On Demand Webinar: Adaptive Multi-arm Multi-stage Clinical Trials
Register to access the replay of our webinar on Adaptive Multi-arm Multi-stage Clinical Trials, presented by Cytel's President & Co-Founder, Cyrus Mehta.
Multi-arm multi-stage adaptive trials compare several treatment arms to a common control arm over several stages. The treatment arms might originate within the same organization, or several organizations might each contribute a treatment arm to be tested on a common platform. At any stage treatment arms may be dropped either for overwhelming efficacy or futility. The sample sizes of the remaining arms, the number and spacing of the remaining stages and the alpha spending function may then be adaptively altered while nevertheless preserving strong control of the family wise error rate (FWER).
Two methods are available for designing trials that have such a high degree of flexibility.
The stage-wise MAMS approach was historically the first to be developed and remains the standard method for designing inferentially seamless phase II/III clinical trials. In this approach, at each stage, the data from each treatment comparison are summarized by a single multiplicity adjusted p-value. These stage-wise p-values are combined by a pre-specified combination function and the resultant test statistic is monitored with respect to the classical two-arm group sequential boundaries. The cumulative MAMS approach is a more recent development in which a separate test statistic is constructed for each treatment comparison from the cumulative data at each stage. These statistics are then monitored with respect to multiplicity adjusted group sequential boundaries.
In this talk I will introduce each method and discuss how they differ in their approach to FWER control. I will then demonstrate that the cumulative MAMS designs out-perform stage-wise MAMS and recommend that they replace the latter as the method of choice for designing multi-arm multi-stage adaptive designs. The methods will be applied to a multi-arm trial of heart failure in patients with reduced ejection fraction.
Cyrus Mehta is a prominent biostatistician, and Fellow of the American Statistical Association. He co-founded Cytel Inc. in 1987 along with Nitin Patel. Their shared vision was to make modern methods in statistics and operations research accessible to clinical researchers, by creating quality software for statistical analyses.
Cyrus's efforts helped establish Cytel as an industry leader in exact statistics, as well as in adaptive and group sequential methods. He remains a driving force behind Cytel’s East®, the industry standard software for trial design, simulation and monitoring.
Experience: As one of the world's leading experts on adaptive clinical trials, Cyrus regularly provides guidance and training to leading pharmaceutical companies, academic collaborators and FDA personnel. He has published more than 100 research articles in scientific journals including JASA, Biometrics, Biometrika, Circulation, The Lancet, The New England Journal of Medicine and Statistics in Medicine.
Cyrus is an adjunct professor of biostatistics at the Harvard T.H. Chan School of Public Health, and holds degrees from the Massachusetts Institute of Technology and the Indian Institute of Technology at Bombay. Cyrus has provided groundbreaking innovations in computational statistics for rare events and statistical design of adaptive trials. He and co-authors, Dr. Nitin Patel and Dr. Karim Hirji received the ASA's 1987 George W. Snedecor Award for best paper in biometry.
Research: Cyrus was a chief contributor to Cytel's development of permutational algorithms and their applications to categorical data analysis, nonparametric tests, power and sample size calculations, contingency tables analysis and, more generally to inference on the parameters in regression models for categorical data. The same algorithms make it computationally feasible to obtain accurate p-values, confidence intervals and sample-size designs for small or unbalanced data sets and sparse contingency tables. These advances have revolutionized general statistical practices.
His recent research focuses on developing group-sequential and adaptive trial methods and supporting software, including adaptive sample size re-estimation or “Promising Zone” designs.
Awards & Recognitions
- Distinguished Alumni Award from Indian Institute of Technology, Bombay (2016)
- Lifetime Achievement Award from the International Indian Statistics Association (2015)
- Zoroastrian Entrepreneur of the Year (2002)
- Received the George W. Snedecor Award from American Statistical Assoc. (1987)
- Fellow of the American Statistical Association (Elected)
- Member of the International Statistical Institute (Elected)
- Mostellar Statistician of the Year (Massachusetts Chapter of the American Statistical Association)