American Joint Committee on Cancer staging system does not accurately predict survival in patients receiving multimodality therapy for esophageal adenocarcinoma Journal Article

Authors: Rizk, N. P.; Venkatraman, E.; Bains, M. S.; Park, B.; Flores, R.; Tang, L.; Ilson, D. H.; Minsky, B. D.; Rusch, V. W.
Article Title: American Joint Committee on Cancer staging system does not accurately predict survival in patients receiving multimodality therapy for esophageal adenocarcinoma
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. © 2007 by American Society of Clinical Oncology.
Keywords: survival; adult; cancer chemotherapy; cancer survival; controlled study; treatment outcome; treatment response; aged; aged, 80 and over; middle aged; survival analysis; retrospective studies; major clinical study; cisplatin; fluorouracil; multimodality cancer therapy; united states; paclitaxel; adjuvant therapy; cancer radiotherapy; chemotherapy, adjuvant; neoadjuvant therapy; radiotherapy, adjuvant; cancer staging; methodology; lymph node metastasis; lymph nodes; neoplasm staging; adenocarcinoma; demography; practice guideline; pathology; retrospective study; prediction; irinotecan; kaplan-meiers estimate; cancer invasion; minimal residual disease; adjuvant chemotherapy; lymph node; prediction and forecasting; predictive value of tests; medical society; esophagus resection; new york city; neoplasm invasiveness; kaplan meier method; esophageal adenocarcinoma; guidelines; statistical model; esophagus tumor; esophageal neoplasms; esophagectomy; likelihood functions; partition coefficient
Journal Title: Journal of Clinical Oncology
Volume: 25
Issue: 5
ISSN: 0732-183X
Publisher: American Society of Clinical Oncology  
Date Published: 2007-02-10
Start Page: 507
End Page: 512
Language: English
DOI: 10.1200/jco.2006.08.0101
PUBMED: 17290058
PROVIDER: scopus
Notes: --- - "Cited By (since 1996): 59" - "Export Date: 17 November 2011" - "CODEN: JCOND" - "Source: Scopus"
Altmetric Score
MSK Authors
  1. Venkatraman Ennapadam Seshan
    285 Seshan
  2. Valerie W Rusch
    652 Rusch
  3. Bruce Minsky
    258 Minsky
  4. Nabil Rizk
    134 Rizk
  5. Raja Flores
    107 Flores
  6. Bernard J Park
    155 Park
  7. Laura Hong Tang
    320 Tang
  8. David H Ilson
    269 Ilson
  9. Manjit S Bains
    227 Bains