ArticleAnnals of epidemiology2023
The application of cross-sectionally derived dementia algorithms to longitudinal data in risk factor analyses.
Article in Annals of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
Abstract
purposeDementia algorithms are often developed in cross-sectional samples but implemented in longitudinal studies to ascertain incident dementia. However, algorithm performance may be higher in cross-sectional settings, and this may impact estimates of risk factor associations.
methodsWe used data from the Religious Orders Study and the Memory and Aging Project (N = 3460) to assess the performance of example algorithms in classifying prevalent dementia in cross-sectional samples versus incident dementia in longitudinal samples. We used an applied example and simulation study to characterize the impact of varying sensitivity, specificity, and unequal sensitivity or specificity between exposure groups (differential performance) on estimated hazard ratios from Cox models.
resultsUsing all items, algorithm sensitivity was higher for prevalent (0.796) versus incident dementia (0.719); hazard ratios had slight bias. Sensitivity differences were larger using a subset of items (0.732 vs. 0.600) and hazard ratios were 13%-19% higher across adjustment sets compared to estimates using gold-standard dementia status. Simulations indicated specificity and differential algorithmic performance between exposure groups may have large effects on hazard ratios.
conclusionsAlgorithms developed using cross-sectional data may be adequate for longitudinal settings when performance is high and non-differential. Poor specificity or differential performance between exposure groups may lead to biases.
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