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Derivation and validation of a risk prediction score for nonsteroidal anti-inflammatory drug-related serious gastrointestinal complications in the elderly
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  • Suhyun Lee,
  • Kyu-Nam Heo,
  • Mee Yeon Lee,
  • Young-Mi Ah,
  • Jaekyu Shin,
  • Ju-Yeun Lee
Suhyun Lee
Seoul National University

Corresponding Author:[email protected]

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Kyu-Nam Heo
Seoul National University
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Mee Yeon Lee
Seoul National University
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Young-Mi Ah
Yeungnam University College of Pharmacy
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Jaekyu Shin
University of California San Francisco Department of Clinical Pharmacy
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Ju-Yeun Lee
Seoul National University
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Aim: Although there is a high risk of gastrointestinal (GI) bleeding in the elderly, few 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 to identify high-risk elderly patients using NSAID for severe GI complications. Methods: We used the following two Korean claims datasets: customized data with an enrollment 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. Patients who experienced serious GI complications, defined as hospitalizations or emergency department visits, were diagnosed with GI bleeding or perforation. We derived a model using logistic regression and cross-validation. Results: In the external validation cohort, we identified 372 cases from 254,551 patients. We identified 8,176 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, NSAID type, complicated GI ulcer history, male sex, concomitant gastroprotective agents, relevant co-medications, severe renal disease, and cirrhosis. Area under the receiver operating characteristic curves was 0.77 (95% confidence interval, 0.75–0.80) in the external validation dataset. Conclusion: The prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high-risk elderly patients.
03 May 2022Submitted to British Journal of Clinical Pharmacology
03 May 2022Assigned to Editor
03 May 2022Submission Checks Completed
31 May 2022Reviewer(s) Assigned
27 Jul 2022Review(s) Completed, Editorial Evaluation Pending
28 Jul 2022Editorial Decision: Revise Major
22 Sep 20221st Revision Received
23 Sep 2022Assigned to Editor
23 Sep 2022Submission Checks Completed
23 Sep 2022Review(s) Completed, Editorial Evaluation Pending
26 Sep 2022Reviewer(s) Assigned
11 Dec 2022Editorial Decision: Revise Major
27 Dec 20222nd Revision Received
28 Dec 2022Submission Checks Completed
28 Dec 2022Assigned to Editor
28 Dec 2022Review(s) Completed, Editorial Evaluation Pending
21 Jan 2023Reviewer(s) Assigned
09 Feb 2023Editorial Decision: Accept