Evolving Acceptance and Use of RWE for Regulatory Decision Making on the Benefit/Risk Assessment of a Drug in Japan

Advancing the role of real-world evidence in comparative effectiveness research

Aim: Comparative effectiveness research (CER) is essential for making informed decisions about drug access. It provides insights into the effectiveness and safety of new drugs compared with existing treatments, thereby guiding better healthcare decisions and ensuring that new therapies meet the real-world needs of patients and healthcare systems. Objective: To provide a tool that assists analysts and decision-makers in identifying the most suitable analytical approach for answering a CER question, given specific data availability contexts. Methods: A systematic literature review of the scientific literature was performed and existing regulatory and health technology assessment (HTA) guidance were evaluated to identify and compare recommendations and best practices. Based on this review a methods flowchart that synthesizes current practices and requirements was proposed. Results: The review did not find any papers that clearly identified the most appropriate analytical approach for answering CER questions under various conditions. Therefore, a methods flowchart was designed to inform analyst and decision makers choices starting from a well-defined scientific question. Conclusion: The proposed methods flowchart offers clear guidance on CER methodologies across a range of settings and research needs. It begins with a well-defined research question and considers multiple feasibility aspects related to CER. This tool aims to standardize methods, ensure rigorous and consistent research quality and promote a culture of evidence-based decision-making in healthcare.

FOUNTAIN: a modular research platform for integrated real-world evidence generation

BACKGROUND

Real-world evidence (RWE) plays a key role in regulatory and healthcare decision-making, but the potentially fragmentated nature of generated evidence may limit its utility for clinical decision-making. Heterogeneity and a lack of reproducibility in RWE resulting from inconsistent application of methodologies across data sources should be minimized through harmonization.

METHODS

This paper's aim is to describe and reflect upon a multidisciplinary research platform (FOUNTAIN; FinerenOne mUlti-database NeTwork for evidence generAtIoN) with coordinated studies using diverse RWE generation approaches and explore the platform's strengths and limitations. With guidance from an executive advisory committee of multidisciplinary experts and patient representatives, the goal of the FOUNTAIN platform is to harmonize RWE generation across a portfolio of research projects, including research partner collaborations and a common data model (CDM)-based program. FOUNTAIN's overarching objectives as a research platform are to establish long-term collaborations among pharmacoepidemiology research partners and experts and to integrate diverse approaches for RWE generation, including global protocol execution by research partners in local data sources and common protocol execution in multiple data sources through federated data networks, while ensuring harmonization of medical definitions, methodology, and reproducible artifacts across all studies. Specifically, the aim of the multiple studies run within the frame of FOUNTAIN is to provide insight into the real-world utilization, effectiveness, and safety of finerenone across its life-cycle.

RESULTS

Currently, the FOUNTAIN platform includes 9 research partner collaborations and 8 CDM-mapped data sources from 7 countries (United States, United Kingdom, China, Japan, The Netherlands, Spain, and Denmark). These databases and research partners were selected after a feasibility fit-for-purpose evaluation. Six multicountry, multidatabase, cohort studies are ongoing to describe patient populations, current standard of care, comorbidity profiles, healthcare resource use, and treatment effectiveness and safety in different patient populations with chronic kidney disease and type 2 diabetes. Strengths and potential limitations of FOUNTAIN are described in the context of valid RWE generation.

CONCLUSION

The establishment of the FOUNTAIN platform has allowed harmonized execution of multiple studies, promoting consistency both within individual studies that employ multiple data sources and across all studies run within the platform's framework. FOUNTAIN presents a proposal to efficiently improve the consistency and generalizability of RWE on finerenone.

