Dark Data in Real-World Evidence: Challenges, Implications, and the Imperative of Data Literacy in Medical Research.

Randomized controlled trials (RCTs) and real-world evidence (RWE) studies are crucial and complementary in generating clinical evidence. RCTs provide controlled settings to validate the clinical effect of specific drugs or medical devices, while RWE integrates extrinsic factors, encompassing external influences affecting real-world scenarios, thus challenging RCT results in practical applications. In this study, we explore the impact of extrinsic factors on RWE outcomes, focusing on "dark data," which refers to data collected but not used or excluded from the analyses. Dark data can arise in many ways during research process, from selecting study samples to data collection and analysis. However, even unused or unanalyzed dark data hold potential insights, providing a comprehensive view of clinical contexts. Extrinsic factors lead to divergent RWE outcomes that could differ from RCTs beyond statistical correction's scope. Two main types of dark data exist: "known-unknown" and "unknown-unknown." The distinction between these dark data types highlights RWE's complexity. The transformation of unknown into known depends on data literacy-powerful utilization capabilities that can be interpreted based on medical expertise. Shifting the focus to excluded subjects or unused data in real-world contexts reveals unexplored potential. Understanding the significance of dark data is vital in reflecting the complexity of clinical settings. Connecting RCTs and RWEs requires medical data literacy, enabling clinicians to decipher meaningful insights. In the big data and artificial intelligence era, medical staff must navigate data complexities while promoting the core role of medicine. Prepared clinicians will lead this transformative journey, ensuring data value shapes the medical landscape.

Long-term change in the target achievement rate of low-density lipoprotein cholesterol in patients with cardiovascular disease.

OBJECTIVES: The goal achievement rate of patients' low-density lipoprotein cholesterol (LDL-C) levels and prescribing pattern of statin potency should be continuously monitored in a real-world clinical setting. This study aimed to describe the comprehensive status of LDL-C management. MATERIALS AND METHODS: Patients first diagnosed with cardiovascular diseases (CVDs) between 2009 and 2018 who were followed for 24 months. LDL-C levels, its changes from baseline, and intensity of statin prescribed were evaluated four times during follow-up. Potential factors associated with goal achievement were also identified. RESULTS: The study included 25,605 patients with CVDs. At diagnosis, the goal achievement rates of the LDL-C level were 58.4, 25.2, and 10.0% for targets of < 100, < 70, and < 55 mg/dL, respectively. The proportion of moderate- and high-intensity statin prescription significantly increased over time (all p < 0.01). Nevertheless, LDL-C levels significantly decreased at 6 months and increased at 12 and 24 months following therapy compared with baseline values. Glomerular filtration rate (GFR) (15 - 29 and < 15 mL/min/1.73m2) and accompanying diabetes mellitus were significantly associated with the goal achievement rate. CONCLUSION: Despite the need for active LDL-C management, the goal achievement rate and prescribing pattern were insufficient after 6 months. In cases with severe comorbidities, the goal attainment rate significantly increased; however, a more aggressive statin prescription was needed even in patients without diabetes or with normal GFR. The prescription rate for high-intensity statins increased over time, but was still low. In conclusion, physicians should aggressively prescribe statins to increase the goal achievement rate in patients with CVDs.

The Present and Future of Artificial Intelligence-Based Medical Image in Diabetes Mellitus: Focus on Analytical Methods and Limitations of Clinical Use.

Artificial intelligence (AI)-based diagnostic technology using medical images can be used to increase examination accessibility and support clinical decision-making for screening and diagnosis. To determine a machine learning algorithm for diabetes complications, a literature review of studies using medical image-based AI technology was conducted using the National Library of Medicine PubMed, and the Excerpta Medica databases. Lists of studies using diabetes diagnostic images and AI as keywords were combined. In total, 227 appropriate studies were selected. Diabetic retinopathy studies using the AI model were the most frequent (85.0%, 193/227 cases), followed by diabetic foot (7.9%, 18/227 cases) and diabetic neuropathy (2.7%, 6/227 cases). The studies used open datasets (42.3%, 96/227 cases) or directly constructed data from fundoscopy or optical coherence tomography (57.7%, 131/227 cases). Major limitations in AI-based detection of diabetes complications using medical images were the lack of datasets (36.1%, 82/227 cases) and severity misclassification (26.4%, 60/227 cases). Although it remains difficult to use and fully trust AI-based imaging analysis technology clinically, it reduces clinicians' time and labor, and the expectations from its decision-support roles are high. Various data collection and synthesis data technology developments according to the disease severity are required to solve data imbalance.

