Toward Optimal Detection of the Common Prenatal Aneuploidies by Quantitative Fluorescent-Polymerase Chain Reaction: Comparison of Two Commercial Assays
Bibliographic record
Abstract
BACKGROUND/AIM: To evaluate and compare the performance of the recently released Aneufast™ v2 (MolgentixSL) and QST*RplusV2 commercial assays (Gen-Probe), both designed for the quantitative fluorescent-polymerase chain reaction (PCR) detection of the common aneuploidies during pregnancy. METHODS: A series of 160 consecutive fetal samples referred for rapid aneuploidy detection testing and an additional 25 samples enriched for the presence of an abnormality were selected for comparison. RESULTS: To confidently rule out a chromosome abnormality, a second round of short tandem repeat typing was required for 14.1% (26) and 9.7% (18) of the specimens analyzed with Aneufast v2 and QST*RplusV2, respectively. Reflex testing was required for 7.6% (14) and 5.9% (11) of the specimens analyzed with respective assays to confidently rule out an autosomal trisomy. For the sex chromosomes, the difference in the amount of follow-up testing is greater between the assays, as a result of the inclusion in the initial PCR of the TAF9L paralogous marker in the QST*RplusV2 assay. CONCLUSIONS: Overall, both assays performed similarly in the detection of aneuploidies. In this sample set, the QST*RplusV2 kit required less frequent reflex testing, which translates into shorter turnaround time and cost savings. The incorporation of the TAF9L paralogous sequence in the initial PCR is advantageous for diagnostic use.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".