Letters to the Editor |
University of Wisconsin Medical School, Madison, Wis.
An extract of the first 250 words of the full text is provided, because this article has no abstract. |
Davey Smith et al have used instrumental variable regression to assess the effect of C-reactive protein (CRP) on blood pressure (BP) in a cross-sectional sample of women.1 By using the 1059G/C polymorphism of the CRP gene as an instrument, they attempted to avoid confounding by unmeasured variables and reverse causality bias and concluded that elevated CRP levels do not lead to high BP. However, this analysis has several limitations. First, the 1059G/C polymorphism is a poor instrument because its effect on CRP level is small. Reported differences in CRP levels between White subjects with the GG and the GC variants were 0.33 mg/L in 1 study,2 0.07 mg/L in another (GG versus GC+CC),3 and nonsignificant in 3 others.46 In fact, in the authors own study the average between-genotype CRP difference was only 0.42 mg/L.1 In the only prospective study on the association of CRP and incidence of hypertension,7 the smallest average difference in CRP level associated to a statistically significant increase in risk was 1.10 mg/L, almost 3x larger than that reported by Davey Smith et al.1 Second, the findings from the instrumental variable models still leave substantial uncertainty. For example, the authors reported that using ordinary linear regression the difference in systolic BP for a doubling of CRP was 1.53 mm Hg with a 95% confidence interval of 0.85 to 2.21. Based on this finding, one would say that systolic BP increases with CRP, although the increase could be the effect of an unknown confounder. On the other
Department of Social Medicine, (G.D.S., D.A.L., R.H., N.T., S.E., I.N.M.D.), University of Bristol, United Kingdom, Division of Cardiovascular and Medical Sciences (A.R., G.D.O.L.), University of Glasgow, United Kingdom, Human Genetics Division (I.N.M.D.), School of Medicine, University of Southampton School of Medicine, United Kingdom
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G. D. Smith Randomised by (your) god: robust inference from an observational study design J Epidemiol Community Health, May 1, 2006; 60(5): 382 - 388. [Full Text] [PDF] |
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