Performance of a universal prenatal screening program incorporating cell-free fetal DNA analysis in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: The emergence of cell-free fetal DNA (cfDNA) testing technology has disrupted the landscape of prenatal screening for trisomies 21 (T21) and 18 (T18). Publicly funded systems around the world are grappling with how to best integrate this more accurate but costly technology, as there is limited evidence about its incremental value in real-world conditions. The objectives of this study were to describe the population-based performance of Ontario's prenatal screening program, which incorporates publicly funded cfDNA screening for specific indications, and the effect of cfDNA testing on the screening and diagnostic choices made by pregnant people. METHODS: We conducted a retrospective, descriptive cohort study using routinely collected data from Better Outcomes & Registry Network (BORN) Ontario, which captures linked population data for prenatal and neonatal health encounters across Ontario. We included all singleton pregnancies with an estimated due date between Sept. 1, 2016, and Mar. 31, 2019, that underwent publicly funded prenatal screening in Ontario, and a comparison cohort from Apr. 1, 2012, and Mar. 31, 2013. We assessed performance of the screening program for the detection of T21 or T18 by calculating sensitivity, specificity, positive predictive value and negative predictive value against diagnostic cytogenetic results or birth outcomes. We assessed the impact of the program by calculating the proportion of T21 screen-positive pregnancies undergoing subsequent cfDNA screening and invasive prenatal diagnostic testing. RESULTS: The study cohort included 373 682 pregnancies. The prenatal screening program had an uptake of 69.9%, a screen-positive rate and sensitivity of 1.6% and 89.9% for T21, and 0.2% and 80.5% for T18, respectively. The test failure rate for cfDNA screening was 2.2%. Invasive prenatal diagnostic testing decreased from 4.4% in 2012-2013 to 2.4% over the study period; 65.2% of pregnant people who received a screen-positive result from cfDNA testing went on to have invasive prenatal diagnostic testing. INTERPRETATION: This publicly funded screening program, incorporating cfDNA analysis for common aneuploidies, showed robust performance, a substantial reduction in invasive prenatal diagnostic testing and that pregnant people exercise autonomy in their choices about prenatal screening and diagnosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".