Long-Term Risk of Cardiovascular Disease Among Type 2 Diabetes Patients According to Average and Visit-to-Visit Variations of HbA1c Levels During the First 3 Years of Diabetes Diagnosis.

BACKGROUND: It remains unclear whether a combination of glycemic variability and glycated hemoglobin (HbA1c) status leads to a higher incidence of cardiovascular disease (CVD). Therefore, to investigate CVD risk according to the glucose control status during early diabetes, we examined visit-to-visit HbA1c variability among patients with type 2 diabetes (T2DM). METHODS: In this 9-year retrospective study, we measured HbA1c levels at each visit and tracked the change in HbA1c levels for 3 years after the first presentation (observation window) in newly diagnosed T2DM patients. We later assessed the occurrence of CVD in the last 3 years (target outcome window) of the study period after allowing a 3-year buffering window. The HbA1c variability score (HVS; divided into quartiles, HVS_Q1-4) was used to determine visit-to-visit HbA1c variability. RESULTS: Among 4,817 enrolled T2DM patients, the mean HbA1c level was < 7% for the first 3 years. The group with the lowest HVS had the lowest rate of CVD (9.4%; 104/1,109 patients). The highest incidence of CVD of 26.7% (8/30 patients) was found in HVS [≥ 9.0%]_Q3, which was significantly higher than that in HVS [6.0-6.9%]_Q1 (P = 0.006), HVS [6.0-6.9%]_Q2 (P = 0.013), HVS [6.0-6.9%]_Q3 (P = 0.018), and HVS [7.0-7.9%]_Q3 (P = 0.040). CONCLUSION: To our knowledge, this is the first long-term study to analyze the importance of both HbA1c change and visit-to-visit HbA1c variability during outpatient visits within the first 3 years. Lowering glucose levels during early diabetes may be more critical than reducing visit-to-visit HbA1c variability.

Angiotensin-converting enzyme inhibitors versus angiotensin receptor blockers: New-onset diabetes mellitus stratified by statin use.

WHAT IS KNOWN AND OBJECTIVES: Regardless of statin use, which is known to induce hyperglycaemia, comparative studies on the risk of new-onset diabetes mellitus (NODM) with angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are needed. This study evaluated the effects of ACEIs and ARBs on NODM in the clinical setting. METHODS: This retrospective cohort study utilized electronic medical record data from Seoul St. Mary's Hospital and Seoul National University Hospital from 2009 to 2012. Patients who were prescribed ACEIs or ARBs for the first time (irrespective of concomitant statin use) were followed up for 5 years. RESULTS AND DISCUSSIONS: A total of 11,703 patients were included, 24.9% (n = 2916) were taking ACEIs and 75.1% (n = 9189) were taking ARBs. Patients on ACEIs had a significantly lower incidence of NODM both with statin use (HR = 0.13, p < 0.001) and without (HR = 0.15, p = 0.009) than patients on ARBs. Age ≥60 years (HR = 1.49, p = 0.010), BMI ≥25 (HR = 1.96, p < 0.010), use of calcium channel blockers (HR = 1.47, p = 0.010), and diuretics (HR = 1.48, p = 0.010) were risk factors for NODM with statin use. WHAT IS NEW AND CONCLUSION: Patients taking ACEIs are less likely to develop NODM than patients taking ARBs, irrespective of statin use. Patients' conditions, including the risk of NODM, should be considered before prescribing ACEIs or ARBs. Future randomized clinical trials are needed to clarify further the relationship between ACEIs and ARBs and their effect on NODM.

Long-Term Changes in HbA1c According to Blood Glucose Control Status During the First 3 Months After Visiting a Tertiary University Hospital.

