{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T21:22:20Z","timestamp":1790544140654,"version":"4.1.0"},"reference-count":67,"publisher":"Wiley","issue":"18","license":[{"start":{"date-parts":[[2024,6,6]],"date-time":"2024-06-06T00:00:00Z","timestamp":1717632000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2024,8,15]]},"abstract":"<jats:p>Adaptive randomized clinical trials are of major interest when dealing with a time\u2010to\u2010event outcome in a prolonged observation window. No consensus exists either to define stopping boundaries or to combine  values or test statistics in the terminal analysis in the case of a frequentist design and sample size adaptation. In a one\u2010sided setting, we compared three frequentist approaches using stopping boundaries relying on \u2010spending functions and a Bayesian monitoring setting with boundaries based on the posterior distribution of the log\u2010hazard ratio. All designs comprised a single interim analysis with an efficacy stopping rule and the possibility of sample size adaptation at this interim step. Three frequentist approaches were defined based on the terminal analysis: combination of stagewise statistics (Wassmer) or of  values (Desseaux), or on patientwise splitting (J\u00f6rgens), and we compared the results with those of the Bayesian monitoring approach (Freedman). These different approaches were evaluated in a simulation study and then illustrated on a real dataset from a randomized clinical trial conducted in elderly patients with chronic lymphocytic leukemia. All approaches controlled for the type I error rate, except for the Bayesian monitoring approach, and yielded satisfactory power. It appears that the frequentist approaches are the best in underpowered trials. The power of all the approaches was affected by the violation of the proportional hazards (PH) assumption. For adaptive designs with a survival endpoint and a one\u2010sided alternative hypothesis, the Wassmer and J\u00f6rgens approaches after sample size adaptation should be preferred, unless violation of PH is suspected.<\/jats:p>","DOI":"10.1002\/sim.10130","type":"journal-article","created":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T03:31:54Z","timestamp":1717731114000},"page":"3364-3382","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Two\u2010stage randomized clinical trials with a right\u2010censored endpoint: Comparison of frequentist and Bayesian adaptive designs"],"prefix":"10.1002","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7767-9483","authenticated-orcid":false,"given":"Luana","family":"Boumendil","sequence":"first","affiliation":[{"name":"INSERM U1153, Team ECSTRRA H\u00f4pital Saint Louis  Paris France"},{"name":"Universit\u00e9 Paris Cit\u00e9  Paris 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