Observational PMCF study
Definition as per ISO 14155:2020 Annex I.4.4:
“Clinical investigation that draws inferences about the possible effect of an intervention on subjects, but the investigator has not assigned subjects into intervention groups and has not made any attempts to collect variables beyond those available burden to the subject.”
In a prospective PMCF study
The assignment to an exposure/treatment was already made by the physician and is the basis for the inclusion of the population of interest into the clinical investigation. After the subject signed the informed consent form, medical history, treatment and outcome data are collected from that point forward. The start of the study is defined as the time the clinical investigation plan (CIP) for the specific questions to be answered by the clinical investigations is initiated. Observational clinical investigations might be another way to generate RWE relevant to effectiveness determinations. Therefore, the RWE Program will also consider the evaluation of observational clinical studies using RWD to support product effectiveness determinations.
Retrospective observational PMCF Study, or cohort reviews use the data already collected by the institution and documented in medical records of subjects meeting specified exposure criteria.
Depending on pseudonymisation versus anonymisation of the data, the subjects need to sign an informed consent form (ICF, Art. 6 GDPR) or be informed of the use of their pseudonymized data (Art. 14 GDPR). Clause 26 of the GDPR states that not apply for processing of anonymous information. The difference between anonymisation and pseudonymisation lies in the traceability of personal data: pseudonymized (encrypted) means personal data, where all information that allows direct conclusions to be drawn about a person’s identity is replaced by a code (e.g. a number) or (e.g. in the case of image recordings) made unrecognizable, the simplest indicator would be the use of a Subject Identification Log (SI-Log); anonymized data cannot be traced back to a person (no SI-Log).
The advantage of setting up a retrospective observational clinical investigation of being less prone to patchy subject compliance than patient surveys but remains susceptible to positive selection bias unless the methodology prevents that. Eliminating bias entirely from retrospective reviews is challenging, requiring strict controls on data collection methods. Regulatory bodies will need to see evidence of stringent bias control methods in order for the data generated to be accepted as valid.
5 tips to implementing a valid retrospective medical device PMCF study:
Draft a protocol, with the support of a scientific committee
Propose a study design consistent with the research questions identified
Collect good quality data
Integrate patient-reported outcome measures
Guarantee Data transparency and privacy.
What are the limitations and when to choose to implement a retrospective PMCF study?
Implementing a retrospective study requires the sponsor to have identified the centres that host the clinical data needed. The willingness of the investigator to be part of the study and the absence of competitors running studies simultaneously in the same centres.
After the implementation of the GDPR in Europe, it is necessary to have an electronic Case Report Form (eCRF) secure and compliant and data centre Hébergeurs de Données de Santé (HDS) certified to host health data.
When considering a retrospective study, it is recommended to implement a feasibility study in one centre in order to evaluate if the study design is adequate to the research question. For example: for vascular protheses, long-term safety evidence requires follow-up data over three years if the sponsor is looking to generate evidence of long-term safety using a retrospective study, knowing that long-term data follow-up will not exist in the hospital data warehouse. Indeed, in practice, the protocol post-operation on follow-up for vascular protheses is limited to three months follow-up if there is no serious complication.
Another limitation is the quality of the data and the data gaps you might identify at the end of the research, which will reduce the quality of the study and the statistical power.
Finally, the site and population need to be representative to limit the biases of the study. If one site includes more than 50% of patients compared to the other centres, the quality and the evidence will be impacted.
Table 1 Current frameworks and guidance documents on the use of RWE and/or PROs
Draft Guidance: Guideline on Registry- BasedStudies (Sep 2020)
Focuses on studies based on disease or condition registries to examine the use, safety and effectiveness of medicines prescribed to or used by patients included in the registry.
It also outlines regulatory considerations related to the establishment and management of patient registries, to enable their use in registry-based studies.
Use of patient disease registries for regulatory purposes – methodological and operational considerations (Nov 2018)
Discusses methodological and operational aspects of the use of patient disease registries and registry studies for regulatory purposes.
MHRA guidance on the use of real-world data in clinical studies to support regulatory decisions.
A focus on medicines, but useful principles set out. This is the beginning of a series of guidance that is expected to cover medical devices specifically.
MHRA guidance on RCT using RWD to support regulatory decisions
Aimed at sponsors planning to conduct an RCT using RWD for a medicinal product. Some applicable principles for devices.
Draft guidance: Submitting Documents Using RWD and RWE to FDA (May 2019)
Guidance to encourage applicants who are using RWD/RWE as part of a regulatory submission to provide information on their use of RWE in a simple, uniform format.
Draft guidance: Rare diseases: Natural history Studies for Drug Development (Mar 2019)
Guidance describes the broad potential uses of a natural history study in all phases of drug development for rare diseases, the strengths and weaknesses of various types of natural history studies, data elements and research plans, and a practical framework for the conduct of a natural history study. This guidance also discusses some considerations for aligning the study design with study objectives and for enhancing the interpretability of study results; patient confidentiality and data protection issues in natural history studies; and potential interactions with FDA related to these studies.
Framework for FDA’s RWE Program (Dec 2018)
The Framework clarifies definitions and establishes a 3-part approach for the RWE Program for evaluating RWE: 1) Whether the RWD are “fit for use”, 2)
Whether the study methodologies used to generate RWE can provide “adequate scientific evidence” to address the regulatory question, and 3) Whether study meets FDA requirements for study conduct.
Final Guidance: Use of RWE to Support Regulatory Decision- Making for Medical Devices (Aug 2017)
Clarifies how FDA evaluates real-world data to determine whether they are sufficient for generating the types of real-world evidence that can be used in regulatory decision-making for medical devices.
Draft guidance: Submitting Documents Using RealWorld Data and Real-World Evidence to FDA for Drugs and Biologics Guidance for Industry (Apr 2019)
This guidance is intended to encourage sponsors and applicants who are using real-world data (RWD) to generate real-world evidence (RWE) as part of a regulatory submission to FDA to provide information on their use of RWE in a simple, uniform format.
Guidance: Use of Electronic Health Record Data in Clinical Investigations (Jul 2018)
This guidance is intended to assist sponsors, clinical investigators, contract research organisations, institutional review boards, and other interested parties on the use of electronic health record data in FDA-regulated clinical investigations.
Framework: Optimizing the Use of RWE to Inform Regulatory Decision-Making (April 2019)
Notice to invite industry submissions using high-quality RWE. Health Canada encourages submissions: that aim to expand evidence-based indications for populations often excluded from clinical trials (ex: children, seniors, and pregnant women); for drugs/diseases where clinical trials are unfeasible such as may be the case with rare diseases; and/or where clinical trials are unethical, as may be the case during emergencies where dosages from animal studies may need to be extrapolated to treat humans potentially exposed to chemical or biological threats.
Framework: Elements of RWD/E Quality Throughout the Prescription Drug Product Life Cycle (March 2019)
Provides overarching principles to guide the generation of real-world evidence that would be consistent with the regulatory standard. Includes an overview of elements that should be addressed in protocol development and characterizes some of the data quality concerns within submissions containing RWE.
Framework: A strategy to optimize the use of real-world evidence across the medical device life cycle in Canada (Mar 2020)
This document, in collaboration with Pan-Canadian Health Technology Assessment Collaborative sets out a strategy to improve the accessibility, affordability and appropriate use of medical devices through the optimisation of RWE. A framework will define points across the medical device life cycle where RWE can be useful, and direct guidance document development for devices on RWE use to support regulatory decisions and HTA recommendations.
** not part of the TGA consideration