Joint estimation of Down syndrome risk and ascertainment rates: a meta-analysis of nine published data sets.

In this paper we present an analysis of nine data sets in which ascertainment and maternal age risk of Down syndrome are estimated jointly using maximum likelihood. We include data on 4825 Down syndrome cases from nine previously published data sets. These include data from studies carried out before the introduction of prenatal screening and from recent studies involving women who had not received prenatal testing. Our results show that, allowing for under-ascertainment, there is a good degree of consistency between the different data sets. We compare the three- and five-parameter constant plus exponential model with a three-parameter logistic model for maternal age-specific risk. We show that the three-parameter logistic model provides a good fit to the data and compare rates from this model with those derived from published studies of uncertain completeness (Cuckle et al., 1987) and those from data sets believed to be complete (Halliday et al., 1995; Hecht and Hook, 1994, 1996). In general, our results agree closely with those of the latter, but achieve greater precision because of the inclusion of additional data. Our derived rates are considerably higher than those of Cuckle et al. (1987), which are embedded in many computer systems for generating risks.