A registry is an organised system that uses observational methods to collect uniform data on specified outcomes in a population defined by a particular disease, condition or exposure. A register is the database deriving from the registry (such as the EU PAS Register), the two terms being often used interchangeably. These terms are sometimes used incorrectly to designate a cohort study with primary data collection or a list of all patients meeting the eligibility criteria for a study. The term ‘patient log-list’ could be used for this purpose.
A patient registry should be considered as a structure for the standardised recording of data from routine clinical practice on individual patients identified by a characteristics or an event, for example the diagnosis of a disease, the occurrence of a condition (e.g., pregnancy), the prescription of a medicinal product, a hospital encounter, or any combination of these.
In European Nordic countries where there is a comprehensive registration of data for a high proportion or all of the population, government-administered patient registries may include hospital encounters, diagnoses and procedures, such as the Norwegian Patient Registry, the Danish National Patient Registry or the Swedish National Patient Register. They may lack information on lifestyle factors, patient-related outcomes and laboratory data. A Review of 103 Swedish Healthcare Quality Registries (J Intern Med 2015; 277(1): 94–136) describes additional healthcare quality registries focusing on specific disorders initiated in Sweden mostly by physicians with data on aspects of disease management, self-reported quality of life, lifestyle, and general health status, providing an important source for research.
As illustrated in Imposed registries within the European postmarketing surveillance system (Pharmacoepidemiol Drug Saf 2018 May 11), the conceptual differences between registries and studies need to be clearly understood.
Patient registries are often integrated into routine clinical practice with systematic and sometimes automated data capture in electronic healthcare records. Whilst the duration of a registry is normally open-ended, that of a study is dictated by the time needed to define and collect data relevant for the specific study objectives. Studies may also require introduction of specific procedures, questionnaires or data collection tools. Studies are set up and managed based on a limited number of endpoints and a specific protocol, whereas patient registries should focus on system(s) specifications in order to ensure continuous, efficient and collaborative data collection, safe data hosting and availability of retrievable, interoperable and re-usable data.
A register can be used as a source of patients for studies based on either primary data collection (where the data collected for new patients are also used for a specific study) or secondary data collection (analogously to the use of electronic healthcare records). For this purpose, registry data can be enriched with additional information on outcomes, lifestyle data, immunisation or mortality information obtained from linkage to the existing databases such as national cancer registries, prescription databases or mortality records.
To support better use of existing registries and facilitate the establishment of new high-quality registries, the EU regulatory network developed the Patient registries initiative. As part of this initiative, the European Medicines Agency (EMA) organised several workshops on disease-specific registries. The reports of these workshops on the EMA Patient registries website describe regulators’ expectation on common data elements to be collected and best practices on topics such as governance, data quality control, data sharing or reporting of safety data. The ENCePP Resource database of data sources is also used to support an inventory of existing disease registries.
Upon request from the European cystic fibrosis society patient registry (ECFSPR), the EMA’s Scientific Advice Working Party issued a Qualification Opinion, concluding that the current status of the registry allows its use as a data source for regulatory purposes for drug utilisation studies, drug efficacy/effectiveness studies and Drug Safety studies. Although it applies only to the ECFSPR, the text of this opinion provides a good indication of the key methodological components expected by regulators for using a disease registry for post-authorisation studies.
The US Agency for Health Care Research and Quality (AHRQ) published a comprehensive document on ‘good registry practices’ entitled Registries for Evaluating Patient Outcomes: A User's Guide, 3rd Edition, which provides methodological guidance on planning, design, implementation, analysis, interpretation and evaluation of the quality of a registry. There is a dedicated section for linkage of registries to other data sources. The EU PARENT Joint Action developed methodological and governance guidelines to facilitate cross-border use of registries.
