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In Japan, an increasing interest in real-world evidence for hypothesis generation and decision-making has emerged in order to overcome limitations and restrictions of clinical trials. We sought to characterize the context and concrete considerations of when to use Medical Data Vision (MDV) and JMDC databases, the main Japanese real-world data (RWD) sources accessible by pharmaceutical companies. Use cases for these databases, and related issues and considerations, were identified and summarized based on a literature search and experience-based knowledge. Studies conducted using MDV or JMDC were mostly descriptive in nature, or explored potential risk factors by evaluating associations with a target outcome. Considerations such as variable ascertainment at different time points, including issues relating to treatment identification and missing data, were highlighted for these two databases. Although several issues were commonly shared (e.g., only month of event occurrence reported), some database-specific issues were also identified and need to be accounted for. In conclusion, MDV and JMDC present limitations that are relatively typical of RWD sources, though some of them are unique to Japan, such as the identification of event occurrence and the inability to track patients visiting different healthcare settings. Addressing study design and careful result interpretation with respect to the specificities and uniqueness of the Japanese healthcare system is of particular importance. This aspect is especially relevant with respect to the growing global interest of conducting RWD studies in Japan.

Background Administrative claims data are a valuable source for clinical studies; however, the use of validated algorithms to identify patients is essential to minimize bias. We evaluated the validity of diagnostic coding algorithms for identifying patients with colorectal cancer from a hospital’s administrative claims data. Methods This validation study used administrative claims data from a Japanese university hospital between April 2017 and March 2019. We developed diagnostic coding algorithms, basically based on the International Classification of Disease (ICD) 10th codes of C18–20 and Japanese disease codes, to identify patients with colorectal cancer. For random samples of patients identified using our algorithms, case ascertainment was performed using chart review as the gold standard. The positive predictive value (PPV) was calculated to evaluate the accuracy of the algorithms. Results Of 249 random samples of patients identified as having colorectal cancer by our coding algorithms, 215 were confirmed cases, yielding a PPV of 86.3% (95% confidence interval [CI], 81.5–90.1%). When the diagnostic codes were restricted to site-specific (right colon, left colon, transverse colon, or rectum) cancer codes, 94 of the 100 random samples were true cases of colorectal cancer. Consequently, the PPV increased to 94.0% (95% CI, 87.2–97.4%). Conclusion Our diagnostic coding algorithms based on ICD-10 codes and Japanese disease codes were highly accurate in detecting patients with colorectal cancer from this hospital’s claims data. The exclusive use of site-specific cancer codes further improved the PPV from 86.3 to 94.0%, suggesting their desirability in identifying these patients more precisely.

Background: Second-hand smoke exposure has been associated with poor mental health. However, among Japanese adults, little is known about the association between second-hand smoking and depressive symptoms. We examined this association in a cross-sectional study among a Japanese general adult population sample. Methods: Japanese adults were recruited from the Japan Multi-Institutional Collaborative Cohort Study in the Okazaki area between 2012 and 2017. Second-hand smoke exposure and smoking status were assessed using a self-administered questionnaire. Based on their frequency of exposure to second-hand smoke, non-smokers and smokers were categorized as “almost never,” “sometimes,” and “almost every day”. Depressive symptoms were defined by a Kessler 6 score ≥5 points. We performed a multivariable Poisson regression analysis to obtain adjusted prevalence ratios (PRs) and 95% confidence intervals (CIs) for depressive symptoms. Results: Overall, 5,121 participants (4,547 non-smokers and 574 smokers) were included whose mean age was 63.6 (standard deviation [SD], 10.3) years for non-smokers and 59.33 (SD, 10.2) years for smokers. The association between second-hand smoking and depressive symptoms was significant among non-smokers, but not among smokers. Among non-smokers, PRs compared with “almost never” were 1.25 (95% CI, 1.09–1.42) for “sometimes” and 1.41 (95% CI, 1.09–1.84) for “almost every day” (P for trend <0.001); among smokers, PRs compared with “almost never” were 1.30 (95% CI, 0.82–2.06) for “sometimes” and 1.44 (95% CI, 0.90–2.33) for “almost every day” (P for trend = 0.144). Conclusions: Second-hand smoking and depressive symptoms were associated among non-smokers. Our findings indicate the importance of tobacco smoke control for mental health.

