Guide to evaluating performance of prediction models for recurrent clinical events.

ABSTRACT:

Background

Many chronic conditions, such as epilepsy and asthma, are typified by recurrent events-repeated acute deterioration events of a similar type. Statistical models for these conditions often focus on evaluating the time to the first event. They therefore do not make use of data available on all events. Statistical models for recurrent events exist, but it is not clear how best to evaluate their performance. We compare the relative performance of statistical models for analysing recurrent events for epilepsy and asthma.

Methods

We studied two clinical exemplars of common and infrequent events: asthma exacerbations using the Optimum Patient Clinical Research Database, and epileptic seizures using data from the Standard versus New Antiepileptic Drug Study. In both cases

SUBMITTER: Bonnett LJ 

PROVIDER: S-EPMC11912649 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature