Quality of reporting of drug exposure in pharmacoepidemiological studies.

PURPOSE: Exposure definitions vary across pharmacoepidemiological studies. Therefore, transparent reporting of exposure definitions is important for interpretation of published study results. We aimed to assess the quality of reporting of exposure to identify where improvement may be needed. METHOD: We systematically reviewed observational pharmacoepidemiological studies that used routinely collected health data, published in 2017 in six pharmacoepidemiological journals. Reporting of exposure was scored using 11 items of the ISPE-ISPOR guideline on reporting of pharmacoepidemiological studies. RESULTS: Of the 91 studies included, all studies reported the type of exposure (100%), while most reported the exposure risk window (85%) and the exposure assessment window (98%). Operationalization of the exposure window was described infrequently: 16% (14/90) of the studies explicitly reported the presence or absence of an induction period if applicable, 11% (5/47), and 35% (17/49) reported how stockpiling and gaps between exposure episodes were handled, respectively, and 35% (17/49) explicitly mentioned the exposure extension. Switching/add-on was reported in 62% (50/81). How switching between drugs was dealt with and specific drug codes were reported in 52 (57%) and 24 (26%) studies, respectively. CONCLUSION: Publications of pharmacoepidemiological studies frequently reported the type of exposure, the exposure risk window, and the exposure assessment window. However, more details on exposure assessment are needed, especially when it concerns the operationalization of the exposure risk window (eg, the presence or absence of an induction period or exposure extension, handling of stockpiling and gaps, and specific codes), to allow for correct interpretation, reproducibility, and assessment of validity.

Considerations for pharmacoepidemiological analyses in the SARS-CoV-2 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has triggered several hypotheses regarding use of specific medicines and risk of infection as well as prognosis. Under these unique circumstances, rapid answers require quick engagement in data collection and analyses; however, appropriate design and conduct of pharmacoepidemiologic studies are needed to generate valid and reliable evidence. In this paper, endorsed by the International Society for Pharmacoepidemiology, we provide methodological considerations for the conduct of pharmacoepidemiological studies in relation to the pandemic across eight domains: (1) timeliness of evidence, including the need to prioritise some questions over others in the acute phase of the pandemic; (2) the need to align observational and interventional research on efficacy; (3) the specific challenges related to "real-time epidemiology" during an ongoing pandemic; (4) what design to use to answer a specific question; (5) considerations on the definition of exposures; (6) what covariates to collect; (7) considerations on the definition of outcomes; and (8) the need for transparent reporting.

Analyzing Missing Data in Perinatal Pharmacoepidemiology Research: Methodological Considerations to Limit the Risk of Bias.

Pharmacoepidemiological studies on the safety of medication during pregnancy are all susceptible to missing data (ie, data that should have been recorded but for some reason were not). Missing data are ubiquitous, irrespective of the data source used. Bias can arise when incomplete data on confounders, outcome measures, pregnancy duration, or even cohort selection criteria are used to estimate prenatal exposure effects that would be obtained from the fully observed data, if these were available for each mother-child dyad. This commentary describes general missing data mechanisms and methods, and illustrates how missing data were handled in recent medication in pregnancy research, according to the utilized data source. We further present one applied example on missing data analysis within MoBa (the Norwegian Mother, Father and Child Cohort Study), and finally illustrate how the causal diagram framework can be helpful in assessing risk of bias due to missing data in perinatal pharmacoepidemiology research. We recommend that applied researchers limit missing data during data collection, carefully diagnose missingness, apply strategies for missing data mitigation under different assumptions, and finally include evaluations of robustness results under these assumptions. Following this set of recommendations can aid future perinatal pharmacoepidemiology research in avoiding the problems that result from failure to consider this important source of bias.

[Developing process of guide on methodological standards in pharmacoepidemiology (T/CPHARMA 002-2019)].

