More than half of breast cancer patients are not well represented in conventional clinical trials, according to a study published in JCO Oncology Practice.
For the retrospective cohort study, researchers analyzed data from the national CancerLinQ Discovery database for women diagnosed with stage I-III breast cancer between 2005 and 2015.
Among the 11,770 patients included in the study, researchers found that 48% were well represented in conventional clinical trials, 45% were under-represented, and 7% were unrepresented.
In the study, patients with comorbidities or concurrent cancer were considered unrepresented in clinical trials. Non-white patients, as well as those under the age of 45 or 70 and older, were considered under-represented. Patients who were white, between 45 and 69 years old, and without comorbidities were considered well represented.
Overall, 71% of the study's patients were between 45 and 69 years old, 72% were white, and 51% were diagnosed with stage II breast cancer. In addition, just 6% had comorbidities, and only 2% had a concurrent cancer.
Among unrepresented patients, 76% were categorized as such due to comorbidities alone, 22% had concurrent cancer, and 2% had both.
In addition, 44% of under-represented patients were categorized as such based on age, 39% based race or ethnicity, and 17% on the basis of both age and race or ethnicity.
In their analysis, researchers used Cox proportional hazards models to evaluate five-year mortality by population group and patient characteristics, including age, comorbidity, and race. They adjusted for cancer stage, subtype, chemotherapy, and diagnosis year.
Notably, when compared with well represented patients, unrepresented patients faced almost three times the risk of five-year mortality.
Although there was no significant difference in the risk of five-year mortality between under-represented patients and well represented patients, under-represented patients who were under the age of 45 had a lower chance of five-year mortality and patients ages 70 and older had a higher chance of five-year mortality when compared with patients who were between 45 and 69 years old. (Gidwani et al., JCO Oncology Practice, 9/24/2021)
This study adds to a growing body of evidence highlighting ways that the lack of representation and under-representation of women and people from marginalized communities in clinical trials impacts patient outcomes. To be clear, we have long known that the lack of representation in clinical trials means that we as an industry do not know the benefits and burdens of many treatments for broad swaths of the patient population. In this example we are understating the harms, but there was also research from last year that suggests that we are actually understating the potential benefits of lung cancer screening based on the lack of representation in research. Which is why my teammates and I have been focusing on untapped ways to increase early-stage lung cancer diagnosis to reduce the health disparities in the nation’s number one cancer killer.
Clinical trial diversity has been an ongoing research focus for my team since 2020 and we held a cross-industry event on this topic in 2021 to understand why the ecosystem has not made more progress given how long we have known about the problem, its impacts, and the wealth of available information on operational changes to make trials for inclusive. One of our takeaways, supported by what the study authors found, is the need for sponsors and researchers to interrogate who we exclude from trial participation both clinically and non-clinically. This study focused on the former, but it would not surprise me if ways in which the analyzed studies were designed would have made it difficult for the populations identified as unrepresented and under-represented to participate. Where were these sites located? How often did patients have to go in-person and during what times? We saw a similar dynamic play out in the initial push to vaccinate the country where many of the assumptions built into the early programs disadvantaged people based on socio-economic, geographic, and other grounds. Recognizing these design choices—and questioning their necessity—will be vital if we want to make progress.
At the end of the day, patients, their loved ones, and their clinical teams want to be able to say that they made the best possible decision for the patient because they had all the necessary information. My hope is that we are on a path to make that true for all patients, not just some.
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