Validation of a method for noninvasive prenatal testing for fetal aneuploidies risk and considerations for its introduction in the Public Health System
Bibliographic record
Abstract
Objective: The aim of this study was to validate noninvasive prenatal testing (NIPT) for fetal aneuploidies by whole-genome massively parallel sequencing (MPS).Methods: MPS was performed on cell-free DNA (cfDNA) isolated from maternal plasma in two groups: a first set of 186 euploid samples and a second set of 195 samples enriched of aneuploid cases (n = 69); digital PCR for fetal fraction (FF) assessment was performed on 178/381 samples. Cases with <10 × 106 reads (n = 54) were excluded for downstream data analysis. Follow-up data (invasive testing results or neonatal information) were available for all samples. Performances in terms of specificity/sensitivity and Z-score distributions were evaluated.Results: All positive samples for trisomy 21 (T21) (n = 43), trisomy 18 (T18) (n = 6) and trisomy 13 (T13) (n = 7) were correctly identified (sensitivity: 99.9%); 5 false positive results were reported: 3 for T21 (specificity = 98.9%) and 2 for T13 (specificity = 99.4%). Besides FF, total cfDNA concentration seems another important parameter for MPS, since it influences the number of reads.Conclusions: The overall test accuracy allowed us introducing NIPT for T21, T18 and T13 as a clinical service for pregnant women after 10 + 4 weeks of gestation. Sex chromosome aneuploidy assessment needs further validation due to the limited number of aneuploid cases in this study.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".