The additional parameters derived here are of use to screening centers that test serum inhibin in the second trimester, ultrasound NT or NF, and serum PAPP-A to­gether with second trimester serum markers. Statistical modeling is essential for DS screening as it forms part of the software used to estimate an individual’s risk. For this purpose meta-analysis provides the most reliable modeling parameters and the most accurate risks are estimated when there is tailoring of variances and covariances to the local population. Another use of modeling is to predict the per­formance of competing policy options. Again the most robust estimates of performance use meta-analysis derived parameters and appropriate tailoring needs to be carried out depending on whether the policy decision is national, regional or local.

Parameter estimation is an ongoing process. Some of the values derived here should be regarded as provisional until the literature expands. There is very little NF data, expressed in MoMs, and sparse information on the correla­tion between first trimester PAPP-A and second trimester serum markers. Moreover, more data is needed to calcu­late covariances for inhibin and PAPP-A so that better tailoring can be carried out.

Since multi-marker serum screening for DS was first introduced there has been a steady increase in the detec­tion rate, in relatively small increments, as new markers have been added. The incorporation of ultrasound markers has continued and accelerated the process.