especially important research?
A: The NATALEE findings match what we saw in another study – the, which looked at adjuvant osimertinib in non–small-cell lung cancer patients with EGFR-mutated, stage IB to IIIA disease – cancer that has not spread to the lymph nodes.
This is another example where you have a treatment being used in earlier-stage disease that’s showing really remarkable outcomes. The study found that 5-year overall survival was 88% in an osimertinib group vs. 78% in a placebo group (P < .001). This is a disease where, in stage IB, we wouldn’t even necessarily give these patients treatment at all, other than surgical resection of the tumor and maybe give them a little bit of chemotherapy.
Even in these smaller, early tumors, osimertinib makes a difference.
Q: As a whole, what are these studies telling us about cancer cells that can’t be easily detected?
A: To find a disease-free survival benefit with adding ribociclib in a stage II, stage III setting, particularly in node-negative disease, is remarkable because it says that the cells in hiding are bad actors, and they are going to cause trouble. The study shows that medications can find these cells and reverse that risk of bad outcomes.
If you think about the paradigm of cancer, that’s pretty remarkable because the ADAURA trial does the same thing: You do surgery for [early-stage] lung cancers that have not spread to the lymph nodes and you figure, “Well, I’ve got it all, right? The margins are real big, healthy, clean.” And yet, people still have recurrences, and you ask the same question: “Can any medicine find those few cells, the hundreds of cells that are still left somewhere in hiding?” And the answer is again, yes. It’s changing the paradigm of our understanding of minimal residual disease.
That’s why there’s so much interest in liquid biopsies. Let’s say that after treatment we don’t see any cancer radiologically, but there’s a signal from a liquid biopsy [detecting residual cancer]. These two trials demonstrate that there’s something we can do about it.
Q: There were quite a few studies about artificial intelligence released at ASCO. Where do we stand on that front?
A: We’re just at the beginning of people thinking about the use of generative AI for clinical decision support, clinical trial matching, and pathology review. But AI, at least for now, still has the issue of making up things that aren’t true. That’s not something patients are going to be okay with.
Q: How can AI be helpful to medical providers considering its limitations?
A: AI is going to be very good at the data-to-information transition. You’ll start seeing people use AI to start clinical notes for them and to match patients to the best clinical trials for them. But fundamentally, the clinician’s role will continue to be to check facts and offer wisdom.
Q: Will AI threaten the careers of oncologists?
A: The body of knowledge about oncology is growing exponentially, and no one can actually keep up. There’s so much data that’s out there that needs to be turned into usable information amid a shortage of oncologists. At the same time, the prevalence of cancer is going up, even though mortality is going down.
Synthesis of data is what oncologists are waiting for from AI. They’ll welcome it as opposed to being worried. That’s the sentiment I heard from my colleagues.
Dr. Kamal has no disclosures.