Purpose: Radiotherapy is used to reduce the risk of breast cancer recurrence after surgery, but it is a potential cause of secondary cancer. We validated the risk of secondary cancer in primary breast cancer who received radiotherapy compared with those who did not from a matched cohort using a large-scale observational study of the Observational Health Data Sciences and Informatics (OHDSI) data network. Materials and Methods: A retrospective comparative cohort study using propensity score-matched cohorts was performed using two Observational Medical Outcome Partnership common data model databases, from tertiary general hospitals in South Korea. Among female patients who underwent surgery after the diagnosis of breast cancer, the risk of secondary primary malignant occurrence after 1:1 matching was analyzed. Results: Among 27,078 patients with breast cancer, there was no significant difference in the risk of secondary cancer following radiotherapy in 4,426 patients after 1:1 propensity-score matching. Further, there were no significant differences in the sensitivity analysis according to age, latency period, and number of radiation treatments. Conclusion There was no difference in the risk of secondary cancer in the patients diagnosed with breast cancer depending on whether or not radiotherapy was performed after surgery. In the future, it is necessary to analyze including data generated during cancer treatment.

Background: Dipeptidyl peptidase-4 (DPP4) inhibitors are frequently prescribed for patients with type 2 diabetes; however, their cost can pose a significant barrier for those with impaired kidney function. This study aimed to estimate the economic benefits of substituting non-renal dose-adjusted (NRDA) DPP4 inhibitors with renal dose-adjusted (RDA) DPP4 inhibitors in patients with both impaired kidney function and type 2 diabetes. Methods: This retrospective cohort study was conducted from January 1, 2012 to December 31, 2018, using data obtained from common data models of five medical centers in Korea. Model 1 applied the prescription pattern of participants with preserved kidney function to those with impaired kidney function. In contrast, model 2 replaced all NRDA DPP4 inhibitors with RDA DPP4 inhibitors, adjusting the doses of RDA DPP4 inhibitors based on individual kidney function. The primary outcome was the cost difference between the two models. Results: In total, 67,964,996 prescription records were analyzed. NRDA DPP4 inhibitors were more frequently prescribed to patients with impaired kidney function than in those with preserved kidney function (25.7%, 51.3%, 64.3%, and 71.6% in patients with estimated glomerular filtration rates [eGFRs] of ≥60, <60, <45, and <30 mL/min/1.73 m2, respectively). When model 1 was applied, the cost savings per year were 7.6% for eGFR <60 mL/min/1.73 m2 and 30.4% for eGFR <30 mL/min/1.73 m2. According to model 2, 15.4% to 51.2% per year could be saved depending on kidney impairment severity. Conclusion Adjusting the doses of RDA DPP4 inhibitors based on individual kidney function could alleviate the economic burden associated with medical expenses.

Objectives: The objective of this study was to develop and validate a multicenter-based, multi-model, time-series deep learning model for predicting drug-induced liver injury (DILI) in patients taking angiotensin receptor blockers (ARBs). The study leveraged a national-level multicenter approach, utilizing electronic health records (EHRs) from six hospitals in Korea. Methods: A retrospective cohort analysis was conducted using EHRs from six hospitals in Korea, comprising a total of 10,852 patients whose data were converted to the Common Data Model. The study assessed the incidence rate of DILI among patients taking ARBs and compared it to a control group. Temporal patterns of important variables were analyzed using an interpretable timeseries model. Results: The overall incidence rate of DILI among patients taking ARBs was found to be 1.09%. The incidence rates varied for each specific ARB drug and institution, with valsartan having the highest rate (1.24%) and olmesartan having the lowest rate (0.83%). The DILI prediction models showed varying performance, measured by the average area under the receiver operating characteristic curve, with telmisartan (0.93), losartan (0.92), and irbesartan (0.90) exhibiting higher classification performance. The aggregated attention scores from the models highlighted the importance of variables such as hematocrit, albumin, prothrombin time, and lymphocytes in predicting DILI. Conclusions Implementing a multicenter-based timeseries classification model provided evidence that could be valuable to clinicians regarding temporal patterns associated with DILI in ARB users. This information supports informed decisions regarding appropriate drug use and treatment strategies.

