Unraveling the genetic link: an umbrella review on HLA-B*15:02 and antiepileptic drug-induced Stevens–Johnson syndrome/toxic epidermal necrolysis
Bibliographic record
Abstract
PURPOSE: This umbrella review was conducted to summarize the association between HLA*1502 allele with antiepileptic induced Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). METHODS: Pubmed, Scopus and EMBASE were searched for eligible reviews in May 2023. Two authors independently screened titles and abstracts and assessed full-text reviews for eligibility. The quality of meta-analyses and case-control studies was appraised with Assessing the Methodological Quality of Systematic Reviews 2 and Newcastle-Ottawa Scale, respectively. Narrative summaries of each antiepileptic drug were analyzed. Preestablished protocol was registered on the International Prospective Register of Systematic Reviews Registry(ID: CRD42023403957). RESULTS: Included studies are systematic reviews, meta-analyses and case-control studies evaluating the association of HLA-B*1502 allele with the following antiepileptics. Seven meta-analyses for carbamazepine, three meta-analyses for lamotrigine (LTG), three case-control studies for oxcarbazepine, nine case-control studies for phenytoin and four case-control studies for phenobarbitone were included. The findings of this umbrella review suggest that there is a strong association between HLA-B-1502 with SJS/TEN for carbamazepine and oxcarbazepine and a milder association for lamotrigine and phenytoin. CONCLUSION: In summary, although HLA-B*1502 is less likely to be associated with phenytoin or lamotrigine-induced SJS/TEN compared to carbamazepine-induced SJS/TEN, it is a significant risk factor that if carefully screened, could potentially reduce the development of SJS/TEN. In view of potential morbidity and mortality, HLA-B*1502 testing may be beneficial in patients who are initiating lamotrigine/phenytoin therapy. However, further studies are required to examine the association of other alleles with the development of SJS/TEN and to explore the possibility of genome-wide association studies before initiation of treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.002 |
| 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".