Microarray as a first genetic test in global developmental delay: a cost-effectiveness analysis
Bibliographic record
Abstract
AIM: Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with array-based comparative genomic hybridization (aCGH) would have on the total cost of the workup for GDD. METHOD: We evaluated the cost-effectiveness of aCGH compared with karyotyping by retrospectively analysing the cost of workup in a cohort of 114 children (69 males; 45 females) representing a consecutive series of children diagnosed with GDD. RESULTS: The average increase in cost if aCGH had been performed instead of karyotyping as a first test was $442 per individual when performed by a private company (98% confidence interval $238-604). In contrast, $106 (98% confidence interval -$17 to $195) would have been saved if aCGH was performed locally in a laboratory already possessing the required technology. The incremental cost per additional diagnosis was estimated to be $12,874 if aCGH was performed in a private laboratory, but <$1379 if performed locally. (Costs reported in Canadian dollars, using 2010 prices.) INTERPRETATION: aCGH would be cost-effective as a first genetic test in the clinical evaluation of individuals with GDD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".