Subscribe to RSS
DOI: 10.3414/ME10-01-0037
Optimal Two-stage Designs for Single-arm Phase II Oncology Trials with Two Binary Endpoints
Publication History
received:
12 May 2010
accepted:
08 July 2010
Publication Date:
18 January 2018 (online)
Summary
Objectives: In phase II clinical trials in oncology, the potential efficacy of a new treatment regimen is assessed in terms of anticancer activity. The standard approach consists of a single-arm two-stage design where a single binary endpoint is compared to a specified target value. However, a new drug would still be considered promising if it showed a lower tumor response rate than the target level but would lead, for example, to disease stabilization.
Methods: We present an analytical solution for the calculation of the type I and type II error rate for a two-stage design where the hypothesis test considers two endpoints and provide optimal and minimax solutions. Furthermore, the problem of inference about the two single endpoints following rejection of the global null hypothesis is addressed by deriving a multiple test procedure that controls the experimentwise type I error rate in the strong sense.
Results: The proposed methods are illustrated with a real data example, and the new design is tabulated for a wide range of parameter values. Similar to two-stage designs with a single endpoint, the characteristics of optimal and minimax designs with two endpoints with respect to expected and maximum sample size can be quite different. Therefore, the choice of an admissible design may be a valuable compromise.
Conclusions: The new procedure extends Simon’s two-stage design to two endpoints. This approach allows a more comprehensive assessment of the overall picture of antitumor efficacy of a new treatment than restriction to a single outcome.
-
References
- 1 Booth CM, Calvert AH, Giaccone G, Lobbezoo MW, Eisenhauer EA, Seymour LK. on behalf of the Task Force on Methodology for the Development of Innovative Cancer Therapies. Design and conduct of phase II studies of targeted anticancer therapy: recommendations from the task force on methodology for the development of innovative cancer therapies (MDICT). European Journal of Cancer 2008; 44: 25-29.
- 2 Retain MJ, Sargent DJ. Optimising the design of phase II oncology trials: the importance of randomization. European Journal of Cancer 2009; 45: 275-280.
- 3 Simon R. Optimal two-stage designs for phase II clinical trials. Controlled Clinical Trials 1989; 10: 1-10.
- 4 Chang MN, Therneau TM, Wieand HS, Cha SS. Designs for group sequential phase II clinical trials. Biometrics 1987; 43: 865-874.
- 5 Shuster J. Optimal two-stage designs for single arm phase II cancer trials. Journal of Biopharmaceutical Statistics 2002; 12: 39-51.
- 6 Jung SH, Lee T, Kim KM, George SL. Admissible two-stage designs for phase II cancer clinical trials. Statistics in Medicine 2004; 23: 561-569.
- 7 Chen TT. Optimal three-stage designs for phase II cancer clinical trials. Statistics in Medicine 1997; 16: 2701-2711.
- 8 Jones CL, Holmgren E. An adaptive Simon Two-Stage Design for Phase 2 studies of targeted therapies. Contemporary Clinical Trials 2007; 28: 654-661.
- 9 Lin X, Allred R, Andrews G. A two-stage phase II trial design utilizing both primary and secondary endpoints. Pharmaceutical Statistics 2008; 7: 88-92.
- 10 Therasse P, Arbuck SG, Eisenhauser EA, Wanders J, Kaplan RS, Rubinstein L, Verweij J, Van Glabbeke M, van Oosterom AT, Christian MC, Gwyther SG. New guidelines to evaluate the response to treatment in solid tumours. Journal of the National Cancer Institute 2000; 92: 205-216.
- 11 Jung SH, Carey M, Kim KM. Graphical search for two-stage designs for phase II clinical trials. Controlled Clinical Trials 2001; 22: 367-372.
- 12 Marcus R, Peritz E, Gabriel KR. On closed testing procedures with special reference to ordered analysis of variance. Biometrika 1976; 63: 655-660.
- 13 Bauer P. Multiple testing in clinical trials. Statistics in Medicine 1991; 10: 871-890.
- 14 Gabriel KR. Simultaneous test procedures – some theory of multiple comparisons. The Annals of Mathematical Statistics 1969; 40: 224-250.
- 15 Sonnemann E. General solutions to multiple testing problems. Biometrical Journal 2008; 50: 641-656 (preface by Finner H 640).
- 16 Lin S, Chen T. Optimal two-stage designs for phase II trials with differentiation of complete and partial responses. Communications in Statistics – Theory and Methods 1998; 29: 923-940.
- 17 Panageas K. An optimal two-stage phase II design utilizing complete and partial response information separately. Controlled Clinical Trials 2002; 23: 367-379.
- 18 Lu Y, Jin H, Lamborn KR. A design of phase II cancer trials using total and complete response endpoints. Statistics in Medicine 2005; 24: 3155-3170.