{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T21:43:02Z","timestamp":1773006182991,"version":"3.50.1"},"reference-count":26,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA253910"],"award-info":[{"award-number":["CA253910"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Biometrical J"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Evaluating the performance of a prediction model is a common task in medical statistics. Standard accuracy metrics require the observation of the true outcomes. This is typically not possible in the setting with time\u2010to\u2010event outcomes due to censoring. Interval censoring, the presence of time\u2010varying covariates, and competing risks present additional challenges in obtaining those accuracy metrics. In this study, we propose two methods to deal with interval censoring in a time\u2010varying competing risk setting: a model\u2010based approach and the inverse probability of censoring weighting (IPCW) approach, focusing on three key time\u2010dependent metrics: area under the receiver\u2010operating characteristic curve, Brier score, and expected predictive cross\u2010entropy. The evaluation is conducted over a medically relevant time interval of interest, . The model\u2010based approach includes all subjects in the risk set, using their predicted risks to contribute to the accuracy metrics. In contrast, the IPCW approach only considers the subset of subjects who are known to be event\u2010free or experience the event within the interval of interest. We performed a simulation study to compare the performance of the two approaches with regard to the three metrics. Furthermore, we demonstrated the three metrics using the two approaches on an example prostate cancer surveillance cohort. Risk predictions were generated from a joint model handling the interval\u2010censored cancer progression and the competing event, early treatment, and repeatedly measured\u00a0biomarkers.<\/jats:p>","DOI":"10.1002\/bimj.70108","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T11:53:07Z","timestamp":1767613987000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Time\u2010Dependent Predictive Accuracy Metrics in the Context of Interval Censoring and Competing Risks"],"prefix":"10.1002","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9823-2613","authenticated-orcid":false,"given":"Zhenwei","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Biostatistics Erasmus Medical Center Rotterdam Rotterdam the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9397-0900","authenticated-orcid":false,"given":"Dimitris","family":"Rizopoulos","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics Erasmus Medical Center Rotterdam Rotterdam the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lisa F.","family":"Newcomb","sequence":"additional","affiliation":[{"name":"Cancer Prevention Program, Public Health Sciences Fred Hutchinson Cancer Center Seattle Washington USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicole S.","family":"Erler","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics Erasmus Medical Center Rotterdam Rotterdam the Netherlands"},{"name":"Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht Utrecht University Utrecht the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X18801312"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5958"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12232"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520\u20100493(1950)078<0001:VOFEIT>2.0.CO;2"},{"key":"e_1_2_9_6_1","unstructured":"Commenges D.2015. \u201cInformation Theory and Statistics: An Overview.\u201d Preprint arXiv November 3.https:\/\/arxiv.org\/abs\/1511.00860."},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541\u20100420.2012.01753.x"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12874\u2010020\u201001100\u20100"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.200610301"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097\u20100258(19960229)15:4<361::AID\u2010SIM168>3.0.CO;2\u20104"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006\u2010341X.2000.00337.x"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006\u2010341X.2005.030814.x"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280214531691"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6133"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.publhealth.18.1.83"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.juro.2015.08.087"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.10010"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541\u20100420.2009.01375.x"},{"key":"e_1_2_9_19_1","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/978-3-030-16399-0","volume-title":"Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating","author":"Steyerberg E. W.","year":"2019"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0b013e3181c30fb2"},{"key":"e_1_2_9_21_1","unstructured":"Tsouprou S.2015. \u201cMeasures of Discrimination and Predictive Accuracy for Interval Censored Survival Data.\u201d.https:\/\/api.semanticscholar.org\/CorpusID:43482073."},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jspi.2008.06.006"},{"key":"e_1_2_9_23_1","unstructured":"Yang Z. D.Rizopoulos E. A. M.Heijnsdijk L. F.Newcomb andN. S.Erler.2024. \u201cA Bayesian Joint Modelling for Misclassified Interval\u2010Censoring and Competing Risks.\u201d Preprint arXiv April 14.https:\/\/arxiv.org\/abs\/2404.09362."},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.70134"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280209105023"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1161\/circulationaha.105.594929"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1093\/clinchem\/39.4.561"}],"container-title":["Biometrical Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/bimj.70108","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/bimj.70108","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/bimj.70108","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T19:27:24Z","timestamp":1772998044000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/bimj.70108"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,5]]},"references-count":26,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1002\/bimj.70108"],"URL":"https:\/\/doi.org\/10.1002\/bimj.70108","archive":["Portico"],"relation":{},"ISSN":["0323-3847","1521-4036"],"issn-type":[{"value":"0323-3847","type":"print"},{"value":"1521-4036","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,5]]},"assertion":[{"value":"2025-01-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-31","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70108"}}