{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T09:05:45Z","timestamp":1779786345647,"version":"3.53.1"},"reference-count":51,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T00:00:00Z","timestamp":1779753600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"funder":[{"name":"Science & Technology Programme of the Sichuan Provincial Health Commission","award":["24WSXT033"],"award-info":[{"award-number":["24WSXT033"]}]},{"name":"Mianyang Philosophy and Social Science Research Program","award":["MY2024YB120"],"award-info":[{"award-number":["MY2024YB120"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Risk prediction models help identify multiple myeloma (MM) patients at high risk of venous thromboembolism (VTE) and guide clinical decisions. However, their applicability and accuracy remain unclear. This study aims to systematically review existing VTE risk models in MM patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We systematically searched PubMed, Embase, Cochrane Library, and Web of Science for studies on VTE risk prediction models in patients with MM, up to March 31, 2026. Two investigators independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies using the PROBAST tool. Data analysis was performed using the \u201cmeta\u201d and \u201cmetafor\u201d packages in R software.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 14 studies on VTE risk prediction models in MM patients were included, involving the development and\/or validation of seven risk assessment tools. Meta-analysis showed that the overall VTE incidence in MM patients was 7.9% (95% CI [6.2\u201310.1%]). The combined area under the curve (AUCs) of the seven tools ranged from 0.57 to 0.68, with the IMPEDE VTE and IMPEDED VTE scores showing the best performance. Only two studies used the Hosmer-Lemeshow test for model calibration, and all studies presented the models in formula form. All included studies were at high risk of bias, mainly in the outcome and analysis domains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Existing VTE risk models for MM patients show low predictive performance (pooled AUC &lt; 0.7) and limited clinical use. Future research should focus on model updating and external validation to improve accuracy and applicability. PROSPERO Registration number ID: CRD420251024346.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.7717\/peerj.21322","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T08:40:16Z","timestamp":1779784816000},"page":"e21322","source":"Crossref","is-referenced-by-count":0,"title":["Risk prediction models for venous thromboembolism among patients with multiple myeloma: a systematic review and meta-analysis"],"prefix":"10.7717","volume":"14","author":[{"given":"Jin","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Hematology, Sichuan Mianyang 404 Hospital, Mianyang, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"You","family":"Pu","sequence":"additional","affiliation":[{"name":"Department of Oncology, Sichuan Mianyang 404 Hospital, Mianyang, Sichuan, 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