28 Jan Improving Adjuvant Clinical Trials By Including Only Patients For Whom Current Therapies Do Not Work Well
MedicalResearch.com Interview with:
Dr. Pusztai
Lajos Pusztai, M.D, D.Phil.
Professor of Medicine
Director of Breast Cancer Translational Research
Co-Director of the Yale Cancer Center Genetics, Genomics and Epigenetics Program
Yale School of Medicine
New Haven, CT 06511
MedicalResearch.com: What is the background for this study?
Response: Overall, about 85% of newly diagnosed stage I-III breast cancer patients will not die of their disease, and this roughly equates to an 85% cure rate. Of course cure rates are higher for stage I cancers and lower for stage III cancers. An 85% overall cure rate is good but not good enough, we continuously try to develop new therapies hoping to push these rates to 90%…,95%…etc. However, it is not possible to cure a patient twice over. For example, if surgery plus endocrine therapy cures all patients, the addition of chemotherapy cannot improve on it no matter how effective it is. If surgery plus endocrine therapy cures 95%, adding the perfect chemo to this treatment can only bring about a 5% improvement, and very good chemo that would push cure from 95% to 97%, would require a very large trial including many thousands of patients.
This is an increasingly common scenario in modern breast cancer adjuvant trials (where the goal is to improve survival and cure); the control arm that receives the current standard of care invariably does better than expected and the experimental arm only improves outcome by 1-3% that does not reach statistical significance. The painful conclusion from these trials is that we do not know if the new drug actually works or not because there were not enough events to demonstrate an effect.
Of course, a lot of patients in the study were also exposed to a new drug with all of its associated toxicities who could not possibly benefit from it.
MedicalResearch.com: What are the main findings?
Response: Our idea is very simple, select patients for adjuvant clinical trial only if their risk for cancer recurrence with current best therapies is higher than a prespecified risk, say 10% or 15% (or any number you would want to pick). This would ensure that 10-15% of the trial participants indeed experience an event and therefore the power of the study to show benefit from the new drug is adequate. This also implies that we include patients who actually need new therapies and exclude most of those who are cured with current therapies.
The current method for patient selection to adjuvant clinical trials is based on setting a threshold for tumor size or having a positive lymph node as eligibility criteria that provide very imprecise estimate of risk of recurrence. We show in the paper that it is possible to use validated multivariate risk calculators that take into account all the important variables that determine outcome (e.g. size of the tumor, number of cancerous lymph nodes, histologic features, benefit from each standard of care treatment modality surgery, endocrine therapy, chemotherapy that is planned for a patient), combine these variables with a mathematically correct weight into a single recurrence risk number. When we use a minimum risk from this model as selection criteria for trial eligibility we end up with more informative trials that yield conclusive results much more frequently than our current method of selecting patients. We show these in simulated trials using parameters from actual ongoing trials.
MedicalResearch.com: What should readers take away from your report?
Response: We propose a simple and practical method to make adjuvant clinical trials more effective by including only patients for whom current therapies do not work very well. Multivariate statistical models can identify patients who have excellent chance for cure with existing therapies and can also identify those who need new advances to improve their chance of cure, we want to include this later group in trials.
MedicalResearch.com: What recommendations do you have for future research as a result of this work?
Response: We hope that companies and clinical trial groups will adopt our method to define eligibility for future adjuvant tirals.
Any disclosures?
None of the authors have any financial or other conflict of interest, but we all have vested personal interest in increasing the efficiency of clinical trials.
Citations:
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Last Updated on January 28, 2018 by Marie Benz MD FAAD