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VP07.01: The Frontline study: comparing frontline screening options and outcomes

Objectives: To ascertain the performance of non-invasive prenatal screening (NIPS) as a frontline screening option in a population with high body mass index (BMI). Methods: 1,000 women attending a public hospital in Australia were offered NIPS free of charge as part of a study examining the uptake of NIPS in a low socio-economic population in Australia. Samples were taken at 11–12 weeks of gestation and analysed using Illumina TruSeq v1.2 methodology and interpreted using the SaFER algorithms. Results: The average BMI for our population was 27.8 (range 14.9–57.5). Only 40% of our population had a BMI in the healthy weight range (18.5–24.9). 26% were overweight (BMI 25–29.9), 16% were obese (BMI 30–34.9) and 15% morbidly obese (BMI 35–57.5). Two samples were below 2% fetal fraction (FF) and required recollection (which indicated no aneuploidy) to obtain a successful result. Both had a high BMI (32.6 and 43.3 respectively), the first on medications for hypothyroidism with no major adverse pregnancy outcomes, the second had very low PAPP-A with the pregnancy later being complicated by intrauterine growth restriction (IUGR) and pre-eclampsia. 2.71% had results less than 4% FF and 6.53% of samples had FF equal to 4% or below. Conclusions: NIPS using whole-genome sequencing successfully obtained results for all but two women on first sampling despite the very high BMI of our population (first report failure rate of 1:500 or 0.2%). Other methodologies, not based on whole-genome sequencing, would have resulted in a higher failure to report rates (based on published literature) in our study population. If a fetal fraction requirement of 4% or below is used (as in other methods) between 27–65 samples would have failed, potentially resulting in a higher need for invasive testing and increased anxiety for those patients. Non-invasive prenatal screening can be successfully offered as a first line prenatal screening test in women with very high BMI when using whole-genome sequencing platforms.