{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T15:56:03Z","timestamp":1792425363303,"version":"4.5.0"},"reference-count":24,"publisher":"Wiley","issue":"27","license":[{"start":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T00:00:00Z","timestamp":1630368000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013428","name":"Stichting Spieren voor Spieren","doi-asserted-by":"publisher","award":["SvS15"],"award-info":[{"award-number":["SvS15"]}],"id":[{"id":"10.13039\/501100013428","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2021,11,30]]},"abstract":"<jats:p>Longitudinal and high\u2010dimensional measurements have become increasingly common in biomedical research. However, methods to predict survival outcomes using covariates that are both longitudinal and high\u2010dimensional are currently missing. In this article, we propose penalized regression calibration (PRC), a method that can be employed to predict survival in such situations. PRC comprises three modeling steps: First, the trajectories described by the longitudinal predictors are flexibly modeled through the specification of multivariate mixed effects models. Second, subject\u2010specific summaries of the longitudinal trajectories are derived from the fitted mixed models. Third, the time to event outcome is predicted using the subject\u2010specific summaries as covariates in a penalized Cox model. To ensure a proper internal validation of the fitted PRC models, we furthermore develop a cluster bootstrap optimism correction procedure that allows to correct for the optimistic bias of apparent measures of predictiveness. PRC and the CBOCP are implemented in the <jats:styled-content>R<\/jats:styled-content> package <jats:styled-content>pencal<\/jats:styled-content>, available from <jats:styled-content>CRAN<\/jats:styled-content>. After studying the behavior of PRC via simulations, we conclude by illustrating an application of PRC to data from an observational study that involved patients affected by Duchenne muscular dystrophy, where the goal is predict time to loss of ambulation using longitudinal blood biomarkers.<\/jats:p>","DOI":"10.1002\/sim.9178","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T22:49:10Z","timestamp":1630450150000},"page":"6178-6196","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Penalized regression calibration: A method for the prediction of survival outcomes using complex longitudinal\u00a0and high\u2010dimensional data"],"prefix":"10.1002","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8102-3356","authenticated-orcid":false,"given":"Mirko","family":"Signorelli","sequence":"first","affiliation":[{"name":"Mathematical Institute Leiden University  Leiden The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2783-688X","authenticated-orcid":false,"given":"Pietro","family":"Spitali","sequence":"additional","affiliation":[{"name":"Department of Human Genetics Leiden University Medical Center  Leiden The\u00a0Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6990-1905","authenticated-orcid":false,"given":"Cristina Al\u2010Khalili","family":"Szigyarto","sequence":"additional","affiliation":[{"name":"Department of Protein Science KTH\u2010Royal Institute of Technology  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"The MARK\u2010MD Consortium","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roula","family":"Tsonaka","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Sciences Leiden University Medical Center  Leiden The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcsm.12517"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.3233\/JND-190454"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2008.05.021"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1201\/b12208"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7391"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-016-0212-5"},{"key":"e_1_2_10_8_1","first-page":"1","article-title":"Joint models with multiple longitudinal outcomes and a time\u2010to\u2010event outcome: a corrected two\u2010stage approach","author":"Mauff K","year":"2020","journal-title":"Stat Comput"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1111\/bmsp.12000"},{"key":"e_1_2_10_10_1","volume-title":"Generalized, Linear, and Mixed Models","author":"McCulloch CE","year":"2008"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2007.00983.x"},{"key":"e_1_2_10_12_1","unstructured":"SignorelliM.pencal: penalized regression calibration (PRC). 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