ArticleAnnals of medicine2026
CT-based variables of perirenal fat are risk factors for assessing pathological T-stage in patients with clear cell renal cell carcinoma.
Article in Annals of medicine, 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
backgroundAdvances in the treatment of clear cell renal cell carcinoma (ccRCC) toward risk-based therapy intensity modulation have necessitated patient-specific assessments of preoperative T-stage.
methodsA derivation cohort of 218 ccRCC patients with known pathological results and preoperative biomarker data was used to develop and validate a predictive model for preoperative T-stage. Perirenal fat characteristics were determined by the measurement or evaluation of preoperative CT images. Multivariate logistic regression was used to identify the predictive factors and to develop a predictive model, which was then internally validated using cross-validation and bootstrapping. Model discrimination was assessed using calibration plots. Finally, nomograms were both plotted to visualize model efficiency.
resultsA total of 218 patients (152 males and 66 females) with pathological tumor T-stage (151 low T-stage and 67 high T-stage) were enrolled in this study. Perinephric fat stranding (PFS), RENAL Nephrometry Score (RNS), and preoperative platelet (PLT) counts were independent predictors of a high ccRCC T-stage. The performance of the predictive model built on these variables notably surpasses that of radiologists (AUC: 0.867 vs 0.680; delong test,
conclusionsPFS, RNS, and preoperative PLT provided excellent predictions of a high pathological T-stage for ccRCC patients. This predictive model can serve as a reference to aid clinicians and surgeons in clinical decision-making.
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