Pharmacoepidemiology refers to the use of epidemiological research methods in studying the application and use of drugs in large populations to evaluate the safety and efficacy of medical products. Therefore, standardized pharmacoepidemiology research is the basis of the above work. Based on systematic reviews of national and international pharmacoepidemiological methodological standards and guidelines, and in combination with Chinese medical and health practice and experts' opinions, the Professional Committee of Pharmacoepidemiology of Chinese Pharmaceutical Association developed the group standard, guide on methodological standards in pharmacoepidemiology (T/CPHARMA 002-2019), to better guide the work of pharmacoepidemiology. The guideline was designed to provide advice and reference for pharmacoepidemiology research by government, regulatory agencies, research institutions, and pharmaceutical manufacturers in China.

An empirical assessment of immeasurable time bias in the setting of nested case-control studies: Statins and all-cause mortality among patients with heart failure.

PURPOSE: Immeasurable time bias exaggerates drug benefits in pharmacoepidemiologic studies due to exposure misclassification that occurs due to the lack of inpatient drug data in many healthcare databases. METHODS: To estimate the magnitude of immeasurable time bias and assess potential approaches to minimize it, we conducted a nested case-control study of statin use and mortality among heart failure patients using the South Korean nationwide healthcare database, which contains both inpatient and outpatient medication data. Using both inpatient and outpatient medication data to define the gold standard exposure definition, we assessed 10 different analytical methods in which exposure was defined using outpatient medication data only. We compared different methodological approaches to reduce immeasurable time bias: restricting to nonhospitalized patients, adjusting for hospitalization, weighting by either measurable time (nonhospitalized time during 90-d period) or outpatient time, and computing the odds ratios (ORs) using 90-day cumulative probability of exposure produced by the Kaplan-Meier product-limit estimator for cases and controls. RESULTS: The three approaches that most closely approximated the gold standard (hazard ratio [HR] 1.20; 95% confidence interval [CI], 1.05-1.37) were weighting by either measurable (HR 1.09; 95% CI, 0.92-1.28) or outpatient time (HR 1.14; 95% CI, 0.96-1.34) in the unexposed or by estimating the 90-day exposure probability (HR 1.31; 95% CI, 1.11-1.51). CONCLUSION: The use of one of these three methods may be suggested as an approach to minimize immeasurable time bias in nested case-control studies.

The ENCePP Code of Conduct: A best practise for scientific independence and transparency in noninterventional postauthorisation studies.

PURPOSE: The ENCePP Code of Conduct provides a framework for scientifically independent and transparent pharmacoepidemiological research. Despite becoming a landmark reference, practical implementation of key provisions was still limited. The fourth revision defines scientific independence and clarifies uncertainties on the applicability to postauthorisation safety studies requested by regulators. To separate the influence of the funder from the investigator's scientific responsibility, the Code now requires that the lead investigator is not employed by the funding institution. METHOD: To assess how the revised Code fits the ecosystem of noninterventional pharmacoepidemiology research in Europe, we first mapped key recommendations of the revised Code against ISPE Good Pharmacoepidemiology Practices and the ADVANCE Code of Conduct. We surveyed stakeholders to understand perceptions on its value and practical applicability. Representatives from the different stakeholders' groups described their experience and expectations. RESULTS: Unmet needs in pharmacoepidemiological research are fulfilled by providing unique guidance on roles and responsibilities to support scientific independence. The principles of scientific independence and transparency are well understood and reinforce trust in study results; however, around 70% of survey respondents still found some provisions difficult to apply. Representatives from stakeholders' groups found the new version promising, although limitations still exist. CONCLUSION: By clarifying definitions and roles, the latest revision of the Code sets a new standard in the relationship between investigators and funders to support scientific independence of pharmacoepidemiological research. Disseminating and training on the provisions of the Code would help stakeholders to better understand its advantages and promote its adoption in noninterventional research.

The Devil's in the details: Reports on reproducibility in pharmacoepidemiologic studies.

