Real-World Outcomes Not Always Reflected in Clinical Trials: Dr Maria Amaya

Maria Amaya, MD, PhD, assistant professor of hematology, University of Colorado School of Medicine, shared important trends she has observed in real-world leukemia data in a recent interview with The American Journal of Managed Care^® (AJMC^®). In her discussion with AJMC, Amaya details the discrepancies she has witnessed between real-world and clinical-trial data in the realm of leukemia studies, the influence of socioeconomic factors on leukemia outcomes, as well as avenues for improvement in this space.

These topics and more were discussed at an Institute for Value-Based Medicine event held in Columbus, Ohio, titled “The Impact of Genetics and Social Factors in Cancer Care.”

This transcript has been lightly edited for clarity.

Transcript

How do the outcomes observed in real-world data compare to those reported in clinical trials for leukemia treatments?

So, one of the things that we have found, we have used this database through a company called Flatiron that has real-world data on leukemia outcomes across the US. One of the things that we have noticed is that there are some different outcomes in terms of clinical trials vs the real-world data that we have gotten from this company. And in particular, one of the things that we have seen is that patients from lower socioeconomic status tend to have worse outcomes compared to patients with higher socioeconomic status. That may be related to access to certain medications that have been otherwise FDA approved by clinical trials.

What patient-specific factors did you find to have the most significant impact on leukemia outcomes in your real-world data analysis?

This database was fairly large. We looked at about 3000 patients, and one of the main things we looked at was demographics based on race, ethnicity, and socioeconomic status. One of the main things that we found is that the differences in socioeconomic status have a larger impact in the survival of patients.

What are the best approaches you can implore to ensure the quality and reliability of real-world data?

As I alluded to previously, we partner with a company called Flatiron, and they collect data from across the United States and work with academic centers and community centers, and they collect data from electronic medical records. They have also ensured that the survival data are fairly accurate. They also pair up data with obituaries to make sure that survival of patients is accurately collected. And so, that's the data set that we have used. It's a large number of data sets. It's very clean. It has a lot of important information for patients with AML [acute myeloid leukemia].

Based on real-world findings you’ve observed, do you see any adjustments necessary to improve patient outcomes? What implications do these findings have for current leukemia treatment protocols and standards of care?

The data drive the things that we need to change. So, as we found out and I’ll present today, patients with lower socioeconomic status across the United States tend to have worse outcomes, and part of the reason, at least, is because the treatments are different. So, we are choosing different treatments and less novel therapies for some of these patients. One of the things that we have to work really hard on is to providing good access to newer therapies for all our patients across the United States.