J A Ajani1, A M Correa2, W L Hofstetter2, D C Rice2, M A Blum3, A Suzuki3, T Taketa3, J Welsh4, S H Lin4, J H Lee5, M S Bhutani5, W A Ross5, D M Maru6, H A Macapinlac7, J Erasmus8, R Komaki4, R J Mehran2, A A Vaporciyan2, S G Swisher2. 1. Departments of Gastrointestinal Medical Oncology, Houston, USA. Electronic address: jajani@mdanderson.org. 2. Departments of Thoracic and Cardiovascular Surgery, Houston, USA. 3. Departments of Gastrointestinal Medical Oncology, Houston, USA. 4. Departments of Radiation Oncology, Houston, USA. 5. Departments of Gastroenterology, Hepatology, and Nutrition, Houston, USA. 6. Departments of Pathology, Houston, USA. 7. Nuclear Medicine, Houston, USA. 8. Departments of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, USA.
Abstract
BACKGROUND: Approximately 25% of patients with esophageal cancer (EC) who undergo preoperative chemoradiation, achieve a pathologic complete response (pathCR). We hypothesized that a model based on clinical parameters could predict pathCR with a high (≥60%) probability. PATIENTS AND METHODS: We analyzed 322 patients with EC who underwent preoperative chemoradiation. All the patients had baseline and postchemoradiation positron emission tomography (PET) and pre- and postchemoradiation endoscopic biopsy. Logistic regression models were used for analysis, and cross-validation via the bootstrap method was carried out to test the model. RESULTS: The 70 (21.7%) patients who achieved a pathCR lived longer (median overall survival [OS], 79.76 months) than the 252 patients who did not achieve a pathCR (median OS, 39.73 months; OS, P = 0.004; disease-free survival, P = 0.003). In a logistic regression analysis, the following parameters contributed to the prediction model: postchemoradiation PET, postchemoradiation biopsy, sex, histologic tumor grade, and baseline (EUS)T stage. The area under the receiver-operating characteristic curve was 0.72 (95% confidence interval [CI] 0.662-0.787); after the bootstrap validation with 200 repetitions, the bias-corrected AU-ROC was 0.70 (95% CI 0.643-0.728). CONCLUSION: Our data suggest that the logistic regression model can predict pathCR with a high probability. This clinical model could complement others (biomarkers) to predict pathCR.
BACKGROUND: Approximately 25% of patients with esophageal cancer (EC) who undergo preoperative chemoradiation, achieve a pathologic complete response (pathCR). We hypothesized that a model based on clinical parameters could predict pathCR with a high (≥60%) probability. PATIENTS AND METHODS: We analyzed 322 patients with EC who underwent preoperative chemoradiation. All the patients had baseline and postchemoradiation positron emission tomography (PET) and pre- and postchemoradiation endoscopic biopsy. Logistic regression models were used for analysis, and cross-validation via the bootstrap method was carried out to test the model. RESULTS: The 70 (21.7%) patients who achieved a pathCR lived longer (median overall survival [OS], 79.76 months) than the 252 patients who did not achieve a pathCR (median OS, 39.73 months; OS, P = 0.004; disease-free survival, P = 0.003). In a logistic regression analysis, the following parameters contributed to the prediction model: postchemoradiation PET, postchemoradiation biopsy, sex, histologic tumor grade, and baseline (EUS)T stage. The area under the receiver-operating characteristic curve was 0.72 (95% confidence interval [CI] 0.662-0.787); after the bootstrap validation with 200 repetitions, the bias-corrected AU-ROC was 0.70 (95% CI 0.643-0.728). CONCLUSION: Our data suggest that the logistic regression model can predict pathCR with a high probability. This clinical model could complement others (biomarkers) to predict pathCR.
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