ArticleJournal of inflammation research2021
A Novel Radiomics Nomogram for the Prediction of Secondary Loss of Response to Infliximab in Crohn's Disease.
Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- The predictive value of machine learning for the response to anti-TNF-α therapy in patients with Crohn's disease: a systematic review and meta-analysis.Frontiers in immunology · 2026Pooled it
- CT‑based radiomics of bowel wall at baseline predicts the efficacy of Ustekinumab at week 16 in patients with Crohn's disease.Abdominal radiology (New York) · 2026Article
- A predictive model for differentiating perianal Crohn's disease activity with 3D transrectal ultrasonography.European radiology · 2026Article
- Novel endoluminal parameters for predicting primary loss of response in Crohn's disease: a multi-center study.Insights into imaging · 2025Article
- Correlation between radiomic features of Crohn's disease and secondary loss of response to infliximab.World journal of gastroenterology · 2025Article
- Radiomics prediction of surgery in ulcerative colitis refractory to medical treatment.Techniques in coloproctology · 2025Article
- Computed tomography enterography-based deep learning radiomics to predict stratified healing in patients with Crohn's disease: a multicenter study.Insights into imaging · 2024Article
- CT-based pancreatic radiomics predicts secondary loss of response to infliximab in biologically naïve patients with Crohn's disease.Insights into imaging · 2024Article
- Deep-Learning, Radiomics and Clinic Based Fusion Models for Predicting Response to Infliximab in Crohn's Disease Patients: A Multicentre, Retrospective Study.Journal of inflammation research · 2024Article
- Predicting Treatment Response in Inflammatory Bowel Diseases: Cross-Sectional Imaging Markers.Journal of clinical medicine · 2023Review
- Radiomics of spinal muscles: toward a radiological biomarker for allograft rejection in lung transplant.La Radiologia medica · 2023Article
- Infliximab response associates with radiologic findings in bio-naïve Crohn's disease.European radiology · 2023Article
- Diagnostic performance of texture analysis in the differential diagnosis of perianal fistulising Crohn's disease and glandular anal fistula.World journal of gastrointestinal surgery · 2023Article
- The Role of Radiomics in Fibrosis Crohn's Disease: A Review.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- Inflammatory bowel disease cross-sectional imaging: What's new?United European gastroenterology journal · 2022Review
- A Novel Clinical Radiomics Nomogram to Identify Crohn's Disease from Intestinal Tuberculosis.Journal of inflammation research · 2021Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe prediction of the loss of response (LOR) to infliximab (IFX) is crucial for optimizing treatment strategies and shifting biologics. However, a secondary LOR is difficult to predict by endoscopy due to the intestinal stricture, perforation, and fistulas. This study aimed to develop and validate a radiomic nomogram for the prediction of secondary LOR to IFX in patients with Crohn's disease (CD). PATIENTS AND
methodsA total of 186 biologic-naive patients diagnosed with CD between September 2016 and June 2019 were enrolled. Secondary LOR was determined during week 54. Computed tomography enterography (CTE) texture analysis (TA) features were extracted from lesions and analyzed using LIFEx software. Feature selection was performed by least absolute shrinkage and selection operator (LASSO) and ten-fold cross validation. A nomogram was constructed using multivariable logistic regression, and the internal validation was approached by ten-fold cross validation.
resultsPredictors contained in the radiomics nomogram included three first-order and five second-order signatures. The prediction model presented significant discrimination (AUC, 0.880; 95% CI, 0.816-0.944) and high calibration (mean absolute error of = 0.028). Decision curve analysis (DCA) indicated that the nomogram provided clinical net benefit. Ten-fold cross validation assessed the stability of the nomogram with an AUC of 0.817 and an accuracy of 0.819.
conclusionThis novel radiomics nomogram provides a predictive tool to assess secondary LOR to IFX in patients with Crohn's disease. This tool will help physicians decide when to switch therapy.
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