BACKGROUND: We evaluated patients visiting a tertiary university hospital due to a diagnosis of diabetes with a goal of achieving blood glucose control and evaluated blood glucose persistence over 7 years according to the change in blood glucose evident at 3 months after the first visit. METHODS: Patients treated from 2009 to 2013 were categorized into four groups according to the change in HbA1c levels during the first 3 months of follow-up (Best_group, ≥ 1.6% decrease; Better_group, 0.5-1.5% decrease; Neutral_group, maintained at -0.4% to +0.4%; Worse_group, ≥ 0.5% increase). Each patient's blood glucose control status was then monitored for 7 years. The incidence of stroke and acute coronary syndrome during this period was confirmed. RESULTS: Overall, 9,776 patients were included. HbA1c values were lower in the Best_group than in the other groups at all time points (all P < 0.001). The rate of reaching targets of < 6.5% or < 7.0% HbA1c decreased over time; the rate at which the estimated glomerular filtration rate decreased to < 30 or < 60 mL/min/1.73m² increased over time (all trends, P < 0.01). CONCLUSION: Blood glucose control status in the first 3 months after initiating hospital care enabled estimation of the patient's glycemic control status for the next 7 years. In cases with poor initial blood glucose control, a new or more active method of blood glucose control should be sought.

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.

Low-density lipoprotein cholesterol reduction and target achievement after switching from statin monotherapy to statin/ezetimibe combination therapy: Real-world evidence.

WHAT IS KNOWN AND OBJECTIVES: This study investigated the additional low-density lipoprotein cholesterol (LDL-C) reductions and target (LDL-C < 100 mg/dL) achievement rates in patients after switching from statin monotherapy to statin/ezetimibe combination therapy, in clinical practice. METHODS: This retrospective study used data recovered from the electronic medical record systems of two tertiary care medical centres for patients treated between 2015 and 2017. Patients prescribed statin/ezetimibe combination therapy after switching from statin monotherapy were enrolled. The observed LDL-C reductions and the percentage of patients achieving LDL-C levels of <100 mg/dL, after 3 months of treatment, were assessed relative to baseline values. RESULTS AND DISCUSSION: A total of 4252 patients with prescriptions for statin/ezetimibe combination therapy were enrolled. Changing from statin monotherapy to the combination therapy resulted in additional LDL-C level reductions of 31.0-41.0% (all intensity groups, P < .01). Similarly, 88.3-91.1% of the enrolled patients successfully achieved LDL-C levels of <100 mg/dL (all intensity groups, P < .01). A subgroup analysis of patients with baseline LDL-C levels ≥ 100 mg/dL showed that switching from moderate- or high-intensity statin monotherapy to a rosuvastatin/ezetimibe combination showed greater LDL-C reductions than did switching to an atorvastatin/ezetimibe combination, within the same statin intensity groups. WHAT IS NEW AND CONCLUSION: The present study provides real-world evidence of the LDL-C reduction benefits associated with statin/ezetimibe combinations in the clinical practice setting. The results also demonstrate that if statin monotherapy does not effectively help patients reach their target LDL-C goals, changing to a statin/ezetimibe combination prescription may show enhanced LDL-C-lowering effects and improve the likelihood of achieving LDL-C targets, in real practice.

Data Pseudonymization in a Range That Does Not Affect Data Quality: Correlation with the Degree of Participation of Clinicians.

Personal medical information is an essential resource for research; however, there are laws that regulate its use, and it typically has to be pseudonymized or anonymized. When data are anonymized, the quantity and quality of extractable information decrease significantly. From the perspective of a clinical researcher, a method of achieving pseudonymized data without degrading data quality while also preventing data loss is proposed herein. As the level of pseudonymization varies according to the research purpose, the pseudonymization method applied should be carefully chosen. Therefore, the active participation of clinicians is crucial to transform the data according to the research purpose. This can contribute to data security by simply transforming the data through secondary data processing. Case studies demonstrated that, compared with the initial baseline data, there was a clinically significant difference in the number of datapoints added with the participation of a clinician (from 267,979 to 280,127 points, P < 0.001). Thus, depending on the degree of clinician participation, data anonymization may not affect data quality and quantity, and proper data quality management along with data security are emphasized. Although the pseudonymization level and clinical use of data have a trade-off relationship, it is possible to create pseudonymized data while maintaining the data quality required for a given research purpose. Therefore, rather than relying solely on security guidelines, the active participation of clinicians is important.

Lack of Acceptance of Digital Healthcare in the Medical Market: Addressing Old Problems Raised by Various Clinical Professionals and Developing Possible Solutions.

