{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T00:31:28Z","timestamp":1776385888889,"version":"3.51.2"},"reference-count":27,"publisher":"Wiley","issue":"28-30","license":[{"start":{"date-parts":[[2025,12,14]],"date-time":"2025-12-14T00:00:00Z","timestamp":1765670400000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>In confirmatory clinical trials with a time\u2010to\u2010event endpoint, the timing of the analysis is often determined based on the observed number of events. In such event\u2010driven trials, the analysis timing is inherently uncertain, making its accurate prediction crucial for optimizing trial costs, personnel allocation, and resource management. Although various methods for predicting analysis timing have been extensively studied under different assumptions, these approaches predominantly rely on data pertaining to the primary endpoint when estimating the time\u2010to\u2010event distribution. To the best of our knowledge, no existing method incorporates longitudinally measured data, such as prostate\u2010specific antigen (PSA) levels in prostate cancer trials. We developed a method for predicting analysis timing within the framework of dynamic prediction using joint models that account for longitudinally measured covariates and time\u2010to\u2010event outcomes. Furthermore, we assessed the prediction performance by comparing it against two alternative methods based on the degree of covariate data: (1) a method without covariates, (2) a method using only baseline covariates, and (3) the proposed method using baseline and longitudinally measured covariates. Numerical experiments demonstrated that the proposed method enhances the accuracy of analysis timing predictions compared with methods that do not utilize longitudinally measured covariates. The proposed method is valuable for accurately predicting analysis timing when longitudinally measured covariates are available.<\/jats:p>","DOI":"10.1002\/sim.70312","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T05:51:24Z","timestamp":1765777884000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Dynamic Prediction of Analysis Timing in Clinical Trials Using Joint Models of Longitudinal and Time\u2010to\u2010Event Data"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3734-6203","authenticated-orcid":false,"given":"Ryunosuke","family":"Machida","sequence":"first","affiliation":[{"name":"Biostatistics Division, Center for Research Administration and Support National Cancer Center  Tokyo Japan"},{"name":"Department of Information and Computer Technology, Graduate School of Engineering Tokyo University of Science  Tokyo Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4443-9993","authenticated-orcid":false,"given":"Kentaro","family":"Sakamaki","sequence":"additional","affiliation":[{"name":"Faculty of Health Data Science Juntendo University  Chiba Japan"},{"name":"Center for Next Generation of Community Health Chiba University Hospital  Chiba Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9630-5882","authenticated-orcid":false,"given":"Tomohiro","family":"Ohigashi","sequence":"additional","affiliation":[{"name":"Department of Information and Computer Technology, Faculty of Engineering Tokyo University of Science  Tokyo Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9857-5819","authenticated-orcid":false,"given":"Takashi","family":"Sozu","sequence":"additional","affiliation":[{"name":"Department of Information and Computer Technology, Faculty of Engineering Tokyo University of Science  Tokyo Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,12,14]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/68.1.316"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780010204"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.843"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8911"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2956"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610926.2011.581189"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/pst.271"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cct.2011.05.013"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1080\/10543400600609445"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cct.2015.07.010"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cct.2015.11.008"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/pst.1732"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.201700083"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2021.12426"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1201\/b12208"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781118032985"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-022-01709-3"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2059"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2009.01273.x"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asm087"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5823"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.9713"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v035.i09"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdu141"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10147-025-02766-6"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/hep.1840200120"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v097.i03"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.70312","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/sim.70312","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.70312","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T00:58:43Z","timestamp":1775869123000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.70312"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":27,"journal-issue":{"issue":"28-30","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["10.1002\/sim.70312"],"URL":"https:\/\/doi.org\/10.1002\/sim.70312","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"value":"0277-6715","type":"print"},{"value":"1097-0258","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"2025-03-13","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-27","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-12-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70312"}}