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Published in: Journal of Gastrointestinal Surgery 8/2014

01-08-2014 | Review Article

Individual Risk Modelling for Esophagectomy: A Systematic Review

Authors: John M. Findlay, Richard S. Gillies, Bruno Sgromo, Robert E. K. Marshall, Mark R. Middleton, Nicholas D. Maynard

Published in: Journal of Gastrointestinal Surgery | Issue 8/2014

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Abstract

Introduction

A number of models have been applied to predict outcomes from esophagectomy. This systematic review aimed to compare their clinical credibility, methodological quality and performance.

Methods

A systematic review of the PubMed, EMBASE and Cochrane databases was performed in October 2012. Model and study quality were appraised using the framework of Minne et al.

Results

Twenty studies were included in total; these were heterogeneous, retrospective and conducted over a number of years; all models were generated via logistic regression. Overall mortality was high, and consequently not representative of current practice. Clinical credibility and methodological quality were variable, with frequent failure to perform internal validation and variable presentation of calibration and discrimination metrics. P-POSSUM demonstrated the best calibration and discrimination for predicting mortality. Other than the Southampton score (which has yet to be externally validated) and the Amsterdam score, no studies had utility in predicting complications.

Conclusion

Whilst a number of models have been developed, adapted or trialled, due to numerous limitations, larger and more contemporary studies are required to develop and validate models further. The role of alternative techniques such as decision tree analysis and artificial neural networks is not known.
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Metadata
Title
Individual Risk Modelling for Esophagectomy: A Systematic Review
Authors
John M. Findlay
Richard S. Gillies
Bruno Sgromo
Robert E. K. Marshall
Mark R. Middleton
Nicholas D. Maynard
Publication date
01-08-2014
Publisher
Springer US
Published in
Journal of Gastrointestinal Surgery / Issue 8/2014
Print ISSN: 1091-255X
Electronic ISSN: 1873-4626
DOI
https://doi.org/10.1007/s11605-014-2524-2

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