Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism

Abstract

To develop a tool for predicting pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (neoCRT) in patients with esophageal cancer by combining inflammatory status and tumor glucose metabolic activity. This study included 127 patients with locally advanced esophageal cancer who had received neoCRT followed by esophagectomy from 2007 to 2016. We collected their neutrophil–lymphocyte ratio (NLR) and standardized uptake value (SUV) obtained from fluorodeoxyglucose positron emission tomography (PET/CT) before and after neoCRT. Univariate and multivariate logistic regression analyses were performed to identify potential predictive factors for pCR. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of predictors were calculated. Between pCR and non-pCR groups, there were no statistically significant differences in patient characteristics, such as sex, age, site, and clinical T/N stage. Multivariate analyses identified four independent predictors for pCR, including pre-OP NLR < 5.4 [OR 11.179; 95% CI 8.385–13.495; p = 0.003], NLR change (ΔNLR) < 3 [OR 4.891; 95% CI 2.274–9.180; p = 0.005], changes in SUV (ΔSUV) > 7.2 [OR 3.033; 95% CI 1.354–6.791; p = 0.007], and SUV changes ratio (ΔSUV ratio) > 58% [OR 3.585; 95% CI 1.576–8.152; p = 0.002]. ΔNLR had the highest accuracy and NPV (84.3% and 90.3%, respectively). Combined factors of ΔNLR < 3 and ΔSUV ratio > 58% had the best PPV for pCR (84.8%). Inflammatory status (ΔNLR) and tumor glucose metabolic activity (ΔSUV ratio), when considered together, constitute a promising low-invasive tool with high efficacy for prediction of treatment response before surgery.