{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T15:57:19Z","timestamp":1747151839078,"version":"3.40.5"},"reference-count":26,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T00:00:00Z","timestamp":1690329600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmaceutical Statistics"],"published-print":{"date-parts":[[2023,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>There is considerable debate surrounding the choice of methods to estimate information fraction for futility monitoring in a randomized non\u2010inferiority maximum duration trial. This question was motivated by a pediatric oncology study that aimed to establish non\u2010inferiority for two primary outcomes. While non\u2010inferiority was determined for one outcome, the futility monitoring of the other outcome failed to stop the trial early, despite accumulating evidence of inferiority. For a one\u2010sided trial design for which the intervention is inferior to the standard therapy, futility monitoring should provide the opportunity to terminate the trial early. Our research focuses on the Total Control Only (TCO) method, which is defined as a ratio of observed events to total events exclusively within the standard treatment regimen. We investigate its properties in stopping a trial early in favor of inferiority. Simulation results comparing the TCO method with alternative methods, one based on the assumption of an inferior treatment effect (TH0), and the other based on a specified hypothesis of a non\u2010inferior treatment effect (THA), were provided under various pediatric oncology trial design settings. The TCO method is the only method that provides unbiased information fraction estimates regardless of the hypothesis assumptions and exhibits a good power and a comparable type I error rate at each interim analysis compared to other methods. Although none of the methods is uniformly superior on all criteria, the TCO method possesses favorable characteristics, making it a compelling choice for estimating the information fraction when the aim is to reduce cancer treatment\u2010related adverse outcomes.<\/jats:p>","DOI":"10.1002\/pst.2327","type":"journal-article","created":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T03:49:55Z","timestamp":1690429795000},"page":"1031-1045","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Information fraction estimation: Strategies for a phase 3 non\u2010inferiority maximum duration design with time to event outcome"],"prefix":"10.1002","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0711-3783","authenticated-orcid":false,"given":"Ha M.","family":"Dang","sequence":"first","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles California USA"},{"name":"Children's Oncology Group  Monrovia California USA"},{"name":"Biostatistics, Programming, and Data Management Johnson &amp; Johnson Medical Devices Companies  Irvine California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark D.","family":"Krailo","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles California USA"},{"name":"Children's Oncology Group  Monrovia California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Todd A.","family":"Alonzo","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles California USA"},{"name":"Children's Oncology Group  Monrovia California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wendy J.","family":"Mack","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John A.","family":"Kairalla","sequence":"additional","affiliation":[{"name":"Children's Oncology Group  Monrovia California USA"},{"name":"Department of Biostatistics, Colleges of Medicine, Public Health and Health Professions University of Florida  Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,7,26]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.seminoncol.2008.07.008"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.20.02730"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1201\/9780367805326"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdx788"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1201\/b11039"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1177\/1740774511401636"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/009286150103500408"},{"volume-title":"Statistical Monitoring of Clinical Trials: A Unified Approach","year":"2006","author":"Proschan MA","key":"e_1_2_10_9_1"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.2307\/2532999"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.201900236"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.2307\/2532094"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780081003"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610929408831263"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1177\/1740774516644752"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12561-009-9004-3"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1997.10473655"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.2307\/2531632"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12561-010-9027-9"},{"volume-title":"Sample Size for Group\u2010Sequential Tests in PASS","year":"2022","author":"PASS 2022","key":"e_1_2_10_20_1"},{"volume-title":"SAS\/STAT 15.2 User's Guide the SEQDESIGN Procedure","year":"2020","author":"SAS\/STAT 15.2 User's Guide","key":"e_1_2_10_21_1"},{"key":"e_1_2_10_22_1","unstructured":"WassmerG PahlkeF.rpact: Confirmatory Adaptive Clinical Trial Design and Analysis. 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