The maze of real-world evidence frameworks: from a desert to a jungle! An environmental scan and comparison across regulatory and health technology assessment agencies

Aim: Regulatory and health technology assessment (HTA) agencies have increasingly published frameworks, guidelines, and recommendations for the use of real-world evidence (RWE) in healthcare decision-making. Variations in the scope and content of these documents, with updates running in parallel, may create challenges for their implementation especially during the market authorization and reimbursement phases of a medicine's life cycle. This environmental scan aimed to comprehensively identify and summarize the guidance documents for RWE developed by most well-established regulatory and reimbursement agencies, as well as other organizations focused on healthcare decision-making, and present their similarities and differences. Methods: RWE guidance documents, including white papers from regulatory and HTA agencies, were reviewed in March 2024. Data on scope and recommendations from each body were extracted by two reviewers and similarities and differences were summarized across four topics: study planning, choosing fit-for-purpose data, study conduct, and reporting. Post-authorization or non-pharmacological guidance was excluded. Results: Forty-six documents were identified across multiple agencies; US FDA produced the most RWE-related guidance. All agencies addressed specific and often similar methodological issues related to study design, data fitness-for-purpose, reliability, and reproducibility, although inconsistency in terminologies on these topics was noted. Two HTA bodies (National Institute for Health and Care Excellence [NICE] and Canada's Drug Agency) each centralized all related RWE guidance under a unified framework. RWE quality tools and checklists were not consistently named and some differences in preferences were noted. European Medicines Agency, NICE, Haute Autorité de Santé, and the Institute for Quality and Efficiency in Health Care included specific recommendations on the use of analytical approaches to address RWE complexities and increase trust in its findings. Conclusion: Similarities in agencies' expectations on RWE studies design, quality elements, and reporting will facilitate evidence generation strategy and activities for manufacturers facing multiple, including global, regulatory and reimbursement submissions and re-submissions. A strong preference by decision-making bodies for local real-world data generation may hinder opportunities for data sharing and outputs from international federated data networks. Closer collaboration between decision-making agencies towards a harmonized RWE roadmap, which can be centrally preserved in a living mode, will provide manufacturers and researchers clarity on minimum acceptance requirements and expectations, especially as novel methodologies for RWE generation are rapidly emerging.

Pharmacovigilance in Vaccines: Importance, Main Aspects, Perspectives, and Challenges-A Narrative Review

Pharmacovigilance plays a central role in safeguarding public health by continuously monitoring the safety of vaccines, being critical in a climate of vaccine hesitancy, where public trust is paramount. Pharmacovigilance strategies employed to gather information on adverse events following immunization (AEFIs) include pre-registration data, media reports, clinical trials, and societal reporting. Early detection of AEFIs during clinical trials is crucial for thorough safety analysis and preventing serious reactions once vaccines are deployed. This review highlights the importance of societal reporting, encompassing contributions from community members, healthcare workers, and pharmaceutical companies. Technological advancements such as quick response (QR) codes can facilitate prompt AEFI reporting. While vaccines are demonstrably safe, the possibility of adverse events necessitates continuous post-marketing surveillance. However, underreporting remains a challenge, underscoring the critical role of public engagement in pharmacovigilance. This narrative review comprehensively examines and synthesizes key aspects of virus vaccine pharmacovigilance, with special considerations for specific population groups. We explore applicable legislation, the spectrum of AEFIs associated with major vaccines, and the unique challenges and perspectives surrounding pharmacovigilance in this domain.

Use of quantitative bias analysis to evaluate single-arm trials with real-world data external controls

PURPOSE

Use of real-world data (RWD) for external controls added to single-arm trials (SAT) is increasingly prevalent in regulatory submissions. Due to inherent differences in the data-generating mechanisms, biases can arise. This paper aims to illustrate how to use quantitative bias analysis (QBA).

METHODS

Advanced non-small cell lung cancer (NSCLC) serves as an example, where many small subsets of patients with molecular tumor subtypes exist. First, some sources of bias that may occur in oncology when comparing RWD to SAT are described. Second, using a hypothetical immunotherapy agent, a dataset is simulated based on expert input for survival analysis of advanced NSCLC. Finally, we illustrate the impact of three biases: missing confounder, misclassification of exposure, and outcome evaluation.

