Investigation of hepatic adverse events due to quetiapine by using the common data model.

PURPOSE: Quetiapine is a drug used to treat schizophrenia, bipolar disorder, and major depressive disorder. However, it can cause mild or severe hepatic adverse events and rarely fatal liver damage. This study was aimed at investigating hepatic toxicity caused by quetiapine use by analyzing the information captured from hospital electronic health records by using the Observational Medical Outcomes Partnership common data model (CDM). METHODS: This was a retrospective observational study involving a nested case-control method. A CDM based on an electronic health record database from five hospitals between January 2009 and May 2020 was used. We analyzed the status of quetiapine use, adverse events, and hepatic impairment. RESULTS: The numbers of patients with non-serious and severe hepatic adverse reactions were 2566 (5.05%) and 835 (1.64%) out of 50 766 patients, respectively. After adjusting for covariates, the odds ratio of hepatic adverse events was 2.35 (95% CI: 2.03-2.72), and the odds ratio of severe hepatic adverse events was 1.76 (95% CI: 1.16-2.66). CONCLUSION: Our findings suggest that quetiapine should be cautiously used, and hepatic function should be monitored in patients using quetiapine because it can cause mild or severe hepatic adverse events, complications, and in rare cases, fatal liver damage.

Second primary malignancy risk in thyroid cancer and matched patients with and without radioiodine therapy analysis from the observational health data sciences and informatics.

PURPOSE: Risk of second primary malignancy (SPM) after radioiodine (RAI) therapy has been continuously debated. The aim of this study is to identify the risk of SPM in thyroid cancer (TC) patients with RAI compared with TC patients without RAI from matched cohort. METHODS: Retrospective propensity-matched cohorts were constructed across 4 hospitals in South Korea via the Observational Health Data Science and Informatics (OHDSI), and electrical health records were converted to data of common data model. TC patients who received RAI therapy constituted the target group, whereas TC patients without RAI therapy constituted the comparative group with 1:1 propensity score matching. Hazard ratio (HR) by Cox proportional hazard model was used to estimate the risk of SPM, and meta-analysis was performed to pool the HRs. RESULTS: Among a total of 24,318 patients, 5,374 patients from each group were analyzed (mean age 48.9 and 49.2, women 79.4% and 79.5% for target and comparative group, respectively). All hazard ratios of SPM in TC patients with RAI therapy were ≤ 1 based on 95% confidence interval(CI) from full or subgroup analyses according to thyroid cancer stage, time-at-risk period, SPM subtype (hematologic or non-hematologic), and initial age (< 30 years or ≥ 30 years). The HR within the target group was not significantly higher (< 1) in patients who received over 3.7 GBq of I-131 compared with patients who received less than 3.7 GBq of I-131 based on 95% CI. CONCLUSION: There was no significant difference of the SPM risk between TC patients treated with I-131 and propensity-matched TC patients without I-131 therapy.

Sodium-Glucose Cotransporter-2 Inhibitor-Related Diabetic Ketoacidosis: Accuracy Verification of Operational Definition.

BACKGROUND: The most important aspect of a retrospective cohort study is the operational definition (OP) of the disease. We developed a detailed OP for the detection of sodium-glucose cotransporter-2 inhibitors (SGLT2i) related to diabetic ketoacidosis (DKA). The OP was systemically verified and analyzed. METHODS: All patients prescribed SGLT2i at four university hospitals were enrolled in this experiment. A DKA diagnostic algorithm was created and distributed to each hospital; subsequently, the number of SGLT2i-related DKAs was confirmed. Then, the algorithm functionality was verified through manual chart reviews by an endocrinologist using the same OP. RESULTS: A total of 8,958 patients were initially prescribed SGLT2i. According to the algorithm, 0.18% (16/8,958) were confirmed to have SGLT2i-related DKA. However, based on manual chart reviews of these 16 cases, there was only one case of SGLT2i-related DKA (positive predictive value = 6.3%). Even after repeatedly narrowing the diagnosis range of the algorithm, the effect of a positive predictive value was insignificant (6.3-10.0%, P > 0.999). CONCLUSION: Owing to the nature of electronic medical record data, we could not create an algorithm that clearly differentiates SGLT2i-related DKA despite repeated attempts. In all retrospective studies, a portion of the samples should be randomly selected to confirm the accuracy of the OP through chart review. In retrospective cohort studies in which chart review is not possible, it will be difficult to guarantee the reliability of the results.

