Understanding Hematology/Oncology Clinical Trials Is Crucial to Patient Communication

With new clinical trial data being published in medical journals and presented during conferences at a rapid pace, hematology/oncology fellows must be mindful of how factors such as trial design and patient population can affect the data. Through this lens, fellows can feel more confident about selecting the best treatment possible for a given patient, according to Matthew Hadfield, DO.

“The propensity for [a fellow] who’s first looking at trials is to read the abstract and say, ‘This [agent] had an overall survival or a progression-free survival benefit,’” Hadfield, assistant professor of medicine at The Warren Alpert Medical School of Brown University in Providence, Rhode Island, said in an interview with Oncology Fellows. “But [fellows] need to do their due diligence and learn how trials are designed. It’s not enough to briefly look at the results and come to your own conclusions. Every study it going to have its own faults, and you need to understand these because, ultimately, it’s your responsibility to understand what you’re prescribing and how it can affect patients.”

In the interview, Hadfield discussed his interest in early-phase data, strategies for fellows to parse the wealth of new findings, and how to discuss clinical trial findings with patients.

Oncology Fellows: What sparked your interest in early-phase clinical trials?

Hadfield: I mostly do phase 1 and early drug development trials. These are of particular interest to me because there are now so many novel therapeutics. There are so many new drug targets, mechanisms of action, and [other] things to be excited about. But we still have a lot of work to do to figure out how to optimize those treatments and get them to patients.

The hope is that you can help someone and prolong their life with one of these therapies when they’ve run out of standard of care [SOC] options. For instance, there was a patient we treated on a trial who had remained on trial for almost a year and made it to his 60th wedding anniversary. Those are the moments that make the job worth it.

With so much new information being published, how do you stay up to date and decide which studies deserve your attention?

The meetings are [important, including] the American Society of Clinical Oncology Annual Meeting, the European Society for Medical Oncology Congress, and the American Association for Cancer Research Annual Meeting. You should use those as your guideposts in terms of what the most relevant studies are at that time.

You should also try to focus on whatever disease area you’re in clinic for at that time and read those studies, particularly the practice-changing ones. Now that I focus on early drug development in melanoma, I look into the melanoma trials to see how they’re changing practice.

When you’re going through treatment algorithms to pick a treatment, such as the National Comprehensive Cancer Network guidelines, it’s helpful to go back and read the study, understand how it was designed, what the control group was, what the patient population was, and how it was statistically designed. All those things are important.

Many individuals will just follow the algorithms. But it is helpful to understand why you’re making a treatment decision and understand the efficacy [of an agent] vs the [toxicity] risks because there is a risk-benefit conversation with patients [that must happen]. You have to make sure they understand what could potentially happen from a treatment and what the intended benefit is. To do that, you have to read the trial and understand it.

What should fellows know about how to dissect clinical trial designs?

Every trial is designed in a specific way. Understanding what the study sponsor [intended] when they designed the trial and the period in which it was designed [are important]. For example, sometimes a trial is designed, and it takes so long to enroll that the SOC has changed. That could explain why [a given drug] doesn’t make sense in the current landscape of how you treat [patients with] a certain type of cancer. The patient populations, where they came from, and their ethnicities also all factor into [data] applicability.

How do you weigh safety vs efficacy data when reading a study?

It’s always a sliding scale. For example, when a patient has metastatic disease and it’s not curable, you’re willing to accept a bit more toxicity than you would for a patient with a curable [disease who would receive] neoadjuvant therapy. A big thing that a lot of individuals don’t think about is that patients enrolled in clinical trials have to [meet] lots of inclusion and exclusion criteria. Patients in the real-world population tend to be sicker, have more comorbidities, and be frailer than those enrolled in a trial. Understanding that the toxicity could possibly be worse in your real-world population is important.

[In terms of efficacy,] when you look at the statistical design, you have to understand what the primary end point of the trial was and what differences the secondary end points were powered to identify. When you’re talking to patients, it’s important to [provide an explanation] that conveys that the efficacy we are hoping for is based on [data from] the trial and [describe] the toxicities that they could potentially develop [before helping] them make that decision.

Another thing we run into a lot are cross-trial comparisons. When you’re talking with patients about trials, you can’t compare the outcome of one trial with another. They were completely different trials that were powered in their own ways statistically. You cannot draw comparisons between the two because they weren’t statistically set up to do that. You have to look at each trial on its own, put [the data] into the broader landscape of all the trials, and figure out how to best treat patients.

How should fellows approach discussing clinical trial data with patients?

It helps to understand your patient, their personality type, and what they’re hoping to learn. Some patients want to know the exact percentages and hazard ratios. There are patients who are that nuanced, and some patients [just] trust you if you think a treatment is a good idea.

The big things that you have to make sure that come across and are understood are that every drug has potential toxicities. We wouldn’t be recommending the drug if there wasn’t a potential efficacy benefit, but every drug has a risk. In melanoma, for instance, we give immunotherapies with a risk of fatal toxicities. It’s your job to stay on top of the literature, make sure you understand the toxicities, and counsel patients so that they know that there are potential toxicities.

This is challenging, especially in the age of immunotherapy, when toxicities are more poorly understood and variable. Sometimes patients develop a toxicity several months into treatment, sometimes they develop it after treatment, and sometimes they don’t develop it at all. Meeting them where they’re at but trying to make sure that they understand that there are risks is important.

In the era of immunotherapy, a lot of patients have this perception that [the treatment] is without adverse effects and that couldn’t be further from the truth. Unfortunately, patients do develop fatal and serious, chronic toxicities. It’s your job when you’re prescribing therapies that patients understand both the benefit but also the risks, so they can make the best informed decision.