SynthesisHealth technology assessment (Winchester, England)2021
Prognostic biomarkers to identify patients likely to develop severe Crohn's disease: a systematic review.
Synthesis in Health technology assessment (Winchester, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Methodological review of the level of statistical support declared in radiological research articles.The British journal of radiology · 2026Review
- Magnetic resonance enterography to predict disabling disease in newly diagnosed Crohn's disease: the METRIC-EF multivariable prediction model, multicentre diagnostic inception cohort study.Health technology assessment (Winchester, England) · 2026Article
- Multimodal biomarkers and prediction models for stricturing and penetrating progression in Crohn's disease.Frontiers in medicine · 2026Review
- Magnetic resonance enterography to predict subsequent disabling Crohn's disease in newly diagnosed patients (METRIC-EF)-multivariable prediction model, multicentre diagnostic inception cohort.European radiology · 2025Article
- Small Bowel Motility Quantified by Cine MRI to Predict Longer-Term Response in Patients with Crohn's Disease Commencing Biological Therapy: The Motility Study.Inflammatory bowel diseases · 2025Article
- Magnetic Resonance Enterography and Intestinal Ultrasound for the Assessment and Monitoring of Crohn's Disease.Journal of Crohn's & colitis · 2024Review
- Analysis of the risk of future gastrointestinal surgery in Crohn's disease with stricture.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association · 2024Article
- Mathematical Models Including microRNA Levels of Mesenteric Adipose Tissue May Predict Postoperative Relapse in Crohn's Disease Patients.Gastro hep advances · 2024Article
- Article
- Detection of 41-kDa bacterial flagellin protein by the lymphocyte transformation test-memory lymphocyte immunostimulation assay.American journal of clinical and experimental immunology · 2022Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundIdentification of biomarkers that predict severe Crohn's disease is an urgent unmet research need, but existing research is piecemeal and haphazard.
objectiveTo identify biomarkers that are potentially able to predict the development of subsequent severe Crohn's disease.
designThis was a prognostic systematic review with meta-analysis reserved for those potential predictors with sufficient existing research (defined as five or more primary studies). DATA SOURCES: PubMed and EMBASE searched from inception to 1 January 2016, updated to 1 January 2018. REVIEW
methodsEligible studies were studies that compared biomarkers in patients who did or did not subsequently develop severe Crohn's disease. We excluded biomarkers that had insufficient research evidence. A clinician and two statisticians independently extracted data relating to predictors, severe disease definitions, event numbers and outcomes, including odds/hazard ratios. We assessed risk of bias. We searched for associations with subsequent severe disease rather than precise estimates of strength. A random-effects meta-analysis was performed separately for odds ratios.
resultsIn total, 29,950 abstracts yielded just 71 individual studies, reporting 56 non-overlapping cohorts. Five clinical biomarkers (Montreal behaviour, age, disease duration, disease location and smoking), two serological biomarkers (anti- LIMITATIONS: Definitions of severe disease varied widely, and some studies confounded diagnosis and prognosis. Risk of bias was rated as 'high' in 92% of studies overall. Some biomarkers that are used regularly in daily practice, for example C-reactive protein, were studied too infrequently for meta-analysis.
conclusionsResearch for individual biomarkers to predict severe Crohn's disease is scant, heterogeneous and at a high risk of bias. Despite a large amount of potential research, we encountered relatively few biomarkers with data sufficient for meta-analysis, identifying only eight biomarkers with potential predictive capability. FUTURE WORK: We will use existing data sets to develop and then validate a predictive model based on the potential predictors identified by this systematic review. Contingent on the outcome of that research, a prospective external validation may prove clinically desirable. STUDY REGISTRATION: This study is registered as PROSPERO CRD42016029363.
fundingThis project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in
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