Exploring the predicted yield of prenatal testing by evaluating a postnatal population with structural abnormalities using a novel mathematical model.

ABSTRACT

OBJECTIVE: To determine the yield of prenatal testing and screening options after identification of fetal structural abnormalities using a novel mathematical model. METHOD: A retrospective chart review was conducted to collect structural abnormality and genetic testing data on infants who were evaluated postnatally by a medical geneticist. A novel mathematical model was used to determine and compare the predicted diagnostic yields of prenatal testing and screening options. RESULTS: Over a quarter of patients with at least one structural abnormality (28.1%, n = 222) had a genetic aberration identified that explained their phenotype. Chromosomal microarray (CMA) had the highest predicted diagnostic yield (26.8%, P < .001). Karyotype (20.8%) had similar yields as genome wide NIPT (21.2%, P = .859) and NIPT with select copy number variants (CNVs) (17.9%, P = .184). Among individuals with an isolated structural abnormality, whole exome sequencing (25.9%) and CMA (14.9%) had the highest predicted yields. CONCLUSION: This study introduces a novel mathematical model for predicting the potential yield of prenatal testing and screening options. This study provides further evidence that CMA has the highest predicted diagnostic yield in cases with structural abnormalities. Screening with expanded NIPT options shows potential for patients who decline invasive testing, but only in the setting of adequate pre-test counseling.