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The Association Between Arthralgia and Vedolizumab Using Natural Language Processing

Authors :
Ashwin N. Ananthakrishnan
Andrew Cagan
Katherine P. Liao
Allison Bond
Jie Huang
Tianrun Cai
Tzu-Chieh Lin
Gwendolyn Kane-Wanger
Shawn N. Murphy
Publication Year :
2018
Publisher :
Oxford University Press, 2018.

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.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....98bd7fd70bb02759603714f5d3536aa9