BACKGROUND: Adjusting maternal serum markers for maternal weight is considered to be a standard practice when screening for pregnancies associated with Down's syndrome. The choice of model for taking maternal weight into account is, however, rarely explicitly evaluated.METHOD: The relationship between the maternal serum markers alphafetoprotein (AFP), human chorionic gonadotropin (HCG) and unconjugated oestriol (uE3), determined with the Beckman Coulter access reagents and maternal weight was investigated in a cohort of 752 Belgian women being screened for pregnancy associated with Down's syndrome. Two different models (the log-linear equation and the linear-reciprocal equation) were used to determine the relationship between the serum markers and maternal weight.RESULTS: A significant relationship between log(10) multiples of median (MoM) values and weight (kg) was obtained for all markers, and the log-linear model had higher coefficients of determination (r(2)) when compared with the linear-reciprocal model. Weight correction with either method achieved the optimum effect that the correction factor for a woman with a population median weight of 65.5 kg was not significantly different from 1. Simulated weight-corrected MoM values with the two approaches were compared and variation was estimated. The mean difference between the weight-corrected MoM values calculated by the two methods was 7.8% (SD 4.3%) for AFP, 14.0% (4.4%) for HCG and 5.9% (3.2%) for uE3. This resulted in a difference in risk estimate of 1.66-5.34% for Down's syndrome owing to weight correction algorithm differences in women of median weight.CONCLUSION: The log-linear weight correction approach was shown to be marginally more effective by a goodness-of-fit analysis. Differences in weight-corrected MoM values estimated with the two approaches are highly significant (p<0.0001, Wilcoxon's paired sample test), but the effect on risk calculation was not significant. It was observed that the changes in risk became significant the more the MoM correction factors deviated from 1.
Biomarkers Body Weight