Background Time-related bias can lead to misleading conclusions. Properly setting the \"time zero\" of follow-up is crucial for avoiding these biases. However, the time-zero setting is challenging when comparing users and non-users of a study drug because the latter do not have a time point for starting treatment. Objective This methodological study aimed to illustrate the impact of different time-zero settings on effect estimates in a comparative effectiveness study using real-world data with a non-user comparator. Methods Data for type 2 diabetes patients were extracted from an administrative claims database, and the onset of diabetic retinopathy (study outcome) was compared between users (treatment group) and non-users (non-use group) of lipid-lowering agents. We applied six time-zero settings to the same dataset. The adjusted hazard ratio (HR) for the outcome was estimated using a Cox regression model in each time-zero setting, and the obtained results were compared among the settings. Results Of the six settings, three (study entry date [SED] vs SED [naïve approach], treatment initiation [TI] vs SED, TI vs Matched [random order]) showed that the treatment had a reduced risk of the outcome (HR [95% CI]: 0.65 [0.61–0.69], 0.92 [0.86–0.97], and 0.76 [0.71–0.82], respectively), one (TI vs Random) had an increased risk (HR [95% CI]: 1.52 [1.40–1.64]) , and two (SED vs SED [cloning method], and TI vs Matched [systematic order]) had neither increased nor decreased risk (HR [95% CI]: 0.95 [0.93–1.13], and 0.99 [0.93–1.07], respectively). Conclusions This study demonstrates that different time-zero settings can lead to different conclusions, even if the same dataset is analyzed for the same research question, probably because improper settings can introduce bias. To minimize such biases, researchers should carefully define time zero, particularly when designing a non-user comparator study using real-world data.

Background Validated coding algorithms are essential to generate high-quality, real-world evidence from claims data studies. Objective We aimed to evaluate the validity of the algorithms to identify patients with bone metastases using claims data from a Japanese hospital. Patients and Methods This study used administrative claims data and electronic medical records at Juntendo University Hospital from April 2017 to March 2019. We developed two candidate claims-based algorithms to detect bone metastases, one based on diagnosis codes alone (Algorithm 1) and the other based on the combination of diagnosis and imaging test codes (Algorithm 2). Of the patients identified by Algorithm 1, 100 patients were randomly sampled. Among these 100 patients, 88 patients met the conditions of Algorithm 2; further, 12 additional patients were randomly sampled from those identified by Algorithm 2, thus obtaining a total of 100 patients for Algorithm 2. They were evaluated for their true diagnosis using the patient chart review as the gold standard. The positive predictive value (PPV) was calculated to assess the accuracy of each algorithm. Results For Algorithm 1, 82 patients were analyzed after excluding 18 patients without diagnostic imaging reports. Of these, 69 patients were true positive by chart review, resulting in a PPV of 84.1% (95% confidence interval (CI) 74.5–90.6). For Algorithm 2, 92 patients were analyzed after excluding eight patients whose diagnoses were not judged by chart review. Of these, 76 patients were confirmed positive by chart review, yielding a PPV of 82.6% (95% CI 73.4–89.1). Conclusion Both claims-based algorithms yielded high PPVs of approximately 85%, with no improvement in PPV by adding imaging test conditions. The diagnosis code-based algorithm is sufficient and valid for identifying bone metastases in this Japanese hospital.

