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Phase II clinical trial design for noncytotoxic anticancer agents for which time to disease progression is the
R Mick1, J J Crowley, R J Carroll
1Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. rmick@cceb.upenn.edu
Abstract:
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.
Insights
This study introduces a new Phase II trial design for cytostatic cancer agents, focusing on time to disease progression. The design efficiently evaluates clinical benefit by comparing paired failure times, showing promise for new cancer treatment development.
Area of Science:
- Oncology
- Clinical Trial Design
- Biostatistics
Background:
- Phase II evaluations are crucial for new cancer treatments.
- Cytotoxic agents historically focused on tumor response rate.
- New cytostatic agents, modulating tumor environments, require different evaluation endpoints like time to progression.
Purpose of the Study:
- To examine a novel Phase II trial design for cytostatic anticancer agents.
- To evaluate clinical efficacy using paired failure times (time to progression).
- To assess the effectiveness of a cytostatic agent based on a growth modulation index > 1.33.
Main Methods:
- Comparing sequentially measured paired failure times within individual patients.
- Utilizing time to progression (TTP(1) and TTP(2)) as endpoints.
- Employing a chi-squared test statistic to analyze paired failure-time data.
Main Results:
- The proposed trial design demonstrates efficiency, particularly with moderate to strong correlations between paired failure times.
- Simulations show varying statistical power (25%-83%) based on correlation levels (0.3-0.7) for detecting a hazard ratio of 1.3.
- The design is effective for evaluating cytostatic agents where growth delay, not cell death, is the primary mechanism.
Conclusions:
- The novel Phase II trial design is efficient for evaluating cytostatic cancer therapies.
- This approach offers a robust method for assessing clinical benefit by focusing on failure-time endpoints.
- The design supports the development of targeted therapies by accurately measuring treatment efficacy through growth modulation.