Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma. Issue 5 (2nd March 2022)

• Record Type: Journal Article
• Authors: Boshier, Piers R; Swaray, Alison; Vadhwana, Bhamini; O'Sullivan, Arun; Low, Donald E; Hanna, George B; Peters, Christopher J
• Is Part Of: British journal of surgery. Volume 109:Issue 5(2022)
• Page Start: 418
• Page End: 425
• Publication Date: 2022-03-02
• Subjects: Surgery -- Periodicals; 617.005
• DOI: 10.1093/bjs/znac044
• Languages: English
• ISSNs: 0007-1323

Abstract

Abstract: Background: Oesophageal adenocarcinoma poses a significant global health burden, yet the staging used to predict survival has limited ability to stratify patients by outcome. This study aimed to identify published clinical models that predict survival in oesophageal adenocarcinoma and to evaluate them using an independent international multicentre dataset. Methods: A systematic literature search (title and abstract) using the Ovid Embase and MEDLINE databases (from 1947 to 11 July 2020) was performed. Inclusion criteria were studies that developed or validated a clinical prognostication model to predict either overall or disease-specific survival in patients with oesophageal adenocarcinoma undergoing surgical treatment with curative intent. Published models were validated using an independent dataset of 2450 patients who underwent oesophagectomy for oesophageal adenocarcinoma with curative intent. Results: Seventeen articles were eligible for inclusion in the study. Eleven models were suitable for testing in the independent validation dataset and nine of these were able to stratify patients successfully into groups with significantly different survival outcomes. Area under the receiver operating characteristic curves for individual survival prediction models ranged from 0.658 to 0.705, suggesting poor-to-fair accuracy. Conclusion: This study highlights the need to concentrate on robust methodologies and improved, independent, validation, to increase the likelihood of clinical adoption of survival predictions models. Abstract : This study examines different models predicting long-term survival of patients with oesophageal cancer and assesses their performance in real-world data.