ArticleThe British journal of radiology2023
Computed tomography-based radiomics nomogram for the pre-operative prediction of BRAF mutation and clinical outcomes in patients with colorectal cancer: a double-center study.
Article in The British journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence in the radiologic diagnosis of major urological cancers: a meta-analysis.World journal of urology · 2026Pooled it
- Radiomics Models as Tools for Predicting Genetic Mutations in Colorectal Cancer: A Systematic Review and Meta-Analysis.Journal of gastrointestinal cancer · 2026Pooled it
- Radiomics in precision medicine for colorectal cancer: a bibliometric analysis (2013-2023).Frontiers in oncology · 2024Pooled it
- Habitat-based amide proton transfer-weighted MRI model for predicting BRAF mutation and prognostic stratification in rectal cancer.Frontiers in oncology · 2026Article
- Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment.Diagnostics (Basel, Switzerland) · 2024Article
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Abstract
objectiveTo develop and validate a radiomics nomogram based on CT for the pre-operative prediction of BRAF mutation and clinical outcomes in patients with colorectal cancer (CRC).
methodsA total of 451 CRC patients (training cohort = 190; internal validation cohort = 125; external validation cohort = 136) from 2 centers were retrospectively included. Least absolute shrinkage and selection operator regression was used to select radiomics features and the radiomics score (Radscore) was calculated. Nomogram was constructed by combining Radscore and significant clinical predictors. Receiver operating characteristic curve analysis, calibration curve and decision curve analysis were used to evaluate the predictive performance of the nomogram. Kaplan‒Meier survival curves based on the radiomics nomogram were used to assess overall survival (OS) of the entire cohort.
resultsThe Radscore consisted of nine radiomics features which were the most relevant to BRAF mutation. The radiomics nomogram integrating Radscore and clinical independent predictors (age, tumor location and cN stage) showed good calibration and discrimination with AUCs of 0.86 (95% CI: 0.80-0.91), 0.82 (95% CI: 0.74-0.90) and 0.82 (95% CI: 0.75-0.90) in the training cohort, internal validation and external validation cohorts, respectively. Furthermore,the performance of nomogram was significantly better than that of the clinical model (
conclusionThe radiomics nomogram showed good performance in predicting BRAF mutation and OS of CRC patients, which could provide valuable information for individualized treatment. ADVANCES IN KNOWLEDGE: The radiomics nomogram could effectively predict BRAF mutation and OS in patients with CRC. High-risk BRAF mutation group identified by the radiomics nomogram was independently associated with poor OS.
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