CT Signs Can Predict Treatment Response and Long-Term Survival: A Study in Locally Advanced Esophageal Cancer with Preoperative Chemotherapy
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Accurate prediction of treatment response and prognosis before surgery allows prompt therapy adjustment. This study aimed to evaluate the efficacy of computed tomography (CT) signs in predicting treatment response and survival for advanced esophageal squamous cell carcinoma patients who received preoperative chemotherapy.
This study retrospectively enrolled 135 consecutive patients with preoperative chemotherapy from September 2005 to December 2011. A logistic regression model was used to evaluate the association between pathologic response and CT signs. Overall survival (OS) and disease-free survival (DFS) were estimated using the Kaplan–Meier method, and a Cox proportional hazards model was constructed to determine associations between CT signs after neoadjuvant chemotherapy and survival outcomes.
Logistic regression showed that the significant predictors of a poor response were the total number of lymph nodes (LNs) (>6) at baseline [odds ratio (OR) 5.07; 95 % confidence interval (CI) 1.86–13.81; P = 0.002] and the CT value change rate (≤17 %) (OR 2.35; 95 % CI 1.05–5.23; P = 0.037). In the Cox analyses, the significant predictors of OS were preoperative tumor thickness (>10 mm) [hazard ratio (HR) 2.33; 95 % CI 1.36–4; P = 0.002), total number of LNs (>6) (HR 1.88; 95 % CI 1.12–3.17; P = 0.017), and short diameter of the largest LN (>10 mm) (HR 1.87; 95 % CI 1.07–3.28; P = 0.028), whereas only the short diameter of the largest LN was a significant predictor of DFS (HR 2.36; 95 % CI 1.23–4.54; P = 0.01).
CT signs can predict therapeutic efficacy and survival outcomes and provide an opportunity to offer additional treatment options before surgery.
KeywordsOverall Survival Esophageal Cancer Preoperative Chemotherapy Esophageal Squamous Cell Carcinoma Patient Large Lymph Node
This work was supported by the National Basic Research Program of China (973 Program) (Grant No. 2011CB707705, 2011CB504300), National Natural Science Foundation of China (Grant No. 81471640, 81301748), the Capital Health Research and Development of Special Foundation (Grant No. 2011-2015-02), Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20130001110108), Beijing Health System High Level Health Technical Personnel Training Plan (Grant No. 2013-3-083), Education Ministry Innovative Research Team in University (Grant No.IRT13003), Beijing Academic Leaders Program (Grant No. 2009-2-17), Beijing Natural Science Foundation (Grant No. 7102029), Capital Medical Developed Research Found (Grant No. 2007-1023), New Scholar Star Program of Ministry of Education.
Conflict of interest
There are no conflict of interest.
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