Literature DB >> 10207716

Comparison of family history measures used to identify high risk of coronary heart disease.

J Silberberg1, J Fryer, J Wlodarczyk, R Robertson, K Dear.   

Abstract

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.

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Year:  1999        PMID: 10207716     DOI: 10.1002/(SICI)1098-2272(1999)16:4<344::AID-GEPI2>3.0.CO;2-Q

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  9 in total

1.  Heredity, diet and lifestyle as determining risk factors for the esophageal cancer on Nanao Island in Southern China.

Authors:  Min Liu; Min Su; Dong-Ping Tian; Guo-Hong Zhang; He-Lin Yang; Yu-Xia Gao
Journal:  Fam Cancer       Date:  2010-06       Impact factor: 2.375

2.  Family history of myocardial infarction, stroke and diabetes and cardiometabolic markers in children.

Authors:  Nina E Berentzen; Alet H Wijga; Lenie van Rossem; Gerard H Koppelman; Bo van Nieuwenhuizen; Ulrike Gehring; Annemieke M W Spijkerman; Henriëtte A Smit
Journal:  Diabetologia       Date:  2016-05-30       Impact factor: 10.122

3.  Developing community-based health education strategies with family history: Assessing the association between community resident family history and interest in health education.

Authors:  Elizabeth C Prom-Wormley; James S Clifford; Jessica L Bourdon; Peter Barr; Courtney Blondino; Kevin M Ball; Joshua Montgomery; Jonathan K Davis; Joseph E Real; Alexis C Edwards; Dawn L Thiselton; Gwen Corley Creighton; De'Nisha Wilson; Cynthia Newbille
Journal:  Soc Sci Med       Date:  2019-02-19       Impact factor: 4.634

4.  Physicians' strategies for using family history data: having the data is not the same as using the data.

Authors:  Peter Taber; Parveen Ghani; Joshua D Schiffman; Wendy Kohlmann; Rachel Hess; Valli Chidambaram; Kensaku Kawamoto; Rosalie G Waller; Damian Borbolla; Guilherme Del Fiol; Charlene Weir
Journal:  JAMIA Open       Date:  2020-10-08

5.  A new estimate of family disease history providing improved prediction of disease risks.

Authors:  Rui Feng; Leslie A McClure; Hemant K Tiwari; George Howard
Journal:  Stat Med       Date:  2009-04-15       Impact factor: 2.373

6.  How should we construct psychiatric family history scores? A comparison of alternative approaches from the Dunedin Family Health History Study.

Authors:  B J Milne; T E Moffitt; R Crump; R Poulton; M Rutter; M R Sears; A Taylor; A Caspi
Journal:  Psychol Med       Date:  2008-03-26       Impact factor: 7.723

7.  Addition of a novel, protective family history category allows better profiling of cardiovascular risk and atherosclerotic burden in the general population. The Asklepios Study.

Authors:  Caroline M Van daele; Tim De Meyer; Marc L De Buyzere; Thierry C Gillebert; Simon L I J Denil; Sofie Bekaert; Julio A Chirinos; Patrick Segers; Guy G De Backer; Dirk De Bacquer; Ernst R Rietzschel
Journal:  PLoS One       Date:  2013-05-02       Impact factor: 3.240

8.  A probabilistic model to predict clinical phenotypic traits from genome sequencing.

Authors:  Yun-Ching Chen; Christopher Douville; Cheng Wang; Noushin Niknafs; Grace Yeo; Violeta Beleva-Guthrie; Hannah Carter; Peter D Stenson; David N Cooper; Biao Li; Sean Mooney; Rachel Karchin
Journal:  PLoS Comput Biol       Date:  2014-09-04       Impact factor: 4.475

9.  A Bayesian hierarchical logistic regression model of multiple informant family health histories.

Authors:  Jielu Lin; Melanie F Myers; Laura M Koehly; Christopher Steven Marcum
Journal:  BMC Med Res Methodol       Date:  2019-03-12       Impact factor: 4.615

  9 in total

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