ENCePP Guide on Methodological Standards in Pharmacoepidemiology
The Guide on Methodological Standards in Pharmacoepidemiology offers a single online resource for methodological guidance in pharmacoepidemiology. For each topic covered, direct links to internationally agreed recommendations, key points from important guidelines, published articles and textbooks are provided. Where relevant, gaps in existing guidance are addressed with what ENCePP considers good practice.
The current version of the Guide is Revision 11, dated July 2023.
In the 11th Revision, the table of contents has been restructured to better reflect the evidence generation flow and provide greater emphasis on important methodology. New recommendations include the use of the causal inference target trial emulation approach to improve internal validity and increase transparency on study designs; the use of the estimand framework to inform study design and analysis choices; and the use of the HARPER protocol template to foster transparency, reproducibility and harmonisation of non-interventional study protocols and facilitate their assessment.
Nearly all chapters have been updated and include new references, and some chapters have been revised to reflect the fast changing environment in the field of pharmacoepidemiology and real-world evidence (RWE): Chapter 9 on Research networks for multi-database studies addresses the expansion and use of DARWIN EU®, and Chapters 16.1 on Comparative Effectiveness Research, 16.5 on Artificial intelligence in pharmacoepidemiology, and 16.6 on RWE and pharmacoepidemiology, have been extensively revised. Revisions were performed by the co-authors in collaboration with the editorial group.
The Foreword from the co-chairs of the ENCePP Steering Group highlights the continued involvement of ENCePP to draw lessons from the COVID-19 pandemic and address new challenges, such as post-acute COVID-19 syndrome (or long COVID) and the lasting impact of the pandemic on secondary use of real-world data (RWD).
This version will continue supporting sound pharmacoepidemiological research and RWE generation and provides a useful resource for researchers, regulators, and marketing authorisation holders and applicants.
The Guide is developed in collaboration between EMA and the ENCePP Research Standards and Guidance Working Group and is regularly updated by structured review to maintain its dynamic nature. It may also be amended as necessary in response to comments received. For this purpose, comments and additional relevant guidance documents are welcome and may be forwarded to ENCePP Secretariat.
Related Documents
Chapters
The increasing ability and expertise to reuse electronic real-world data (RWD) from routine healthcare systems continues to open up opportunities for investigators to conduct non-interventional studies on the utilisation, safety and effectiveness of medicinal products, and stimulate the development.
Epidemiology is the study of the occurrence of health phenomena in the population, their frequency and their relationship with determinants.
Generating adequate evidence involves formulating the right research question(s), identifying and collecting fit-for-purpose data, applying suitable study designs, and conducting the appropriate analyses.
The study protocol is the core document of a study, to be developed as a key step in any study once the research question has been clearly defined.
An epidemiological study measures a parameter of occurrence (generally incidence, prevalence or risk or rate ratio) of a health phenomenon (e.g., a disease) in a specified population and with a specified time reference (time point or time period).
Historically, pharmacoepidemiological studies relied on patient-reported information or paper-based health records.
Self-selection in epidemiological studies may introduce selection bias and influence the validity of study results.
Effect modification and interaction are often encountered in epidemiological research, and it is important to recognise their occurrence.
There are two main approaches for data collection: collection of data to address the specific research question under study or use of data already collected for another purpose, e.g., for clinical management of patients, for reimbursement purposes, or for another research question.
A growing number of pharmacoepidemiological studies use data from networks of databases, often from different countries.
Identification and integration of evidence derived from results from several studies with the same or similar research objective can extend our understanding of the research question.
A general overview of methods for signal detection and recommendations for their application are provided in the report of the CIOMS Working Group VIII Practical aspects of signal detection in pharmacovigilance.
Compared to the protocol that includes a section outlining the analyses, the SAP is a more technical, stand-alone document describing in detail the planned analyses, population definitions and methodology.
Quality in research is a measure of excellence that impacts medicines development and public health. What is quality management system (QMS)? (American Society for Quality, 2022) defines a QSM as a formalised system that documents processes, procedures, and responsibilities.
Aspects of dissemination and communication of study results include, but are not limited to, reports to health authorities and study sponsors, presentations in scientific fora, scientific publications, patient-focused communications, and websites dedicated to publishing study reports.
In the European Union, the conduct of pharmacoepidemiological studies needs to respect applicable Union data protection rules, namely the General Data Protection Regulation (EU) 2016/679 (GDPR) and Member State laws adopted in line with the GDPR
Comparative effectiveness research (CER) is designed to inform healthcare decisions for the prevention, the diagnosis and the treatment of a given health condition.
A systematic review (SR) attempts to collate all empirical evidence that fits pre-specified eligibility criteria to answer a specific research question.
Planning a pregnancy may lead to discontinuation of non-essential medicines before conception