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The impact of truncation and missing family links in population-based registers on familial risk estimates

Leu, Monica, 1977 (author)
Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för samhällsmedicin och folkhälsa,Institute of Medicine, School of Public Health and Community Medicine
Czene, Kamila (author)
Reilly, Marie (author)
 (creator_code:org_t)
2007
2007
English.
In: American Journal of Epidemiology. - 0002-9262 .- 1476-6256. ; 166:12, s. 1461-7
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Family history information is often incomplete in population-based disease registers because of truncation and/or missing family links. In this study, the authors simulated complete populations of related individuals with realistic age, family structure, and incidence rates. After mimicking the realities of register-based data, such as left truncation of family history and missing family links due to death, the authors explored recovery of familial association parameters from standard epidemiologic models. Truncation of family history produced almost no bias for a familial risk of 2 and 50 years of follow-up, but it had a dramatic impact when the familial risk was 10. The age distribution of disease and the magnitude of background incidence rates also affected family history loss and thus the magnitude of bias. One can safeguard against bias by starting follow-up later, with the number of registration years to be ignored in the analysis depending on the value of familial risk. The missing familial links due to death had no effect, except when there was differential mortality for cases with and without a family history of disease. In summary, truncation, and to a lesser extent missing family links, induces bias in familial risk estimates from population-based registers.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)

Keyword

bias (epidemiology)
familial risk
medical record linkage
missing data
registries

Publication and Content Type

ref (subject category)
art (subject category)

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Czene, Kamila
Reilly, Marie
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University of Gothenburg

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