Conducting Post Market Registries – Rationale and Execution (Part 1)

1 June, 2015, by ClinCaptureTeam

In this paper, we aim to educate around the different types of registry studies, and some of the specifications in its execution. This paper was written by Clinovo’s founder and President Ale Gicqueau, for the 2015 Association of Clinical Research Professionals (ACRP) Global Conference and Exhibition.

Introduction:

At the end of 2012, the FDA approved expanded labeling for the Edwards SAPIEN Transcatheter Heart Valve, making the device available to a larger group of patients with aortic stenosis.  This opened a new avenue for device companies to expand indications of approved devices into wider patient populations.  The methods needed to achieve these successes require careful planning and development of a flexible and configurable database. Further, agencies such as the Agency for Healthcare Research and Quality (AHRQ) recommend Device registries as the most effective manner to collect long-term safety data on devices.

Registry Studies versus Clinical Trials

Consider this example

In order to deliver this message in a more successful manner, let’s take a precise example. A sponsor wants to do an observational study on a commercial device for treating a condition. They need an additional piece of data about the outcome, which they forgot to collect in clinical trials. The additional information requires that the patient submit to an unscheduled MRI. This design is not observational. The reason is observational studies—by definition—do not dictate interventions. But the protocol for this study dictates an invasive, unscheduled procedure be given to the subject. It isn’t always the primary treatment that moves the study from observational to investigational, it might be an invasive diagnostic procedure you are adding to the mix.

Design of Registries

The design of registry studies therefore needs to take into these contextual specifications. Implementing a registry study is similar in many ways to an investigational clinical trial. In the planning phase, we define the hypotheses related to the safety, efficacy and cost of the device, the endpoints or outcomes that will support or refute the hypotheses, and the inclusion and exclusion criteria for who will be in the study. A determination is then made if safety monitoring boards, IRBs, or other committees are necessary.

In the design phase, the details of the registry study are worked out and a protocol is written. The most common designs for registries are: Cohort studies, Case-controlled studies and Case Series studies. Cohort designs follow over time a group of people who possess a common characteristic to see if they develop a particular endpoint or outcome. While Cohort studies may provide data for subsets of the population you are interested in, they may be limiting, and not collect the breadth of data desired.  Case Controlled series provide comparison data, but may be more difficult to manage, and slower to enroll. In case-control studies, we look at ‘cases’ of patients who have a particular outcome or who have had a particular adverse event and ‘controls’ who have not, and then you look backwards to see what proportion had an exposure or characteristic of interest.  Case series studies allow clinicians to provide data on all treated patients, and obtain valuable longitudinal data to demonstrate both safety and effectiveness of the device.

In another example, in 2004 Cordis began a registry designed to assess stenting outcomes in relation to the outcomes of their SAPPHIRE trial, which was used as the historic comparison group. The research question was to see if non-academic physicians would achieve the same level of success as the academic investigators used in the clinical study (the hypothesis was that they would.) The registry was conducted because of concerns by FDA and the Centers for Medicare and Medicaid Services (CMS) that the device worked only safely and effectively in the hands of experienced clinicians. The study involved 74 sites and 1493 patients. The large number of sites and subjects are characteristic of registry studies.

Selecting subjects and comparison groups

This next step is critical in differentiating post market studies with initial clinical trials. The target population, first, consists of all the patients with a common disease or condition or a common exposure. For example, the target population might be all people with cataracts, all women with urinary incontinence, or all people who have been exposed to radiation for cancer treatment. Then broad inclusion/exclusion criteria are used to select a representative population of patients. You want to keep the inclusion and exclusion as broad as possible so that the final data will be applicable to the general population. Selecting comparison groups may be trickier in observational studies than in clinical trials because subjects have a choice as to which intervention they receive. Treatment bias is the notion that, given a choice between your new technology and an existing technology, the sickest patients will choose you, while less-ill patients may choose the comparator. The result will be an unfair imbalance in adverse events for the new technology. Key demographic factors—such as age, lifestyle, and disease advancement—are collected and statistically applied to help correct for treatment bias. Comparison groups may be “internal” (data collected simultaneously), “external” (data collected outside of the registry, such as a previous clinical trial, Medicare data, or billing data provided by patients), or “historical” (data collected under the registry protocol but not simultaneously). Comparison groups are essential when you want to distinguish between alternative procedures, assess the magnitude of differences, or determine the strength of associations between groups.

What data should be collected?

Once the comparison groups established, you collect the same kind of data that you do for randomized, controlled trials. For example, you need data from patient demographics, medical history, health status, the patient’s experience with the technology or device, and the primary endpoints, secondary endpoints, adverse events, and technology deficiencies (the ‘outcomes domain’.)

Data Sources for Registries

Contrary to popular belief, registry data is not de-identified. Depending on the data sources, registries may use certain personal identifiers to locate specific patients and link the data to other sources. For example, Social Security numbers (SSN) can be used to identify individuals in the National Death Index (NDI). The data may come from many different sources: outpatient clinic records, inpatient hospital records, laboratory records, billing records, and even payer claims data! Data may come from medical chart abstraction, electronic medical records, institutional or organizational databases, administrative databases, death and birth records, census databases, or other registry databases.

End of Part 1 

Ale Gicqueau,
President and Founder at Clinovo
www.clinovo.com

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