RESULTS

For each simulated scenario, bias was induced by removing or adding data; hazard ratios (HRs) were estimated applying conventional analyses. Estimating the bias-adjusted treatment effect and uncertainty required carefully selecting the bias model and bias factors. Although the magnitude of each biased and bias-adjusted HR appeared moderate in all three hypothetical scenarios, the direction of bias was variable.

CONCLUSION

These findings suggest that QBA can provide an intuitive framework for bias analysis, providing a key means of challenging assumptions about the evidence. However, the accuracy of bias analysis is itself dependent on correct specification of the bias model and bias factors. Ultimately, study design should reduce bias, but QBA allows us to evaluate the impact of unavoidable bias to assess the quality of the evidence.

Maximizing the Value of Real-World Data and Real-World Evidence to Accelerate Healthcare Transformation in China: Summary of External Advisory Committee Meetings

Use of real-world data (RWD) is gaining wide attention. To bridge the gap between diverse healthcare stakeholders and to leverage the impact of Chinese real-world evidence (RWE) globally, a multi-stakeholder External Advisory Committee (EAC) and EAC meetings were initiated, aiming to elucidate the current and evolving RWD landscape in China, articulate the values of RWE in ensuring Chinese patients' equitable access to affordable medicines and solutions, and identify strategic opportunities and partnerships for expansion of RWE generation in China. Chinese and international experts who are clinicians and academic researchers were selected as EAC members based on their professional background and familiarity with RWD/RWE. Three EAC meetings were held quarterly in 2023. Various topics were presented and discussed for insights and suggestions. Nine experts from China, one from South Korea, and two from Europe were selected as EAC members and attended these meetings. Experts' presentations were summarized by theme, including the RWD landscape and RWE enablement in China, as well as global development of a patient-centric ecosystem. Experts' insights and suggestions on maximizing the RWD/RWE value to accelerate healthcare transformation in China were collected. We concluded that though data access, sharing, and quality are still challenging, RWD is developing to support evidence generation in the medicinal product lifecycle, inform clinical practice, and empower patient management in China. RWD/RWE creates value, accelerates healthcare transformation, and improves patient outcomes. Fostering a patient-centric ecosystem across healthcare stakeholders and maintaining global partnerships and collaboration are essential for unlocking the power of RWD/RWE.

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.

Building trust in real world evidence (RWE): moving transparency in RWE towards the randomized controlled trial standard

The increasing use of RWE in regulatory and reimbursement decision-making indicates the significant progress that has been made in building trust in RWE through greater transparency. This review of the published literature and key online sources was conducted to provide an update on progress towards greater transparency in RWE, based on four key barriers to trust identified in a 2016 paper and applying learnings from transparency initiatives established for RCTs, such as the US FDA Amendments Act (FDAAA) 2007 Final Rule. Multiple initiatives from the US FDA, EMA and organizations such as the ISPOR-ISPE Joint Task Force have yielded new guidance documents and tools that enable greater transparency in RWE study methodology (STaRT-RWE and HARPER templates), data source selection and quality (SPIFD2 framework, REQueST tool), strategy (the Center for Open Science RWE Study Registry), and will therefore improve transparency in RWE study reporting. Programs such as the REPEAT Initiative and RWE DUPLICATE are investigating reproducibility of RWE studies and improving understanding of the circumstances when valid inference on treatment effects can be obtained from RWE studies. Further work is needed to embed and to implement the new tools and guidance that are available, and thus raise standards for RWE transparency towards the levels expected for RCTs.

Clinical Pharmacology Applications of Real-World Data and Real-World Evidence in Drug Development and Approval-An Industry Perspective