Background: The genetically predicted lipid-lowering effect of HMGCR or PCSK9 variant can be used to assess drug proxy effects on kidney function. Methods: Mendelian randomization (MR) analysis-identified HMGCR and PCSK9 genetic variants were used to predict the low-density lipoprotein (LDL) cholesterol-lowering effects of medications targeting related molecules. Primary summary-level outcome data for log-estimated glomerular filtration rate (eGFR; creatinine) were provided by the CKDGen Consortium (n = 1,004,040 European) from a meta-analysis of CKDGen and UK Biobank data. We also conducted a separate investigation of summary-level data from CKDGen (n = 567,460, log-eGFR [creatinine]) and UK Biobank (n = 436,581, log-eGFR [cystatin C]) samples. Summary-level MRs using an inverse variance weighted method and pleiotropy-robust methods were performed. Results: Summary-level MR analysis indicated that the LDL-lowering effect predicted genetically by HMGCR variants (50-mg/dL decrease) was significantly associated with a decrease in eGFR (–1.67%; 95% confidence interval [CI], –2.20% to –1.13%). Similar significance was found in results from the pleiotropy-robust MR methods when the CKDGen and UK Biobank data were analyzed separately. However, the LDL-lowering effect predicted genetically by PCSK9 variants was significantly associated with an increase in eGFR (+1.17%; 95% CI, 0.10%–2.25%). The results were similarly supported by the weighted median method and in each CKDGen and UK Biobank dataset, but the significance obtained by MR-Egger regression was attenuated. Conclusion Genetically predicted HMG-CoA reductase inhibition was associated with low eGFR, while genetically predicted PCSK9 inhibition was associated with high eGFR. Clinicians should consider that the direct effect of different types of lipid-lowering medication on kidney function can vary.

Objectives: . The BRAFV600E mutation is a major driver mutation in papillary thyroid cancer. The aim of this study was to elucidate the correlation between DNA methylation and gene expression changes induced by the BRAFV600E mutation in thyroid cells. Methods: . We used Nthy/BRAF cell lines generated by transfection of Nthy/ori cells with the wild-type BRAF gene (Nthy/WT cells) and the V600E mutant-type BRAF gene (Nthy/V600E cells). We performed gene expression microarray and DNA methylation array analyses for Nthy/WT and Nthy/V600E cells. Two types of array data were integrated to identify inverse correlations between methylation and gene expression. The results were verified in silico using data from The Cancer Genome Atlas (TCGA) and in vivo through pyrosequencing and quantitative real-time polymerase chain reaction (qRT-PCR). Results: . In the Nthy/V600E cells, 199,821 probes were significantly hypermethylated, and 697 genes showed a “hypermethylation-downregulation” pattern in Nthy/V600E. Tumor suppressor genes and apoptosis-related genes were included. In total, 66,446 probes were significantly hypomethylated, and 227 genes showed a “hypomethylation-upregulation” pattern in Nthy/V600E cells. Protooncogenes and developmental protein-coding genes were included. In the TCGA analysis, 491/697 (70.44%) genes showed a hypermethylation-downregulation pattern, and 153/227 (67.40%) genes showed a hypomethylation-upregulation pattern. Ten selected genes showed a similar methylation-gene expression pattern in pyrosequencing and qRT-PCR. Conclusion . Induction of the BRAFV600E mutation in thyroid cells led to frequent hypermethylation. Anticancer genes, such as those involved in tumor suppression or apoptosis, were downregulated by upstream hypermethylation, whereas carcinogenic genes, such as protooncogenes, were upregulated by hypomethylation. Our results suggest that the BRAFV600E mutation in thyroid cells modulates DNA methylation and results in cancer-related gene expression.

Appropriate monitoring of intradialytic biosignals is essential to minimize adverse outcomes because intradialytic hypotension and arrhythmia are associated with cardiovascular risk in hemodialysis patients. However, a continuous monitoring system for intradialytic biosignals has not yet been developed. Methods: This study investigated a cloud system that hosted a prospective, open-source registry to monitor and collect intradialytic biosignals, which was named the CONTINUAL (Continuous mOnitoriNg viTal sIgN dUring hemodiALysis) registry. This registry was based on real-time multimodal data acquisition, such as blood pressure, heart rate, electrocardiogram, and photoplethysmogram results. Results: We analyzed session information from this system for the initial 8 months, including data for some cases with hemodynamic complications such as intradialytic hypotension and arrhythmia. Conclusion: This biosignal registry provides valuable data that can be applied to conduct epidemiological surveys on hemodynamic complications during hemodialysis and develop artificial intelligence models that predict biosignal changes which can improve patient outcomes.