{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T04:17:27Z","timestamp":1792815447220,"version":"4.5.0"},"reference-count":32,"publisher":"Wiley","issue":"23-24","license":[{"start":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T00:00:00Z","timestamp":1792195200000},"content-version":"vor","delay-in-days":16,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"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":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>In the absence of censoring, locally estimated scatterplot smoothing (LOESS) is a powerful tool to estimate the relationship between a continuous covariate and the probability of an event and is often used to visually assess calibration of prognostic models. Since follow\u2010up in prognostic studies is often incomplete, we aimed to study the extension of LOESS to right\u2010censored data. In line with other work, we first obtained inverse\u2010probability\u2010of\u2010censoring (IPC) weights through Kaplan\u2013Meier estimation. When censoring varied by covariate levels, we used Cox regression with a spline function of the covariate to obtain IPC weights. We then applied LOESS to the weighted event indicators to estimate the relationship between the covariate and the probability of an event within a specific time horizon. We illustrated the application of LOESS for censored data (LOESScd) using patients with complex coronary artery disease. We used the LOESScd to estimate the association between continuous predictors and the probability of death within 10\u2009years. LOESScd estimates closely followed grouped Kaplan\u2013Meier estimates, especially in case of weak smoothing. Covariate\u2010dependent IPC weights improved LOESScd when censoring varied by covariate levels. We then examined the finite\u2010sample behavior of LOESScd in simulations motivated by four typical prognostic model validation scenarios. In 2000 samples of 1800 patients, bias was limited and coverage was close to nominal. In conclusion, LOESScd is a promising estimator of the relationship of a continuous covariate with the probability of an event in the presence of right\u2010censoring. LOESScd is especially useful for estimating calibration curves when validating prognostic models.<\/jats:p>","DOI":"10.1002\/sim.70783","type":"journal-article","created":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T07:38:21Z","timestamp":1792222701000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Locally Estimated Scatterplot Smoothing for Censored Survival Data"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2096-606X","authenticated-orcid":false,"given":"David","family":"van Klaveren","sequence":"first","affiliation":[{"name":"Department of Public Health Erasmus University Medical Center Rotterdam  Rotterdam the Netherlands"},{"name":"Predictive Analytics and Comparative Effectiveness Center Institute for Clinical Research and Health Policy Studies, Tufts Medical Center  Boston Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3337-233X","authenticated-orcid":false,"given":"Peter C.","family":"Austin","sequence":"additional","affiliation":[{"name":"ICES  Toronto Ontario Canada"},{"name":"Institute for Health Policy, Management and Evaluation, University of Toronto  Toronto Ontario Canada"},{"name":"Sunnybrook Research Institute  Toronto Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick W.","family":"Serruys","sequence":"additional","affiliation":[{"name":"CORRIB Research Centre for Advanced Imaging and Core Laboratory University of Galway  Galway Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1613-7450","authenticated-orcid":false,"given":"Ben","family":"van Calster","sequence":"additional","affiliation":[{"name":"Department of Development and Regeneration KU Leuven  Leuven Belgium"},{"name":"Leuven Unit for Health Technology Assessment Research (LUHTAR) KU Leuven  Leuven Belgium"},{"name":"Julius Center for Health Sciences and Primary Care University Medical Center Utrecht  Utrecht the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8271-5493","authenticated-orcid":false,"suffix":"Jr","given":"Frank E.","family":"Harrell","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Vanderbilt University School of Medicine  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,17]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.2307\/2286407"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5941"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj\u20102023\u2010074820"},{"key":"e_1_2_10_5_1","unstructured":"National Institute of Standards and Technology \u201ce\u2010Handbook of Statistical Methods\u2014Chapter 4.1.4.4 \u201d(2025) https:\/\/www.itl.nist.gov\/div898\/handbook\/pmd\/section1\/pmd144.html."},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/sj.bjc.6601118"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.2307\/2281868"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517\u20106161.1972.tb00899.x"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.2307\/2291132"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176345644"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1994.10476781"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.2202\/1557\u20104679.1052"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6949"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2016.03.009"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8570"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1177\/1536867X1401400403"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1198\/000313001317098185"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/s0140\u20106736(13)60141\u20105"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/s0140\u20106736(19)31997\u2010x"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/s0140\u20106736(20)32114\u20100"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1038425655"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1080\/10543406.2010.521874"},{"key":"e_1_2_10_23_1","unstructured":"\u201cBinNor: Simultaneous Generation of Multivariate Binary and Normal \u201d(2025) https:\/\/CRAN.R\u2010project.org\/package=BinNor. 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