Observational studyInflammatory bowel diseases2018
The Association Between Arthralgia and Vedolizumab Using Natural Language Processing.
Observational study in Inflammatory bowel diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
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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
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Beyond the Gut: A Systematic Review and Meta-analysis of Advanced Therapies for Inflammatory Bowel Disease-associated Extraintestinal Manifestations.Journal of Crohn's & colitis · 2024Pooled it
- A decade of clinical data with vedolizumab: the past, present, and future.Therapeutic advances in gastroenterology · 2026Review
- On the use of natural language processing to implement the target trial framework using unstructured data from the electronic health record.Global epidemiology · 2025Article
- Accurate, Robust, and Scalable Machine Abstraction of Mayo Endoscopic Subscores From Colonoscopy Reports.Inflammatory bowel diseases · 2025Article
- Large Language Models Outperform Traditional Natural Language Processing Methods in Extracting Patient-Reported Outcomes in Inflammatory Bowel Disease.Gastro hep advances · 2025Article
- An Insight into Patients' Perspectives of Ulcerative Colitis Flares via Analysis of Online Public Forum Posts.Inflammatory bowel diseases · 2024Article
- Large language models outperform traditional natural language processing methods in extracting patient-reported outcomes in IBD.medRxiv : the preprint server for health sciences · 2024Article
- Initiation of vedolizumab did not provoke new-onset spondylarthritis in patients with inflammatory bowel disease: A prospective 24-week study with imaging assessments.United European gastroenterology journal · 2024Observational
- Real-world effectiveness of ustekinumab and vedolizumab in TNF-exposed pediatric patients with ulcerative colitis.Journal of pediatric gastroenterology and nutrition · 2024Article
- Artificial intelligence for predicting treatment responses in autoimmune rheumatic diseases: advancements, challenges, and future perspectives.Frontiers in immunology · 2024Review
- A Systematic Temporal Extraction Pipeline for Medical Concepts in Clinical Notes.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Artificial Intelligence for Inflammatory Bowel Diseases (IBD); Accurately Predicting Adverse Outcomes Using Machine Learning.Digestive diseases and sciences · 2022Article
- Artificial Intelligence for Disease Assessment in Inflammatory Bowel Disease: How Will it Change Our Practice?Gastroenterology · 2022Review
- Review
- Evolving Role and Future Directions of Natural Language Processing in Gastroenterology.Digestive diseases and sciences · 2021Review
- Review
- Clinical characteristics and comorbidities in adult-onset Still's disease using a large US administrative claims database.Rheumatology (Oxford, England) · 2020Article
- Low Rate of Drug Discontinuation, Frequent Need for Dose Adjustment, and No Association with Development of New Arthralgia in Patients Treated with Vedolizumab: Results from a Tertiary Referral IBD Center.Digestive diseases and sciences · 2020Article
- High-throughput phenotyping with electronic medical record data using a common semi-supervised approach (PheCAP).Nature protocols · 2019Article
- Application of Big Data analysis in gastrointestinal research.World journal of gastroenterology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
Background: The gut-selective nature of vedolizumab has raised questions regarding increased joint pain or arthralgia with its use in inflammatory bowel disease (IBD) patients. As arthralgias are seldom coded and thus difficult to study, few studies have examined the comparative risk of arthralgia between vedolizumab and tumor necrosis factor inhibitor (TNFi). Our objectives were to evaluate the application of natural language processing (NLP) to identify arthralgia in the clinical notes and to compare the risk of arthralgia between vedolizumab and TNFi in IBD. Methods: We performed a retrospective study using a validated electronic medical record (EMR)-based IBD cohort from 2 large tertiary care centers. The index date was the first date of vedolizumab or TNFi prescription. Baseline covariates were assessed 1 year before the index date; patients were followed 1 year after the index date. The primary outcome was arthralgia, defined using NLP. Using inverse probability of treatment weight to balance the cohorts, we then constructed Cox regression models to calculate the hazard ratio (HR) for arthralgia in the vedolizumab and TNFi groups. Results: We studied 367 IBD patients on vedolizumab and 1218 IBD patients on TNFi. Patients on vedolizumab were older (mean age, 41.2 vs 34.9 years) and had more prevalent use of immunomodulators (52.3% vs 31.9%) than TNFi users. Our data did not observe a significantly increased risk of arthralgia in the vedolizumab group compared with TNFi (HR, 1.20; 95% confidence interval, 0.97-1.49). Conclusions: In this large observational study, we did not find a significantly increased risk of arthralgia associated with vedolizumab use compared with TNFi.
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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.