Estimation of progression-free survival for all treated patients in the randomized discontinuation trial design

Theodore G. Karrison, Mark J. Ratain, Walter M. Stadler, Gary L. Rosner

Research output: Contribution to journalArticlepeer-review

Abstract

The randomized discontinuation trial (RDT) design is an enrichment-type design that has been used in a variety of diseases to evaluate the efficacy of newtreatments. TheRDTdesign seeks to select a more homogeneous group of patients, consisting of those who are more likely to show a treatment benefit if one exists. In oncology, the RDT design has been applied to evaluate the effects of cytostatic agents, that is, drugs that act primarily by slowing tumor growth rather than shrinking tumors. In the RDT design, all patients receive treatment during an initial, open-label run-in period of duration T. Patients with objective response (substantial tumor shrinkage) remain on therapy while those with early progressive disease are removed from the trial. Patients with stable disease (SD) are then randomized to either continue active treatment or switched to placebo. The main analysis compares outcomes, for example, progression-free survival (PFS), between the two randomized arms. As a secondary objective, investigators may seek to estimate PFS for all treated patients, measured from the time of entry into the study, by combining information from the run-in and post run-in periods. For t ≤ T, PFS is estimated by the observed proportion of patientswho are progression-free among all patients enrolled. For t > T, the estimate can be expressed as Ŝ (t) = p̂ OR × Ŝ OR(t-T) + p̂ SD × Ŝ SD(t - T), where p OR is the estimated probability of response during the run-in period, p̂ SD is the estimated probability of SD, and Ŝ OR(t - T) and Ŝ SD(t - T) are the Kaplan-Meier estimates of subsequent PFS in the responders and patients with SD randomized to continue treatment, respectively. In this article, we derive the variance of Ŝ(t), enabling the construction of confidence intervals for both S(t) and the median survival time. Simulation results indicate that the method provides accurate coverage rates. An interesting aspect of the design is that outcomes during the run-in phase have a negative multinomial distribution, something not frequently encountered in practice.

Original languageEnglish (US)
Pages (from-to)155-162
Number of pages8
JournalAmerican Statistician
Volume66
Issue number3
DOIs
StatePublished - Nov 2 2012

Keywords

  • Confidence limits
  • Enrichment design
  • Negative multinomial distribution
  • Phase ii clinical trials

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Statistics, Probability and Uncertainty

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