Abstract
Prognostic nutritional index (PNI) is a recognized indicator of both immune and nutritional status. It was firstly used as a preoperative prognostic indicator, and its role in the prognosis of patients with metastatic renal cell carcinoma (mRCC) has not yet been investigated in large-scale study. The purpose of this work was to investigate the prognostic role of pretreatment PNI in patients with mRCC with sorafenib or sunitinib as first-line targeted therapy. In this retrospective single-center research, the Kaplan-Meier method was used to estimate the progression-free survival (PFS) and overall survival (OS) of 178 mRCC patients who received first-line therapy of sorafenib or sunitinib. Log-rank test was used to compare the survival outcomes of patients with low pretreatment PNI (PNI<51.62) and high pretreatment PNI (PNI≥51.62), and Cox proportional hazard regression model was used to compare PFS and OS between these two groups. Prognostic accuracy was determined using Harrell concordance index. The overall median PFS and OS time for all 178 patients were 11months (95% CI 9-12months) and 24months (95% CI 19-33months), respectively. Patients with low pretreatment PNI both had significantly shorter median PFS (7 vs 19months, P<0.001) and OS (14 vs 50months, P<0.001) than those with high PNI. Multivariate analysis showed that pretreatment PNI was an independent predictor of OS (HR 1.658, 95% CI 1.040-2.614, P=0.033) and an independent predictor of PFS as well (HR 1.842, 95% CI 1.226-2.766, P=0.003). The model built by the addition of pretreatment PNI improved predictive accuracy of PFS and OS compared with the International Metastatic Renal Cell Carcinoma Database Consortium Model (Heng model) (c-index: 0.68 and 0.70). Comparing to NLR (neutrophil-to-lymphocyte ratio) (0.69 and 0.72), PNI might be a preciser factor to predict PFS and OS (0.71 and 0.73). Low pretreatment PNI could be a significant risk factor for mRCC patients who received tyrosine kinase inhibitors as first-line target therapy and increase the accuracy of established prognostic model.
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