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Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review

BACKGROUND: This study was designed to review the methodology and reporting of gastric cancer prognostic models and identify potential problems in model development. METHODS: This systematic review was conducted following the CHARMS checklist. MEDLINE and EMBASE were searched. Information on patient...

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Autores principales: Feng, Qi, May, Margaret T., Ingle, Suzanne, Lu, Ming, Yang, Zuyao, Tang, Jinling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766665/
https://www.ncbi.nlm.nih.gov/pubmed/31641669
http://dx.doi.org/10.1155/2019/5634598
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author Feng, Qi
May, Margaret T.
Ingle, Suzanne
Lu, Ming
Yang, Zuyao
Tang, Jinling
author_facet Feng, Qi
May, Margaret T.
Ingle, Suzanne
Lu, Ming
Yang, Zuyao
Tang, Jinling
author_sort Feng, Qi
collection PubMed
description BACKGROUND: This study was designed to review the methodology and reporting of gastric cancer prognostic models and identify potential problems in model development. METHODS: This systematic review was conducted following the CHARMS checklist. MEDLINE and EMBASE were searched. Information on patient characteristics, methodological details, and models' performance was extracted. Descriptive statistics was used to summarize the methodological and reporting quality. RESULTS: In total, 101 model developments and 32 external validations were included. The median (range) of training sample size, number of death, and number of final predictors were 360 (29 to 15320), 193 (14 to 9560), and 5 (2 to 53), respectively. Ninety-one models were developed from routine clinical data. Statistical assumptions were reported to be checked in only nine models. Most model developments (94/101) used complete-case analysis. Discrimination and calibration were not reported in 33 and 55 models, respectively. The majority of models (81/101) have never been externally validated. None of the models have been evaluated regarding clinical impact. CONCLUSIONS: Many prognostic models have been developed, but their usefulness in clinical practice remains uncertain due to methodological shortcomings, insufficient reporting, and lack of external validation and impact studies. IMPACT: Future research should improve methodological and reporting quality and emphasize more on external validation and impact assessment.
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spelling pubmed-67666652019-10-22 Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review Feng, Qi May, Margaret T. Ingle, Suzanne Lu, Ming Yang, Zuyao Tang, Jinling Biomed Res Int Review Article BACKGROUND: This study was designed to review the methodology and reporting of gastric cancer prognostic models and identify potential problems in model development. METHODS: This systematic review was conducted following the CHARMS checklist. MEDLINE and EMBASE were searched. Information on patient characteristics, methodological details, and models' performance was extracted. Descriptive statistics was used to summarize the methodological and reporting quality. RESULTS: In total, 101 model developments and 32 external validations were included. The median (range) of training sample size, number of death, and number of final predictors were 360 (29 to 15320), 193 (14 to 9560), and 5 (2 to 53), respectively. Ninety-one models were developed from routine clinical data. Statistical assumptions were reported to be checked in only nine models. Most model developments (94/101) used complete-case analysis. Discrimination and calibration were not reported in 33 and 55 models, respectively. The majority of models (81/101) have never been externally validated. None of the models have been evaluated regarding clinical impact. CONCLUSIONS: Many prognostic models have been developed, but their usefulness in clinical practice remains uncertain due to methodological shortcomings, insufficient reporting, and lack of external validation and impact studies. IMPACT: Future research should improve methodological and reporting quality and emphasize more on external validation and impact assessment. Hindawi 2019-09-18 /pmc/articles/PMC6766665/ /pubmed/31641669 http://dx.doi.org/10.1155/2019/5634598 Text en Copyright © 2019 Qi Feng et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Feng, Qi
May, Margaret T.
Ingle, Suzanne
Lu, Ming
Yang, Zuyao
Tang, Jinling
Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review
title Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review
title_full Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review
title_fullStr Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review
title_full_unstemmed Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review
title_short Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review
title_sort prognostic models for predicting overall survival in patients with primary gastric cancer: a systematic review
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766665/
https://www.ncbi.nlm.nih.gov/pubmed/31641669
http://dx.doi.org/10.1155/2019/5634598
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