Various digital healthcare devices and apps, such as blood glucose meters, blood pressure monitors, and step-trackers are commonly used by patients; however, digital healthcare devices have not been widely accepted in the medical market as of yet. Despite the various legal and privacy issues involved in their use, the main reason for its poor acceptance is that users do not use such devices voluntarily and continuously. Digital healthcare devices generally do not provide valuable information to users except for tracking self-checked glucose or walking. To increase the use of these devices, users must first understand the health data produced in the context of their personal health, and the devices must be easy to use and integrated into everyday life. Thus, users need to know how to manage their own data. Medical staff must teach and encourage users to analyze and manage their patient-generated healthcare data, and users should be able to find medical values from these digital devices. Eventually, a single customized service that can comprehensively analyze various medical data to provide valuable customized services to users, and which can be linked to various heterogeneous digital healthcare devices based on the integration of various health data should be developed. Digital healthcare professionals should have detailed knowledge about a variety of digital healthcare devices and fully understand the advantages and disadvantages of digital healthcare to help patients understand and embrace the use of such devices.

Comparative analysis of the efficacy of angiotensin II receptor blockers for uric acid level change in asymptomatic hyperuricaemia.

WHAT IS KNOWN AND OBJECTIVE: There is much controversy over how angiotensin II receptor blockers (ARB) or angiotensin-converting enzyme inhibitors (ACEI) affect blood uric acid levels. Though ARB is not used to lorcwer the uric acid concentration in the blood, losartan, one of the ARB series, is known to reduce the uric acid concentration in the blood and is a preferred drug for hypertensive patients with gout. However, there is no clear conclusive consideration which ARB should be selected for the patients who have simply increased uric acid concentration, other than gout patients. This research aims to compare the variations of the uric acid concentration in the blood in accordance with the prescription of ACEI or ARB targeting patients who were not diagnosed with gout. METHODS: This research was conducted on the patients who were, for the first time, prescribed ACEI or ARB for a total of 7 years from January 2009 to December 2015. This study has extracted the uric acid values after between 60 days and 120 days (average 90 days, defined as Visit 1) on the basis of the first prescription date of ACEI or ARB. RESULTS AND DISCUSSION: In this study, ACEI was 17.0% of usage (3787/22 293 patients) and ARB was 83.0% (18 506/22 293 patients). Unlike ACEI (5.91 ± 0.03 vs 5.86 ± 0.03 mg/dL, P = .059), ARB showed a statistically significant decrease after 3 months (5.71 ± 0.01 vs 5.69 ± 0.01 mg/dL, P = .023). In the case of irbesartan (n = 1530, 6.13 ± 0.06 mg/dL vs 5.89 ± 0.05 mg/dL, P < .001) and olmesartan (n = 2719, 5.70 ± 0.04 mg/dL vs 5.63 ± 0.03 mg/dL, P = .008), the decrease in the uric acid after 3 months was revealed as statistically significant. In elderly aged over 60 years, only irbesartan (n = 855, 5.75 ± 0.07 mg/dL vs 5.59 ± 0.07 mg/dL, P = .006) showed a significant decrease in the uric. When the eGFR was less than 60 mL/min/1.73 m2 , both ACEI (n = 1108, 6.95 ± 0.07 mg/dL vs 6.73 ± 0.07 mg/dL, P = .001) and ARB (n = 5280, 6.88 ± 0.03 vs 6.60 mg/dL ± 0.03 mg/dL, P < .001) showed a significant decrease in the uric acid. WHAT IS NEW AND CONCLUSION: Although all types of ACEIs and ARBs are being prescribed with similar purposes, ARB (or ACEI) medication does not have a class effect and has varying effects on uric acid levels. The decreases in uric acid levels were relatively small. ARBs seem to be more advantageous than ACEIs for hyperuricaemia patients without gout who are aiming to maintain uric acid decrease levels. Furthermore, irbesartan can be a good substitute for losartan in view of the fact that at least the uric acid level is not increased.

Discontinuation rate and reason for discontinuation after sodium-glucose cotransporter 2 inhibitor prescription in real clinical practice.

