Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 4 appraisals
Gut
Digital twins in IBD-bridging data, biology and trial innovation
Clinical trials in IBD face difficulties of escalating complexity, high costs and challenges in recruitment. Digital twins are virtual, data-driven replicas of individual patients that model disease trajectories and treatment responses, which offer a potential innovative change in the conduct of clinical trials in IBD. Built from multimodal datasets integrating clinical, molecular, imaging and real-world data, digital twins can generate synthetic control arms, enable adaptive randomisation and predict disease relapse or treatment response. Early studies across oncology, cardiology and endocrinology demonstrate their feasibility and potential to improve statistical power while reducing patient burden. However, the integration of digital twins into clinical trials in IBD will require rigorous validation frameworks, transparent data governance and attention to algorithmic bias and consent. In this review, we explore how digital twins may transform IBD research-from in silico simulation to adaptive, patient-centred trial design-and outline the regulatory, ethical and logistical challenges to be considered in order to successfully integrate them into future trials.
10 July 2026
Read appraisal →BMJ open gastroenterology
Safety and efficacy of advanced combination therapies for treating inflammatory bowel disease in adults: a systematic review and meta-analysis
OBJECTIVES: To systematically synthesise available evidence on the safety of advanced combination therapy (ACT) in adults with inflammatory bowel disease (IBD), with secondary exploratory evaluation of efficacy outcomes. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Searches of Embase (via Ovid), MEDLINE and PubMed were initially undertaken on 9 May 2025 and updated on 8 April 2026. Additional studies were identified through hand-searching and reference list screening. Eligible publications were restricted to those published between 1 January 2015 and 31 March 2026. ELIGIBILITY CRITERIA: We included randomised controlled trials as well as observational and descriptive studies. Conference abstracts, reviews, editorials and commentaries were excluded. Inclusion was restricted to publications in English. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened studies, extracted data and assessed risk of bias using Joanna Briggs Institute tools and Cochrane RoB-1. Pooled proportions of total adverse events (TAEs), serious adverse events (SAEs) and treatment discontinuations were calculated using random-effects meta-analysis. Subgroup analyses were conducted by drug class. Where meta-analysis was not appropriate, findings were narratively synthesised. RESULTS: Fifty-two studies (n=2022 participants) were included. The most frequent combinations were anti-TNFa plus integrin inhibitors and interleukin (IL) 23 plus integrin inhibitors. Pooled analyses demonstrated low rates of SAEs (eg, anti-TNFa plus integrin inhibitors: 2.7%, 95% CI 0.22% to 6.86%) and discontinuations (6.38%, 95% CI 2.36% to 11.58%), although heterogeneity was substantial and certainty of evidence was very low, with some analyses based on small sample sizes. CONCLUSION: ACT may be associated with low rates of SAEs in selected patients with refractory IBD; however, the evidence is limited by small sample sizes, heterogeneity and predominantly observational designs. Robust conclusions regarding safety and efficacy cannot be made due to very low GRADE certainty. PROSPERO REGISTRATION NUMBER: CRD420251025883.
13 June 2026
Read appraisal →Journal of ethnopharmacology
Exploring the molecular mechanism of Shenling baizhu formula in the treatment of ulcerative colitis via the cGMP-PKG signaling pathway
ETHNOPHARMACOLOGICAL RELEVANCE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by symptoms such as persistent diarrhea. Shenlingbaizhu Formula (SLBZ), a classical Chinese herbal formula with centuries of clinical application, has long been used to treat such gastrointestinal disorders. This historical efficacy provides a strong ethnopharmacological rationale for investigating its therapeutic potential and underlying mechanisms in UC. AIM OF THE STUDY: To elucidate the molecular mechanism by which SLBZ ameliorates UC by restoring the intestinal barrier via the sGC-cGMP-PKG signaling pathway. MATERIALS AND METHODS: To systematically investigate the therapeutic effects of SLBZ on UC, we established a dextran sulfate sodium (DSS)-induced colitis model in 57BL/6 mice. Comprehensive evaluations were conducted to assess intestinal barrier function and elucidate underlying mechanisms, including histological analysis, immunofluorescence staining of tight junction proteins, 16S rDNA sequencing for gut microbiota profiling, transcriptomic analysis for gene expression patterns, and Western blot validation of key proteins. Furthermore, a multi-tiered experimental strategy was employed, integrating molecular modeling, machine learning algorithms, graph neural network (GNN) approaches and in vitro experiments using Caco-2 cell monolayers, to systematically validate the sGC-cGMP-PKG signaling pathway and identify bioactive compounds responsible for SLBZ's therapeutic effects. RESULTS: SLBZ treatment markedly alleviated UC symptoms in mice and restored intestinal barrier function through dual mechanisms: upregulation of tight junction proteins (ZO-1/Occludin) and modulation of gut microbiota composition. Transcriptomic analysis pinpointed the cGMP-PKG signaling pathway as a central therapeutic target. Through an integrated approach combining molecular docking, machine learning (random forest algorithm), and deep neural network analysis, we identified soluble guanylate cyclase (sGC) as the primary molecular target, with Choerospondin emerging as a key bioactive component. Mechanistic investigations demonstrated that SLBZ robustly activated the sGC-cGMP-PKG axis both in vivo (colon tissues) and in vitro (Caco-2 cells), culminating in significant suppression of intestinal epithelial apoptosis. CONCLUSION: SLBZ alleviates UC by activating the sGC-cGMP-PKG pathway to restore intestinal barrier function through tight junction upregulation and microbiota modulation. Our study both validates SLBZ's traditional use and identifies this pathway as a novel therapeutic target for UC.
12 June 2026
Read appraisal →Cell reports
Artificial intelligence-driven donor-recipient gut microbiome matching for optimized fecal microbiota transplantation
Fecal microbiota transplantation (FMT) has emerged as a promising therapy for gastrointestinal diseases, yet its clinical efficacy remains individually variable. Here, we analyze multi-kingdom and functional profiles in pre- and post-FMT metagenomes from 515 FMTs across 30 cohorts and 12 diseases, in which 94 metagenomes from 44 FMTs are newly collected. We reveal a robust association between clinical efficacy and post-FMT microbiome convergence of recipients toward donors, across diseases. To predict post-FMT microbial convergence, we develop MOZAIC (Microbiome Matching Optimization via Artificial Intelligence), a framework that integrates multi-dimensional donor-recipient microbiota features. MOZAIC achieves an average area under the curve (AUC) of 0.88 and accuracy/recall >0.80 in forecasting microbiome convergence, with 78.7% accuracy in predicting clinical outcomes, and retrospectively simulates a 1.44-fold improvement (from 49.4% to 71.0%) in clinical response rates over baseline. This study establishes microbiome convergence as a key mediator of FMT and provides a scalable tool for precision matching in microbiota-based therapies.
28 May 2026
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