{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:20:26Z","timestamp":1786980026653,"version":"build-2736575974"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["World J Urol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Renal cell carcinoma (RCC) is a significant urological malignancy with a rising incidence, increasingly linked to metabolic dysregulation and chronic systemic inflammation. While traditional metrics such as body mass index (BMI) are commonly used, they may not fully capture the biological heterogeneity underlying carcinogenesis. This study investigated the associations of the Metabolic Score for Insulin Resistance (METS-IR) and the Systemic Inflammation Response Index (SIRI) with subsequent RCC risk, together with their joint effects and longitudinal trajectory patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective analysis within the UK Biobank prospective cohort, comprising 410,766 participants aged 37\u201373 years. METS-IR and SIRI were calculated from baseline blood samples. Incident RCC was ascertained through national cancer registries. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), because the outcome was time to incident RCC with variable follow-up and right censoring. Nonlinear relationships were evaluated using restricted cubic splines, and joint effects were assessed on an additive scale. Dynamic trajectory analysis based on repeat assessment data was treated as exploratory.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>During a median follow-up of 13.65 years, 1,752 (0.43%) participants developed RCC, with a median time to diagnosis of 8.01 years among cases. Both biomarkers were independently associated with RCC risk. In fully adjusted models, each 1-SD increase in METS-IR was associated with a 26% higher RCC risk (HR: 1.26; 95% CI: 1.12\u20131.42), showing a linear dose-response pattern. SIRI showed a non-linear association, with risk increasing more sharply beyond an index value of approximately 1.2; participants in the highest quartile had a 57% higher risk (HR: 1.57; 95% CI: 1.35\u20131.83)than those in the lowest quartile. Participants with concomitantly high METS-IR and high SIRI had the highest risk (HR: 2.40; 95% CI: 2.06\u20132.79), although additive interaction metrics did not show statistical evidence of interaction. In exploratory trajectory analyses, persistently high METS-IR or SIRI was associated with higher RCC risk, whereas estimates for improved and worsened groups were more imprecise.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>METS-IR and SIRI were independently associated with RCC risk in this cohort. Their combined assessment may improve risk stratification. The findings further suggest that metabolic and inflammatory trajectory patterns may carry different prognostic information, although these longitudinal results should be interpreted cautiously and not as evidence of causality or risk reversibility.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00345-026-06487-x","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T11:29:36Z","timestamp":1779967776000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Joint effects and dynamic trajectories of metabolic insulin resistance and systemic inflammation in the risk of renal cell carcinoma: a UK Biobank cohort analysis"],"prefix":"10.1007","volume":"44","author":[{"given":"Shuang","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feipeng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinlong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanlong","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianjun","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meixia","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dechao","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,28]]},"reference":[{"issue":"1","key":"6487_CR1","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1186\/s12885-025-13902-w","volume":"25","author":"N Zhou","year":"2025","unstructured":"Zhou N, Bai H, Zhang Z, Yu B, Zhao H, Li J et al (2025) Global, regional, and national burden of kidney cancer and attributable risk factors in adults aged 65 years and older from 1990 to 2021 and projections to 2040. 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