The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Recent Publication: A Gatekeeping Procedure to Test a Primary and a Secondary Endpoint in a Group Sequential Design with Multiple Interim Looks
A recent publication in Biometrics ‘A Gatekeeping Procedure to Test a Primary and a Secondary Endpoint in a Group Sequential Design with Multiple Interim Looks’ greatly extends the results of Glimm et al. ( 2010) and Tamhane et al ( 2010) which studied the problem of testing a primary and secondary endpoint, subject to a gatekeeping constraint, using a group sequential design (GSD) with K = 2 looks. This extends the methodology to provide for multiple (K>2) looks. The methodology is applied to the data from the RALES study (Pitt et al., 1999; Wittes et al., 2001).
The Global Cardiovascular Clinical Trialists Forum is a key event bringing together leading experts from across the spectrum of opinion leaders, clinical trialists, investigators, regulators, statisticians and practitioners to address the most pressing questions in cardiovascular clinical development today. At the December conference, eminent biostatisticians Cyrus Mehta and Stuart Pocock led a packed workshop tackling the advantages and limitations of adaptive designs within this space.
Following the recent publication of their review article Adaptive Designs for Clinical Trials in the New England Journal of Medicine, co-authors Cyrus Mehta ( President and Co-Founder of Cytel, and Adjunct Professor of Biostatistics at Harvard University) and Deepak L. Bhatt M.D C M.P.H. (Executive Director of Interventional Cardiovascular Programs, Brigham and Women’s Hospital Heart and Vascular Center) were invited to participate in a live video discussion with the journal.
'The aim of a discussion should not be victory but progress.'
This principle, expressed by the French essayist Joseph Joubert, applies effectively to the spirit of scientific debate. More specifically, within the clinical development space, the field of adaptive designs has seen its fair share of both discussion and progress. In this blog we’ll take a look at one debated area- the efficiency of Adaptive SSR designs.
One consideration every sponsor of a biomarker-stratified confirmatory trial must take into account, is whether to evaluate the biomarker subpopulation (S) against the rest of the population (S') or against the full population (F).
Mathematically, one would think this makes very little difference as F is partitioned into S and S'. If the null hypothesis is rejected for both S and S' then clearly it is rejected for F too. Similarly, if it is rejected for S and not for S' then the therapy is effective for the biomarker subpopulation, and ineffective for the rest of the population.
As it turns out, whether or not a given biomarker is indeed a predictive biomarker should affect the choice of statistical methodology in time-to-event trials.
Inference on Confidence Intervals for Adaptive Designs: The Latest Breed of Adaptive Clinical Trials
Most people familiar with adaptive clinical trial designs are familiar with those statistical designs that reject the null hypothesis. These include now familiar designs like the promising zone design and the adaptive switch design.
A newer breed of adaptive designs, however, aims to apply adaptation techniques to confidence intervals.
Why You Should Not Power for Superiority Upfront: Promising Zone Clinical Trials with "Adaptive Switch"
Powering a trial for superiority can be financially risky. In some instances it may also prove unnecessary.
Cytel President and co-founder Cyrus Mehta has co-authored a paper on Infantile Hemangioma, recently published in the New England Journal of Medicine. The successful study was designed as an adaptive confirmatory dose-response which confirmed that 3mg per kilogram per day of propranolol for 6 months is an effective resolution for hemangioma.
Cardiovascular outcome trials (CVOTs) have earned the reputation of being the untamable behemoths of the clinical world. Needless to say these trials are long and require extremely large sample-sizes. The Contrave LIGHT study required 8900 patients. The SAVOR TIMI trial enrolled 16,492 patients. Even the EXAMINE trial, which benefited from a promising zone design, required 650 patients.
However, since the explosive controversy over the FDA’s conditional approval of anti-obesity drug Contrave four years ago, there is much we have learned about how to make these trials shorter while also diminishing the financial risks of investing in them. For example, one of our clients managed to shorten the expected study length of an a CVOT by two years using a four point MACE Assessment (see below).
In this post, we explore some of the lessons we have learned when designing these large-scale clinical trials.