Self-controlled case series analysis with event-dependent observation periods

C. Paddy Farrington, Karim Anaya-Izquierdo, Heather J. Whitaker, Mounia N. Hocine, Ian Douglas, Liam Smeeth

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

The self-controlled case series method may be used to study the association between a time-varying exposure and a health event. It is based only on cases, and it controls for fixed confounders. Exposure and event histories are collected for each case over a predefined observation period. The method requires that observation periods should be independent of event times. This requirement is violated when events increase the mortality rate, since censoring of the observation periods is then event dependent. In this article, the case series method for rare nonrecurrent events is extended to remove this independence assumption, thus introducing an additional term in the likelihood that depends on the censoring process. In order to remain within the case series framework in which only cases are sampled, the model is reparameterized so that this additional term becomes estimable from the distribution of intervals from event to end of observation. The exposure effect of primary interest may be estimated unbiasedly. The age effect, however, takes on a new interpretation, incorporating the effect of censoring. The model may be fitted in standard loglinear modeling software; this yields conservative standard errors. We describe a detailed application to the study of antipsychotics and stroke. The estimates obtained from the standard case series model are shown to be biased when event-dependent observation periods are ignored. When they are allowed for, antipsychotic use remains strongly positively associated with stroke in patients with dementia, but not in patients without dementia. Two detailed simulation studies are included
Original languageEnglish
Pages (from-to)417-426
Number of pages10
JournalJournal of the American Statistical Association
Volume106
Issue number494
DOIs
Publication statusPublished - Jun 2011

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Dependent Observations
Series
Censoring
Dementia
Stroke
Rare Events
Mortality Rate
Term
Standard error
Biased
Likelihood
Time-varying
Health
Simulation Study
Model
Interval
Software
Observation
Dependent
Requirements

Cite this

Self-controlled case series analysis with event-dependent observation periods. / Farrington, C. Paddy; Anaya-Izquierdo, Karim; Whitaker, Heather J.; Hocine, Mounia N.; Douglas, Ian; Smeeth, Liam.

In: Journal of the American Statistical Association, Vol. 106, No. 494, 06.2011, p. 417-426.

Research output: Contribution to journalArticle

Farrington, C. Paddy ; Anaya-Izquierdo, Karim ; Whitaker, Heather J. ; Hocine, Mounia N. ; Douglas, Ian ; Smeeth, Liam. / Self-controlled case series analysis with event-dependent observation periods. In: Journal of the American Statistical Association. 2011 ; Vol. 106, No. 494. pp. 417-426.
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