BACKGROUND The survival impact of neoadjuvant chemoradiotherapy (CRT) on esophageal cancer remains difficult to establish for specific patients. The aim of the current study was to create a Web-based prediction tool providing individualized survival projections based on tumor and treatment data. METHODS Patients diagnosed with esophageal cancer between 1997 and 2005 were selected from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database. The covariates analyzed were sex, T and N classification, histology, total number of lymph nodes examined, and treatment with esophagectomy or CRT followed by esophagectomy. After propensity score weighting, a log-logistic regression model for overall survival was selected based on the Akaike information criterion. RESULTS A total of 824 patients with esophageal cancer who were treated with esophagectomy or trimodal therapy met the selection criteria. On multivariate analysis, age, sex, T and N classification, number of lymph nodes examined, treatment, and histology were found to be significantly associated with overall survival and were included in the regression analysis. Preoperative staging data and final surgical margin status were not available within the SEER-Medicare data set and therefore were not included. The model predicted that patients with T4 or lymph node disease benefitted from CRT. The internally validated concordance index was 0.72. CONCLUSIONS The SEER-Medicare database of patients with esophageal cancer can be used to produce a survival prediction tool that: 1) serves as a counseling and decision aid to patients and 2) assists in risk modeling. Patients with T4 or lymph node disease appeared to benefit from CRT. This nomogram may underestimate the benefit of CRT due to its variable downstaging effect on pathologic stage. It is available at skynet.ohsu.edu/ nomograms. Cancer 2014;120:492-498.
|Original language||English (US)|
|Number of pages||7|
|State||Published - Feb 15 2014|
- esophageal cancer
- predictive tool
ASJC Scopus subject areas
- Cancer Research