Erschienen in:
01.12.2015 | Thoracic Oncology
CT Signs Can Predict Treatment Response and Long-Term Survival: A Study in Locally Advanced Esophageal Cancer with Preoperative Chemotherapy
verfasst von:
Xiao-Yan Zhang, MD, Wan-Pu Yan, MD, Yu Sun, MD, Xiao-Ting Li, MPH, Ying Chen, MD, Meng-Ying Fan, MD, Ying Wu, MD, Zhen Liang, MD, Hong-Chao Xiong, MD, Zhi-Long Wang, MD, Ying-Shi Sun, MD, Ke-Neng Chen, MD
Erschienen in:
Annals of Surgical Oncology
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Sonderheft 3/2015
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Abstract
Background
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.
Methods
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.
Results
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).
Conclusions
CT signs can predict therapeutic efficacy and survival outcomes and provide an opportunity to offer additional treatment options before surgery.