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Comparison of family history measures used to identify high risk of coronary heart disease
Author(s) -
Silberberg Jonathan,
Fryer Jayne,
Wlodarczyk John,
Robertson Randall?,
Dear Keith
Publication year - 1999
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/(sici)1098-2272(1999)16:4<344::aid-gepi2>3.0.co;2-q
Subject(s) - categorical variable , covariate , family history , pedigree chart , demography , family aggregation , population , statistics , sample size determination , medicine , contrast (vision) , mathematics , computer science , biology , genetics , sociology , gene , artificial intelligence
We examined 15 published continuous family history measures (scores) as well as two new formulations in terms of several desirable properties. We applied the scores to sample pedigrees and found that some systematically increase with family size. In contrast to aggregate scores, non‐aggregate scores are sensitive to the age, sex, and covariate status of individual relatives but are unstable when the families are small. We also applied these scores to our own population case‐control data, characterised by a high proportion of missing and false‐negative responses. In these small families, all scores provided significant discrimination between CHD cases and controls beyond the usual categorical definition of positive family history, but appeared no better than detailed categorical definitions or even simple counts. Our new formulations offer no solution to the problems of few data; most scores apply asymptotic approximations to differences between observed and expected number of affected relatives and are not suited to small families. All scores would be improved by ruling out families with only one affected relative, as is being done in the NHLBI Family Heart Study. We recommend that researchers, when using a family history measure, consider the number of informative families and other characteristics of their data prior to choosing any particular formulation. Genet. Epidemiol. 16:344–355, 1999. © 1999 Wiley‐Liss, Inc.