한빛사논문
- 조회426
In-Sun Oh 1,2,3, Han Eol Jeong 1,4, Hyesung Lee 1,4, Kristian B Filion 2,3,5, Yunha Noh 1,2,3, Ju-Young Shin 1,4,6
1School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.
2Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada.
3Centre for Clinical Epidemiology, Lady Davis Research Institute-Jewish General Hospital, Montreal, Quebec, Canada.
4Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.
5Department of Medicine, McGill University, Montreal, Quebec, Canada.
6Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, South Korea.
Correspondence author: Ju-Young Shin
Abstract
Background: Immeasurable time bias arises from the lack of in-hospital medication information. It has been suggested that time-varying adjustment for hospitalization may minimize this potential bias. However, whereas we examined this issue in one case study, there remains a need to assess the validity of this approach in other settings.
Methods: Using a Monte Carlo simulation, we generated synthetic immeasurable time-varying hospitalization-related factors of duration, frequency and timing. Nine scenarios were created by combining three frequency scenarios and three duration scenarios, where the empirical cohort distribution of hospitalization was used to simulate the 'timing'. We used Korea's healthcare database and a case example of β-blocker use and mortality among patients with heart failure. We estimated the gold-standard hazard ratio (HR) with 95% CI using inpatient and outpatient drug data, and that of the pseudo-outpatient setting using outpatient data only. We assessed the validity of adjusting for time-varying hospitalization in nine different scenarios, using relative bias, confidence limit ratio (CLR) and mean squared error (MSE) compared with the empirical gold-standard estimate across bootstrap resamples.
Results: With the real-world gold standard (HR 0.73; 95% CI 0.67-0.80) as the reference estimate, adjusting for time-varying hospitalization (0.71; 0.63-0.80) effectively reduced the immeasurable time bias and had the following performance metrics across the nine scenarios: relative bias (range: -7.08% to 0.61%), CLR (1.28 to 1.36) and MSE (0.0005 to 0.0031).
Conclusions: The approach of adjusting for time-varying hospitalization consistently reduced the immeasurable time bias in Monte Carlo simulated data.
논문정보
- Research article
- 2023년 05월 (BRIC 등록일 2023-05-23)
- 국내(교신)+국외 연구진
- 의약학 > 약학
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