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. 2003 May;40(Pt 3):219-31.
doi: 10.1258/000456303321610501.

The effect of temporal variation in biochemical markers of trisomy 21 across the first and second trimesters of pregnancy on the estimation of individual patient-specific risks and detection rates for Down's syndrome

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The effect of temporal variation in biochemical markers of trisomy 21 across the first and second trimesters of pregnancy on the estimation of individual patient-specific risks and detection rates for Down's syndrome

K Spencer et al. Ann Clin Biochem. 2003 May.

Abstract

Background: In a previous study we examined the changes in the median multiple of the median (MoM) with gestation of free beta human chorionic gonadotrophin (F beta-hCG), total human chorionic gonadotrophin (ThCG), alpha-fetoprotein (AFP) and pregnancy-associated plasma protein A (PAPP-A) in a large series of Down's syndrome pregnancies. Results showed that there was a significant temporal variation of the MoM for each marker. In this paper, we assess the impact of this temporal shift on the estimation of patient-specific risks and the detection rates (DRs) for Down's syndrome pregnancies.

Methods: Individual patient-specific risks, DRs and false positive rates were estimated using statistical modelling techniques and computer simulations. The data for these simulations were the regressed mean log(10) analyte MoMs, marker standard deviations (as log(10) MoM) and correlation coefficients derived from the analysis of over 1000 cases of Down's syndrome and 150,000 unaffected pregnancies between 6 and 20 weeks of gestation reported in our previous study. Two models were compared: the classical constant median separation model, which assumes no variation in median shift with gestation (model 1), and a variable median separation model (model 2), which takes account of the changes in median shift with gestation as described in our previous study.

Results: When individual patient-specific risks calculated for various MoM values using model 1 were compared with those derived from model 2, considerable differences in risk estimates were observed for all marker combinations, particularly in the first trimester. Using a 1 in 250 cut-off risk, DRs at each gestation in the second trimester for the AFP+F beta-hCG combination were maximized at 14-17 weeks of gestation and were virtually identical at 63-65% for model 1 and model 2. A similar trend was observed for the AFP+ThCG combination, with an optimum gestational range of 15-18 weeks and DRs of 66-68%. In the first trimester, using a 1 in 250 cut-off risk, DRs were more variable with gestation for the prime marker combination of F beta-hCG+PAPP-A, varying from 73% at 8 weeks to 65% at 13 weeks with model 1 and from 75% to 66% with model 2.

Conclusion: Risk algorithms should take into account temporal variation in marker MoMs in order to produce accurate patient-specific risks. This also helps to maximize DRs, particularly when samples are taken out with the optimal gestational range.

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