Background Use of real-world evidence (RWE) has been limited for evaluating effectiveness because of the lack of confidence in its reliability. Examining whether a rigorously designed observational study using real-world data (RWD) can reproduce the results of a randomized controlled trial (RCT) will provide insights into the implementation of high-quality RWE studies that can produce valid conclusions. Objective We aimed to replicate published RCTs using a Japanese claims and health checkup database and examine whether the emulated RWE studies’ results agree with those of the original RCTs. Methods We selected three RCTs on diabetes medications for replication in patients with type 2 diabetes. The study outcome was either the change or percentage change in HbA1c levels from baseline. We designed three observational studies using the RWD to mimic the critical study elements of the respective RCTs as closely as possible. We performed 1:1 propensity score nearest-neighbor matching to balance the groups for potential confounders. The differences in outcomes between the groups and their 95% confidence intervals (CIs) were calculated in each RWE study, and the results were compared with those of the RCT. Results Patient characteristics, such as age, sex, and duration of diabetes, differed between the RWE studies and RCTs. In Trial 1 emulation, the percentage changes in HbA1c levels were larger in the treatment group than in the comparator group (difference −6.21, 95% confidence interval (CI) −11.01 to −1.40). In Trial 2, the change in HbA1c level was larger in the treatment group (difference −0.01; 95% CI −0.25 to 0.23), and in Trial 3, it was smaller in the treatment group (difference 0.46; 95% CI −0.01 to 0.94). These results did not show regulatory or estimate agreement with the RCTs. Conclusions None of the three emulated RWE studies using this claims and health checkup database reproduced the same conclusions as the RCTs. These discrepancies could largely be attributed to design differences between RWE studies and RCTs, primarily due to the lack of necessary data in the database. This particular RWD source may not be the best fit for evaluating treatment effects using laboratory data as the study outcome.

The generation of real-world evidence (RWE), which describes patient characteristics or treatment patterns using real-world data (RWD), is rapidly growing more popular as a tool for decision-making in Japan. The aim of this review was to summarize challenges to RWE generation in Japan related to pharmacoepidemiology, and to propose strategies to address some of these challenges. We first focused on data-related issues, including the lack of transparency of RWD sources, linkage across different care settings, definitions of clinical outcomes, and the overall assessment framework of RWD when used for research purposes. Next the study reviewed methodology-related challenges. As lack of design transparency impairs study reproducibility, transparent reporting of study design is critical for stakeholders. For this review, we considered different sources of biases and time-varying confounding, along with potential study design and methodological solutions. Additionally, the implementation of robust assessment of definition uncertainty, misclassification, and unmeasured confounders would enhance RWE credibility in light of RWD source-related limitations, and is being strongly considered by task forces in Japan. Overall, the development of guidance for best practices on data source selection, design transparency, and analytical methods to address different sources of biases and robustness in the process of RWE generation will enhance credibility for stakeholders and local decision-makers.

Background: It is known that physical activity affects glucose metabolism. However, there have been no reports on the influence of physical activity earlier in life on subsequent glucose metabolism. Therefore, we analyzed the influence of physical activity in earlier decades of life on insulin resistance in middle aged and older residents in Japan. Methods: The subjects were 6,883 residents of Okazaki City between the ages of 40 and 79 years who underwent physical examinations at the Okazaki City Medical Association Public Health Center from April 2007 through August 2011. They gave informed consent for participation in the study. Data on individual characteristics were collected via a questionnaire and from the health examination records. Fasting blood glucose and insulin levels were used to calculate the homeostatic model assessment of insulin resistance (HOMA-IR). HOMA-IR >1.6 was considered to indicate insulin resistance for the purpose of logistic regression models. Results: The study sample included 3,683 men and 3,200 women for whom complete information was available. For those who exercised regularly throughout their teens to their 30s–40s, the odds ratio for having insulin resistance was 0.75 (95% confidence interval [CI], 0.58–0.96) for men and 0.76 (95% CI, 0.58–0.99) for women after adjusting for other variables, including age, body mass index, and present physical activity. A linear trend was also observed in both men and women. Conclusions: Subjects who have exercised regularly in the early decades of life are less likely to have insulin resistance later in life.

