4.6 Article

Predictors of pathological complete response to neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma

Journal

WORLD JOURNAL OF SURGICAL ONCOLOGY
Volume 12, Issue -, Pages -

Publisher

BIOMED CENTRAL LTD
DOI: 10.1186/1477-7819-12-170

Keywords

Pathological complete response; Esophageal cancer; Predictors; Neoadjuvant chemoradiotherapy

Funding

  1. National Science Council, Executive Yuan [NSC101-2314-B-182-094-MY2]
  2. Chang Gung University, Taiwan, Republic of China [NMRPD1B1431]

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Backgrounds: In this study, we evaluated the factors associated with a pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) for esophageal squamous cell carcinoma (ESCC). Methods: Pre-nCRT parameters in ESCC patients treated between 1999 and 2006 were analyzed to identify predictors of pCR. All patients received 5-fluorouracil/cisplatin-based chemotherapy and external beam radiation followed by scheduled esophagectomy. Variables were analyzed using univariate and multivariate analyses with pCR as the dependent variable. Estimated pCR rate was calculated with a regression model. Results: Fifty-nine (20.9%) of 282 patients achieved pCR. Univariate analysis identified four patient factors (age, smoking status, drinking history and hypertension), one pre-nCRT parameter (tumor length) as significant predictors of pCR (all P < 0.05). On multivariate analysis, tumor length <= 3 cm (favorable, odds ratio (OR): 4.85, P = 0.001), patient age >55 years (favorable, OR: 1.95, P = 0.035), and being a non-smoker (favorable, OR: 3.6, P = 0.003) were independent predictors of pCR. The estimated pCR rates based on a logistic regression including those three predictors were 71%, 35 to approximately 58%, 19 to approximately 38%, and 12% for patients with 3, 2, 1 and 0 predictors, respectively. Conclusion: Age, smoking habit and tumor length were important pCR predictors. These factors may be used to predict outcomes for ESCC patients receiving nCRT, to develop risk-adapted treatment strategies, and to select patients who could participate in trials on new therapies.

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