Predicting the prognosis of patients with renal cell carcinoma based on systemic immune inflammatory index and prognostic nutritional index
Authors: Jiang Xi , Zhou Tingting , Liu Chenjing , Xu Na , Chen Xiaobin , Wang Dong 
Published: November 2024

Background
To analyze the value of preoperative systemic immune inflammatory index (SII) and prognostic nutritional index (PNI) in predicting the prognosis of patients with renal cell carcinoma after operation, and draw nomograms to predict the overall survival (OS) of patients.
Methods
The clinical data of 240 patients with renal cell carcinoma were analyzed retrospectively, and the values of SII and PNI were calculated. Receiver operating characteristic curve was used to determine the optimal cutoff value of SII and PNI, which were divided into two groups: high and low SII and high and low PNI. Kaplan-Meier method was used to draw the survival curve, and the overall survival time of the two groups was analyzed. log-rank test was used to analyze the postoperative survival. Univariate and multivariate Cox regression models were used to analyze the independent influencing factors affecting the prognosis of patients with renal cell carcinoma. According to the independent influencing factors of patients' prognosis, the prediction model of nomogram was established, and the prediction accuracy and discrimination ability of nomogram were evaluated by the consistency index (C-index) and calibration curve.
Results
The 1-, 3- and 5- survival rates of patients in low SII group and high SII group were 98.10%, 92.30%, 87.20% and 90.00%, 72.90% and 57.40%, respectively. The survival rate of patients in low SII group was higher than that in high SII group, and the overall survival rate difference between the two groups was statistically significant (P < 0.001). The 1-, 3- and 5- survival rates of patients in low PNI group and high PNI group were 86.90%, 67.90%, 40.80% and 97.60%, 93.00% and 87.60% respectively. The survival rate of patients in low PNI group was lower than that in high PNI group, and the overall survival rate between the two groups was statistically significant (P < 0.001). Multivariate Cox regression model analysis showed that SII, PNI, hemoglobin, tumor necrosis, surgical method, pathological type, AJCC stage and Fuhrman grade were independent factors affecting the prognosis of patients with renal cell carcinoma. According to the results of Cox regression analysis, the prediction model of OS nomogram of renal cell carcinoma patients was constructed. The C index was 0.915, which indicated that the nomogram model had good accuracy and discrimination. The survival probability calibration curve showed that the nomogram was in high agreement with the actual results.
Conclusions
Preoperative high level of hemoglobin and PNI are protective factors for postoperative prognosis of patients with renal cell carcinoma. Preoperative high level of SII, tumor necrosis, radical nephrectomy, non-clear cell carcinoma, high AJCC stage and Fuhrman grade are risk factors for postoperative prognosis of patients with renal cell carcinoma. The nomograph model based on SII, PNI, hemoglobin, tumor necrosis, surgical method, pathological type, AJCC stage and Fuhrman grade has good accuracy and differentiation.