SynthesisJournal of cancer research and clinical oncology2023
Predictive performance of radiomics for peritoneal metastasis in patients with gastric cancer: a meta-analysis and radiomics quality assessment.
Synthesis in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using artificial intelligence and statistics for managing peritoneal metastases from gastrointestinal cancers.Briefings in functional genomics · 2025Pooled it
- Article
- Development of a multimodal predictive model using PET/CT radiomics and clinical data for preoperative assessment of lymphovascular invasion in gastric cancer.American journal of translational research · 2025Article
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe purpose of this meta-analysis is to systematically review the diagnostic performance of radiomic techniques in predicting peritoneal metastasis in patients with gastric cancer, and to evaluate the quality of current research.
methodsWe searched PubMed, Web of Science, EBSCO, Embase, and Cochrane databases for relevant studies up to April 3, 2023. Data extraction and quality evaluation were performed by two independent reviewers. Then we performed statistical analysis, including plotting the forest plot and summary receiver operating characteristic (SROC) curve, and source of heterogeneity analysis, through the MIDAS module in Stata 15. We performed meta-regression and subgroup analyses to analyze the sources of heterogeneity. Using the QUADAS-2 scale and the RQS scale to assess the quality of retrieved studies.
resultsTen studies with 6199 patients were finally included in our meta-analysis. Pooled sensitivity and specificity were 0.77 (95% confidence interval [CI]: 0.66, 0.86), and 0.88 (95% CI 0.80, 0.93), respectively. The overall AUC was 0.89 (95% CI 0.86, 0.92). The heterogeneity of this meta-analysis was high, with I
conclusionUndoubtedly, radiomics has potential value in diagnosing peritoneal metastasis of gastric cancer, but the quality of current research is inconsistent, and more standardized and high-quality research is still needed in the future to achieve the transformation of radiomics results into clinical applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.