Japanese Journal of Pharmacoepidemiology/Yakuzai ekigaku
Online ISSN : 1882-790X
Print ISSN : 1342-0445
ISSN-L : 1342-0445
Original Article
Validation of Epidemiological Methods for Studying the Infection Risk in Rheumatoid Arthritis with Methotrexate Combined Biologicals using Propensity Scores
Takuma KOINUMAManabu AKAZAWA
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2021 Volume 26 Issue 1 Pages 27-40

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Abstract

Objective:In epidemiological studies, changes in patient conditions caused by treatment would be chronologically repeated. Thus, the manner of representing this change can create time-dependent bias which researchers should address. In this study, we aimed to validate the estimators obtained using various epidemiological methods based on the infection risk between the administration of methotrexate (MTX) alone and MTX combined biologicals.

Design:Cohort study

Methods:We extracted data regarding 3769 rheumatoid arthritis (RA) patients, consisting of 2805 patients with MTX alone and 964 patients with MTX combined biologicals from the claims data from JMDC Inc.. We represented each time course using the time axis of the elapsed time, the prescription number, and the administration time to make the corresponding data set. Subsequently, we performed time-conditional propensity score (PS) matching for matched points in each time axis. We also performed Inverse Probability Weighting Estimator (IPW) and Augmented Inverse Probability Weighting Estimator (AIPW) analyses.

Results:The Odds Ratios (OR) estimated by each method using the time axis of the elapsed time, the prescription number, and the administration time were 1.48 (95%CI 0.71-3.11), 1.60 (95%CI 0.72-3.55), and 1.04 (95%CI 0.58-1.86), respectively. We performed PS weighting, of each Average Treatment Effect obtained from IPW, and the AIPW were estimated to be 0.31% (95%CI −0.91-1.53) and 0.29% (95%CI −0.91-1.49), respectively, and the average treatment effect on the treated was estimated to be 0.10% (95%CI −1.11-1.32). We support the findings of a previous study which showed that the combination of biologicals was not statistically associated with increased infection risk.

Conclusion:This study suggests that estimators from different perspectives might be obtained by using some epidemiological methods. Therefore, our results could contribute to the establishment of an improved methodology.

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© 2021 Japanese Society for Pharmacoepidemiology
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