Estimation of sodium-glucose cotransporter 2 inhibitor-related genital and urinary tract infections via electronic medical record-based common data model.

WHAT IS KNOWN AND OBJECTIVES: In Korea, the side effects of sodium-glucose cotransporter 2 inhibitors (SGLT2i) have not been clearly reported, aside from voluntary reporting. We aimed to develop detection algorithms for SGLT2i-related genital tract infections (GTIs) and urinary tract infections (UTIs) via a common data model (CDM), an electronic medical record-based database for supporting multi-hospital clinical research. We estimated the occurrence of GTIs and UTIs and-by assessing the status of each step of the algorithm-we also aimed to determine how clinicians responded to the SGLT2i-related GTIs and UTIs. METHODS: We targeted all patients who were prescribed SGLT2i at Catholic University Seoul St. Mary's Hospital and Hallym University Dongtan Sacred Heart Hospital from January 2014 to August 2018. We developed algorithms for detection of SGLT2i-related GTIs or UTIs that divided patients into "most likely," "possibly" or "less likely" categories of GTIs or UTIs. The numbers of patients at each step were extracted. RESULTS AND DISCUSSION: A total of 4253 patients received their first prescription of SGLT2i. According to the algorithm used in this study, the proportions of "most likely GTI" and "possibly GTI" were 0.9% (37 out of 4253) and 19.4% (826 out of 4253 patients), respectively. Similarly, the proportions of "most likely UTI" and "possibly UTI" were 0.9% (38 out of 4253) and 20.2% (858 out of 4253 patients), respectively. Compared to the various existing prospective studies, both GTIs and UTIs showed lower occurrence among patients who met "most likely" criteria and higher occurrence among those who met "possibly" criteria. When a GTI or UTI occurred or was suspected, the overall rate of discontinuing SGLT2i was 51.8% (1721 out of 3323). Despite a confirmed or suspected GTI and an UTI, 62.8% (1460 out of 2323) and 14.2% (142 out of 1000) of patients continued to take SGLT2i, respectively. The discontinuation rate for suspected GTIs was significantly lower than that for suspected UTIs (37.2% vs. 85.8%, p < 0.001). WHAT IS NEW AND CONCLUSION: In this study, although the GTIs appeared to have a similar occurrence as UTIs, however, the discontinuation rate of SGLT2i for suspected GTIs was relatively lower. Our study is novel in that we identified how the physicians approached SGLT2i-related GTIs or UTIs at each step in a real-world clinical practice setting. Although we could estimate SGLT2i-related GTIs and UTIs via CDM, we were limited in our ability to accurately detect mild drug side effects via CDM, which lacked data for operational definition.

Text Extraction and Standardization System Development for Pathological Records in the Korea Biobank Network.

In Korea, the Korea Centers for Disease Control and Prevention operates the Korea BioBank Network (KBN). KBN has pathological records that collected in Korea and it is useful dataset for research. In this study, we established system that time efficient and reduced error by step-by-step data extraction process from KBN pathological records. We tested the extraction process by 769 lung cancer cohorts and 1292 breast cancer cohorts and accuracy is 91%. We expect this system can be used to efficiently process data from multiple institutions, including Korea BioBank Network.

Text Extraction and Standardization System Development for Pathological Records in the Korea Biobank Network.

In Korea, the Korea Centers for Disease Control and Prevention operates the Korea BioBank Network (KBN). KBN has pathological records that collected in Korea and it is useful dataset for research. In this study, we established system that time efficient and reduced error by step-by-step data extraction process from KBN pathological records. We tested the extraction process by 769 lung cancer cohorts and 1292 breast cancer cohorts and accuracy is 91%. We expect this system can be used to efficiently process data from multiple institutions, including Korea BioBank Network.