Prediction Model for Estimating the Survival Benefit of Adjuvant Radiotherapy for Gallbladder Cancer Samuel J. Wang, C. David Fuller, Jong-Sung Kim, Dean F. Sittig, Charles R. Thomas Jr, and Peter M. Ravdin From the Departments of Radiation Medicine and Medical Informatics and Clinical Epidemiology, Oregon Health and Science University; Department of Mathematics and Statistics, Portland State University; Applied Research in Medical Informatics, Northwest Perma- nente, PC, Portland, OR; Department of Radiation Oncology and Graduate Divi- sion of Radiological Sciences, Univer- sity of Texas Health Science Center at San Antonio, San Antonio; and Depart- ment of Biostatistics, M.D. Anderson Cancer Center, Houston, TX. Submitted October 5, 2007; accepted January 15, 2008; published online ahead of print at www.jco.org on March 31, 2008. Supported in part by the Oregon Clini- cal and Translational Research Institute Career Development Pilot Project grant program (S.J.W.). Published, in part, as an abstract in the Proceedings of the 49th Annual Meet- ing of the American Society for Thera- peutic Radiology and Oncology, October 28-November 1, 2007, Los Angeles, CA. Authors’ disclosures of potential con- flicts of interest and author contribu- tions are found at the end of this article. Corresponding author: Samuel J. Wang, MD, PhD, Department of Radiation Medicine, KPV4, Oregon Health and Science University, 3181 SW Sam Jack- son Park Rd, Portland, OR 97239-3098; e-mail: wangsa@ohsu.edu. © 2008 by American Society of Clinical Oncology 0732-183X/08/2613-1/$20.00 DOI: 10.1200/JCO.2007.14.7934 A B S T R A C T Purpose The benefit of adjuvant radiotherapy (RT) for gallbladder cancer remains controversial because most published data are from small, single-institution studies. The purpose of this study was to construct a survival prediction model to enable individualized predictions of the net survival benefit of adjuvant RT for gallbladder cancer patients based on specific tumor and patient characteristics. Methods A multivariate Cox proportional hazards model was constructed using data from 4,180 patients with resected gallbladder cancer diagnosed from 1988 to 2003 from the Surveillance, Epidemiol- ogy, and End Results database. Patient and tumor characteristics were included as covariates and assessed for association with overall survival (OS) with and without adjuvant RT. The model was internally validated for discrimination and calibration using bootstrap resampling. Results On multivariate regression analysis, the model showed that age, sex, papillary histology, stage, and adjuvant RT were significant predictors of OS. The survival prediction model demonstrated good calibration and discrimination, with a bootstrap-corrected concordance index of 0.71. The model predicts that adjuvant RT provides a survival benefit in node-positive or  T2 disease. A nomogram and a browser-based software tool were built from the model that can calculate individualized estimates of predicted net survival gain attributable to adjuvant RT, given specific input parameters. Conclusion In the absence of large, prospective, randomized, clinical trial data, a regression model can be used to make individualized predictions of the expected survival improvement from the addition of adjuvant RT after gallbladder cancer resection. J Clin Oncol 26. © 2008 by American Society of Clinical Oncology INTRODUCTION Biliary tract cancers are relatively rare in the United States but carry a poor prognosis. 1 Gall- bladder cancer is the most common biliary tract neoplasm, with an annual incidence of approxi- mately 5,000 cases per year and an annual mortal- ity of 2,800 deaths per year. 2 Surgery remains the only definitively curative therapy for resectable gallbladder cancer. 3 Even after complete resec- tion, however, locoregional recurrence rates are high. Consequently, there is considerable interest inexploringthepotentialbenefitofadjuvantchem- otherapy and/or radiotherapy (RT). Because of the rarity of gallbladder cancer, the actual benefit of adjuvant therapy has not been well estab- lished. 4 Only small gallbladder studies are re- ported in the literature, some of which seem to indicate a potential benefit from adjuvant chem- otherapy and/or RT. 5-7 Because of the rarity of gallbladder cancer, it may prove to be difficult to accrue sufficient numbers of patients for a large- scale prospective randomized clinical trial. As a result, clinicians currently have little evidence to rely on when attempting to determine whether adjuvant RT will be beneficial to their patients. The specific aim of this study was to con- struct a survival prediction model to estimate the potential survival benefit of adjuvant RT after resection of gallbladder cancer. To this end, we constructed a Cox proportional haz- ards multivariate regression model based on the Surveillance, Epidemiology, and End Results (SEER) database, 8 the largest epidemiologic cancer registry in the United States. The goal was to construct a decision aid that can estimate the potential benefit of adjuvant RT for an in- dividual gallbladder cancer patient. JOURNAL OF CLINICAL ONCOLOGY O R I G I N A L R E P O R T VOLUME 26  NUMBER 13  MAY 1 2008 © 2008 by American Society of Clinical Oncology 1 http://jco.ascopubs.org/cgi/doi/10.1200/JCO.2007.14.7934 The latest version is at Published Ahead of Print on April 7, 2008 as 10.1200/JCO.2007.14.7934 Copyright 2008 by American Society of Clinical Oncology Copyright © 2008 by the American Society of Clinical Oncology. All rights reserved. Downloaded from jco.ascopubs.org by Samuel Wang on April 8, 2008 from 72.87.38.21.