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Combined and intraoperative risk modelling for oesophagectomy: A systematic review
BACKGROUND: Oesophageal cancer is the eighth most common malignancy worldwide and is associated with a poor prognosis. Oesophagectomy remains the best prospect for a cure if diagnosed in the early disease stages. However, the procedure is associated with significant morbidity and mortality and is un...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405120/ https://www.ncbi.nlm.nih.gov/pubmed/37555117 http://dx.doi.org/10.4240/wjgs.v15.i7.1485 |
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author | Grantham, James Paul Hii, Amanda Shenfine, Jonathan |
author_facet | Grantham, James Paul Hii, Amanda Shenfine, Jonathan |
author_sort | Grantham, James Paul |
collection | PubMed |
description | BACKGROUND: Oesophageal cancer is the eighth most common malignancy worldwide and is associated with a poor prognosis. Oesophagectomy remains the best prospect for a cure if diagnosed in the early disease stages. However, the procedure is associated with significant morbidity and mortality and is undertaken only after careful consideration. Appropriate patient selection, counselling and resource allocation is essential. Numerous risk models have been devised to guide surgeons in making these decisions. AIM: To evaluate which multivariate risk models, using intraoperative information with or without preoperative information, best predict perioperative oesophagectomy outcomes. METHODS: A systematic review of the MEDLINE, EMBASE and Cochrane databases was undertaken from 2000-2020. The search terms used were [(Oesophagectomy) AND (Model OR Predict OR Risk OR score) AND (Mortality OR morbidity OR complications OR outcomes OR anastomotic leak OR length of stay)]. Articles were included if they assessed multivariate based tools incorporating preoperative and intraoperative variables to forecast patient outcomes after oesophagectomy. Articles were excluded if they only required preoperative or any post-operative data. Studies appraising univariate risk predictors such as preoperative sarcopenia, cardiopulmonary fitness and American Society of Anesthesiologists score were also excluded. The review was conducted following the preferred reporting items for systematic reviews and meta-analyses model. All captured risk models were appraised for clinical credibility, methodological quality, performance, validation and clinical effectiveness. RESULTS: Twenty published studies were identified which examined eleven multivariate risk models. Eight of these combined preoperative and intraoperative data and the remaining three used only intraoperative values. Only two risk models were identified as promising in predicting mortality, namely the Portsmouth physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM) and POSSUM scores. A further two studies, the intraoperative factors and Esophagectomy surgical Apgar score based nomograms, adequately forecasted major morbidity. The latter two models are yet to have external validation and none have been tested for clinical effectiveness. CONCLUSION: Despite the presence of some promising models in forecasting perioperative oesophagectomy outcomes, there is more research required to externally validate these models and demonstrate clinical benefit with the adoption of these models guiding postoperative care and allocating resources. |
format | Online Article Text |
id | pubmed-10405120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-104051202023-08-08 Combined and intraoperative risk modelling for oesophagectomy: A systematic review Grantham, James Paul Hii, Amanda Shenfine, Jonathan World J Gastrointest Surg Systematic Reviews BACKGROUND: Oesophageal cancer is the eighth most common malignancy worldwide and is associated with a poor prognosis. Oesophagectomy remains the best prospect for a cure if diagnosed in the early disease stages. However, the procedure is associated with significant morbidity and mortality and is undertaken only after careful consideration. Appropriate patient selection, counselling and resource allocation is essential. Numerous risk models have been devised to guide surgeons in making these decisions. AIM: To evaluate which multivariate risk models, using intraoperative information with or without preoperative information, best predict perioperative oesophagectomy outcomes. METHODS: A systematic review of the MEDLINE, EMBASE and Cochrane databases was undertaken from 2000-2020. The search terms used were [(Oesophagectomy) AND (Model OR Predict OR Risk OR score) AND (Mortality OR morbidity OR complications OR outcomes OR anastomotic leak OR length of stay)]. Articles were included if they assessed multivariate based tools incorporating preoperative and intraoperative variables to forecast patient outcomes after oesophagectomy. Articles were excluded if they only required preoperative or any post-operative data. Studies appraising univariate risk predictors such as preoperative sarcopenia, cardiopulmonary fitness and American Society of Anesthesiologists score were also excluded. The review was conducted following the preferred reporting items for systematic reviews and meta-analyses model. All captured risk models were appraised for clinical credibility, methodological quality, performance, validation and clinical effectiveness. RESULTS: Twenty published studies were identified which examined eleven multivariate risk models. Eight of these combined preoperative and intraoperative data and the remaining three used only intraoperative values. Only two risk models were identified as promising in predicting mortality, namely the Portsmouth physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM) and POSSUM scores. A further two studies, the intraoperative factors and Esophagectomy surgical Apgar score based nomograms, adequately forecasted major morbidity. The latter two models are yet to have external validation and none have been tested for clinical effectiveness. CONCLUSION: Despite the presence of some promising models in forecasting perioperative oesophagectomy outcomes, there is more research required to externally validate these models and demonstrate clinical benefit with the adoption of these models guiding postoperative care and allocating resources. Baishideng Publishing Group Inc 2023-07-27 2023-07-27 /pmc/articles/PMC10405120/ /pubmed/37555117 http://dx.doi.org/10.4240/wjgs.v15.i7.1485 Text en ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Systematic Reviews Grantham, James Paul Hii, Amanda Shenfine, Jonathan Combined and intraoperative risk modelling for oesophagectomy: A systematic review |
title | Combined and intraoperative risk modelling for oesophagectomy: A systematic review |
title_full | Combined and intraoperative risk modelling for oesophagectomy: A systematic review |
title_fullStr | Combined and intraoperative risk modelling for oesophagectomy: A systematic review |
title_full_unstemmed | Combined and intraoperative risk modelling for oesophagectomy: A systematic review |
title_short | Combined and intraoperative risk modelling for oesophagectomy: A systematic review |
title_sort | combined and intraoperative risk modelling for oesophagectomy: a systematic review |
topic | Systematic Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405120/ https://www.ncbi.nlm.nih.gov/pubmed/37555117 http://dx.doi.org/10.4240/wjgs.v15.i7.1485 |
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