Bayesian sequential monitoring strategies for trials of digestive cancer therapeutics.

Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE

Original Publication: London : BioMed Central, [2001-

Bayes Theorem* ; Research Design*; Humans ; Clinical Trials, Phase II as Topic/methods ; Digestive System Neoplasms/drug therapy ; Immunotherapy/methods ; Antineoplastic Agents/therapeutic use ; Computer Simulation

Background: New therapeutics in oncology have presented challenges to existing paradigms and trial designs in all phases of drug development. As a motivating example, we considered an ongoing phase II trial planned to evaluate the combination of a MET inhibitor and an anti-PD-L1 immunotherapy to treat advanced oesogastric carcinoma. The objective of the paper was to exemplify the planning of an adaptive phase II trial with novel anti-cancer agents, including prolonged observation windows and joint sequential evaluation of efficacy and toxicity.
Methods: We considered various candidate designs and computed decision rules assuming correlations between efficacy and toxicity. Simulations were conducted to evaluate the operating characteristics of all designs.
Results: Design approaches allowing continuous accrual, such as the time-to-event Bayesian Optimal Phase II design (TOP), showed good operating characteristics while ensuring a reduced trial duration. All designs were sensitive to the specification of the correlation between efficacy and toxicity during planning, but TOP can take that correlation into account more easily.
Conclusions: While specifying design working hypotheses requires caution, Bayesian approaches such as the TOP design had desirable operating characteristics and allowed incorporating concomittant information, such as toxicity data from concomitant observations in another relevant patient population (e.g., defined by mutational status).
(© 2024. The Author(s).)

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Keywords: Adaptive design; Bayesian; Oncology; Phase II

0 (Antineoplastic Agents)

Date Created: 20240719 Date Completed: 20240719 Latest Revision: 20240719

20240720

10.1186/s12874-024-02278-3

39030498