WHAT IS KNOWN AND OBJECTIVES: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are novel antidiabetic agents that have advantages of weight loss and prevention of cardiovascular diseases. However, SGLT2i have various side effects. To understand their effectiveness, we analysed patients who had discontinued the use of dapagliflozin, an SGLT2i, 3 months after the initial prescription. We evaluated the discontinuation rate of dapagliflozin and the incidence rate of its side effects. METHODS: Patients who were initially prescribed dapagliflozin for blood sugar control from December 2014 to December 2016 were analysed. Data of patients in whom dapagliflozin administration was discontinued 90 days after initial prescription were collected separately, and the reasons were evaluated by a direct chart review. RESULTS AND DISCUSSION: A total of 8.96% (149/1663) patients discontinued dapagliflozin or switched medications within 3 months. Dapagliflozin was discontinued in 24.8% (37/149) of cases due to unexpected causes such as increased blood sugar and weight gain. The patients who discontinued dapagliflozin use due to side effects comprised 49.7% (74/149). Two major side effects were genital tract infection in women (P < .001 compared with men) and urinary tract infection, which increased with age (P = .030). Malpractice of medical personnel, insurance problems or causes of termination not related to dapagliflozin use comprised 14.1% (21/149). WHAT IS NEW AND CONCLUSION: The incidence of side effects with dapagliflozin was not as high as expected. Physicians should consider instructions prior to prescribing dapagliflozin so that its discontinuation would decrease considerably.

Identifying genetic variants underlying medication-induced osteonecrosis of the jaw in cancer and osteoporosis: a case control study.

BACKGROUND: Bisphosphonate-induced osteonecrosis of the jaw (BRONJ) presents with a typical pattern of jaw necrosis in patients who have been prescribed bisphosphonates (BPs) and other antiangiogenetic drugs to treat osteoporosis or bone-related complications of cancer. METHODS: This study divided 38 patients with BRONJ into two groups according to the prescribing causes: cancer (n = 13) and osteoporosis (n = 25), and underwent whole exome sequencing and compared them with normal controls (n = 90). To identify candidate genes and variants, we conducted three analyses: a traditional genetic model, gene-wise variant score burden, and rare-variant analysis methods. RESULTS: The stop-gain mutation (rs117889746) of the PZP gene in the BRONJ cancer group was significantly identified in the additive trend model analysis. In the cancer group, ARIDS, HEBP1, LTBP1, and PLVAP were identified as candidate genes. In the osteoporosis group, VEGFA, DFFA, and FAM193A genes showed a significant association. No significant genes were identified in the rare-variant analysis pipeline. Biologically accountable functions related to BRONJ occurrence-angiogenesis-related signaling (VEGFA and PLVAP genes), TGF-ß signaling (LTBP1 and PZP genes), heme toxicity (HEBP1) and osteoblast maturation (ARIDS)-were shown in candidate genes. CONCLUSION: This study showed that the candidate causative genes contributing to the development of BRONJ differ according to the BP dose and background disease.

Proceed with Caution When Using Real World Data and Real World Evidence.

Clinical studies can be conducted to gather real world evidence (RWE) not available from randomized controlled trials, providing new information and knowledge. Although the concept of RWE emerged relatively recently, numerous clinical studies are utilizing it. However, many researchers are engaging in trial and error that may not overcome the various biases that occur in electronic medical record (EMR)-based RWE studies. While RWE can reflect the real world, there are still limitations to its acceptance. There are many hurdles in using RWE and solutions must be explored. Results based on RWE may be overestimated and it can be difficult to derive good quality results. This paper discusses data quality management, direct chart review, sample size, study design, and the interpretation of EMR-based RWE. More specifically, this paper shares the experience of the various hurdles that occur when conducting RWE studies and discusses the easy-to-false errors. RWE is still in the developmental stage and numerous aspects of RWE use remain unclear. Nonetheless, despite its many limitations, increasing use of RWE is still anticipated. This will require continued experience and effort in using RWE, as well as upgrading RWE research through the accumulation of information on such experiences and efforts.

Correction to: Release of overexpressed CypB activates ERK signaling through CD147 binding for hepatoma cell resistance to oxidative stress.

The original version of this article contained a mistake. The bands for HA Tag and t-ERK in Figs. 2d, 2h, 3d are incorrect. The author informs that these errors had no influence in the scientific content of the paper. The corrected figures (Figs. 2 and 3) are given below.

Variability in Total Cholesterol Is Associated With the Risk of End-Stage Renal Disease: A Nationwide Population-Based Study.

