Imperial College London
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DrPiersBoshier

Faculty of Medicine, Department of Surgery & Cancer

Clinical Research Fellow
 
 
 
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Contact

 

piers.boshier03 CV

 
 
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Location

 

1035Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Boshier:2022:bjs/znac044,
author = {Boshier, PR and Swaray, A and Vadhwana, B and O'Sullivan, A and Low, DE and Hanna, GB and Peters, CJ and POEM, Biomarkers Consortium and OCCAMS Consortium},
doi = {bjs/znac044},
journal = {British Journal of Surgery},
pages = {418--425},
title = {Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma},
url = {http://dx.doi.org/10.1093/bjs/znac044},
volume = {109},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Boshier,PR
AU  - Swaray,A
AU  - Vadhwana,B
AU  - O'Sullivan,A
AU  - Low,DE
AU  - Hanna,GB
AU  - Peters,CJ
AU  - POEM,Biomarkers Consortium and OCCAMS Consortium
DO  - bjs/znac044
EP  - 425
PY  - 2022///
SN  - 0007-1323
SP  - 418
TI  - Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma
T2  - British Journal of Surgery
UR  - http://dx.doi.org/10.1093/bjs/znac044
UR  - https://www.ncbi.nlm.nih.gov/pubmed/35233634
UR  - https://academic.oup.com/bjs/article/109/5/418/6540610
UR  - http://hdl.handle.net/10044/1/95378
VL  - 109
ER  -
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