Predicting Residual Disease in Incidental Gallbladder Cancer: Risk Stratification for Modified Treatment Strategies.

Journal Article (Journal Article)

INTRODUCTION: Re-operation is advised for patients with T1b or greater incidental gallbladder cancer (GBCA). The presence of residual disease (RD) impacts resectability, chemotherapy, and survival. This study created a preoperative model to predict RD at re-operation. METHODS: Patients with re-operation for incidental GBCA from 1992-2015 were included. The relationship between pathology data from initial cholecystectomy and RD at re-operation was assessed with logistic regression and classification and regression tree (CART) analysis. RESULTS: Two hundred fifty-four patients were included and 188 underwent definitive re-resection (74.0%). Distant RD was identified in 69 (27.2%) patients and locoregional only RD in 82 (32.3%). On multivariate analysis, T3 (OR 22.7, 95% CI 5.5-94.4) and poorly differentiated tumors (OR 4.3, 95% CI 1.4-13.3) were associated with RD (p < 0.001-0.012). AUC of multivariate model was 0.78 (95% CI 0.72-0.83). CART analysis split patients into groups based on percentage with RD: 87% RD with T3, 67% RD with T1b/T2 and poorly differentiated, and 35% RD with T1b/T2 and well/moderate differentiated tumors. CONCLUSION: Based on T stage and grade from cholecystectomy, this study developed a model for predicting RD at re-operation in incidental GBCA. This model delineates patient groups with variable percentages of RD and could be used to stratify high-risk patients for prospective trials.

Full Text

Duke Authors

Cited Authors

  • Creasy, JM; Goldman, DA; Gonen, M; Dudeja, V; Askan, G; Basturk, O; Balachandran, VP; Allen, PJ; DeMatteo, RP; D'Angelica, MI; Jarnagin, WR; Peter Kingham, T

Published Date

  • August 2017

Published In

Volume / Issue

  • 21 / 8

Start / End Page

  • 1254 - 1261

PubMed ID

  • 28484891

Pubmed Central ID

  • PMC5521173

Electronic International Standard Serial Number (EISSN)

  • 1873-4626

Digital Object Identifier (DOI)

  • 10.1007/s11605-017-3436-8


  • eng

Conference Location

  • United States