ArticleBMC urology2026
The low-grade Inflammation Score (INFLA-Score) as a predictor of overall survival in prostate cancer: a UK biobank cohort study.
Article in BMC urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveInflammation plays a crucial role in the progression and prognosis of prostate cancer (PCa). The aim of this study was to investigate the association of the low-grade inflammation score (INFLA-score) with overall survival in patients with prostate cancer.
methodsUtilizing data from the UK Biobank, we included 13,166 men diagnosed with PCa. The predictive accuracy of systemic inflammatory biomarkers for overall survival was assessed and compared using the C-statistic. Survival curves were plotted using the Kaplan-Meier method and differences in in overall survival between groups were compared by the log-rank test. Restricted cubic spline (RCS) curves were used to explore the relationship between biomarkers and survival. Independent prognostic biomarkers associated with overall survival (OS) were determined using multivariable Cox proportional hazards regression analysis.
resultsThe INFLA-score demonstrated the highest predictive accuracy for overall survival among all evaluated biomarkers, with a C-statistic of 0.556 (0.544,0.567). Patients with a high INFLA-score had significantly worse overall survival (shorter survival time) than those with a low INFLA-score (33.76% vs. 66.24%; log-rank p < 0.001). RCS analysis revealed a significant dose-response relationship between the INFLA-score and survival in PCa patients. After adjusting for potential confounders, a high INFLA-score remained an independent predictor of poor OS (HR = 1.24, 95% CI: 1.15-1.33, p < 0.001).
conclusionsThe INFLA-score was independently associated with overall survival of PCa patients. As an easily obtainable and integrative measure of low-grade inflammation, it shows significant promise for clinical application in risk stratification and survival prediction.
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