Derivation and validation of a risk prediction score for nonsteroidal anti‐inflammatory drug‐related serious gastrointestinal complications in the elderly

Author:

Lee Suhyun1ORCID,Heo Kyu‐Nam1ORCID,Lee Mee Yeon1,Ah Young‐Mi2,Shin Jaekyu3,Lee Ju‐Yeun1ORCID

Affiliation:

1. College of Pharmacy and Research Institute of Pharmaceutical Sciences Seoul National University 1, Gwanak‐ro Seoul 08826 Republic of Korea

2. College of Pharmacy Yeungnam University Gyeongsan Gyeongbuk 38541 Republic of Korea

3. Department of Clinical Pharmacy, School of Pharmacy University of California, San Francisco 533 Parnassus Avenue, U585, Box 0622 San Francisco California 94143‐0622 USA

Abstract

AimsFew studies have quantified the impact of risk factors on GI complications in elderly nonsteroidal anti‐inflammatory drug (NSAID) users. This study aimed to develop and validate a risk prediction score for severe GI complications to identify high‐risk elderly patients using NSAID.MethodsWe used the following two Korean claims datasets: customized data with an enrolment period 2016–2017 for model development, and the sample data in 2019 for external validation. We conducted a nested case–control study for model development and validation. NSAID users were identified as the elderly (≥65 years) who received NSAIDs for more than 30 days. Serious GI complications were defined as hospitalizations or emergency department visits, with a main diagnosis of GI bleeding or perforation. We applied the logistic least absolute shrinkage and selection operator (LASSO) regression model for variable selection and model fitting.ResultsWe identified 8176 cases and 81 760 controls with a 1:10 matched follow‐up period in the derivation cohort. In the external validation cohort, we identified 372 cases from 254 551 patients. The risk predictors were high‐dose NSAIDs, nonselective NSAID, complicated GI ulcer history, male sex, concomitant gastroprotective agents, relevant co‐medications, severe renal disease and cirrhosis. Area under the receiver operating characteristic curve was 0.79 (95% confidence interval, 0.77–0.81) in the external validation dataset.ConclusionsThe prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high‐risk elderly patients.

Funder

National Research Foundation of Korea

Seoul National University

Publisher

Wiley

Subject

Pharmacology (medical),Pharmacology

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