Clinical Application Value Of Prognostic Nutritional Index For Predicting Survival In Patients With Esophageal Squamous Cell Carcinoma Undergoing Radical Chemoradiotherapy Or Radiotherapy

Abstract

The prognostic nutrition index (PNI) has been shown to have prognostic value in several common cancers. We explore its clinical application value in the prognosis of patients with esophageal squamous cell carcinoma (ESCC) undergoing radical chemoradiotherapy (CRT) or radiotherapy (RT). Overall, 193 patients with ESCC who received radiotherapy with or without chemotherapy at Sichuan Cancer Hospital from March 20, 2012 to December 25, 2017 were retrospectively analyzed. Based on serum measurements before treatment, PNI at ESCC recurrence was calculated as albumin (g/L) + 5 × total lymphocyte count. Kaplan-Meier method and Cox proportional regression model were used to analyze the relationship between PNI and overall survival. The PNI of 193 ESCC patients was 49.01 ± 4.68. The optimal cutoff value of PNI was calculated to be 47.975, and the patients were divided into a low PNI group (<47.975) and a high PNI group (≥47.975). PNI is related to tumor length, T-stage, and Synchronous chemotherapy in ESCC patients (P <0.05). The median OS for the entire group was 22.37 months. The median OS of patients in the high PNI group (PNI ≥ 47.975) and low PNI group (PNI <47.975) were 32.63 months and 15.4 months, respectively, and the 3-year survival rates were 47.5% and 32.2%, and 5-year survival rates were 37.7% and 16.8%, respectively, and the differences were statistically significant (P = 0.001). Univariate analysis showed that PNI, tumor length, T stage and Synchronous chemotherapy were related to the prognosis of ESCC patients (P <0.05). Multivariate analysis showed that tumor length (P = 0.019), synchronous chemotherapy (P = 0.009), and PNI (P = 0.003) were independent prognostic factors affecting the prognosis of patients in ESCC treated with RT or CRT. The calculation of PNI value is simple, reliable and repeatable, which can improve the accuracy of patients' prognosis. And it needs to be further confirmed by the prospective study of large sample size.