Phase II clinical trial design for noncytotoxic anticancer agents for which time to disease progression is the primary endpoint.
Phase II evaluation is a critical screening step in the development of new cancer treatments. Historically, anticancer agents have been cytotoxic; they kill existing cells. As such, the primary endpoint for phase II evaluation has been tumor response rate, the percentage of patients whose tumors shrink > 50%. Biotechnology has led to promising new anticancer agents that are cytostatic. In contrast to cytotoxics, these agents modulate tumor environments and/or cellular targets and are expected to delay tumor growth. Phase II evaluation of such agents may instead focus on failure-time endpoints, such as time to disease progression. We examine a phase II trial design that evaluates clinical benefit by comparing sequentially measured paired failure times within each treated patient. Clinical efficacy is defined by a hazard ratio. Assuming patients eligible for a phase II study of a new cytostatic agent have failed previous cancer treatment, their most recent prior time to progression interval, TTP(1), is uncensored. Time to progression after the cytostatic agent, TTP(2), may or may not be censored at analysis. The design is motivated by a "growth modulation index" (TTP(2)/TTP(1)) and the proposition that a cytostatic agent be considered effective if the index is greater than 1.33. A chi(2) test statistic is employed to evaluate the paired failure-time data (TTP(1), TTP(2)). The degree of correlation between the paired failure times is a key feature of this design. Power of the test was evaluated through simulation of trials. Assuming a null hazard ratio equal to 1.0, a trial designed to detect an alternative hazard ratio equal to 1.3, based on accrual of 25 patients/year for 2 years (50 patients total) and with an additional 2 years of follow-up, has 25%, 46%, and 83% power based on correlations of 0.3, 0.5 and 0.7, respectively. These results demonstrate efficiency of the trial design, given moderate to strong correlations between paired failure times.
Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. rmick@cceb.upenn.edu
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Crowley
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Carroll
D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use*; D017322:Clinical Trials, Phase II as Topic / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D018450:Disease Progression; D015233:Models, Statistical; D012107:Research Design; D013997:Time Factors
D000970:Antineoplastic Agents