ArticleStatistics in medicine2016
Using family members to augment genetic case-control studies of a life-threatening disease.
Article in Statistics in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- A review of Mendelian randomization in amyotrophic lateral sclerosis.Brain : a journal of neurology · 2022Review
- Gene-based and pathway-based testing for rare-variant association in affected sib pairs.Genetic epidemiology · 2020Article
- Survival Bias in Mendelian Randomization Studies: A Threat to Causal Inference.Epidemiology (Cambridge, Mass.) · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Survival bias is difficult to detect and adjust for in case-control genetic association studies but can invalidate findings when only surviving cases are studied and survival is associated with the genetic variants under study. Here, we propose a design where one genotypes genetically informative family members (such as offspring, parents, and spouses) of deceased cases and incorporates that surrogate genetic information into a retrospective maximum likelihood analysis. We show that inclusion of genotype data from first-degree relatives permits unbiased estimation of genotype association parameters. We derive closed-form maximum likelihood estimates for association parameters under the widely used log-additive and dominant association models. Our proposed design not only permits a valid analysis but also enhances statistical power by augmenting the sample with indirectly studied individuals. Gene variants associated with poor prognosis can also be identified under this design. We provide simulation results to assess performance of the methods. Copyright © 2016 John Wiley & Sons, Ltd.
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Registered trials
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