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Estimating a population cumulative incidence under calendar time trends.

Authors :
Hansen, Stefan N.
Overgaard, Morten
Andersen, Per K.
Parner, Erik T.
Source :
BMC Medical Research Methodology. 1/11/2017, Vol. 17, p1-10. 10p. 1 Diagram, 1 Chart, 2 Graphs.
Publication Year :
2017

Abstract

<bold>Background: </bold>The risk of a disease or psychiatric disorder is frequently measured by the age-specific cumulative incidence. Cumulative incidence estimates are often derived in cohort studies with individuals recruited over calendar time and with the end of follow-up governed by a specific date. It is common practice to apply the Kaplan-Meier or Aalen-Johansen estimator to the total sample and report either the estimated cumulative incidence curve or just a single point on the curve as a description of the disease risk.<bold>Methods: </bold>We argue that, whenever the disease or disorder of interest is influenced by calendar time trends, the total sample Kaplan-Meier and Aalen-Johansen estimators do not provide useful estimates of the general risk in the target population. We present some alternatives to this type of analysis.<bold>Results: </bold>We show how a proportional hazards model may be used to extrapolate disease risk estimates if proportionality is a reasonable assumption. If not reasonable, we instead advocate that a more useful description of the disease risk lies in the age-specific cumulative incidence curves across strata given by time of entry or perhaps just the end of follow-up estimates across all strata. Finally, we argue that a weighted average of these end of follow-up estimates may be a useful summary measure of the disease risk within the study period.<bold>Conclusions: </bold>Time trends in a disease risk will render total sample estimators less useful in observational studies with staggered entry and administrative censoring. An analysis based on proportional hazards or a stratified analysis may be better alternatives. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712288
Volume :
17
Database :
Academic Search Index
Journal :
BMC Medical Research Methodology
Publication Type :
Academic Journal
Accession number :
120681066
Full Text :
https://doi.org/10.1186/s12874-016-0280-6