Comparison of different strategies in prenatal screening for Down's syndrome: cost effectiveness analysis of computer simulation
Bibliographic record
Abstract
OBJECTIVES: To assess and compare the cost effectiveness of three different strategies for prenatal screening for Down's syndrome (integrated test, sequential screening, and contingent screenings) and to determine the most useful cut-off values for risk. DESIGN: Computer simulations to study integrated, sequential, and contingent screening strategies with various cut-offs leading to 19 potential screening algorithms. DATA SOURCES: The computer simulation was populated with data from the Serum Urine and Ultrasound Screening Study (SURUSS), real unit costs for healthcare interventions, and a population of 110 948 pregnancies from the province of Québec for the year 2001. MAIN OUTCOME MEASURES: Cost effectiveness ratios, incremental cost effectiveness ratios, and screening options' outcomes. RESULTS: The contingent screening strategy dominated all other screening options: it had the best cost effectiveness ratio ($C26,833 per case of Down's syndrome) with fewer procedure related euploid miscarriages and unnecessary terminations (respectively, 6 and 16 per 100,000 pregnancies). It also outperformed serum screening at the second trimester. In terms of the incremental cost effectiveness ratio, contingent screening was still dominant: compared with screening based on maternal age alone, the savings were $C30,963 per additional birth with Down's syndrome averted. Contingent screening was the only screening strategy that offered early reassurance to the majority of women (77.81%) in first trimester and minimised costs by limiting retesting during the second trimester (21.05%). For the contingent and sequential screening strategies, the choice of cut-off value for risk in the first trimester test significantly affected the cost effectiveness ratios (respectively, from $C26,833 to $C37,260 and from $C35,215 to $C45,314 per case of Down's syndrome), the number of procedure related euploid miscarriages (from 6 to 46 and from 6 to 45 per 100,000 pregnancies), and the number of unnecessary terminations (from 16 to 26 and from 16 to 25 per 100,000 pregnancies). CONCLUSIONS: Contingent screening, with a first trimester cut-off value for high risk of 1 in 9, is the preferred option for prenatal screening of women for pregnancies affected by Down's syndrome.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".