Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma

Several researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection. The data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC). The RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication. The present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.