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

• Main Authors: Qi Feng, Margaret T. May, Suzanne Ingle, Ming Lu, Zuyao Yang, Jinling Tang
• Format: Article
• Language: English
• Published: Hindawi Limited 2019-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2019/5634598

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.