The benefit of adjuvant radiotherapy for gallbladder cancer remains controversial because most published data are from small, single-institution studies.
Dr Samuel Wang and colleagues from Oregon, USA constructed a survival prediction model to enable individualized predictions of the net survival benefit of adjuvant radiotherapy for gallbladder cancer patients.
The prediction model was based on specific tumor and patient characteristics.
|The survival prediction model had a bootstrap-corrected concordance index of 0.7|
|Journal of Clinical Oncology|
The team constructed a multivariate Cox proportional hazards model using data from 4,180 patients with resected gallbladder cancer from the Surveillance, Epidemiology, and End Results database.
The patients were diagnosed from 1988 to 2003.
The team included patient and tumor characteristics as covariates and assessed for association with overall survival with and without adjuvant radiotherapy.
The model was internally validated for discrimination and calibration using bootstrap resampling.
The researchers showed on multivariate regression analysis that age, sex, papillary histology, stage, and adjuvant radiotherapy were significant predictors of overall survival.
The survival prediction model demonstrated good calibration and discrimination, with a bootstrap-corrected concordance index of 0.7.
The team found that the model predicts that adjuvant radiotherapy provides a survival benefit in node-positive or T2 disease.
The team built a nomogram and a browser-based software tool from the model.
The model can calculate individualized estimates of predicted net survival gain attributable to adjuvant radiotherapy, given specific input parameters.
Dr Wang's team concluded, "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 radiotherapy after gallbladder cancer resection."