Benefits, challenges and ethical principles associated with implementing noninvasive prenatal testing: a Delphi study
Bibliographic record
Abstract
BACKGROUND: Noninvasive prenatal testing is a recent technology that provides some genetic information about the fetus through the analysis of cell-free fetal DNA circulating in maternal blood. We aimed to identify the benefits, challenges and guiding ethical principles most relevant to the clinical integration of noninvasive prenatal testing in Canada, according to experts throughout the country. METHODS: We conducted a 3-round Delphi study involving Canadian experts of contemporary discussions about the ethical and societal implications of prenatal testing and genomic technologies. In round 1, we asked participants to identify clinical benefits and challenges related to the implementation of noninvasive prenatal testing in Canada, and the ethical principles they think should guide it. In round 2, we asked participants to select the most important elements stated by their peers. In round 3, participants were informed of the aggregated results from round 2, and invited to revise or confirm their selection. RESULTS: = 16) prioritized by Canadian experts as being most relevant to the implementation of noninvasive prenatal testing in Canada. INTERPRETATION: Although multiple and diverse potential issues were identified, Canadian experts agreed on 2 sets of requirements for the responsible implementation of noninvasive prenatal testing in Canada. Interdisciplinary appraisals may be instrumental to responsible policy-making related to the implementation of noninvasive prenatal testing in Canada.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".