Current Status, Challenges, and Future Perspectives of Real-World Data and Real-World Evidence in Japan

Usefulness and caveats of real-world data for research on hypertension and its association with cardiovascular or renal disease in Japan

The role of real-world data, collected from clinical practice rather than clinical trials, has become increasingly important for investigating real-life situations, such as treatment effects. In Japan, evidence on hypertension, cardiovascular diseases, and kidney diseases using real-world data is increasing. These studies are mainly based on "the insurer-based real-world data" collected as electronic records, including data from health check-ups and medical claims such as JMDC database, DeSC database, the Japan Health Insurance Association (JHIA) database, or National Databases of Health Insurance Claims and Specific Health Checkups (NDB). Based on the insurer-based real-world data, traditional but finely stratified associations between hypertension and cardiovascular or kidney diseases can be explored. The insurer-based real-world data are also useful for pharmacoepidemiological studies that capture the distribution and trends of drug prescriptions; combined with annual health check-up data, the effectiveness of drugs can also be examined. Despite the usefulness of insurer-based real-world data collected as electronic records from a wide range of populations, we must be cautious about several points, including issues regarding population uncertainty, the validity of cardiovascular outcomes, the accuracy of blood pressure, traceability, and biases, such as indication and immortal biases. While a large sample size is considered a strength of real-world data, we must keep in mind that it does not overcome the problem of systematic error. This review discusses the usefulness and pitfalls of insurer-based real-world data in Japan through recent examples of Japanese research on hypertension and its association with cardiovascular or kidney disease.

Annual trends in atypical haemolytic uremic syndrome management in Japan and factors influencing early diagnosis and treatment: a retrospective study

Atypical haemolytic uremic syndrome (aHUS) is a rare disorder characterised by complement-mediated thrombotic microangiopathy (TMA). Despite clinical guidelines, the diagnosis and treatment of aHUS in its early stages remains challenging. This study examined the annual trends in aHUS clinical practices in Japan and explored factors influencing early diagnosis and treatment. Using data from the 2011-2020 Diagnosis Procedure Combination database, 3096 cases with the HUS disease code were identified, of which 217 were confirmed as aHUS and treated with eculizumab or plasma exchange. Early initiation, defined as starting eculizumab or plasma exchange within 7 days of admission, was the focus of the study. Our study revealed no significant changes over time in the number of aHUS diagnoses, cases treated with eculizumab, or early initiation cases. Early initiation cases underwent haemodialysis earlier and had ADAMTS13 activity measured earlier, shorter hospital stays, and lower hospitalisation costs than late initiation cases. In conclusion, we found no increase in the number of newly diagnosed aHUS cases or early treatment initiation over time. Early recognition of TMA and differentiation of the causative disease are crucial for identifying potential aHUS cases, which may lead to better patient prognoses.

Risk of Urogenital Bacterial Infection with Sodium-Glucose Cotransporter-2 Inhibitors: A Retrospective Cohort Study Using a Claims Database

INTRODUCTION

The association between sodium-glucose cotransporter-2 (SGLT2) inhibitors and the risk of urogenital infections remains controversial. This study aimed to investigate the association between SGLT2 inhibitors and the incidence of perineal soft tissue infections, including Fournier's gangrene (FG), genital bacterial infections, and urinary tract infections (UTIs), using administrative claims data in Japan.

METHODS

In this retrospective cohort study, we utilized the JMDC Claims Database. The study included patients aged 18 years or older diagnosed with type 2 diabetes mellitus, identified by a diagnostic code, who received new prescriptions for SGLT2 inhibitors or dipeptidyl peptidase 4 (DPP-4) inhibitors between April 2014 and August 2020. Using one-to-one propensity score (PS) matching, we compared the incidence of perineal soft tissue infections, including FG, genital bacterial infection, and UTIs between groups treated with SGLT2 and DPP-4 inhibitors. Hazard ratios (HR) and their 95% confidence intervals (CI) were estimated using the Cox proportional hazards model.

RESULTS

We identified 34,897 patients in the SGLT2 inhibitor group and 135,311 patients in the DPP-4 inhibitor group. After one-to-one PS matching, 31,665 pairs were generated. The mean age of the patients was 51 years, with approximately 70% being male. The use of SGLT2 inhibitors was associated with a decreased risk of UTI (HR 0.90, 95% CI 0.83-0.98) and an increased risk of genital bacterial infection (HR 1.23, 95% CI 1.03-1.46) compared to DPP-4 inhibitors. However, no significant association was observed with perineal soft tissue infection (HR 1.05, 95% CI 0.61-1.81).

CONCLUSIONS

SGLT2 inhibitors were associated with a reduced risk of UTI and an increased risk of genital bacterial infection. They showed no significant association with perineal soft tissue infection when compared to DPP-4 inhibitors. Future research should explore broader demographics, focusing on the elderly and achieving gender balance, to gain a comprehensive understanding of infection risks.

Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study

BACKGROUND

The integrity and reliability of clinical research outcomes rely heavily on access to vast amounts of data. However, the fragmented distribution of these data across multiple institutions, along with ethical and regulatory barriers, presents significant challenges to accessing relevant data. While federated learning offers a promising solution to leverage insights from fragmented data sets, its adoption faces hurdles due to implementation complexities, scalability issues, and inclusivity challenges.

OBJECTIVE

This paper introduces Federated Learning for Everyone (FL4E), an accessible framework facilitating multistakeholder collaboration in clinical research. It focuses on simplifying federated learning through an innovative ecosystem-based approach.

METHODS

The "degree of federation" is a fundamental concept of FL4E, allowing for flexible integration of federated and centralized learning models. This feature provides a customizable solution by enabling users to choose the level of data decentralization based on specific health care settings or project needs, making federated learning more adaptable and efficient. By using an ecosystem-based collaborative learning strategy, FL4E encourages a comprehensive platform for managing real-world data, enhancing collaboration and knowledge sharing among its stakeholders.

RESULTS

Evaluating FL4E's effectiveness using real-world health care data sets has highlighted its ecosystem-oriented and inclusive design. By applying hybrid models to 2 distinct analytical tasks-classification and survival analysis-within real-world settings, we have effectively measured the "degree of federation" across various contexts. These evaluations show that FL4E's hybrid models not only match the performance of fully federated models but also avoid the substantial overhead usually linked with these models. Achieving this balance greatly enhances collaborative initiatives and broadens the scope of analytical possibilities within the ecosystem.

CONCLUSIONS

FL4E represents a significant step forward in collaborative clinical research by merging the benefits of centralized and federated learning. Its modular ecosystem-based design and the "degree of federation" feature make it an inclusive, customizable framework suitable for a wide array of clinical research scenarios, promising to revolutionize the field through improved collaboration and data use. Detailed implementation and analyses are available on the associated GitHub repository.

Long-term efficacies of selective vasodilators in pulmonary arterial hypertension: a comprehensive comparison using a spontaneous reporting database

There is no clinical evidence of differences in drugs associated with long-term survival in patients with pulmonary arterial hypertension (PAH) due to the small population and lack of information on death in Japanese medical database systems. This study evaluated whether patient data from a spontaneous reporting database could be used for comparing the effects of pulmonary vasodilators on long-term survival in PAH patients. PAH patient data reported in the Japanese Adverse Drug Event Report (JADER) database from April 2004 to July 2022 were extracted. Kaplan-Meier curves were used to compare survival times. Adjusted hazard ratios (aHRs) for all-cause mortality were determined using Cox proportional hazards models. Of 1969 PAH patients reported in the JADER database, 1208 were included in the survival analyses. The patient demographics were similar to those of the PAH population reported in the Japan Pulmonary Hypertension Registry. Among drugs targeting the prostacyclin pathway, epoprostenol was most associated with long-term survival (aHR, 0.38; 95% confidence interval (CI), 0.23-0.64). The PAH patients treated with endothelin receptor antagonists had improved survival, especially among the macitentan users (aHR, 0.30; 95% CI, 0.22-0.42). Sildenafil was associated with a poor prognosis in the PAH patients (aHR, 1.56; 95% CI, 1.19-2.04). Although our results must be interpreted with caution due to several limitations inherent to spontaneous reporting databases, our approach using the JADER database for survival analysis may provide useful information in limited situations such as the treatment of rare diseases including PAH.

Real-world evidence of systemic treatment practices for biliary tract cancer in Japan: Results of a database study

PURPOSE

To describe the real-world treatment patterns of systemic therapies for biliary tract cancer (BTC) and to examine the frequency and management of biliary infection in Japan.

METHODS

Patients diagnosed with BTC and prescribed systemic therapy between January 2011 and September 2020 were retrieved from the Japanese Medical Data Vision database. The look-back period was set to 5 years. Patient characteristics, treatment patterns, and biliary infection-induced treatment interruption were analyzed.

RESULTS

The full analysis set comprised 22 742 patients with a mean age of 71.0 years and 61.6% were male. The most common BTC type was extrahepatic cholangiocarcinoma (44.6%). The three most common first-line regimens were S-1 monotherapy (33.0%), gemcitabine+cisplatin (32.5%), and gemcitabine monotherapy (18.7%) over the entire observation period (January 2011-September 2021). Patients who received monotherapies tended to be older. Biliary infection-induced treatment interruption occurred in 29.5% of patients, with a median time to onset of 64.0 (interquartile range 29.0-145.0) days. The median duration of intravenous antibiotics was 12.0 (interquartile range 4.0-92.0) days.

CONCLUSIONS

These results demonstrated potential challenges of BTC in Japanese clinical practice particularly use of multiple regimens, commonly monotherapies, which are not recommended as first-line treatment, and the management of biliary infections during systemic therapy.

Integrated Real-World Data Warehouses Across 7 Evolving Asian Health Care Systems: Scoping Review

BACKGROUND

Asia consists of diverse nations with extremely variable health care systems. Integrated real-world data (RWD) research warehouses provide vast interconnected data sets that uphold statistical rigor. Yet, their intricate details remain underexplored, restricting their broader applications.

OBJECTIVE

Building on our previous research that analyzed integrated RWD warehouses in India, Thailand, and Taiwan, this study extends the research to 7 distinct health care systems: Hong Kong, Indonesia, Malaysia, Pakistan, the Philippines, Singapore, and Vietnam. We aimed to map the evolving landscape of RWD, preferences for methodologies, and database use and archetype the health systems based on existing intrinsic capability for RWD generation.

METHODS

A systematic scoping review methodology was used, centering on contemporary English literature on PubMed (search date: May 9, 2023). Rigorous screening as defined by eligibility criteria identified RWD studies from multiple health care facilities in at least 1 of the 7 target Asian nations. Point estimates and their associated errors were determined for the data collected from eligible studies.

RESULTS

Of the 1483 real-world evidence citations identified on May 9, 2023, a total of 369 (24.9%) fulfilled the requirements for data extraction and subsequent analysis. Singapore, Hong Kong, and Malaysia contributed to ≥100 publications, with each country marked by a higher proportion of single-country studies at 51% (80/157), 66.2% (86/130), and 50% (50/100), respectively, and were classified as solo scholars. Indonesia, Pakistan, Vietnam, and the Philippines had fewer publications and a higher proportion of cross-country collaboration studies (CCCSs) at 79% (26/33), 58% (18/31), 74% (20/27), and 86% (19/22), respectively, and were classified as global collaborators. Collaboration with countries outside the 7 target nations appeared in 84.2% to 97.7% of the CCCSs of each nation. Among target nations, Singapore and Malaysia emerged as preferred research partners for other nations. From 2018 to 2023, most nations showed an increasing trend in study numbers, with Vietnam (24.5%) and Pakistan (21.2%) leading the growth; the only exception was the Philippines, which declined by -14.5%. Clinical registry databases were predominant across all CCCSs from every target nation. For single-country studies, Indonesia, Malaysia, and the Philippines favored clinical registries; Singapore had a balanced use of clinical registries and electronic medical or health records, whereas Hong Kong, Pakistan, and Vietnam leaned toward electronic medical or health records. Overall, 89.9% (310/345) of the studies took >2 years from completion to publication.

CONCLUSIONS

The observed variations in contemporary RWD publications across the 7 nations in Asia exemplify distinct research landscapes across nations that are partially explained by their diverse economic, clinical, and research settings. Nevertheless, recognizing these variations is pivotal for fostering tailored, synergistic strategies that amplify RWD's potential in guiding future health care research and policy decisions.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/43741.

Expert survey on real-world data utilization and real-world evidence generation for regulatory decision-making in drug lifecycle in Korea

As the importance of utilizing real-world data (RWD)/real-world evidence (RWE) for supporting regulatory scientific decision-making continues to grow, experiences and inputs from experts become crucial for developing a systematic and practice-oriented plan for the use of fit-for-purpose RWD/RWE. This study aimed to survey relevant experts from government agencies, industries, and academia to identify prerequisites for the drug life cycle in Korea. The questionnaire comprised the following: (A) the definition and categories of RWD/RWE, (B) the suitability and feasibility of using RWD/RWE at each authorization stage by the types of RWD, and (C) the challenges and solutions for the use of RWD/RWE. A total of 46 respondents completed the online survey, with 89.1% of them having prior experience with RWD/RWE usage. A majority of respondents agreed that RWD can be obtained from various sources. Among these sources, the registry was the most suitable source. It is suitable to compensate for the limitations of randomized control trials and ensure quality in data collection. Though there was consensus among the respondents for the use of RWD/RWE in post-marketing surveillance, the use of such data in new drug application (NDA) was disagreeable. Respondents considered it necessary to write a protocol in advance for RWD collection and RWE generation, for all RWD types. In conclusion, this study examined the perceptions of experts for RWD/RWE use at each approval stage of drugs. The results suggest that guidelines for the fit-for-purpose use of RWD/RWE should be developed via careful deliberation among experts in the future.

The Journey of Data Within a Global Data Sharing Initiative: A Federated 3-Layer Data Analysis Pipeline to Scale Up Multiple Sclerosis Research

BACKGROUND

Investigating low-prevalence diseases such as multiple sclerosis is challenging because of the rather small number of individuals affected by this disease and the scattering of real-world data across numerous data sources. These obstacles impair data integration, standardization, and analysis, which negatively impact the generation of significant meaningful clinical evidence.

OBJECTIVE

This study aims to present a comprehensive, research question-agnostic, multistakeholder-driven end-to-end data analysis pipeline that accommodates 3 prevalent data-sharing streams: individual data sharing, core data set sharing, and federated model sharing.

METHODS

A demand-driven methodology is employed for standardization, followed by 3 streams of data acquisition, a data quality enhancement process, a data integration procedure, and a concluding analysis stage to fulfill real-world data-sharing requirements. This pipeline's effectiveness was demonstrated through its successful implementation in the COVID-19 and multiple sclerosis global data sharing initiative.

RESULTS

The global data sharing initiative yielded multiple scientific publications and provided extensive worldwide guidance for the community with multiple sclerosis. The pipeline facilitated gathering pertinent data from various sources, accommodating distinct sharing streams and assimilating them into a unified data set for subsequent statistical analysis or secure data examination. This pipeline contributed to the assembly of the largest data set of people with multiple sclerosis infected with COVID-19.

CONCLUSIONS

The proposed data analysis pipeline exemplifies the potential of global stakeholder collaboration and underlines the significance of evidence-based decision-making. It serves as a paradigm for how data sharing initiatives can propel advancements in health care, emphasizing its adaptability and capacity to address diverse research inquiries.

Utilization of anonymization techniques to create an external control arm for clinical trial data

BACKGROUND

Subject-level real-world data (RWD) collected during daily healthcare practices are increasingly used in medical research to assess questions that cannot be addressed in the context of a randomized controlled trial (RCT). A novel application of RWD arises from the need to create external control arms (ECAs) for single-arm RCTs. In the analysis of ECAs against RCT data, there is an evident need to manage and analyze RCT data and RWD in the same technical environment. In the Nordic countries, legal requirements may require that the original subject-level data be anonymized, i.e., modified so that the risk to identify any individual is minimal. The aim of this study was to conduct initial exploration on how well pseudonymized and anonymized RWD perform in the creation of an ECA for an RCT.

METHODS

This was a hybrid observational cohort study using clinical data from the control arm of the completed randomized phase II clinical trial (PACIFIC-AF) and RWD cohort from Finnish healthcare data sources. The initial pseudonymized RWD were anonymized within the (k, ε)-anonymity framework (a model for protecting individuals against identification). Propensity score matching and weighting methods were applied to the anonymized and pseudonymized RWD, to balance potential confounders against the RCT data. Descriptive statistics for the potential confounders and overall survival analyses were conducted prior to and after matching and weighting, using both the pseudonymized and anonymized RWD sets.

RESULTS

Anonymization affected the baseline characteristics of potential confounders only marginally. The greatest difference was in the prevalence of chronic obstructive pulmonary disease (4.6% vs. 5.4% in the pseudonymized compared to the anonymized data, respectively). Moreover, the overall survival changed in anonymization by only 8% (95% CI 4-22%). Both the pseudonymized and anonymized RWD were able to produce matched ECAs for the RCT data. Anonymization after matching impacted overall survival analysis by 22% (95% CI -21-87%).

CONCLUSIONS

Anonymization may be a viable technique for cases where flexible data transfer and sharing are required. As anonymization necessarily affects some aspects of the original data, further research and careful consideration of anonymization strategies are needed.

Trends in teicoplanin loading dose implementation from 2010 to 2019 and evaluation of safety and efficacy factors: a retrospective cohort study based on a Japanese administrative claims database

BACKGROUND

The loading dose of teicoplanin (TEIC) is recommended for implementation. However, there is significant discrepancy between the dose settings in the package insert and, in the guidelines, and the actual status of loading doses in Japan is unclear. Furthermore, TEIC causes liver injury as side effect. Although the risk of developing liver injury has not been reported to be increased following a loading dose based on the guidelines, there is a lack of reports in large populations. Therefore, we evaluated the trend in the loading dose and factors affecting the efficacy and safety of TEIC administration.

METHODS

A Japanese administrative claims database was used in this study. Trends in loading doses were evaluated in target populations administered TEIC between 2010 and 2019. Patient characteristics were adjusted by propensity score matching based on the guideline group (total dose of 3 days > 1,600 mg) and non-guideline group (≤ 1,600 mg) of the loading dose. Finally, univariable and multivariable conditional logistic regression analysis was performed to evaluate factors affecting 30-day mortality and liver injury.

RESULTS

A total of 10,030 patients were selected based on these criteria. The proportion of loading doses based on the recommended guidelines showed an increase over time, regardless of the implementation of therapeutic drug monitoring (TDM), but especially so in cases where TDM was implemented, the loading doses were administered in accordance with the recommendations of the guidelines. Conditional logistic regression analysis showed a relationship between drug management and guidance fees (odds ratio [OR]: 0.45, 95% confidence interval [CI]: 0.36‒0.55), a reimbursement indicating pharmacist intervention, and a reduction in 30-day mortality. In addition, loading doses based on the recommended guidelines had no influence on liver injury, and other factors were not significantly associated with increased incidence of liver injury.

CONCLUSION

Thus, this study implies the benefits of pharmacological management as indicated by drug management and guidance fee and supports the implementation of loading doses based on the guideline on TEIC administration.

Real-world evidence to advance knowledge in pulmonary hypertension: Status, challenges, and opportunities. A consensus statement from the Pulmonary Vascular Research Institute's Innovative Drug Development Initiative's Real-world Evidence Working Group

This manuscript on real-world evidence (RWE) in pulmonary hypertension (PH) incorporates the broad experience of members of the Pulmonary Vascular Research Institute's Innovative Drug Development Initiative Real-World Evidence Working Group. We aim to strengthen the research community's understanding of RWE in PH to facilitate clinical research advances and ultimately improve patient care. Herein, we review real-world data (RWD) sources, discuss challenges and opportunities when using RWD sources to study PH populations, and identify resources needed to support the generation of meaningful RWE for the global PH community.

Integrated Real-World Study Databases in 3 Diverse Asian Health Care Systems in Taiwan, India, and Thailand: Scoping Review

BACKGROUND

The use of real-world data (RWD) warehouses for research in Asia is on the rise, but current trends remain largely unexplored. Given the varied economic and health care landscapes in different Asian countries, understanding these trends can offer valuable insights.

OBJECTIVE

We sought to discern the contemporary landscape of linked RWD warehouses and explore their trends and patterns in 3 Asian countries with contrasting economies and health care systems: Taiwan, India, and Thailand.

METHODS

Using a systematic scoping review methodology, we conducted an exhaustive literature search on PubMed with filters for the English language and the past 5 years. The search combined Medical Subject Heading terms and specific keywords. Studies were screened against strict eligibility criteria to identify eligible studies using RWD databases from more than one health care facility in at least 1 of the 3 target countries.

RESULTS

Our search yielded 2277 studies, of which 833 (36.6%) met our criteria. Overall, single-country studies (SCS) dominated at 89.4% (n=745), with cross-country collaboration studies (CCCS) being at 10.6% (n=88). However, the country-wise breakdown showed that of all the SCS, 623 (83.6%) were from Taiwan, 81 (10.9%) from India, and 41 (5.5%) from Thailand. Among the total studies conducted in each country, India at 39.1% (n=133) and Thailand at 43.1% (n=72) had a significantly higher percentage of CCCS compared to Taiwan at 7.6% (n=51). Over a 5-year span from 2017 to 2022, India and Thailand experienced an annual increase in RWD studies by approximately 18.2% and 13.8%, respectively, while Taiwan's contributions remained consistent. Comparative effectiveness research (CER) was predominant in Taiwan (n=410, or 65.8% of SCS) but less common in India (n=12, or 14.8% of SCS) and Thailand (n=11, or 26.8% of SCS). CER percentages in CCCS were similar across the 3 countries, ranging from 19.2% (n=10) to 29% (n=9). The type of RWD source also varied significantly across countries, with India demonstrating a high reliance on electronic medical records or electronic health records at 55.6% (n=45) of SCS and Taiwan showing an increasing trend in their use over the period. Registries were used in 26 (83.9%) CCCS and 31 (75.6%) SCS from Thailand but in <50% of SCS from Taiwan and India. Health insurance/administrative claims data were used in most of the SCS from Taiwan (n=458, 73.5%). There was a consistent predominant focus on cardiology/metabolic disorders in all studies, with a noticeable increase in oncology and infectious disease research from 2017 to 2022.

CONCLUSIONS

This review provides a comprehensive understanding of the evolving landscape of RWD research in Taiwan, India, and Thailand. The observed differences and trends emphasize the unique economic, clinical, and research settings in each country, advocating for tailored strategies for leveraging RWD for future health care research and decision-making.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/43741.

Strategies to Address Current Challenges in Real-World Evidence Generation in Japan

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.

Prevalence of multimorbidity and its associations with hospitalisation or death in Japan 2014-2019: a retrospective cohort study using nationwide medical claims data in the middle-aged generation

OBJECTIVE

To describe the prevalence of multimorbidity and its associations with clinical outcomes across age groups.

DESIGN

Retrospective cohort study using nationwide medical claims data.

SETTING

Carried out in Japan between April 2014 and March 2019.

PARTICIPANTS

N=246 671 Japanese individuals aged 20-74 enrolled in the health insurance were included into the baseline data set for fiscal year (FY) 2014. Of those, N=181 959 individuals were included into the cohort data set spanning FY2014-FY2018.

EXPOSURES

Multimorbidity was defined as having ≥2 of 15 chronic conditions according to the International Classification of Diseases 10th Revision codes of the Charlson Comorbidity Index.

PRIMARY AND SECONDARY OUTCOMES

Primary outcome: the standardised prevalence of multimorbidity across age groups was evaluated using data from FY2014 and extrapolated to the Japanese total population.

SECONDARY OUTCOME

hospitalisation or death events were traced by month using medical claims data and insurer enrolment data. Associations between multimorbidity and 5-year hospitalisation and/or death events across age groups were analysed using a Cox regression model.

RESULTS

The standardised prevalence rate of multimorbidity in the nationwide Japanese total population was estimated to 26.1%. The prevalence rate with age was increased, approximately 5% (ages 20-29), 10% (30-39), 20% (40-49), 30% (50-59), 50% (60-69) and 60% (70-74). Compared with individuals aged 20-39 without multimorbidity, those with multimorbidity had a higher incidence of clinical events in any age group (HR=2.43 (95% CI 2.30 to 2.56) in ages 20-39, HR=2.55 (95% CI 2.47 to 2.63) in ages 40-59 and HR=3.41 (95% CI 3.23 to 3.53) in ages ≥60). The difference in the incidence of clinical events between multimorbidity and no multimorbidity was larger than that between age groups.

CONCLUSIONS

Multimorbidity is already prevalent in the middle-aged generation and is associated with poor clinical outcomes. These findings underscore the significance of multimorbidity and highlight the urgent need for preventive intervention at the public healthcare level.

Current Medical Technology Reimbursement System in Japan

OBJECTIVES

The process for reimbursement of medical technologies in Japan is complex, and to date, it has not been well described overall. This article aims to provide an overview of the reimbursement system for medical technologies in Japan, including the reimbursement application process and the payment decision making.

METHODS

Conduct review for relevant health policy and regulation and gather opinion from the key stakeholders.

RESULTS

The Japanese functional category listing system for the reimbursement of medical technologies is a unique fee-for-service payment system, and the timing for the listing is dependent on the application category. A key positive aspect of the current system is the level of transparency and the predictable pathway for reimbursement of new medical technologies. Conversely, the current reimbursement process may not capture the true extent of the innovation of new technologies, especially when creating a new functional category and/or a new medical procedure coding.

CONCLUSIONS

There are potential areas where changes could improve access, efficiencies, and value, such as the price revision system based on the market survey, the foreign average price assessment, and the health technology assessment system. These additions and modifications in policy and regulation of reimbursement will help facilitate the effective and efficient access to new innovative medical technologies within the context of a sustainable and affordable National Health Insurance system in Japan.

The Current Status of Secondary Use of Claims, Electronic Medical Records, and Electronic Health Records in Epidemiology in Japan: Narrative Literature Review

BACKGROUND

Real-world data, such as claims, electronic medical records (EMRs), and electronic health records (EHRs), are increasingly being used in clinical epidemiology. Understanding the current status of existing approaches can help in designing high-quality epidemiological studies.

OBJECTIVE

We conducted a comprehensive narrative literature review to clarify the secondary use of claims, EMRs, and EHRs in clinical epidemiology in Japan.

METHODS

We searched peer-reviewed publications in PubMed from January 1, 2006, to June 30, 2021 (the date of search), which met the following 3 inclusion criteria: involvement of claims, EMRs, EHRs, or medical receipt data; mention of Japan; and published from January 1, 2006, to June 30, 2021. Eligible articles that met any of the following 6 exclusion criteria were filtered: review articles; non-disease-related articles; articles in which the Japanese population is not the sample; articles without claims, EMRs, or EHRs; full text not available; and articles without statistical analysis. Investigations of the titles, abstracts, and full texts of eligible articles were conducted automatically or manually, from which 7 categories of key information were collected. The information included organization, study design, real-world data type, database, disease, outcome, and statistical method.

RESULTS

A total of 620 eligible articles were identified for this narrative literature review. The results of the 7 categories suggested that most of the studies were conducted by academic institutes (n=429); the cohort study was the primary design that longitudinally measured outcomes of proper patients (n=533); 594 studies used claims data; the use of databases was concentrated in well-known commercial and public databases; infections (n=105), cardiovascular diseases (n=100), neoplasms (n=78), and nutritional and metabolic diseases (n=75) were the most studied diseases; most studies have focused on measuring treatment patterns (n=218), physiological or clinical characteristics (n=184), and mortality (n=137); and multivariate models were commonly used (n=414). Most (375/414, 90.6%) of these multivariate modeling studies were performed for confounder adjustment. Logistic regression was the first choice for assessing many of the outcomes, with the exception of hospitalization or hospital stay and resource use or costs, for both of which linear regression was commonly used.

CONCLUSIONS

This literature review provides a good understanding of the current status and trends in the use of claims, EMRs, and EHRs data in clinical epidemiology in Japan. The results demonstrated appropriate statistical methods regarding different outcomes, Japan-specific trends of disease areas, and the lack of use of artificial intelligence techniques in existing studies. In the future, a more precise comparison of relevant domestic research with worldwide research will be conducted to clarify the Japan-specific status and challenges.

An Attempt to Replicate Randomized Trials of Diabetes Treatments Using a Japanese Administrative Claims and Health Checkup Database: A Feasibility Study

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.

Customer-centric product presentations for monoclonal antibodies

Delivering customer-centric product presentations for biotherapeutics, such as monoclonal antibodies (mAbs), represents a long-standing and paramount area of engagement for pharmaceutical scientists. Activities include improving experience with the dosing procedure, reducing drug administration-related expenditures, and ultimately shifting parenteral treatments outside of a controlled healthcare institutional setting. In times of increasingly cost-constrained markets and reinforced with the coronavirus pandemic, this discipline of "Product Optimization" in healthcare has gained momentum and changed from a nice-to-have into a must. This review summarizes latest trends in the healthcare ecosystem that inform key strategies for developing customer-centric products, including the availability of a wider array of sustainable drug delivery options and treatment management plans that support dosing in a flexible care setting. Three disease area archetypes with varying degree of implementation of customer-centric concepts are introduced to highlight relevant market differences and similarities. Namely, rheumatoid arthritis and inflammatory bowel disease, multiple sclerosis, and oncology have been chosen due to differences in the availability of subcutaneously dosed and ready-to-use self-administration products for mAb medicines and their follow-on biologics. Different launch scenarios are described from a manufacturer's perspective highlighting the necessity of platform approaches. To unfold the full potential of customer-centric care, value-based healthcare provider reimbursement schemes that incentivize the efficiency of care need to be broadly implemented.

An overview of methodological flaws of real-world studies investigating drug safety in the post-marketing setting

INTRODUCTION

The evaluation of the post-marketing safety profile of drugs is a continuous monitoring process for approved and marketed medicines and it is crucial for detecting new adverse drug reactions. As such, real-world studies are essential to complement pre-marketing evidence with information concerning drug risk-benefit profile and use in wider patient populations and they have a great potential to support post-marketing drug safety evaluations.

AREAS COVERED

A detailed description of the main limitations of real-world data sources (i.e. claims databases, electronic healthcare records, drug/disease registers and spontaneous reporting system databases) and of the main methodological challenges of real-world studies in generating real-world evidence is provided.

EXPERT OPINION

Real-world evidence biases can be ascribed to both the methodological approach and the specific limitations of the different real-world data sources used to carry out the study. As such, it is crucial to characterize the quality of real-world data, by establishing guidelines and best practices for the assessment of data fitness for purpose. On the other hand, it is important that real-world studies are conducted using a rigorous methodology, aimed at minimizing the risk of bias.

Promise of Real-World Evidence for Patient Centricity in Gulf Cooperation Council Countries: Call to Action

Presently, Gulf Cooperation Council countries are lagging in the generation of real-world data and use of real-world evidence for patient-centered care compared with the global average. In a collaborative effort, experts from multiple domains of the healthcare environment from the Gulf Cooperation Council countries came together to present their views and recommended key action points for the generation of robust real-world data and leveraging real-world evidence in the countries. The opinions of the experts are presented, along with existing barriers to the effective generation of real-world evidence in the countries. The Gulf Cooperation Council countries are undergoing transformative changes paving the way for improved healthcare measures; however, the challenges in generating reliable, robust, accessible, and secure real-world evidence are persistent. Hence, ongoing public-private engagements, as well as collaborations between regulators, policymakers, healthcare professionals, insurance and pharmaceutical companies, and patients, are warranted. A few notable examples of real-world evidence studies highlighting the benefits of real-world evidence for gaining valuable insights into patient-centric decision making are also discussed. The actionable steps identified for successful real-world evidence generation would provide long-term, real-world evidence-based patient-centric benefits for the countries.

The critical issue linking lipids and inflammation: Clinical utility of stopping oxidative stress

The formation of an atheroma begins when lipoproteins become trapped in the intima. Entrapped lipoproteins become oxidized and activate the innate immune system. This immunity represents the primary association between lipids and inflammation. When the trapping continues, the link between lipids and inflammation becomes chronic and detrimental, resulting in atherosclerosis. When entrapment ceases, the association between lipids and inflammation is temporary and healthy, and the atherogenic process halts. Therefore, the link between lipids and inflammation depends upon lipoprotein retention in the intima. The entrapment is due to electrostatic forces uniting apolipoprotein B to polysaccharide chains on intimal proteoglycans. The genetic transformation of contractile smooth muscle cells in the media into migratory secretory smooth muscle cells produces the intimal proteoglycans. The protein, platelet-derived growth factor produced by activated platelets, is the primary stimulus for this genetic change. Oxidative stress is the main stimulus to activate platelets. Therefore, minimizing oxidative stress would significantly reduce the retention of lipoproteins. Less entrapment decreases the association between lipids and inflammation. More importantly, it would halt atherogenesis. This review will analyze oxidative stress as the critical link between lipids, inflammation, and the pathogenesis of atherosclerosis. Through this perspective, we will discuss stopping oxidative stress to disrupt a harmful association between lipids and inflammation. Numerous therapeutic options will be discussed to mitigate oxidative stress. This paper will add a new meaning to the Morse code distress signal SOS-stopping oxidative stress.

Influence of pharmacists and infection control teams or antimicrobial stewardship teams on the safety and efficacy of vancomycin: A Japanese administrative claims database study

Introduction

Methicillin-resistant Staphylococcus aureus (MRSA) has a high mortality and requires effective treatment with anti-MRSA agents such as vancomycin (VCM). Management of the efficacy and safety of VCM has been implemented with the assignment of pharmacists in hospital wards and the establishment of teams related to infectious diseases. However, there are no reports evaluating the association between these factors and the efficacy and safety of VCM in large populations.

