Perirenal fat thickness may be a significant predictor of prognosis and postoperative renal function in renal cancer surgery patients

Renal cell carcinoma accounts for a significant number of kidney malignancy-related fatalities globally. Perirenal Fat Thickness (PRFT) may indicate a state of nutritional excess in patients, which is potentially directly linked to both the incidence and prognosis of kidney cancer. This study investigated the association between perirenal fat thickness (PRFT) and overall survival (OS), as well as the predictive value of PRFT for postoperative estimated glomerular filtration rate (eGFR) in patients with renal cell carcinoma (RCC). A retrospective cohort of 1647 RCC patients from 2014 to 2021 was analyzed, divided into radical nephrectomy (RN) and partial nephrectomy (PN) groups. Preoperative measurements included visceral fat area, PRFT, and subcutaneous fat area. Kaplan-Meier curves compared OS between high and low PRFT groups, while Cox regression analyses identified prognostic factors for OS, and linear regression analyses assessed predictors of postoperative eGFR. PRFT significantly influenced OS in RN patients in univariate analysis (HR: 0.32; 95% CI: 0.19-0.52; P < 0.001), but not in PN patients. After adjusting for covariates such as age, sex, sarcomatoid features, necrosis, T stage, Fuhrman grade, smoking status, subcutaneous adipose tissue, and BMI, PRFT remained an independent risk factor for OS (HR: 0.56; 95% CI: 0.33-0.96; P < 0.001). Kaplan-Meier analysis showed that higher PRFT was associated with improved OS in RN patients. Univariate linear regression revealed that high PRFT correlated with reduced postoperative eGFR in both RN (β = -0.2, P = 0.002) and PN (β = -0.34, P < 0.001) groups; however, this correlation was not significant after multivariate adjustment. In conclusion, Low PRFT is independently associated with higher mortality in RCC patients undergoing RN. High PRFT is associated with reduced postoperative eGFR in initial analyses, but this association was not significant in multivariate analysis.