OBJECTIVE: Recent data suggest that visit-to-visit variability of cholesterol is associated with cardiovascular events. We evaluated the role of lipid variability as a determinant of end-stage renal disease (ESRD). APPROACH AND RESULTS: Using nationally representative data from the Korean National Health Insurance System, 8 493 277 subjects who were free of ESRD and who underwent ≥3 health examinations during 2005 to 2010 were followed to the end of 2015. Total cholesterol (TC) variability was measured using the coefficient of variation, SD, and the variability independent of the mean. The primary outcome was the development of ESRD, defined as a combination of the relevant disease code and the initiation of renal replacement therapy. There were 11 247 cases of ESRD during a median follow-up of 6.1 years. There was a graded association between a higher TC variability and incident ESRD. In the multivariable adjusted model, the hazard ratios and 95% confidence intervals comparing the highest versus lowest quartiles of coefficient of variation of TC were 2.66 (95% confidence interval, 2.52-2.82). The results were consistent when the variability of TC was modeled using SD and variability independent of the mean and were independent of preexisting chronic kidney disease. CONCLUSIONS: Increasing TC variability was associated with an increasing incidence of ESRD.

Real-world Evidence versus Randomized Controlled Trial: Clinical Research Based on Electronic Medical Records.

Real-world evidence (RWE) and randomized control trial (RCT) data are considered mutually complementary. However, compared with RCT, the outcomes of RWE continue to be assigned lower credibility. It must be emphasized that RWE research is a real-world practice that does not need to be executed as RCT research for it to be reliable. The advantages and disadvantages of RWE must be discerned clearly, and then the proper protocol can be planned from the beginning of the research to secure as many samples as possible. Attention must be paid to privacy protection. Moreover, bias can be reduced meaningfully by reducing the number of dropouts through detailed and meticulous data quality management. RCT research, characterized as having the highest reliability, and RWE research, which reflects the actual clinical aspects, can have a mutually supplementary relationship. Indeed, once this is proven, the two could comprise the most powerful evidence-based research method in medicine.

Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study.

Aims: A high visit-to-visit variability in cholesterol levels has been suggested to be an independent predictor of major adverse cardiovascular events in patients with coronary artery disease (CAD). Because whether this notion applies to general population is not known, we aimed to investigate the associations between total cholesterol (TC) variability and the risk of all-cause mortality, myocardial infarction (MI), and stroke. Methods and results: We identified 3 656 648 subjects without a history of MI and stroke who underwent ≥3 health examinations from 2002 to 2007 in the Korean National Health Insurance System cohort. Total cholesterol variability was measured using the coefficient of variation (CV), standard deviation (SD), and variability independent of the mean (VIM). There were 84 625 deaths (2.3%), 40 991 cases of MI (1.1%), and 42 861 cases of stroke (1.2%) during the median follow-up of 8.3 years. There was a linear association between higher TC variability and outcome measures. In the multivariable adjusted model, the hazard ratios and 95% confidence intervals comparing the highest vs. lowest quartiles of CV of TC were 1.26 (1.24-1.28) for all-cause mortality, 1.08 (1.05-1.11) for MI, and 1.11 (1.08-1.14) for stroke, which was independent of mean TC levels and the use of lipid-lowering agents. The results were consistent when modelling variability of TC using SD and VIM, and in various sensitivity analyses. Conclusion: High variability in lipid levels is associated with adverse health-related outcomes. These findings suggest that lipid variability is an important risk factor in the general population.

The differences in the incidence of diabetes mellitus and prediabetes according to the type of HMG-CoA reductase inhibitors prescribed in Korean patients.

BACKGROUND: Very few studies conducted in Korea have investigated the relationship between statins and the incidence of diabetes. Therefore, we analyzed the progression from normal blood glucose to prediabetes and then to diabetes mellitus (DM) according to the type, intensity, and dose of statin prescribed. METHODS: Data of patients who were first prescribed statins between 2009 and 2011 were extracted from electronic medical records. Patients with normal blood glucose or prediabetes were observed for 4 years after initiation of statin therapy. RESULTS: A total of 2890 patients were included in our study and analyzed on the basis of the first statin they were prescribed. The incidence rate of DM in patients with prediabetes was 1.72 times that of patients with normal glucose levels (odds ratio = 1.72, 95% confidence interval = 1.41-2.10, P < .001). Regarding progression from normal blood glucose to prediabetes, the incidence rate of prediabetes was significantly lower in patients prescribed pitavastatin (odds ratio = 0.62, 95% confidence interval = 0.40-0.96, P = .031) compared to that in patients prescribed atorvastatin. Regarding the progression from normal blood glucose or prediabetes to DM, there were no significant differences among all statins. CONCLUSIONS: Lower DM incidence in patients prescribed pitavastatin appears to be primarily because of the lower rate of progression from normal blood glucose to prediabetes. These findings indicate that avoiding statins because of DM risk is unjustified and that clinicians should prescribe statins from the appropriate potency group.