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Because predicting patients' future survival statuses on the basis of such recorded longitudinal information might be of great interest, joint modeling of longitudinal and time\u2010to\u2010event data has been intensively discussed as a toolkit to implement such a prediction. To achieve a desirable predictive performance, averaging over multiple candidate predictive models to account for the model uncertainty might be a more suitable statistical approach than selecting the single best model. Although Bayesian model averaging can be one of the approaches, several problems related to model weights with marginal likelihoods have been discussed. To address these problems, we here propose a Bayesian predictive model averaging (BPMA) method that uses Bayesian leave\u2010one\u2010out cross\u2010validation predictive densities to account for the subject\u2010specific and time\u2010dependent nature of the prediction. We examine the operating characteristics of the proposed BPMA method in terms of the predictive accuracy (ie, the calibration and discrimination abilities) in extensive simulation studies. In addition, we discuss the strengths and limitations of the proposed method by applying it to an immuno\u2010oncology clinical trial in patients with advanced ovarian cancer.<\/jats:p>","DOI":"10.1002\/sim.9897","type":"journal-article","created":{"date-parts":[[2023,9,14]],"date-time":"2023-09-14T13:11:53Z","timestamp":1694697113000},"page":"4990-5006","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Bayesian predictive model averaging approach to\u00a0joint\u00a0longitudinal\u2010survival modeling: Application to\u00a0an\u00a0immuno\u2010oncology clinical trial"],"prefix":"10.1002","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1070-0185","authenticated-orcid":false,"given":"Zixuan","family":"Yao","sequence":"first","affiliation":[{"name":"Department of Biomedical Statistics and Bioinformatics Kyoto University Graduate School of Medicine  Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4344-3317","authenticated-orcid":false,"given":"Satoshi","family":"Morita","sequence":"additional","affiliation":[{"name":"Department of Biomedical Statistics and Bioinformatics Kyoto University Graduate School of Medicine  Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sumiyuki","family":"Nishida","sequence":"additional","affiliation":[{"name":"Department of Respiratory Medicine and Clinical Immunology Osaka University Graduates School of Medicine  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haruo","family":"Sugiyama","sequence":"additional","affiliation":[{"name":"Department of Cancer Immunology Osaka University Graduates School of Medicine  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,9,13]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2010.01546.x"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4205"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.201600235"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280218811837"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280218802300"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-020-09927-9"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1009212519"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2014.931236"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1214\/17-BA1091"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1201\/b16018"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-016-9696-4"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1097\/CJI.0000000000000405"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1158\/2326-6066.CIR-17-0386"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/2051-1426-1-18"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.publhealth.20.1.145"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780198524847.001.0001"},{"key":"e_1_2_11_18_1","first-page":"809","article-title":"Joint modeling of longitudinal and time\u2010to\u2010event data: an overview","volume":"14","author":"Tsiatis AA","year":"2004","journal-title":"Stat Sin"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.201600221"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2008.00704.x"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1979.10481632"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0b013e3181c30fb2"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyab047"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12232"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8570"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1201\/b14835"},{"key":"e_1_2_11_27_1","unstructured":"Stan Developent Team.RStan: the R interface to Stan.http:\/\/mc\u2010stan.org. 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