Patient attitudes and preferences about expanded noninvasive prenatal testing
Bibliographic record
Abstract
Introduction: Noninvasive prenatal testing (NIPT) using cell-free DNA (cfDNA) is typically carried out to screen for common fetal chromosomal anomalies, with the option to screen for a wider range of chromosomal changes (expanded NIPT) becoming increasingly available. However, little is known about pregnant patients’ attitudes and preferences regarding expanded NIPT. Methods: To address this gap, we surveyed general-risk patients having first-tier cfDNA screening at a private prenatal clinic on their expectations for expanded NIPT. Patients were asked questions regarding their current pregnancy and previous pregnancy history, their opinions on fetal DNA screenings during pregnancy and incidental findings, information and opinions on financial resources for NIPT, as well as socio-cultural questions to determine patient demographics. Results: Of the 200 survey participants, the majority were educated, self-reported as white, had a higher than average income, and reported no aneuploidy risk factors. When asked what information they would like to receive from cfDNA screening, the vast majority of participants wanted all information available that could have an immediate impact on fetal health (88%) or an immediate impact on infant health from birth (82%). Many participants also wanted information that could have a future impact on the child’s health or an immediate or future impact on the pregnant woman’s own health. Most participants wanted information about the sex of fetus (86%) and common trisomies (71%), with almost half of participants desiring information about rare autosomal aneuploidies and/or all genetic information that may affect the baby. In addition, participants were found to be comfortable screening for conditions that are well-known, influence care during pregnancy, and are treatable. Finally, while most respondents either had insurance coverage for NIPT or were able to afford NIPT out of pocket, the majority of our participants felt that expanded NIPT should be either free for everyone or for those considered high risk. Discussion: Our findings suggest that with appropriate pre-test counseling, pregnant patients may choose NIPT for an expanding list of conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".