types of events, such as a diagnosis of cardiomyopathy, are routinely maintained, for then a relatively large number of cases can be readily obtained and matched with controls to identify possible risk factors for the outcome. Also, event reporting systems, such as the MedSun system currently being implemented by the FDA, lend themselves to case-control studies to identify possible safety concerns with devices, provided that there is a means of selecting controls to match the cases and to ascertain the “exposure” status (e.g., device use or not) of both cases and controls.

Registry-Based Studies

A registry is a system for collecting information about a class of individuals or patients who have in common a disease, injury, condition, medical procedure or product, or similar characteristic or exposure. A registry study is an investigation that uses registry data alone or in combination with other data. Some registries are based on diagnoses and include information about people with that diagnosis who receive certain interventions and people with the diagnosis who do not. Other registries include only individuals who have received a device or intervention. The former approach is most useful for comparative studies of those who have and have not been treated with a device. In some cases, the registration consists only of limited information about the subject at the time the device was first used. In more elaborate settings, registrants are prospectively followed for outcome events, forming a prospective observational study.

DISPROPORTIONALITY ANALYSES OF SPONTANEOUS ADVERSE EVENT REPORTING DATABASES

An adverse event reporting system is not a study design as such. Adverse event reports can, however, be combined with information from simple registries or other data sources to conduct case-control studies.

Recently, new techniques for analyzing event databases have been gaining attention, mostly in the pharmaceutical arena. The remainder of this appendix reviews the application of these techniques to drugs and provides an example of an application to device databases.

Overview

Disproportionality analyses are the most common technique for analyzing adverse drug reaction databases, and they can also be used for analyzing adverse device events. They are a means of assessing the association between use of a device and outcome when denominator data are not available for estimating population parameters, as is the case with adverse



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