Methods

This study used the Japanese administrative claims database accumulated from 2010 to 2019. The population was divided into two groups, therapeutic drug monitoring (TDM) group and non-TDM group, and adjusted by propensity score matching. We performed multivariate logistic regression analysis to determine the influence of pharmacists and infection control teams or antimicrobial stewardship teams on acute kidney injury (AKI) and 30-day mortality.

Results

The total number of patients was 73 478 (TDM group, n = 55 269; non-TDM group, n = 18 209). After propensity score matching, 18 196 patients were matched in each group. Multivariate logistic regression analysis showed that pharmacological management for each patient contributed to the reduction of AKI (odds ratio [OR]: 0.812, 95% confidence interval [CI]: 0.723‒0.912) and 30-day mortality (OR: 0.538, 95% CI: 0.503‒0.575). However, the establishment of infectious disease associated team in facilities and the assignment of pharmacists in the hospital wards had no effect on AKI and 30-day mortality. In addition, TDM did not affect the reduction in AKI (OR: 1.061, 95% CI: 0.948‒1.187), but reduced 30-day mortality (OR: 0.873, 95% CI: 0.821‒0.929).

Conclusion

Pharmacologic management for individual patients, rather than assignment systems at facilities, is effective to reduce AKI and 30-day mortality with VCM administration.

Real world data and data science in medical research: present and future

Real world data (RWD) are generating greater interest in recent times despite being not new. There are various purposes of the RWD analytics in medical research as follows: effectiveness and safety of medical treatment, epidemiology such as incidence and prevalence of disease, burden of disease, quality of life and activity of daily living, medical costs, etc. The RWD research in medicine is a mixture of digital transformation, statistics or data science, public health, and regulatory science. Most of the articles describing the RWD or real-world evidence (RWE) in medical research cover only a portion of these specializations, which might lead to an incomplete understanding of the RWD. This article summarizes the overview and challenges of the RWD analysis in medical fields from methodological perspectives. As the first step for the RWD analysis, data source of the RWD should be comprehended. The progress of the RWD is closely related to the digitization, especially of medical administrative data and medical records. Second, the selection of appropriate statistical and epidemiological methods is highly critical for an RWD analysis than those for randomized clinical trials. This is because it contains greater varieties of bias, which should be controlled by balancing the underlying risk between treatment groups. Last, the future of the RWD is discussed in terms of overcoming limited data by proxy confounders, using unstructured text data, linking of multiple databases, using the RWD or RWE for a regulatory purpose, and evaluating values and new aspects in medical research brought by the RWD.

Context and Considerations for Use of Two Japanese Real-World Databases in Japan: Medical Data Vision and Japanese Medical Data Center

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.

Status of Medications Prescribed for Psychiatric Disorders in Korean Pediatric and Adolescent Patients

While mental health services for children are increasing, few psychiatric drugs have been approved for such use. We analyzed claim data from 19,557 South Korean pediatric and adolescent patients (<20 years) who were diagnosed with schizophrenia, bipolar disorder, major depressive disorder, anxiety disorder, attention deficit-hyperactivity disorder (ADHD), or a tic disorder. Among these diseases, depressive episodes were the most common, followed by an anxiety disorder, ADHD, bipolar disorder, tic disorder, and schizophrenia. For each disease, prescriptions were categorized as full-label (approved indication with pediatric dosing in the package insert (PI)), partial-label (approved indication without pediatric dosing in the PI), and contraindication (contraindicated for the specific pediatric age in the PI). For schizophrenia, major depressive disorder, and anxiety disorder, more than 50% of the patients were prescribed partial-labeled medications. Additionally, more than 5% of patients with major depressive disorder were prescribed medications that were contraindicated for their age group. Our findings reveal that children with full-labeled psychiatric conditions are commonly administered drugs that are not explicitly approved for either their disease state or age, including off-label and unlicensed drugs. To use pharmaceuticals more safely, expanding drug indications using real-world data are needed.

Building an Artificial Intelligence Laboratory Based on Real World Data: The Experience of Gemelli Generator

The problem of transforming Real World Data into Real World Evidence is becoming increasingly important in the frameworks of Digital Health and Personalized Medicine, especially with the availability of modern algorithms of Artificial Intelligence high computing power, and large storage facilities.Even where Real World Data are well maintained in a hospital data warehouse and are made available for research purposes, many aspects need to be addressed to build an effective architecture enabling researchers to extract knowledge from data.We describe the first year of activity at Gemelli Generator RWD, the challenges we faced and the solutions we put in place to build a Real World Data laboratory at the service of patients and health researchers. Three classes of services are available today: retrospective analysis of existing patient data for descriptive and clustering purposes; automation of knowledge extraction, ranging from text mining, patient selection for trials, to generation of new research hypotheses; and finally the creation of Decision Support Systems, with the integration of data from the hospital data warehouse, apps, and Internet of Things.