PURPOSE: The U.S. Food and Drug Administration's Sentinel Initiative "modular programs" have been shown to replicate findings from conventional protocol-driven, custom-programmed studies. One such parallel assessment-dabigatran and warfarin and selected outcomes-produced concordant findings for three of four study outcomes. The effect estimates and confidence intervals for the fourth-acute myocardial infarction-had more variability as compared with other outcomes. This paper evaluates the potential sources of that variability that led to unexpected divergence in findings. METHODS: We systematically compared the two studies and evaluated programming differences and their potential impact using a different dataset that allowed more granular data access for investigation. We reviewed the output at each of five main processing steps common in both study programs: cohort identification, propensity score estimation, propensity score matching, patient follow-up, and risk estimation. RESULTS: Our findings point to several design features that warrant greater investigator attention when performing observational database studies: (a) treatment of recorded events (eg, diagnoses, procedures, and dispensings) co-occurring on the index date of study drug dispensing in cohort eligibility criteria and propensity score estimation and (b) construction of treatment episodes for study drugs of interest that have more complex dispensing patterns. CONCLUSIONS: More precise and unambiguous operational definitions of all study parameters will increase transparency and reproducibility in observational database studies.

Validation of the Swedish Multiple Sclerosis Register: Further Improving a Resource for Pharmacoepidemiologic Evaluations.

The Swedish Multiple Sclerosis Register is a national register monitoring treatment and clinical course for all Swedish multiple sclerosis (MS) patients, with high coverage and close integration with the clinic. Despite its great value for epidemiologic research, it has not previously been validated. In this brief report, we summarize a large validation of >3,000 patients in the register using clinical chart review in the context of the COMBAT-MS study. While further improving the data quality for a central cohort of patients available for future epidemiologic research, this study also allowed us to estimate the accuracy and completeness of the register data.

Methodologic limitations of prescription opioid safety research and recommendations for improving the evidence base.

PURPOSE: The ongoing opioid epidemic has claimed more than a quarter million Americans' lives over the past 15 years. The epidemic began with an escalation of prescription opioid deaths and has now evolved to include secondary waves of illicit heroin and fentanyl deaths, while the deaths due to prescription opioid overdoses are still increasing. In response, the Centers for Disease Control and Prevention (CDC) moved to limit opioid prescribing with the release of opioid prescribing guidelines for chronic noncancer pain in March 2016. The guidelines represent a logical and timely federal response to this growing crisis. However, CDC acknowledged that the evidence base linking opioid prescribing to opioid use disorders and overdose was grades 3 and 4. METHODS: Motivated by the need to strengthen the evidence base, this review details limitations of the opioid safety studies cited in the CDC guidelines with a focus on methodological limitations related to internal and external validity. RESULTS: Internal validity concerns were related to poor confounding control, variable misclassification, selection bias, competing risks, and potential competing interventions. External validity concerns arose from the use of limited source populations, historical data (in a fast-changing epidemic), and issues with handling of cancer and acute pain patients' data. We provide a nonexhaustive list of 7 recommendations to address these limitations in future opioid safety studies. CONCLUSION: Strengthening the opioid safety evidence base will aid any future revisions of the CDC guidelines and enhance their prevention impact.

Exploring the Potential Routine Use of Electronic Healthcare Record Data to Strengthen Early Signal Assessment in UK Medicines Regulation: Proof-of-Concept Study.

INTRODUCTION: Electronic healthcare record (EHR) databases are used within pharmacoepidemiology studies to confirm or refute safety signals arising from spontaneous adverse event reports. However, there has been limited routine use of such data earlier in the signal management process, to help rapidly contextualise signals and strengthen preliminary assessment or to inform decisions regarding action including the need for further studies. This study explores the value of EHR used in this way within a regulatory environment via an automated analysis platform. METHODS: Safety signals raised at the UK Medicines and Healthcare products Regulatory Agency (MHRA) between July 2014 and June 2015 were individually reviewed by a multi-disciplinary team. They assessed the feasibility of identifying the exposure and event of interest using primary care data from the Clinical Practice Research Datalink (CPRD) within the Commonwealth Vigilance Workbench (CVW) Longitudinal Module platform, which was designed to facilitate routine descriptive analysis of signals using EHR. Three signals, where exposure and event could be well identified, were retrospectively analysed using the platform. RESULTS: Of 69 unique new signals, 20 were for drugs prescribed predominately in secondary care or available without prescription, which would not be identified in primary care. A further 17 were brand, formulation, or dose-specific issues, were related to mortality, were relevant only to a subgroup of patients, or were drug interactions, and hence could not be reviewed using the platform given its limitations. Analyses of exposure and incidence of the adverse event could be produced using CPRD within the CMV Longitudinal Module for 32 (46%) signals. The case studies demonstrated that the data provided supporting evidence for confirming initial assessment of the signal and deciding upon the need for further action. CONCLUSIONS: CPRD can routinely provide useful early insights into clinical context when assessing a large proportion of safety signals within a regulatory environment provided that a flexible approach is adopted within the analysis platform.

