Can decision analysis help us decide whether ultrasound screening for fetal anomalies is worth it?
Decision analysis is a widely used tool to improve clinical decision making when randomized controlled trials are infeasible, underpowered, or lack generalizability. We performed an exploratory decision analysis of routine second trimester ultrasound to detect fetal anomalies, focusing on the assumptions that would have the greatest impact. Six outcome categories were considered: (1) abnormal ultrasound, anomalous child, (2) abnormal ultrasound, elective abortion of anomalous fetus, (3) abnormal ultrasound, healthy child, (4) abnormal ultrasound, elective abortion of healthy fetus, (5) normal ultrasound, healthy child, and (6) normal ultrasound, anomalous child. Live birth and fetal death rates for nine sonographically detectable anomalies were obtained from the California Birth Defects Monitoring Program. The sensitivity and specificity of ultrasound were estimated through meta-analysis of recent series. Plausible ranges for the probabilities of cesarean delivery and elective abortion, by anomaly, were determined through review of the literature. Standard gamble, willingness-to-pay, and human capital estimates of utility were rescaled for comparability. We found that routine ultrasound appears to be the preferred strategy for most women. This choice is sensitive primarily to the specificity of ultrasound and women's willingness-to-pay for the reassurance of a normal ultrasound.
Romano
P S
PS
Department of Medicine, University of California, Davis 95817, USA. psromano@ucdavis.edu
Waitzman
N J
NJ
D000013:Congenital Abnormalities / Q000000981:diagnostic imaging* / Q000191:economics; D003365:Costs and Cost Analysis; D003661:Decision Support Techniques; D005260:Female; D005333:Fetus / Q000002:abnormalities*; D006801:Humans; D011247:Pregnancy; D011336:Probability; D016032:Randomized Controlled Trials as Topic; D012680:Sensitivity and Specificity; D016216:Ultrasonography, Prenatal / Q000191:economics / Q000706:statistics & numerical data*