Preoperative systemic inflammation response index indicates poor prognosis in patients treated with resection of renal cell carcinoma with inferior vena cava tumor thrombus.

Abstract

To evaluate the prognostic value of systemic Inflammation Response Index (SIRI) in patients with renal cell carcinoma and inferior vena cava tumor thrombus (RCC-IVCTT) treated with radical nephrectomy and IVCTT thrombectomy. We retrospectively reviewed the clinical data of 144 consecutive patients with RCC-IVCTT who received radical nephrectomy and IVCTT thrombectomy at our center from January 2008 to August 2018. Receiver operating characteristic curve analysis was performed to calculate the optimal cutoff value of preoperative SIRI. Kaplan-Meier analysis was used to compare progression-free survival (PFS) and overall survival (OS). Univariable and multivariable Cox proportional hazard models were constructed to identify the independent prognostic factor for OS and PFS. The Harrell concordance index (C-index) was used to assess whether preoperative SIRI could improve the predictive accuracy of the existent prognostic models including Tumor, Node, Metastasis (TNM) stage model, University of California at Los Angeles Integrated Staging System (UISS) model and Stage, Size, Grade and Necrosis (SSIGN) model. Elevated preoperative SIRI was significantly correlated with clinicopathologic features that are associated with tumor progression. Patients were divided into a high or low SIRI group by the optimal cutoff value of SIRI. Patients in the high SIRI group had longer postoperative hospital stays and lost more blood during surgery. Kaplan Meier curve showed that high SIRI was correlated with decreased OS (P = 0.036) and PFS (P = 0.039) for patients with RCC-IVCTT after surgery. Increased preoperative SIRI was an independently risk factor for decreased OS (P = 0.038) and PFS (P = 0.021). To evaluate PFS, integrating SIRI to each model led to an increased predictive accuracy of 13.2% for TNM staging model (P = 0.007), 14.4% for UISS model (P = 0.000), 12.9% for SSIGN model (P = 0.003). To evaluate OS, integrating SIRI to each model led to an increased predictive accuracy of 13.2% for TNM staging model (P = 0.006), 12.8% for UISS model (P = 0.004), 12.4% for SSIGN model (P = 0.008). Preoperative SIRI serves as an independent predictor of prognosis for patients with RCC-IVCTT after surgery. Adding preoperative SIRI to the established prognostic models enhance their predictive accuracy.