British journal of clinical pharmacology · 2023
Derivation and validation of a risk prediction score for nonsteroidal anti-inflammatory drug-related serious gastrointestinal complications in the elderly.
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Lee Suhyun, Heo Kyu-Nam, Lee Mee Yeon, Ah Young-Mi, Shin Jaekyu, Lee Ju-Yeun
Аннотация
AIMS: 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 for severe GI complications to identify high-risk elderly patients using NSAID.
METHODS: We 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.
RESULTS: We 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.
CONCLUSIONS: The prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high-risk elderly patients.
METHODS: We 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.
RESULTS: We 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.
CONCLUSIONS: The prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high-risk elderly patients.