{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T13:17:39Z","timestamp":1787318259684,"version":"build-2736575974"},"reference-count":34,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Frailty can impact the prognosis of cancer patients. We aimed to elucidate longitudinal frailty trajectories in cancer patients undergoing immunotherapy and to analyze the factors influencing these trajectories.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A prospective observational cohort study was conducted among cancer patients scheduled for immunotherapy from December 2022 to November 2023. Sociodemographic and disease-related information was collected. The Chinese version of the Tilburg Frailty Indicator, the Activities of Daily Living scale, the Hospital Anxiety and Depression Scale, the Nutritional Risk Screening 2002, and the Social Support Rating Scale were used to assess patients before the first immunotherapy session (T\n                      <jats:sub>0<\/jats:sub>\n                      ) and 1 week after each subsequent immunotherapy session until the sixth cycle (T\n                      <jats:sub>1<\/jats:sub>\n                      \u2013T\n                      <jats:sub>6<\/jats:sub>\n                      ). A growth mixed model was applied to explore frailty trajectories. Univariate and multivariate logistic regression analyses were performed to identify variables associated with each trajectory.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 205 patients completed the treatment cycles and were included in the analysis. The overall frailty score demonstrated significant changes (p = 0.037), with an initial increase followed by a subsequent decrease during the six treatment cycles. Four distinct frailty trajectories were identified: the \u201cpersistently non-frail group\u201d (Class 1), the \u201cpersistently frail group\u201d (Class 2), the \u201cfrailty deterioration\u2013remission group\u201d (Class 3), and the \u201cfrailty remission\u2013deterioration group\u201d (Class 4). Compared with Class 1, patients in Class 2 were more likely to have nutritional risk (odds ratio [OR] = 4.173, 95% confidence interval [CI]: 1.637\u201312.664) and live in rural areas (OR = 6.869, 95% CI: 2.589\u201318.223), while the likelihood of being male was significantly lower (OR = 0.365, 95%, CI: 0.136\u20130.982). In Class 3, more patients had depression (OR = 6.663, 95% CI: 2.266\u201319.592), had low social support (OR = 9.483, 95% CI: 1.493\u201360.249), and were dependent on their spouses (OR = 5.728, 95% CI: 1.584\u201320.716) or their children for care (OR = 7.847, 95% CI: 1.994\u201330.885); however, being male and the presence of anxiety were associated with lower odds (OR = 0.316, 95% CI: 0.122\u20130.815; OR = 0.281, 95% CI: 0.100\u20130.789, respectively). Patients with distant tumor metastasis (OR = 12.712, 95% CI: 2.930\u201353.988), pre-treatment frailty (OR = 8.427, 95% CI: 1.973\u201336.003), and no history of chemotherapy (OR = 0.182, 95% CI: 0.033\u20130.994) were more likely to be in Class 4.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>There was significant heterogeneity in the frailty trajectories of cancer patients undergoing immunotherapy. Identifying factors associated with different frailty trajectories is crucial for implementing targeted interventions to improve prognosis in these patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fonc.2025.1684827","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T05:15:14Z","timestamp":1763702114000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Frailty trajectories and their determinants in cancer patients undergoing immunotherapy: a prospective longitudinal 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