Construction of artificial neural network (ANN) based on predictive value of prognostic nutritional index (PNI) and neutrophil-to-lymphocyte ratio (NLR) in patients with cervical squamous cell carcinoma

To explore the analytical worth of prognostic nutritional index (PNI) and neutrophil-to-lymphocyte ratio (NLR) in patients with cervical squamous cell carcinoma. The clinical data of 539 patients with cervical cancer in the Affiliated Tumor Hospital of Nantong University from December 2007 to October 2016 were analyzed retrospectively. The ROC is used to select the best cutoff values of PNI and NLR, which are 48.95 and 2.4046. Cox regression analysis was used for univariate and multivariate analysis. Survival differences were assessed by Kaplan-Meier (KM) survival method. Finally, a 3-layer artificial neural network (ANN) model is established. In cervical squamous cell carcinoma, the KM survival curve showed that the overall survival (OS) rate of high-level PNI group was significantly higher than that of low-level PNI group (P .005). According to Cox multivariate analysis, preliminary diagnosed PNI and NLR were independent prognostic factors of cervical squamous cell carcinoma (P