Unravelling the Genetic Link: An Umbrella Review on HLA-B∗15:02 and Anti-Epileptic Drug-induced Stevens–Johnson Syndrome / Toxic Epidermal Necrolysis
Bibliographic record
Abstract
Abstract Purpose This umbrella review was conducted to summarize the evidence between association between HLA*1502 allele with various antiepileptic induced Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Methods Pubmed, Scopus and EMBASE were searched for eligible reviews in May 2023. Study was registered in PROSPERO. Two authors independently screened titles and abstracts and assessed full-text reviews for eligibility. The quality of meta-analyses was appraised with AMSTAR-2 and the quality of case control studies were appraised with Newcastle- Ottawa Scale (NOS). Narrative summaries of each anti-epileptic drug were analysed. Pre-established protocol was registered on the International Prospective Register of Systematic Reviews database (ID: CRD42023403957). Results Included studies are meta-analyses and case control studies evaluating the association of HLA-B*1502 allele with the following antiepileptics: 7 meta-analyses for Carbamazepine (CBZ), 3 meta-analyses for Lamotrigine (LTG), 3 case-control studies for Oxcarbazepine (OXC), 9 case-control studies Phenytoin (PHT) and 4 case-control studies study for Phenobarbitone. The findings of this umbrella review suggest that there is strong association between HLA B-1502 with SJS/TEN for Carbamazepine and Oxcarbazepine and a milder association for Lamotrigine and Phenytoin. Conclusions 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 which if carefully screened could potentially reduce 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 development of SJS/TEN and to explore the possibility of genome-wide association studies prior to initiation of treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".