Results obtained from analyses of registry data may be affected by the same biases as those of studies described in Chapter 5.2 Bias and confounding. Registries are particularly sensitive to the occurrence of selection bias. This is due to the fact that factors that may influence the enlistment of patients in a registry may be numerous (including clinical, demographic and socio-economic factors) and difficult to predict and identify, potentially resulting in a biased sample of the patient population in case the recruitment has not been exhaustive. In addition, studies that use registry data may also introduce selection bias in the recruitment or selection of registered patient for the specific study, as well as in the differential completeness of follow-up and data collection. It is therefore important to systematically compare the characteristics of the study population with those of the source population.
The randomised registry trial is a new study design that combines the robustness of randomised studies with the higher generalisability of registry data, see Chapter 5.6.3.
In assessing both safety and effectiveness, special populations can be identified based on age (e.g., paediatric or elderly), pregnancy status, renal or hepatic function, race, or genetic differences. Some registries are focused on these particular populations. Examples of these are the birth registries in Nordic countries.
The FDA’s Guidance for Industry-Establishing Pregnancy Exposure Registries advises on good practice for designing a pregnancy registry with a description of research methods and elements to be addressed. The Systematic overview of data sources for Drug Safety in pregnancy research provides an inventory of pregnancy exposure registries and alternative data sources on safety of prenatal drug exposure and discusses their strengths and limitations. Example of population-based registers allowing to assess outcome of drug exposure during pregnancy are the European network of registries for the epidemiologic surveillance of congenital anomalies EUROCAT, and the pan-Nordic registries which record drug use during pregnancy as illustrated in Selective serotonin reuptake inhibitors and venlafaxine in early pregnancy and risk of birth defects: population based cohort study and sibling design (BMJ 2015;350:h1798).
For paediatric populations, specific and detailed information as neonatal age (e.g. in days, not just in years), pharmacokinetic parameters and organ maturation need to be considered and is usually missing from the classical datasources, therefore paediatric specific registries are important. The CHMP Guideline on Conduct of Pharmacovigilance for Medicines Used by the Paediatric Population provides further relevant information. An example of registry which focuses on paediatric patients is Pharmachild, which captures children with juvenile idiopathic arthritis undergoing treatment with methotrexate or biologic agents.
Annex 1 of Module VIII of the Good pharmacovigilance practice provides guidance on use of patient registries for regulatory purpose. It emphasises that the choice of the registry population and the design of the registry should be driven by its objective(s) in terms of outcomes to be measured and analyses and comparisons to be performed. As existing disease registries gather insights into the natural history and clinical aspects of diseases and allow comparison of outcomes between different treatments prescribed for the same indication, they are generally preferred to product registries for regulatory purposes. Module VIII also acknowledges that, due to their observational nature, registries should not normally be used to demonstrate efficacy in real world setting, although in some cases (such as rare disease, rare exposure or special population), they may be the only opportunity to provide insight into effectiveness of a medicinal product. On the other hand, when efficacy has been demonstrated in randomised clinical trials (RCTs), registries may be useful to study effectiveness in heterogeneous populations and effect modifiers, such as doses that have been prescribed by physicians and that may differ from those used in RCTs, patient sub-groups defined by variables such as age, co-morbidities, use of concomitant medication or genetic factors, or factors related to a defined country or healthcare system that might influence effectiveness.
Incorporating data from clinical practice into the drug development process is a growing interest from health technology assessment (HTA) bodies and payers since reimbursement decisions can benefit from better estimation and prediction of effectiveness of treatments at the time of product launch. An example of where registries can provide clinical practice data is the building of predictive models that incorporate data from both RCTs and registries to bridge the efficacy-effectiveness gap, i.e. to generalise results observed in RCTs to a real-world setting. Collecting relevant HTA data in early development and planning post-authorisation data collection may therefore support rapid relative effectiveness assessment and decision-making on drug pricing and reimbursement. In this context, the EUnetHTA Joint Action 3 project has issued guidelines for the definition of the research questions and the choice of data sources and methodology that will support the generation of post-launch evidence.