IntroductionAlthough patients with HBV have a risk of reactivation after immunosuppressive therapy (IST), the status of their risk management is unclear in Japan. This study aims to describe the proportion of patients who received preventive management of HBV reactivation during ISTs in patients with chronic HBV infection of HBsAg or resolved HBV infection.MethodA retrospective cohort study was conducted using the JMDC Japanese claims database from April 2011 to June 2021. Patients with HBV infections of HbsAg who received ISTs or patients who had resolved HBV infections who received ISTs were identified from the database and evaluated for appropriate management to prevent HBV reactivation.ResultsIn total, 6242 eligible patients were identified. The proportions of patients with appropriate HBV reactivation management, stratified by the HBV reactivation risk level of IST, was 43.1% (276/641) for high-risk, 40.2% (223/555) for intermediate-risk and 14.9% (741/4965) for low-risk patients. When the evaluation period for the outcome calculation was shortened from 360 to 180 days, the proportion for high risk increased to 52.7%. The odds ratios of large hospitals for receiving appropriate management were 2.16 (95% CI 1.12–4.44) in the high-risk, 4.63 (95% CI 2.34–10.25) in the intermediate-risk and 3.60 (95% CI 3.07–4.24) in the low-risk patients.ConclusionHBV reactivation management was tailored according to the reactivation risk associated with IST. However, adherence to HBV reactivation management guidelines was sub-optimal, even among high-risk patients. This is especially the case for ensuring smaller-sized medical institutions, highlighting the need for further educational activities.Plain Language SummaryThe study assesses the implementation of guideline-based management of hepatitis B virus reactivation during immunosuppressive therapy in Japan. The appropriate management of hepatitis B virus treatment involves prophylactic nucleos(t)ide analog (NUC) therapy and regular monitoring of hepatitis B virus DNA. This study aims to assess the extent to which these management practices are implemented in a clinical setting in Japan using a retrospective cohort study using the Japanese Medical Claims Database. The analysis identified 6242 eligible patients and identified whether they received appropriate management to prevent hepatitis B virus reactivation based on the level of risk associated with their immunosuppressive therapy. Based on the guidelines, the proportions of patients receiving appropriate reactivation management were 43.1% for high-risk, 40.2% for intermediate-risk and 14.9% for low-risk immunosuppressive therapy patients. Shortening the evaluation period from 360 to 180 days showed an increase in the proportion of high-risk patients to 52.7%, which indicated the potential challenge for continued monitoring after immunosuppressive therapy administration. The study shows that large hospitals present higher odds of patients receiving appropriate management. Overall, adherence to hepatitis B virus reactivation management guidelines was suboptimal, especially in smaller medical institutions, emphasizing the need for additional educational activities.

Introduction While direct-acting antivirals (DAA) are effective treatment for hepatitis C virus (HCV) patients, concerns about drug-drug interactions (DDIs) remain a significant challenge. Although there are several studies investigating the risk of DDIs associated with DAA therapy, there is limited research evaluating DDIs of DAA therapy in real-world settings in Japan. We investigated prescription patterns of comedication associated with DDIs risk in HCV patients receiving DAA therapy using a large Japanese database. Methods This was a descriptive epidemiological study, using the Japanese administrative claims database provided by DeSC Healthcare, Inc. Patients who initiated sofosbuvir/velpatasvir (SOF/VEL) or glecaprevir/pibrentasvir (GLE/PIB) between April 2017 and August 2023 were identified from the data. The primary outcome was DDIs associated with comedications which were assessed based on both Japanese package inserts and the Liverpool HEP Drug Interaction Checker (Liverpool HEP checker). Results Patients included in this study were 7,338, with 467 prescribed SOF/VEL and 6,871 prescribed GLE/PIB. The mean age of the patients was 69.9 years (SD = 13.1), with 50% being male. The median number of comedications was higher in the SOF/VEL group (14.0; IQR = 14.0) than in the GLE/PIB group (9.0; IQR = 12.0) and based on package insert and Liverpool HEP checker, the DDI risk was present in 59.3% (277) of the SOF/VEL group and 51.5% (3,542) of the GLE/PIB group. DDI risk involving two or more medications in combination with a DAA was 14.1% (66) in the SOF/VEL group and 24.0% (1,648) in the GLE/PIB group. In terms of DDI severity, in the SOF/VEL group there were no patients identified under the level “Contraindication (Red)” category, indicating medications that do not co-administered, in contrast with the 1.7% (115) in the GLE/PIB group who were identified as “contraindication (red)”. Conclusion A considerable proportion of patients were prescribed medications with DDI risk during DAA treatment. A small but notable proportion of patients were on “Contraindication (Red)” medications. Consideration of the potential DDI risks associated with comedications by healthcare professionals is advised, referring not only to package inserts but also tools such as Liverpool HEP checker to guide safe prescribing when initiating DAA therapy for HCV patients.