A comprehensive update on the <i>human leukocyte antigen</i> and idiosyncratic adverse drug reactions
Bibliographic record
Abstract
Introduction Idiosyncratic adverse drug reactions (IADRs) or drug hypersensitivity reactions (DHRs) represent a major health problem because they are unpredictable and can be severe with potential life-long or even lethal consequences. Their pathophysiology is not clear but thought to be immune mediated, supported by the significant statistical association of these reactions with specific alleles of the human leukocyte antigen (HLA) gene.Area covered This comprehensive update review summarizes the currently available evidence on the role of HLA gene locus in IADRs and discusses the present understanding of the pathophysiology of IADRs. We searched the available literature in PubMed and Google Scholar with no date restriction for publications on HLA and adverse drug reactions. Findings are summarized and discussed in the context of the currently available evidence.Expert opinion The role of the immune system in IADRs and the role of pharmacogenetic testing in this field is evident. HLA genetic testing is very promising in the management of these reactions. Many obstacles seem to prevent pharmacogenetic testing to meet its full potential including cost and health care providers’ education. Further work in needed to provide more evidence and allow widespread use of pharmacogenetic testing in the clinical practice.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".