{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T13:07:20Z","timestamp":1791464840753,"version":"4.3.4"},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T00:00:00Z","timestamp":1776384000000},"content-version":"vor","delay-in-days":10,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Asociaci\u00f3n Espa\u00f1ola Contra el C\u00e1ncer. AYUDA PROYECTOS AECC 2020","award":["PROYE20075INZI"],"award-info":[{"award-number":["PROYE20075INZI"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Frailty is a prognostic determinant in older patients, yet the most effective tools to predict survival remain unclear. This study aimed to assess the predictive performance of different frailty assessment tools for 1-year mortality in the oncogeriatric population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A multicenter cohort study (PROFIT Study) involved patients aged \u226565 with cancer, evaluated in oncology clinics and post-acute oncogeriatric units. Frailty was measured using the Geriatric 8 questionnaire (G8), Short Physical Performance Battery (SPPB), and the Frailty Index Indice Fr\u00e1gil\u2014Valoraci\u00f3n Integral Geri\u00e1trica (IF-VIG). One-year mortality was monitored. Predictive ability was analyzed using receiver operating characteristic curves with optimized cut-offs, and covariate-adjusted Cox regression models were used to evaluate the association between frailty and mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 229 patients (mean age 75.1\u2009\u00b1\u20096.4\u2009years; 68.6% male; cancer type: 47.2% lung cancer, 17.9% colorectal, 25.3% other gastrointestinal, 9.6% prostate; tumoral stage IV: 85.2%), 146 (63.7%) died within 1 year. All tools showed predictive value, with IF-VIG demonstrating the highest sensitivity and SPPB the highest specificity. Optimized cut-offs improved performance compared to standard thresholds (G8: 12.5 vs 14; SPPB: 8 vs 9; IF-VIG: 0.16 vs 0.25). Adjusted Cox models confirmed significant associations with 1-year mortality: hazard ratio [HR] 1.97 (95% CI 1.30\u20132.99) for G8, 2.35 (95% CI 1.52\u20133.64) for SPPB, and 2.42 (95% CI 1.50\u20133.90) for IF-VIG.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>All frailty tools were significantly associated with 1-year mortality. SPPB and IF-VIG outperformed G8 in prognostic accuracy, highlighting their potential utility in clinical decision-making for older patients with cancer.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/gerona\/glag099","type":"journal-article","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T11:43:27Z","timestamp":1776253407000},"source":"Crossref","is-referenced-by-count":2,"title":["Predicting 1-year mortality in older cancer patients: performance of G8, SPPB, and IF-VIG in the PROFIT Study"],"prefix":"10.1093","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7971-5943","authenticated-orcid":false,"given":"Maria Cristina","family":"Ferrara","sequence":"first","affiliation":[{"name":"School of Medicine and Surgery, University of Milano-Bicocca , Monza,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabricio","family":"Zambom-Ferraresi","sequence":"additional","affiliation":[{"name":"IdiSNA, Navarrabiomed, 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