ArticlePhysical and engineering sciences in medicine2022
The value of CT-based radiomics nomogram in differential diagnosis of different histological types of gastric cancer.
Article in Physical and engineering sciences in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Predictive performance of radiomics for peritoneal metastasis in patients with gastric cancer: a meta-analysis and radiomics quality assessment.Journal of cancer research and clinical oncology · 2023Pooled it
- Preoperative prediction of serosal invasion in gastric cancer using multiphase contrast-enhanced CT radiomics.Frontiers in oncology · 2026Article
- The impact of Inter-observation variation on radiomic features of pulmonary nodules.Frontiers in oncology · 2025Article
- Epstein-Barr virus positive gastric cancer: the pathological basis of CT findings and radiomics models prediction.Abdominal radiology (New York) · 2024Article
- Clinical utility of multi-row spiral CT in diagnosing hepatic nodular lesions, gastric cancer, and Crohn's disease: a comprehensive meta-analysis.American journal of clinical and experimental immunology · 2024Article
- Synergizing traditional CT imaging with radiomics: a novel model for preoperative diagnosis of gastric neuroendocrine and mixed adenoneuroendocrine carcinoma.Frontiers in oncology · 2024Article
- Efficacy and safety of gastroscopic hemostasis in the treatment of acute gastric hemorrhage: A meta-analysis.World journal of gastrointestinal oncology · 2023Article
- Imaging in Gastric Cancer: Current Practice and Future Perspectives.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To establish and verify a nomogram based on computed tomography (CT) radiomics analysis to predict the histological types of gastric cancer preoperatively for patients with surgical indications. A sum of 171 patients with gastric cancer were included into this retrospective study. The least absolute shrinkage and selection operator (LASSO) was used for feature selection while the multivariate Logistic regression method was used for radiomics model and nomogram building. The area under curve (AUC) was used for performance evaluation in this study. The radiomics model got AUCs of 0.755 (95% CI 0.650-0.859), 0.71 (95% CI 0.543-0.875) and 0.712 (95% CI 0.500-0.923) for histological prediction in the training, the internal and external verification cohorts. The radiomics nomogram based on radiomics features and Carbohydrate antigen 125 (CA125) showed good discriminant performance in the training cohort (AUC: 0.777; 95% CI 0.679-0.875), the internal (AUC: 0.726; 95% CI 0.5591-0.8933) and external verification cohort (AUC: 0.720; 95% CI 0.5036-0.9358). The calibration curve of the radiomics nomogram also showed good results. The decision curve analysis (DCA) shows that the radiomics nomogram is clinically practical. The radiomics nomogram established and verified in this study showed good performance for the preoperative histological prediction of gastric cancer, which might contribute to the formulation of a better clinical treatment plan.
Indexed as
Identifiers
What OpenQuestion holds
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.