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Novel designs for multi‐arm clinical trials with survival outcomes with an application in ovarian cancer
Author(s) -
Royston Patrick,
Parmar Mahesh K. B.,
Qian Wendi
Publication year - 2003
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1430
Subject(s) - outcome (game theory) , computer science , clinical trial , randomized controlled trial , research design , bootstrapping (finance) , surrogate endpoint , sample size determination , medicine , statistics , econometrics , surgery , mathematics , mathematical economics
With the increasing pace of drug development, it is not unusual for several promising treatment regimens to be ready simultaneously for testing in a randomized phase III setting. Various limiting factors, including the time needed to transfer research results to clinical practice and a narrow ‘window of opportunity’, may make it unfeasible to perform trials to test such regimens sequentially against a control treatment in a traditional two‐arm parallel group design. We present an approach to trial design based on eliminating inferior contenders at an early stage, allowing through to a second stage only treatments that show a predefined degree of advantage against a control treatment. The first stage of testing utilizes a marker known to be a valid intermediate outcome measure or surrogate for the definitive outcome. The experimental arms are compared pairwise with control according to this intermediate outcome measure. Arms that survive the comparison enter a second stage of patient accrual culminating in comparisons against control on the outcome measure of primary interest. We show how the design may be realized in practice by considering hypothetically distinct trials at stages 1 and 2, each with their own operating characteristics. The overall operating characteristics are computed from the stage 1 and 2 size and power and the correlation between the treatment effects on the intermediate and primary outcome measures according to a bivariate Normal approximation. The correlation is estimated by bootstrapping individual patient data from previous trials. We illustrate the general approach in a design of a real trial of four new chemotherapy regimens for advanced ovarian cancer. The intermediate outcome measure is progression‐free survival. An international randomized controlled trial using the new design is already under way. Copyright © 2003 John Wiley & Sons, Ltd.