Laura is the editorial director of The American Journal of Managed Care® (AJMC®) and all its brands, including The American Journal of Accountable Care®, Evidence-Based Oncology™, and The Center for Biosimilars®. She has been working on AJMC® since 2014 and has been with AJMC®'s parent company, MJH Life Sciences, since 2011. She has an MA in business and economic reporting from New York University.
The populations represented in randomized controlled trials often do not match the populations being treated in the real world due to eligibility criteria, which can be challenging when translating those results to real-world decisions, explained speakers during a session at the European Hematology Association 2021 Virtual Congress.
Randomized controlled trials (RCTs) may be the gold standard for trials, but the stringent eligibility criteria often mean that many patients who more closely represent real-world populations are ineligible for the trials.
During a session at the European Hematology Association 2021 Virtual Congress, speakers discussed the differences in how RCTs translate to the real world, which patients in real-world practices would be eligible or ineligible, and the real-world outcomes and challenges in multiple myeloma (MM).
To start the session, Faith Davies, MD, professor in the Department of Medicine and director of the Clinical Myeloma Program at the Perlmutter Cancer Center at NYU Langone, explained the difference between efficacy and effectiveness. Efficacy is whether the drug can work as determined in an RCT.
“That's really, really important, because it provides very robust evidence of the drug working,” she explained. “However, it's in a very specialized clinical setting, where the influences from, I guess, the outside world are minimized as much as possible.”
On the other hand, effectiveness is what is needed in the clinic. Effectiveness is whether or not the drug does work.
“So does the drug work under real-world conditions when we have all of that noise and those competing factors?” she asked. “And the way we determine this is by using our robust, real-world, or observational, data. And we see if the data from the randomized controlled trials is actually generalizable to our clinical setting.”
A 2014 study reviewed 21 cancer trials to understand whether the patients in the trials were similar to real-world patients with respect to characteristics and survival.1 The researchers demonstrated that studies had an average of 16 eligibility criteria and the majority of the criteria were related to comorbidities and performance status.
However, patients with MM tend to be elderly and frail with a number of comorbidities, Davies said. As a result, these patients are not well represented in clinical trials and RCTs. In addition, a disproportionate number of patients from a lower socioeconomic class and who are racial/ethnic minorities are underrepresented in trials.
“So, I think that really illustrates why it's important to supplement our randomized control data with some of this real-world evidence,” she said.
In MM there are a number of registries and databases that collect data on patients, and they can be used to see, if RCTs were performed on the patients in the group, how many would actually meet the common eligibility criteria. Surprisingly, according to Davies, somewhere between 20% and 40% of the patients in these registries would not be eligible for many of the common RCTs.
There were some common patient and disease characteristics that result in many patients being ineligible. In addition to being elderly or frail, patients were deemed ineligible for studies looking at proteasome inhibitors (PIs) and immunomodulatory imide drugs if they had previously received those therapies. While that may make sense for the trial, it does not represent what happens in clinical practice, Davies pointed out.
Renal function is another area of eligibility that excludes a lot of patients, especially since the disease is characterized by renal impairment.
“So, there's actually quite a lot of reasons why patients can't make it into clinical trials—all very reasonable reasons—but also may not necessarily reflect our day-to-day clinical practice,” Davies said.
In the real-world setting, there are also many factors that need to be taken into account when making treatment decisions. The patient’s circumstances and their preferences both affect treatment feasibility. There could be patient-related factors, disease-related factors, and treatment-related factors that affect what treatment the patient wishes to be on.
Patient-related factors include the decision to take a more aggressive or intensive approach vs the desire to have less toxicity. Some patients may want an oral medication for convenience, while others prefer the intravenous medication. And the patient’s desire to keep working may also need to be factored in if there is a regimen that can fit around this.
Finally, there’s the financial burden, which Davies admitted is “one that we really don’t particularly like talking about.” There are direct costs of medicine but also indirect costs that need to be measured and taken into account when treating a patient.
In conclusion, she noted that there are now 2 sets of data that physicians need to use to decide the best treatment approach for an individual patient. Moving forward, real-world effectiveness data will be used to compliment RCT data.
“By taking both sets of data, we can really see some of the advantages and disadvantages of our treatment approaches, and really determine how well they're going to work in routine clinical practice,” Davies said.
Following Davies, Ajai Chari, MD, professor of medicine, director of clinical research in the Multiple Myeloma Program, and associate director of clinical research at Mount Sinai, reviewed outcomes of patients who were eligible for RCTs vs those who were ineligible.
Chari and his colleagues used electronic health record data on approximately 3000 patients in the United States with relapsed/refractory MM (RRMM) who had at least 2 lines of prior therapy.2 They reviewed 2 cohorts:
These cohorts were evaluated for their eligibility in ASPIRE, ROUMALINE-MM1, POLLUX, and ELOQUENT-2 for cohort 1 and ENDEAVOR and CASTOR for cohort 2. Chari and his colleagues found that 80.2% of the patients in cohort 1 and 53.0% of the patients in cohort 2 would have been ineligible for 1 or more of the trials.
Reasons for ineligibility included renal insufficiency, PI refractory, lenalidomide refractory, prior monoclonal antibody therapy, and comorbidities, such as other cancers, cardiac issues, and potentially infection.
The ineligible patients had a worse overall survival (OS), Chari pointed out. In cohort 1, the 3-year OS for ineligible patients was 63.5% vs 74.7% for the eligible patients. In cohort 2, the 3-year OS was 46.2% for ineligible patients vs 61.0% for eligible patients.
“So, this isn't just a matter of our patients are ineligible. The patients being excluded are actually adversely affected in terms of overall survival,” he said. In multiple studies, “the patients who were ineligible for the clinical trials have worse outcomes by either time-to-next therapy, overall survival, or progression.”
Patients with MM have cardiac issues, but these patients are excluded from trials, which makes it challenging to translate the results of a study to clinical practice. Renal insufficiency is another common feature associated with MM and can be a reason for ineligibility. However, OS and progression-free survival are worse for patients with renal insufficiency, Chari explained.
Overall, patient selection factors in clinical trials can have a significant impact on the outcomes of trials. Patients who are ineligible for trials can have worse outcomes than the patients in the trials, and yet clinicians are basing their treatment decisions for patients on the results of those trials, he said.
“I think the benefit of clinical trials that we see may not be routinely achievable in the real world,” Chari concluded.
1. Unger JM, Barlow WE, Martin DP, et al. Comparison of survival outcomes among cancer patients treated in and out of clinical trials. J Natl Cancer Inst. 2014;106(3):dju002. doi:10.1093/jnci/dju002
2. Chari A, Romanus D, Palumbo A, et al. Randomized clinical trial representativeness and outcomes in real-world patients: comparison of 6 hallmark randomized clinical trials of relapsed/refractory multiple myeloma. Clin Lymphoma Myeloma Leuk. 2020;20(1):8-17.e16. doi:10.1016/j.clml.2019.09.625