OBJECTIVE: To compare different screening policies for Down's syndrome across a broad range of outcomes, using decision analysis, with particular reference to the role of maternal serum testing. DESIGN: A decision tree was used to combine data from local sources and the medical literature to predict the likely frequency of several outcomes. Sensitivity analyses were used to test the robustness of the conclusions drawn. SETTING: Oxfordshire Health Authority. MAIN OUTCOME MEASURES: Live births with and without Down's syndrome; miscarriages with Down's syndrome; cases of Down's syndrome detected antenatally; amniocenteses performed (and associated miscarriages); direct NHS screening costs; number of women offered screening. RESULTS: Screening policies for Down's syndrome that include serum testing can produce better population outcomes than programmes that do not. Each option for screening for Down's syndrome that we considered had significant drawbacks. In Oxfordshire, offering serum testing to women of all ages would prevent the birth of approximately one more baby with Down's syndrome per year than would a policy of screening for women aged 30 years or more. The cost of preventing this one extra Down's birth would be one or two normal babies lost after amniocentesis, 4500 blood tests for young women (with the associated anxiety and counselling), approximately 200 false positive serum test results and amniocenteses (with the associated anxiety and distress), and 90,000 pounds for the extra tests, counselling, and amniocenteses. Opinions are divided as to which policy is the better option for the population. CONCLUSIONS: Decision analysis is a useful tool for determining the likely consequences of different policy options across a broad range of outcomes. This focuses debate and decision making on outcomes of care, which in turn makes it clear that the choice of screening programme for Down's syndrome depends on the relative importance ascribed to the different outcomes. If individuals' values vary widely it may be impossible to find one screening policy that meets the needs of all pregnant women.
OBJECTIVE: To compare different screening policies for Down's syndrome across a broad range of outcomes, using decision analysis, with particular reference to the role of maternal serum testing. DESIGN: A decision tree was used to combine data from local sources and the medical literature to predict the likely frequency of several outcomes. Sensitivity analyses were used to test the robustness of the conclusions drawn. SETTING: Oxfordshire Health Authority. MAIN OUTCOME MEASURES: Live births with and without Down's syndrome; miscarriages with Down's syndrome; cases of Down's syndrome detected antenatally; amniocenteses performed (and associated miscarriages); direct NHS screening costs; number of women offered screening. RESULTS: Screening policies for Down's syndrome that include serum testing can produce better population outcomes than programmes that do not. Each option for screening for Down's syndrome that we considered had significant drawbacks. In Oxfordshire, offering serum testing to women of all ages would prevent the birth of approximately one more baby with Down's syndrome per year than would a policy of screening for women aged 30 years or more. The cost of preventing this one extra Down's birth would be one or two normal babies lost after amniocentesis, 4500 blood tests for young women (with the associated anxiety and counselling), approximately 200 false positive serum test results and amniocenteses (with the associated anxiety and distress), and 90,000 pounds for the extra tests, counselling, and amniocenteses. Opinions are divided as to which policy is the better option for the population. CONCLUSIONS: Decision analysis is a useful tool for determining the likely consequences of different policy options across a broad range of outcomes. This focuses debate and decision making on outcomes of care, which in turn makes it clear that the choice of screening programme for Down's syndrome depends on the relative importance ascribed to the different outcomes. If individuals' values vary widely it may be impossible to find one screening policy that meets the needs of all pregnant women.
Authors: N J Wald; H S Cuckle; J W Densem; K Nanchahal; P Royston; T Chard; J E Haddow; G J Knight; G E Palomaki; J A Canick Journal: BMJ Date: 1988-10-08
Authors: J Geraghty; P Butler; H Seaman; J Snowball; S Sarkar; R Blanks; S Halloran; K Bodger; C J Rees Journal: Br J Cancer Date: 2014-09-16 Impact factor: 7.640