A design of phase II cancer trials using total and complete response endpoints.
Phase II clinical trials in oncology are used for initial evaluation of the therapeutic efficacy of a new treatment regimen. Simon's two-stage design based on total response (TR) rate is commonly used for such trials. Several authors have proposed alternative strategies to consider either response and toxicity or response and early progression. Because TR consists of both partial response (PR) and complete response (CR) and these two types of responses have different effects on subsequent patient outcome, Lin and Chen proposed a flexible design that is based on a weighted average of PR and CR rates as a way to recognize the differential significance of the two levels of response. Panageas and colleagues, on the other hand, used a trinomial model and direct search to consider a rejection region for PR and CR separately. In this paper, we reformat their hypotheses to assess efficacy based on TR and CR. A new two-stage optimum phase II trial design based on TR and CR is developed. We provide guides on searching the stopping and rejecting regions and on determining sample size. An example of a phase II trial for glioblastomas treatment is presented. In this trial, physicians would be interested in either stable disease (SD), PR, or CR as an indication of efficacy. However, because PR and CR rarely occur, observation of any PR or CR will lean towards acceptance of the treatment. Our design has the advantage of being close to the traditional Simon two-stage design while still having the flexibility to treat responses (PR and CR in this example) differently than SD.
Lu
Ying
Y
Biostatistics Core, UCSF Comprehensive Cancer Center, USA. ying.lu@radiology.ucsf.edu
Jin
Hua
H
Lamborn
Kathleen R
KR
D000970:Antineoplastic Agents / Q000627:therapeutic use; D001932:Brain Neoplasms / Q000188:drug therapy; D017322:Clinical Trials, Phase II as Topic / Q000379:methods*; D005909:Glioblastoma / Q000188:drug therapy; D006801:Humans; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D012107:Research Design
D000970:Antineoplastic Agents