Since the 21st Century Cures Act was signed into law in 2016, real-world data (RWD) and real-world evidence (RWE) have attracted great interest from the healthcare ecosystem globally. The potential and capability of RWD/RWE to inform regulatory decisions and clinical drug development have been extensively reviewed and discussed in the literature. However, a comprehensive review of current applications of RWD/RWE in clinical pharmacology, particularly from an industry perspective, is needed to inspire new insights and identify potential future opportunities for clinical pharmacologists to utilize RWD/RWE to address key drug development questions. In this paper, we review the RWD/RWE applications relevant to clinical pharmacology based on recent publications from member companies in the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) RWD Working Group, and discuss the future direction of RWE utilization from a clinical pharmacology perspective. A comprehensive review of RWD/RWE use cases is provided and discussed in the following categories of application: drug-drug interaction assessments, dose recommendation for patients with organ impairment, pediatric plan development and study design, model-informed drug development (e.g., disease progression modeling), prognostic and predictive biomarkers/factors identification, regulatory decisions support (e.g., label expansion), and synthetic/external control generation for rare diseases. Additionally, we describe and discuss common sources of RWD to help guide appropriate data selection to address questions pertaining to clinical pharmacology in drug development and regulatory decision making.

Cross-national comparative study of orphan drug policies in Saudi Arabia, the United States, and the European Union

Background

Rare diseases are chronic, serious, and life-threatening conditions that have not received sufficient attention from drug developers due to their rarity. Policies have been implemented to encourage research and incentivize the development of orphan drugs. However, the implementation of these policies has been inconsistent worldwide.

Objective

The primary aim of this study was to compare orphan drug policies in the United States, Europe, and Saudi Arabia (SA) and assess their impact on the number of approved indications.

Method

Lists of all drugs granted orphan designations and authorized for marketing in the United States, European Union, and SA were extracted using orphan drug lists available in regulatory body databases. The availability of these drugs, regarding their approval for orphan indication and designation, was assessed and classified using Anatomical Therapeutic Chemical codes.

Result

A total of 792 orphan drug designations with at least one authorized indication were identified in this study. Of these, 92% were designated by the Food and Drug Administration (FDA), and 27% were designated by the European Medicine Agency (EMA). The FDA, EMA, and Saudi Food and Drug Authority approved 753, 435, and 253 orphan drugs, respectively.

Conclusion

Fewer orphan drug approvals were found in SA than in the United States and Europe. This highlights the need to focus on rare diseases and orphan drugs and for policies to be created in SA to attract pharmaceutical markets and fulfill unmet orphan drug approval needs.

Statistical Considerations on the Use of RWD/RWE for Oncology Drug Approvals: Overview and Lessons Learned

Despite increasing utilization of real-world data (RWD)/real-world evidence (RWE) in regulatory submissions, their application to oncology drug approvals has seen limited success. Real-world data is most commonly summarized as a benchmark control for a single arm study or used to augment the concurrent control in a randomized clinical trial (RCT). While there has been substantial research on usage of RWD/RWE, our goal is to provide a comprehensive overview of their use in oncology drug approval submissions to inform future RWD/RWE study design. We will review examples of applications and summarize the strengths and weaknesses of each example identified by regulatory agencies. A few noteworthy case studies will be reviewed in detail. Operational aspects of RWD/RWE study design/analysis will be also discussed.

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.

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.

Descriptive Analysis for the Trend of Pharmacovigilance Planning in Risk Management Plans on New Drugs Approved During 2016-2019

BACKGROUND

Japanese pharmaceutical authorities have conducted regulatory renovations of pharmacovigilance planning (PVP) since implementing new procedures for developing post-marketing study plans in 2018 in order to promote more focused and scientific approaches. This study aimed to descriptively assess the effects of those regulatory renovations on PVP for new drugs in Japan.

METHODS

We identified PVP information (drug characteristics, efficacy and safety issues, and additional activities) from the first version of risk management plans for new drugs approved between 2016 and 2019. The following indicators were analyzed: (1) proportion of the number of drugs with at least one efficacy issue among all the drugs, (2) proportion of the number of safety issues with additional activity among all the safety issues, and (3) proportion of database studies among all additional activities.

RESULTS

In total, 168 drugs, 1212 safety issues, and 301 additional activities were identified. The proportion of drugs with at least one efficacy issue decreased from 91.4% in 2016 to 27.3% in 2019, and the proportion of safety issues with additional activity also decreased from 93.9% in 2016 to 53.7% in 2019. In contrast, the proportion of database studies increased from 0 to 19.2%. The percentages of additional activities targeting important identified and potential risks also gradually decreased during the 4-year period.

