Dose-finding design and benchmark for a right censored endpoint. Issue 6 (1st November 2020)

• Record Type: Journal Article
• Authors: Andrillon, Anaïs; Chevret, Sylvie; Lee, Shing M; Biard, Lucie
• Is Part Of: Journal of biopharmaceutical statistics. Volume 30:Issue 6(2020)
• Page Start: 948
• Page End: 963
• Publication Date: 2020-11-01
• Subjects: Dose-finding -- survival data -- late-onset toxicity -- competing risks -- treatment discontinuation -- benchmark; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2020.1821702
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Dose-finding trials aim to determine a safe dose to be tested in larger trials for efficacy. In oncology, designs generally assume conventional monotonic increasing dose-toxicity relationships, mostly with binary outcomes (e.g., dose-limiting toxicity or not), measured in the first cycle of therapy or for a fixed number of cycles. However, with new anti-cancer agents such as molecularly targeted therapies and immunotherapies, late-onset toxicities have become more frequent. Designs with prolonged observation windows and censored endpoints analyzed using survival models, appear particularly suited to these settings. Moreover, in this setting, the observation of the late-onset toxicity endpoint could be precluded by trial discontinuation due to death, progression, patient withdrawal, or physician discretion, defining a competing event to toxicity. We propose extensions of the Continual Reassessment Method (CRM) dose-finding design using survival working models for right-censored endpoints and for handling treatment discontinuation in the toxicity observation window, namely the Survival-CRM (Surv-CRM) and the informative survival-CRM (iSurv-CRM). We also developed a benchmark approach for its evaluation. In a simulation study, we compared the performance of the Surv-CRM and iSurv-CRM, to those of the Time-to-event (TITE)-CRM and the nonparametric benchmark. The performance of the proposed methods was consistent with the complexity of scenarios as assessed by the nonparametric benchmark. Without treatment discontinuations, the Surv-CRM provides proportions of correct dose selection close to those of the TITE-CRM with fewer observed toxicities and patients assigned to overtoxic dose levels. In the presence of treatment discontinuation, the iSurv-CRM outperforms the TITE-CRM in identifying the correct dose level.