A sensitive and rapid alternative to HLA typing as a genetic screening test for abacavir hypersensitivity syndrome
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Abacavir hypersensitivity reaction (ABC HSR) is a potentially life-threatening adverse reaction that affects approximately 8% of patients that initiate this antiretroviral drug. Independent groups have shown a strong predictive association between ABC HSR and HLA-B*5701, indicating that exclusion of HLA-B*5701 positive individuals from abacavir treatment would largely prevent ABC HSR. However, the limited availability and relatively high cost of human leukocyte antigen (HLA) typing represent barriers to the widespread implementation of this pharmacogenetic approach to abacavir prescribing. To facilitate routine screening, we have developed a rapid flow cytometry method for HLA-B57 phenotyping using commercially available B17 monoclonal antibodies. METHODS: Whole blood samples from 84 human immunodeficiency virus (HIV) patients were examined by standard flow cytometry methods, using a two-colour B17-specific immunofluorescence assay in the CD45 lymphocyte population. RESULTS: All eight HLA-B57 individuals examined tested positive, while HLA-B57/58 negative individuals (n=74) tested negative for this flow cytometry test. Two non-HLA-B57 individuals showed weak cross-reactivity. CONCLUSION: In our predominantly Caucasian population, B17/CD45 dual staining was sufficient to identify individuals carrying B17 cell surface antigens. This approach, utilizing flow cytometry methods that are widely available in HIV laboratories, therefore offers a sensitive, rapid and cost-effective screening assay prior to abacavir prescription. Following risk stratification with this assay, it would be anticipated that identification of HLA-B*5701 using molecular HLA typing methods would be required in <10% of the screened population.
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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 | 0.000 | 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