Phase II trials powered to detect tumor subsets through the application of predictive markers.
Authors: John D. Roberts, V. Ramakrishnan
Journal: Clinical Cancer Research (2006)

B44   Classical phase II trial designs assume a patient population with a homogeneous tumor type and yield an estimate of a stochastic probability of tumor response. Clinically, however, oncology is moving towards tumor subtyping based upon predictive markers. For a given phase II trial predictive markers may be defined prospectively (on the basis of previous results) or identified retrospectively on the basis of analysis of responding and non-responding tumors. Retrospective analysis has the advantages that the analysis can be supervised by grouping responding and non-responding tumors; and multiple hypotheses, including hypotheses not formulated at the time of trial design, can be tested. We propose a phase II trial design in which a trial is powered to detect the presence of responding subset(s) as identified either prospectively or retrospectively by predictive markers. Relevant parameters in such a design include the prevalence of the smallest subset of interest, the hypothesized response rate within that subset, the expected total response rate, and the targeted probabilities of type I and II errors (α and β). Extensions of this design to simultaneous or sequential multiple subtyping and imperfect assays for predictive markers will also be considered. Sample size calculations for different scenarios will be presented. The methods could be used to design phase II trials or to provide estimates of the utility of markers of a given presumed predictive power. An implication of this approach is that phase II trials based upon classical designs are too small. On the other hand, trials involving reasonable numbers of patients must target relatively high threshold response rates within tumor subsets.Two examples from the recent literature:(1) In a retrospective analysis of tumors from patients with non-small cell lung cancer treated with the epidermal growth factor receptor (EGFR)-targeted agent, gefitinib, Lynch et al (NEJM 350:2129) discovered a new set of mutations of the EGFR that conferred sensitivity to gefitinib. Within a sample of 275 patients, the response rate to gefitinib was 9%. Among the subset of patients with tumor samples available for analysis, 8 of 9 patients with novel EGFR mutations experienced a response, whereas in an independent sample of non-small cell lung cancers the prevalence of EGFR mutation was 8%. Using our proposed method, the minimum sample size for a phase II trial targeted to identify a tumor subset with a prevalence of 8%, a hypothesized response rate in EGFR mutated type of 50% and an expected total response rate of 20% is 63 (5% α, 80% power).(2) A recently reported phase II trial tested the activity of tipifinib in melanoma according to a classical phase II design (Gajewski et al, J Clin Oncol, 24, Proc ASCO, abstract 8014). No responses were seen in the first 14 patients and the study was closed. Tipifinib is targeted to N-RAS, which is mutated in about 20% of melanomas. To test the hypothesis that the response rate to tipifinib in N-RAS mutated melanoma is 100%, assuming the prevalence of N-RAS in melanoma is 20%, a sample of 14 patients has 97% power (5% α). On the other hand, to test the hypothesis that the response rate to tipifinib in N-RAS mutated melanoma is 50% (a response rate we would consider of interest) and the expected total response rate is 20%, a sample of 14 patients has only a 12% power. Using our proposal, to achieve a minimum acceptable power of 80%, the minimum sample size required is 79, assuming a mutated N-RAS subset prevalence of 20%, a hypothesized response rate within this subset of 50%, and a total response rate of 30%.