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  • Title: American Joint Committee on Cancer staging system does not accurately predict survival in patients receiving multimodality therapy for esophageal adenocarcinoma.
    Author: Rizk NP, Venkatraman E, Bains MS, Park B, Flores R, Tang L, Ilson DH, Minsky BD, Rusch VW, American Joint Committee on Cancer.
    Journal: J Clin Oncol; 2007 Feb 10; 25(5):507-12. PubMed ID: 17290058.
    Abstract:
    PURPOSE: In patients with adenocarcinoma of the esophagus who receive preoperative chemoradiotherapy (CRT), American Joint Committee on Cancer (AJCC) stage, pathologic complete response (pCR), and estimated treatment response are various means used to stratify patients prognostically after surgery. However, none of these methods has been formally evaluated. The purpose of this study was to establish prognostic pathologic variables after CRT. PATIENTS AND METHODS: A retrospective review was performed of patients with esophageal adenocarcinoma who received CRT before esophagectomy. Data collected included demographics, CRT details, pathologic findings, and survival. Statistical methods included recursive partitioning and Kaplan-Meier analyses. RESULTS: Two hundred seventy-six patients were appropriate for this analysis. Kaplan-Meier analysis indicates that the current AJCC system poorly distinguishes between stages 0 to IIA (P = .52), IIB to III (P = .87), and IVA to IVB (P = .30). The presence of a pCR conferred improved survival over residual disease (P = .01). Recursive partitioning analysis indicates that involved lymph nodes and metastatic disease are the best predictors of survival and that depth of invasion and degree of treatment response are less predictive. CONCLUSION: The current AJCC staging system is not a good predictor of survival after CRT. Although patients with a pCR do have improved long-term survival relative to patients with residual disease, this method places too much emphasis on residual depth of invasion and fails to identify patients with residual disease who have good long-term survival. Recursive partitioning analysis more accurately identifies nodal disease and metastatic disease as the most important prognostic variables. Degree of treatment response is less prognostic than nodal involvement.
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