Defining and Predicting Early Recurrence after Resection for Gallbladder Cancer.

Abstract

The optimal time interval to define early recurrence (ER) among patients who underwent resection of gallbladder cancer (GBC) is not well defined. We soughtto develop and validate a novel GBC recurrence risk (GBRR) score to predict ER among patients undergoing resection for GBC. Patients who underwent curative-intent resection for GBC between 2000 and 2018 were identified from the US Extrahepatic Biliary Malignancy Consortiumdatabase. A minimum p value approach in the log-rank test was used to define the optimal cutoff forER. A risk stratification model was developed to predict ER based on relevant clinicopathological factors and was externally validated. Among 309 patients, 103 patients (33.3%) had a recurrence at a median follow-up period of 15.1months. The optimal cutoff for ER was defined at 12months (p = 3.04 × 10-18). On multivariable analysis, T3/T4 disease (HR: 2.80; 95% CI 1.58-5.11) and poor tumordifferentiation (HR: 1.91; 95% CI 1.11-3.25) were associated with greater hazards of ER. The GBRR score was developed using β-coefficients of variables in the final model, and patients were classified into three distinct groups relative to the risk forER (12-month RFS; low risk: 88.4%, intermediate risk: 77.9%, high risk: 37.0%, p < 0.001). The external validation demonstrated good model generalizability with good calibration (n = 102: 12-month RFS; low risk: 94.2%, intermediate risk: 59.8%, high risk: 42.0%, p < 0.001). The GBRR score is available online at https://ktsahara.shinyapps.io/GBC_earlyrec/ . A novel online calculator was developed to help clinicians predict the probability of ER after curative-intent resection for GBC. The proposed web-based tool may help in the optimization of surveillance intervals and the counselling of patients about their prognosis.