The improvement of the antenatal detection of fetal neural tube defects using discriminant analysis

Abstract

Discriminant analysis was applied to the antenatal diagnosis of fetal neural tube defects. Alpha-fetoprotein, gestational age, and seven easily assayed biochemical variables were used to generate the discriminant function, which was derived from a retrospective study on data from 130 pregnancies, including 25 which were associated with fetal anencephaly and 13 with fetal spina bifida. This function was used to generate a diagnosis in a blind study of 40 previously unassayed samples: 20 problem samples from another centre interspersed with 20 normal samples. The same function was used over a period of 2 years to predict prospectively the outcome of 669 pregnancies with respect to neural tube defects. Of these 55 were found to be associated with fetal neural tube defects. Classification is shown to be more reliable than using alpha-fetoprotein and gestational age alone. The results demonstrate a successful application of discriminant analysis to medical diagnosis.