Prescripción potencialmente inadecuada en mayores de 65 años según los criterios de Beers originales y su versión adaptada / Identifying potentially inappropriate prescriptions in patients over 65 years-old using original Beers criteria and their Spanish adaptation

Objetivo: Comparar la detección de prescripción potencialmente inadecuada (PPI) con el uso de los criterios de Beers, referente global en la evaluación de la farmacoterapia del paciente aciano, en su versión original y en su adaptación española. Diseño: Estudio observacional retrospectivo. Emplazamiento: Un área de salud en la Región de Murcia. Participantes: Ciudadanos mayores de 65 años que hayan recogido, al menos, una receta médica durante el periodo de estudio (n = 7.856). Método: Análisis de la información de la historia clínica informatizada de atención primaria (enfermedades y prescripciones) durante el periodo de estudio (12 meses, año 2012). Se utilizaron los criterios de Beers en su versión original de 2012 y su adaptación española para evaluar la PPI. Se estudió la proporción de pacientes con PPI a nivel global y por cada criterio concreto, y la diferencia entre ambas versiones. Resultados: La mediana de edad de la población estudiada fue de 76años, con predominio del sexo femenino (56,6%). Respecto al uso de medicamentos, la muestra presentó una mediana de 13 principios activos y 66 recetas. Respecto a la población estudiada, el porcentaje de pacientes con PPI según la versión original de los criterios de Beers es del 44,8%, ascendiendo al 49,4% cuando se utiliza la adaptación. Conclusiones: La PPI es frecuente en nuestro entorno. La aplicación directa de los criterios de Beers en su versión original, sin tener en cuenta la idiosincrasia del mercado farmacéutico local, proporciona una infraestimación del volumen de PPI en el paciente mayor de 65 años (AU)

Objective: To compare the detection of potentially inappropriate medication (PIM) using the original Beers criteria, a global reference for evaluating prescriptions in the elderly, and their Spanish version. Design: Retrospective observational study Location: A Primary Care area in the province of Murcia, Spain. Participants: A total of 7,856 subjects aged 65 and over, with at least one drug prescribed in a Primary Care Area of Spain during study period. Method: Illnesses and treatments registered in the Primary Care computerised medical history of patients were analysed during a 12 month study period (2012). The original Beers criteria and their Spanish adaptation were used to evaluate PIM, considering both sets of criteria overall, and individually. Results: The median age of the patients was 76.0 years, with the majority females (56.6%). Patients received a median of 13 active substances and 66 medical prescriptions. The percentage of patients prescribed PIM ranged from 44.8% according to the original Beers criteria to 49.4% with the Spanish adaptation. Conclusions: PIMs are frequent in our context. The original Beers criteria, if not adapted to the local drug catalogue, underestimated the frequency of PIM in the elderly population studied (AU)

Evaluation of Electronic Healthcare Databases for Post-Marketing Drug Safety Surveillance and Pharmacoepidemiology in China.

INTRODUCTION: Electronic healthcare databases (EHDs) are used increasingly for post-marketing drug safety surveillance and pharmacoepidemiology in Europe and North America. However, few studies have examined the potential of these data sources in China. METHODS: Three major types of EHDs in China (i.e., a regional community-based database, a national claims database, and an electronic medical records [EMR] database) were selected for evaluation. Forty core variables were derived based on the US Mini-Sentinel (MS) Common Data Model (CDM) as well as the data features in China that would be desirable to support drug safety surveillance. An email survey of these core variables and eight general questions as well as follow-up inquiries on additional variables was conducted. These 40 core variables across the three EHDs and all variables in each EHD along with those in the US MS CDM and Observational Medical Outcomes Partnership (OMOP) CDM were compared for availability and labeled based on specific standards. RESULTS: All of the EHDs' custodians confirmed their willingness to share their databases with academic institutions after appropriate approval was obtained. The regional community-based database contained 1.19 million people in 2015 with 85% of core variables. Resampled annually nationwide, the national claims database included 5.4 million people in 2014 with 55% of core variables, and the EMR database included 3 million inpatients from 60 hospitals in 2015 with 80% of core variables. Compared with MS CDM or OMOP CDM, the proportion of variables across the three EHDs available or able to be transformed/derived from the original sources are 24-83% or 45-73%, respectively. CONCLUSIONS: These EHDs provide potential value to post-marketing drug safety surveillance and pharmacoepidemiology in China. Future research is warranted to assess the quality and completeness of these EHDs or additional data sources in China.

