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. 2009 Apr 15;28(8):1269-83.
doi: 10.1002/sim.3526.

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

Rui Feng  1 , Leslie A McClure, Hemant K Tiwari, George Howard
Affiliations

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

Rui Feng et al. Stat Med. .

Abstract

Complex diseases often aggregate within families and using the history of family members' disease can potentially increase the accuracy of the risk assessment and allow clinicians to better target on high risk individuals. However, available family risk scores do not reflect the age of disease onset, gender and family structures simultaneously. In this paper, we propose an alternative approach for a family risk score, the stratified log-rank family score (SLFS), which incorporates the age of disease onset of family members, gender differences and the relationship among family members. Via simulation, we demonstrate that the new SLFS is more closely associated with the true family risk for the disease and more robust to family sizes than two existing methods. We apply our proposed method and the two existing methods to a study of stroke and heart disease. The results show that assessing family history can improve the prediction of disease risks and the SLFS has strongest positive associations with both myocardial infarction and stroke.

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Figures

Figure 1
Figure 1
Mean (s.e.) of correlation coefficient between the estimated family risk score and the true family risk. β0 = 2, β1 = 0.5, β2 = 0.1 (SLFS, Williams et al.’s family risk score, and Reed et al.’s are in the left, middle, and right panels, respectively and shown in blue, red, and green in the online figure.).
Figure 2
Figure 2
Power to find significant correlation coefficients at the significance level of 0.05 and for varying family size (m) and family risk coefficients (γ).
Figure 3
Figure 3
Histogram of family sizes in REGARDS.
Figure 4
Figure 4
10-year incidence rate (per person per year) of MI and stroke among different groups in REGARDS.
Figure 5
Figure 5
Histograms of family history scores for MI and stroke.
Figure 6
Figure 6
Effects of quartiles of family history scores on MI and stroke estimated from the Cox models. The effect estimates are connected for each method and vertical bars indicate the 95 per cent confidence intervals of the estimates.
See this image and copyright information in PMC

References

    1. Castrobeiras A, Muniz J, Fernandezfuertes I, Ladocanosa A, Juane R, Pasalodospita J, Penaslado M. Family history as an independent risk factor for ischemic-heart-disease in a low incidence area (Galicia, Spain) European Heart Journal. 1993;14(11):1445–1450. - PubMed
    1. Eaton CB, Bostom AG, Yanek L, Laurino JP, McQuade W, Hume A, Selhub J. Family history and premature coronary heart disease. Journal of American Board of Family Practice. 1996;9(5):312–318. - PubMed
    1. Vogel VG. Assessing women’s potential risk of developing breast cancer. Oncology (Williston Park) 1996;10(10):1451–1458. 1461; Discussion 1462–1463. - PubMed
    1. Friedlander Y, Arbogast P, Schwartz SM, Marcovina SM, Austin MA, Rosendaal FR, Reiner AP, Psaty BM, Siscovick DS. Family history as a risk factor for early onset myocardial infarction in young women. Atherosclerosis. 2001;156(1):201–207. - PubMed
    1. Graffagnino C, Gasecki AP, Doig GS, Hachinski VC. The importance of family history in cerebrovascular disease. Stroke. 1994;25(8):1599–1604. - PubMed

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