Economic evaluation of prenatal screening for Down syndrome in the U.S.A

Prenat Diagn. 1998 Dec;18(12):1241-52. doi: 10.1002/(sici)1097-0223(199812)18:12<1241::aid-pd440>3.0.co;2-m.

Abstract

Maternal serum screening for Down syndrome involves biochemical tests such as alpha-fetoprotein (alpha FP), human chorionic gonadotrophin (hCG) and unconjugated oestriol (uE3), either alone or in combination, that have variable detection and false-positive rates. Choosing a screening protocol requires a trade-off between a desired detection rate and an acceptable false-positive rate. Selecting a screening protocol that maximizes the net benefit to society provides one approach. We have developed a general formula for calculating the per case net social benefit of a screening test and have applied it to United States data. The maximum net benefit associated with each of the various screening options currently available is estimated and the model is further applied to determine the conditions under which the addition of a new marker to an existing protocol can be justified. For each test, or combination of tests, optimal net benefits occur at different detection and false-positive rates. Net benefits are strongly and positively dependent on maternal age; high net benefits are associated with older patients and low, or even negative, net benefits with younger patients. Also, net benefits are affected by the term risk cut-off rate. For triple testing, the 1:351 Down syndrome term risk cut-off appears to provide a higher net benefit than that obtained with 1:250 or 1:300. The optimization of societal net benefit provides a powerful approach to evaluating screening strategies, but the policies used must also consider individuals' freedom in decision making at each step of the prenatal diagnosis pathway.

MeSH terms

  • Adult
  • Cost-Benefit Analysis / economics
  • Cost-Benefit Analysis / statistics & numerical data
  • Down Syndrome / blood
  • Down Syndrome / diagnosis*
  • Down Syndrome / economics*
  • False Positive Reactions
  • Female
  • Humans
  • Maternal Age
  • Models, Economic*
  • Pregnancy
  • Prenatal Diagnosis / economics*
  • Prenatal Diagnosis / statistics & numerical data
  • Risk Assessment
  • Sensitivity and Specificity
  • United States