Methods for time-varying exposure related problems in pharmacoepidemiology: An overview.

PURPOSE: Lack of control for time-varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance on some of the available methodologies used to address problems related to time-varying exposure and confounding in pharmacoepidemiology and other observational studies. The methods are explored from a conceptual rather than an analytical perspective. METHODS: The methods described in this study have been identified exploring the literature concerning to the time-varying exposure concept and basing the search on four fundamental pharmacoepidemiological problems, construction of treatment episodes, time-varying confounders, cumulative exposure and latency, and treatment switching. RESULTS: A correct treatment episodes construction is fundamental to avoid bias in treatment effect estimates. Several methods exist to address time-varying covariates, but the complexity of the most advanced approaches-eg, marginal structural models or structural nested failure time models-and the lack of user-friendly statistical packages have prevented broader adoption of these methods. Consequently, simpler methods are most commonly used, including, for example, methods without any adjustment strategy and models with time-varying covariates. The magnitude of exposure needs to be considered and properly modelled. CONCLUSIONS: Further research on the application and implementation of the most complex methods is needed. Because different methods can lead to substantial differences in the treatment effect estimates, the application of several methods and comparison of the results is recommended. Treatment episodes estimation and exposure quantification are key parts in the estimation of treatment effects or associations of interest.

Good practices for real-world data studies of treatment and/or comparative effectiveness: Recommendations from the joint ISPOR-ISPE Special Task Force on real-world evidence in health care decision making.

PURPOSE: Real-world evidence (RWE) includes data from retrospective or prospective observational studies and observational registries and provides insights beyond those addressed by randomized controlled trials. RWE studies aim to improve health care decision making. METHODS: The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) created a task force to make recommendations regarding good procedural practices that would enhance decision makers' confidence in evidence derived from RWD studies. Peer review by ISPOR/ISPE members and task force participants provided a consensus-building iterative process for the topics and framing of recommendations. RESULTS: The ISPOR/ISPE Task Force recommendations cover seven topics such as study registration, replicability, and stakeholder involvement in RWE studies. These recommendations, in concert with earlier recommendations about study methodology, provide a trustworthy foundation for the expanded use of RWE in health care decision making. CONCLUSION: The focus of these recommendations is good procedural practices for studies that test a specific hypothesis in a specific population. We recognize that some of the recommendations in this report may not be widely adopted without appropriate incentives from decision makers, journal editors, and other key stakeholders.

Conducting Privacy-Preserving Multivariable Propensity Score Analysis When Patient Covariate Information Is Stored in Separate Locations.

Distributed networks of health-care data sources are increasingly being utilized to conduct pharmacoepidemiologic database studies. Such networks may contain data that are not physically pooled but instead are distributed horizontally (separate patients within each data source) or vertically (separate measures within each data source) in order to preserve patient privacy. While multivariable methods for the analysis of horizontally distributed data are frequently employed, few practical approaches have been put forth to deal with vertically distributed health-care databases. In this paper, we propose 2 propensity score-based approaches to vertically distributed data analysis and test their performance using 5 example studies. We found that these approaches produced point estimates close to what could be achieved without partitioning. We further found a performance benefit (i.e., lower mean squared error) for sequentially passing a propensity score through each data domain (called the "sequential approach") as compared with fitting separate domain-specific propensity scores (called the "parallel approach"). These results were validated in a small simulation study. This proof-of-concept study suggests a new multivariable analysis approach to vertically distributed health-care databases that is practical, preserves patient privacy, and warrants further investigation for use in clinical research applications that rely on health-care databases.