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Published on: February 23, 2011
The effects of gestation dating on the calculation of patient-specific risks in Down's syndrome screening:
J C Bishop1, F D Dunstan, A B Nix
1Department of Medical Statistics, University of Newcastle upon Tyne, UK.
When screening for Down's syndrome using biochemical markers, the measurements are adjusted for the gestational age of the fetus because the concentrations of the markers are known to change with gestational age. This adjustment is performed by referring each marker measurement to the population median for that marker for the appropriate estimated gestational age group. The measurement of gestational age is subject to error, whichever method is used, and so the population median used is usually the median of a mixture of distributions for different true gestational ages. Most screening programmes aim for a specific number of weeks and this produces a concentrated distribution of true gestational ages. This fact, combined with dating errors, leads to an asymmetric mixture for each gestational age group and hence to bias in the estimates of the medians. In a previous communication we have shown how the proportions in this mixture distribution can be estimated and how the true medians corresponding to a true gestational age can be estimated. The calculations presented were performed using a single marker, and the details of our method were restricted to this situation. This paper extends the method to the multimarker situation and, as expected, leads to a gain in the detection rate for a specified false positive rate. The true patient-specific risk estimates are again markedly different from the quoted nominal value obtained by ignoring the dating errors. The data set on which the method is illustrated uses two markers, although the technique generalises in an obvious way to more than two.
When screening for Down's syndrome using biochemical markers, the measurements are adjusted for the gestational age of the fetus because the concentrations of the markers are known to change with gestational age. This adjustment is performed by referring each marker measurement to the population median for that marker for the appropriate estimated gestational age group. The measurement of gestational age is subject to error, whichever method is used, and so the population median used is usually the median of a mixture of distributions for different true gestational ages. Most screening programmes aim for a specific number of weeks and this produces a concentrated distribution of true gestational ages. This fact, combined with dating errors, leads to an asymmetric mixture for each gestational age group and hence to bias in the estimates of the medians. In a previous communication we have shown how the proportions in this mixture distribution can be estimated and how the true medians corresponding to a true gestational age can be estimated. The calculations presented were performed using a single marker, and the details of our method were restricted to this situation. This paper extends the method to the multimarker situation and, as expected, leads to a gain in the detection rate for a specified false positive rate. The true patient-specific risk estimates are again markedly different from the quoted nominal value obtained by ignoring the dating errors. The data set on which the method is illustrated uses two markers, although the technique generalises in an obvious way to more than two.
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