Minimizing signal detection time in postmarket sequential analysis: balancing positive predictive value and sensitivity.

ABSTRACT:

Purpose

Outcome misclassification in retrospective epidemiologic analyses has been well-studied, but little is known about such misclassification with respect to sequential statistical analysis during surveillance of medical product-associated risks, a planned capability of the US Food and Drug Administration's Sentinel System.

Methods

Using a vaccine example, we model and simulate sequential database surveillance in an observational data network using a variety of outcome detection algorithms. We consider how these algorithms, as characterized by sensitivity and positive predictive value, impact the length of surveillance and timeliness of safety signal detection. We show investigators/users of these networks how they can perform preparatory study design calculations that c

SUBMITTER: Maro JC 

PROVIDER: S-EPMC7181336 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature