{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T13:09:19Z","timestamp":1788786559765,"version":"build-2803163510"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":6,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001695","name":"JST","doi-asserted-by":"publisher","award":["JPMJCR2231"],"award-info":[{"award-number":["JPMJCR2231"]}],"id":[{"id":"10.13039\/501100001695","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000646","name":"JSPS","doi-asserted-by":"publisher","award":["24\u00a0K15175"],"award-info":[{"award-number":["24\u00a0K15175"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000646","name":"JSPS","doi-asserted-by":"publisher","award":["25KJ1104"],"award-info":[{"award-number":["25KJ1104"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000646","name":"JSPS","doi-asserted-by":"publisher","award":["JP20H03240"],"award-info":[{"award-number":["JP20H03240"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000646","name":"JSPS","doi-asserted-by":"publisher","award":["JP25K02261"],"award-info":[{"award-number":["JP25K02261"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Prognostic stratification in multiple myeloma (MM) relies on staging systems fixed at diagnosis, discarding temporal information accumulated during treatment. We developed a dynamic multimodal framework that predicts residual overall survival from observation windows of 1\u201318\u00a0months post-diagnosis. The model integrates DeepInsight-transformed gene expression, longitudinal trajectories of 10 laboratory analytes, and treatment history through missingness-aware gated fusion. On the Multiple Myeloma Research Foundation (MMRF) cohort from the Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile (CoMMpass) study (n\u2009=\u2009752), five-fold-specific models trained on the development dataset achieved a mean concordance index (C-index) of 0.773\u2009\u00b1\u20090.024 and 1-year time-dependent area under the receiver operating characteristic curve (AUC) of 0.789\u2009\u00b1\u20090.021 on a common held-out CoMMpass validation split, outperforming the evaluated survival-learning baselines including DeepSurv, a Cox proportional hazards neural network, and random survival forests. Kaplan\u2013Meier stratification showed significant separation at all primary landmarks (log-rank $P&amp;lt;.001$, hazard ratios 3.46\u20133.93). A distilled student model retaining only the DeepInsight gene expression representation and five baseline clinical features transferred to an independent microarray cohort (GSE24080, n\u2009=\u2009507) without retraining, achieving a C-index of 0.672 and a time-dependent AUC at 1-year of 0.740, supporting cross-cohort transferability in a reduced-input setting. Interpretability analyses recovered ubiquitin-proteasome, endoplasmic reticulum (ER) stress, and Interferon Alpha Response signals consistent with established myeloma biology. These findings support the potential of dynamic multimodal modeling for longitudinal prognostic assessment in MM.<\/jats:p>","DOI":"10.1093\/bib\/bbag475","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T11:45:08Z","timestamp":1786535108000},"source":"Crossref","is-referenced-by-count":0,"title":["Dynamic multimodal survival prediction in multiple myeloma integrating gene expression, longitudinal laboratory measurements, and treatment history"],"prefix":"10.1093","volume":"27","author":[{"given":"Shangru","family":"Jia","sequence":"first","affiliation":[{"name":"Laboratory for Medical Science Mathematics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Artem","family":"Lysenko","sequence":"additional","affiliation":[{"name":"Laboratory for Medical Science Mathematics, Department of Biological Sciences, School of Science, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7095-7332","authenticated-orcid":false,"given":"Keith A","family":"Boroevich","sequence":"additional","affiliation":[{"name":"RIKEN Center for Integrative Medical Sciences , 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7668-3501","authenticated-orcid":false,"given":"Alok","family":"Sharma","sequence":"additional","affiliation":[{"name":"Laboratory for Medical Science Mathematics, Department of Biological Sciences, School of Science, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 ,","place":["Japan"]},{"name":"RIKEN Center for Integrative Medical Sciences , 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045 ,","place":["Japan"]},{"name":"Centre for Sustainable Futures, The University of the South Pacific , Laucala Campus, Laucala Bay Road, Suva ,","place":["Fiji"]},{"name":"College of Informatics, Korea University, 145 Anam-ro, Seongbuk-gu , Seoul 02841 ,","place":["Republic of Korea"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5439-7918","authenticated-orcid":false,"given":"Tatsuhiko","family":"Tsunoda","sequence":"additional","affiliation":[{"name":"Laboratory for Medical Science Mathematics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 ,","place":["Japan"]},{"name":"Laboratory for Medical Science Mathematics, Department of Biological Sciences, School of Science, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 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