Prediction model for estimating the survival benefit of adjuvant radiotherapy for gallbladder cancer

被引:109
作者
Wang, Samuel J.
Fuller, C. David
Kim, Jong-Sung
Sittig, Dean F.
Thomas, Charles R., Jr.
Ravdin, Peter M.
机构
[1] Oregon Hlth & Sci Univ, Dept Radiat Med, Portland, OR 97239 USA
[2] Oregon Hlth & Sci Univ, Dept Med Informat, Portland, OR 97239 USA
[3] Oregon Hlth & Sci Univ, Dept Clin Epidemiol, Portland, OR 97239 USA
[4] Portland State Univ, Dept Math & Stat, Portland, OR 97207 USA
[5] NW Permante, Appl Res Med Informat, Portland, OR USA
[6] Univ Texas Hlth Sci Ctr San Antonio, Dept Radiat Oncol, San Antonio, TX 78229 USA
[7] Univ Texas Hlth Sci Ctr San Antonio, Grad Div Radiol Sci, San Antonio, TX 78229 USA
[8] Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
关键词
D O I
10.1200/JCO.2007.14.7934
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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, Epidemiology, 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.
引用
收藏
页码:2112 / 2117
页数:6
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