Effect of screening algorithm, parameter values and median smoothing on patient-specific risk estimates for Down's syndrome screening

The efficiency of a screening programme for Down's syndrome is usually expr essed in terms of the detection rate for a given false positive rate. Two p rogrammes with approximately equal detection rates and false positive rates would then be regarded as being broadly equivalent. While this might be th e case at a population level, we show in this paper that it may be far from true at the individual patient level. Different algorithms, or even differ ent implementations of the same algorithm can lead to calculation of very d ifferent individual risks and can result in different decisions for individ ual patients. Even though two programmes might lead to the same number of r eferrals, they could be referring quite different women. We consider the ef fect of using different parameter values within an algorithm, different alg orithms and alternative ways of estimating the gestational age-dependent me dians of the marker values. We show that the combined effects of these fact ors could explain much of the range of risks reported in the UK National Ex ternal Quality Assessment Scheme for Down's syndrome screening.