CONCLUSION

Notable changes in the three indicators during 2016-2019 were observed, which suggests that regulatory renovation has affected PVP in Japan.

Use of National Database of Health Insurance Claims and Specific Health Checkups for examining practical utilization and safety signal of a drug to support regulatory assessment on postmarketing drug safety in Japan

The Pharmaceuticals and Medical Devices Agency (PMDA) has conducted many pharmacoepidemiological studies for postmarketing drug safety assessments based on real-world data from medical information databases. One of these databases is the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), containing health insurance claims of almost all Japanese individuals (over 100 million) since April 2009. This article describes the PMDA's regulatory experiences in utilizing the NDB for postmarketing drug safety assessment, especially focusing on the recent cases of use of the NDB to examine the practical utilization and safety signal of a drug. The studies helped support regulatory decision-making for postmarketing drug safety, such as considering a revision of prescribing information of a drug, confirming the appropriateness of safety measures, and checking safety signals in real-world situations. Different characteristics between the NDB and the MID-NET^® (another database in Japan) were also discussed for appropriate selection of data source for drug safety assessment. Accumulated experiences of pharmacoepidemiological studies based on real-world data for postmarketing drug safety assessment will contribute to evolving regulatory decision-making based on real-world data in Japan.

Real-world evidence of biological agents in dermatology: A review of its applications, advantages, and limitations

Randomized controlled trials (RCTs) are regarded as the gold standard of evidence-based medicine. However, the disadvantages of RCTs have been well-documented for a lengthy period of time. Due to the carefully controlled conditions, a small group of patients is studied, resulting in a lack of external validity and generalizability. To address this issue, real-world evidence (RWE) has grown in importance as a complement to randomized controlled trials (RCTs). We introduce and describe the databases used by RWE in this post. Applications of RWE are described in following aspects with examples of patients in the use of biological agents with skin diseases: (1) support the safety and efficacy outcomes of RCTs; (2) reveal real-world situations of adverse event management; (3) optimal treatment plans; (4) treatment's real-world cost burden. We also focus on its superiority of generalizability, external validity, and time and economic efficiencies as well as its deficiencies in data resources, study design, and statistical methodologies.

Impact of "time zero" of Follow-Up Settings in a Comparative Effectiveness Study Using Real-World Data with a Non-user Comparator: Comparison of Six Different Settings

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.

Meta-analysis of individualized treatment rules via sign-coherency

Medical treatments tailored to a patient's baseline characteristics hold the potential of improving patient outcomes while reducing negative side effects. Learning individualized treatment rules (ITRs) often requires aggregation of multiple datasets(sites); however, current ITR methodology does not take between-site heterogeneity into account, which can hurt model generalizability when deploying back to each site. To address this problem, we develop a method for individual-level meta-analysis of ITRs, which jointly learns site-specific ITRs while borrowing information about feature sign-coherency via a scientifically-motivated directionality principle. We also develop an adaptive procedure for model tuning, using information criteria tailored to the ITR learning problem. We study the proposed methods through numerical experiments to understand their performance under different levels of between-site heterogeneity and apply the methodology to estimate ITRs in a large multi-center database of electronic health records. This work extends several popular methodologies for estimating ITRs (A-learning, weighted learning) to the multiple-sites setting.

The challenges and opportunities in using real-world data to drive advances in healthcare in East Asia: expert panel recommendations

OBJECTIVE

To provide recommendations for overcoming the challenges associated with the generation and use of real-world evidence (RWE) in regulatory approvals, health technology assessments (HTAs), and reimbursement decision-making in East Asia.

METHODS

A panel of experts convened at the International Society for Pharmacoeconomics and Outcomes Research Asia Pacific 2020 congress to discuss the challenges limiting the use of RWE in healthcare decision-making and to provide insights into the perspectives of regulators, HTA agencies, the pharmaceutical industry, and physicians in China, Japan, and Taiwan. A nonsystematic literature review was conducted to expand on the themes addressed.

