Metabolic Tumor Volume Change Predicts Long-term Survival and Histological Response to Preoperative Chemotherapy in Locally Advanced Esophageal Cancer.

Abstract

Here, we assess the ability of metabolic tumor volume (MTV) as measured by F-fluorodeoxyglucose-positron emission tomography/computed tomography (F-FDG PET/CT) to evaluate neoadjuvant chemotherapy response for patients with locally advanced esophageal cancer (EC). Optimal methods to evaluate treatment response for EC patients have not yet been established. Although previous studies have reported the value of standardized uptake value (SUV), the accuracy of predicting histological response or long-term survival in EC is limited. In all, 102 EC patients without distant metastasis who underwent F-FDG PET/CT both before and after the preoperative chemotherapy series were analyzed. The median primary tumor MTV values before and after preoperative chemotherapy were 22.55 (range 0.4-183.1) and 2.75 (0-52.9), respectively, and the median MVT reduction rate was 86.5%. We found the most significant difference in survival between PET responders and nonresponders with a cut-off value of 60% MTV reduction, using a 10% stepwise cut-off analysis [2-year progression-free survival (PFS): 79.2 vs 44.4%; hazard ratio (HR) 3.397; P < 0.0001). With this cut-off value, histological response (P = 0.0091), tumor location (P = 0.0102), pT (P = 0.0011), and pN (P = 0.0110) were significantly associated with PET response. Univariate analysis of PFS indicated a correlation between PFS and tumor size, cT, decrease of primary lesion by CT, SUVmax reduction rate, MTV reduction rate, pT, pN, and pM. Multivariate analysis further identified pM (HR 3.063; P = 0.0279) and MTV reduction rate (HR 2.471; P = 0.0263) to be independent prognostic predictors, but not decrease of primary lesion by CT or SUVmax reduction rate. MTV change is clinically useful in predicting both long-term survival and histological response to preoperative chemotherapy in EC patients, after determining the optimal cut-off value based on survival analysis.