Issues associated with possible implementation of Non‐Invasive Prenatal Testing (NIPT) in first‐tier screening: A rapid scoping review
Bibliographic record
Abstract
In recent years, as the implementation and use of Non-Invasive Prenatal Testing (NIPT) have increased, the cost of the test has been decreasing. The cost of NIPT is expected to fall further in the upcoming years. As a result of the decreasing cost of NIPT, many jurisdictions may change their prenatal screening policies toward abandoning serum-based screening and instead, implement and support NIPT as the first-tier screening for all women. There are several concerns in replacing first-trimester screening with NIPT. In this scoping review, we aimed to map the existing knowledge about possible issues in the systematic implementation of NIPT as the primary method of first-tier screening and to assess if any jurisdiction has altered its policy and discontinued serum-based prenatal screening in exchange for NIPT. The Medline database (Ovid) and Google Scholar was searched and all the studies discussing, investigating, or reporting on the systematic implementation of NIPT as the primary method of first-tier screening were included. All the studies went through a two-stage screening process and included full-text articles were reviewed. We did not find any articles indicating a country or region that replaced traditional prenatal screening by NIPT. The included articles were charted, and the data about the possible issues in the systematic implementation of NIPT as the primary method of first-tier screening are summarized narratively and presented in tables in four categories. The findings of this scoping review may be informative for stakeholders and policymakers regarding recent changes in NIPT implementation policies around the world and may aid with developing policy for NIPT implementation with a broader perspective.
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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 | 0.079 | 0.260 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.023 | 0.023 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".