External Quality Assessment of <i>HLA-B*5701</i> Reporting: An International Multicentre Survey
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: HLA-B*5701 strongly predicts abacavir hypersensitivity (HSR), but implementation of effective routine screening into clinical practice requires testing be practical and accurate. We tested the proficiency of HLA-B*5701 typing among laboratories using sequence-specific primer PCR. DESIGN AND METHODS: DNA panels (1 and 2) were distributed to seven laboratories (A to G) for blinded typing of the HLA-B*5701 allele. Panel 1 (n = 10 samples; n = 7 laboratories) included 3 positives and other closely related B17 subtypes (B*5702, B*5703, B*5704 and B*5801). Panel 2 (n = 96 samples; n = 4 laboratories) included 36 positives among a broad spectrum of other B alleles. Two laboratories (A and B) also submitted 96 routine samples, typed by the same methodology, to the reference centre for additional analysis by sequence-based typing. RESULTS: All laboratories correctly typed panel 1 for HLA-B*5701 carriage. Laboratories A, B and C identified HLA-B*5701 alleles in panel 2 with 100% sensitivity and 100% specificity. Laboratory D reported one false negative, reportedly due to a sampling error. The results obtained for routine samples typed by laboratories A and B and those generated by the reference laboratory using sequencing were fully concordant. CONCLUSIONS: Detection of HLA-B*5701 alleles among laboratories was 100% specific and 99.4% sensitive, indicating that participating HIV testing laboratories were currently offering effective primary screening to identify individuals at high risk of abacavir HSR. Accurate reporting of HLA-B*5701 status is critical for the safe administration of this drug and participation in quality assurance programmes by all sites who report HLA-B*5701 status should be promoted.
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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 | 0.003 | 0.000 |
| 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 | 0.000 | 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 it