How well does pathologic stage predict survival for esophageal adenocarcinoma after neoadjuvant therapy?
Year: 2015
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Cancer staging systems are designed to predict survival and stratify patients. The 7(th) edition of the American Joint Commission on Cancer (AJCC7) staging system for esophageal cancer was modeled using survival data on patients who underwent esophagectomy without induction or adjuvant therapy. In the United States, the standard of care for patients with locally advanced tumors often includes neoadjuvant therapy. The prognostic value of the pathologic stage for these patients is unknown. METHODS: Data from the Surveillance Epidemiology and End Results (SEER) were used to identify 1,243 patients with adenocarcinoma of the esophagus who underwent surgery after neoadjuvant therapy from 1988-2009. Included in the analysis were pathologically-staged, non-metastatic patients who had radiation as part of their neoadjuvant therapy. The AJCC7 staging system and an alternate system were modeled using Kaplan-Meier survival methods. The two systems were compared using log-rank chi-squared statistics, with large chi-squared values indicating accuracy in survival prediction. RESULTS: The AJCC staging system was able to predict survival for patients who had neoadjuvant therapy (P<0.001, chi-squared =81.8); however, there was little distinction between stage subgroups. Patients with neoadjuvant radiotherapy had improved survival for pathologic stage II and III disease. An alternative, simpler staging system was better able to stratify patients with neoadjuvant therapy (P<0.001, chi-squared =100.5). CONCLUSIONS: The current AJCC staging system is able to predict survival in esophageal adenocarcinoma patients undergoing neoadjuvant therapy, however, there is less distinction among stage subgroups. An alternative, simpler stage grouping may better stratify patients receiving neoadjuvant therapy.
Source: PubMed Central
Authors: Jae Y Kim, Rebecca A Nelson, Joseph Kim, Dan Raz
Institutions: City Of Hope National Medical Center, City of Hope
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2236270365