RESULTS

The use of RWE in regulatory approvals, HTAs, and reimbursement decision-making remains limited by legal/regulatory, technical, and attitudinal challenges in East Asia.

CONCLUSIONS

We recommend approaches and initiatives that aim to drive improvements in the utilization of RWE in healthcare decision-making in East Asia and other regions. We encourage large-scale collaborations that leverage the full range of skills offered by different stakeholders. Government agencies, hospitals, research organizations, patient groups, and the pharmaceutical industry must collaborate to ensure appropriate access to robust and reliable real-world data and seek alignment on how to address prioritized evidence needs. Increasingly, we believe that this work will be conducted by multidisciplinary teams with expertise in healthcare research and delivery, data science, and information technology. We hope this work will encourage further discussion among all stakeholders seeking to shape the RWE landscape in East Asia and other regions and drive next-generation healthcare.

Pragmatic Clinical Studies: An Emerging Clinical Research Discipline for Improving Evidence-Based Practice of Cardiovascular Diseases in Asia

Pragmatic clinical studies, an emerging clinical research discipline, include a wide range of studies that are largely embedded with routine clinical practice and aim to evaluate the comparative effectiveness and safety of different clinical intervention strategies. Increased availability and quality of electronic medical/health records drives the development of pragmatic clinical studies. In this review, we describe evolution of the conceptual framework of pragmatic clinical studies and share perspectives on the importance of pragmatic clinical studies in evidence-based practice for cardiovascular diseases, as a complement to conventional randomized controlled trials. We also highlight specific needs of pragmatic clinical studies in improving evidence-based practice for cardiovascular disease in Asian countries. The main challenges of pragmatic clinical studies are discussed briefly in this review.

A State-of-the-Art Roadmap for Biomarker-Driven Drug Development in the Era of Personalized Therapies

Advances in biotechnology have enabled us to assay human tissue and cells to a depth and resolution that was never possible before, redefining what we know as the “biomarker”, and how we define a “disease”. This comes along with the shift of focus from a “one-drug-fits-all” to a “personalized approach”, placing the drug development industry in a highly dynamic landscape, having to navigate such disruptive trends. In response to this, innovative clinical trial designs have been key in realizing biomarker-driven drug development. Regulatory approvals of cancer genome sequencing panels and associated targeted therapies has brought personalized medicines to the clinic. Increasing availability of sophisticated biotechnologies such as next-generation sequencing (NGS) has also led to a massive outflux of real-world genomic data. This review summarizes the current state of biomarker-driven drug development and highlights examples showing the utility and importance of the application of real-world data in the process. We also propose that all stakeholders in drug development should (1) be conscious of and efficiently utilize real-world evidence and (2) re-vamp the way the industry approaches drug development in this era of personalized medicines.

Multi-Criteria Decision Analysis for Benefit-Risk Analysis by National Regulatory Authorities

The approval process for pharmaceuticals has always included a consideration of the trade-offs between benefits and risks. Until recently, these trade-offs have been made in panel discussions without using a decision model to explicitly consider what these trade-offs might be. Recently, the EMA and the FDA have embraced Multi-Criteria Decision Analysis (MCDA) as a methodology for making approval decisions. MCDA offers an approach for improving the quality of these decisions and, in particular, by using quantitative and qualitative data in a structured decision model to make trade-offs in a logical, transparent and auditable way. This paper will review the recent use of MCDA by the FDA and EMA and recommend its wider adoption by other National Regulatory Authorities (NRAs) and the pharmaceutical industry.

The "Coming of Age" of Real-World Evidence in Drug Development and Regulation

Real world evidence (RWE) has the potential to inform drug discovery, development, and regulatory decision making. The emergence and availability of large population-based datasets around the globe have stoked enthusiasm in the research community. However, much work remains to refine research methodologies, evolve the science, and define the place of RWE as a complementary source of evidence to randomized controlled trials.