SynthesisFrontiers in medicine2026
Systematic review and meta-analysis of risk prediction models for anastomotic leak after gastric cancer surgery.
Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The study aimed to evaluate risk prediction models for anastomotic leak (AL) after gastric cancer (GC) surgery through a systematic review and meta-analysis. Methods: We searched Chinese and English databases from inception to 25 December 2025. The Prediction model Risk Of Bias ASsessment Tool (PROBAST) was used for quality assessment. A meta-analysis was performed to pool the area under the receiver operating characteristic curve (AUC) values from externally validated studies. Subgroup analyses were performed to explore optimism bias. Predictors were qualitatively synthesized. Results: A total of 18 studies (15,783 patients) were included. The pooled external validation AUC was 0.795 (95% CI: 0.741-0.840; Conclusion: Current AL prediction models show moderate-to-good discrimination but suffer from overfitting and methodological bias. Postoperative dynamic indicators may improve performance, but this requires confirmation. Future research should focus on prospective, multicenter, cross-regional external validation and better calibration reporting. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=272725, PROSPERO (CRD420251272725).
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