Elizabeth Phillips

Background
Seasonal variation in adverse drug reactions may reflect changes in environmental exposures, prescribing, or host susceptibility.

Objective
Evaluate seasonality and pandemic-era trends in Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN).

Methods
We performed a cross-sectional pharmacovigilance study of the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) from 2010-2023. Primary seasonality analysis used Northern Hemisphere reports with complete event dates from 2010-2019. Time series models trained on pre-pandemic data were used to generate counterfactual forecasts through December 2023 and evaluate the impact of the COVID-19 pandemic. Influenza, respiratory syncytial virus (RSV), and photosensitivity served as positive controls.

Results
Among 5,947 SJS/TEN reports, monthly and seasonal variation was not significant, and seasonality strength, assessed using Seasonal-Trend Decomposition using Loess (STL), was low (0.163). In contrast, influenza, RSV, and photosensitivity demonstrated robust seasonal patterns. During the pandemic, influenza and RSV fell substantially below forecasts, whereas SJS/TEN reporting remained near or modestly above expected levels. The magnitude of the SJS/TEN deviation was sensitive to the pre-pandemic training interval, with progressively later training windows yielding smaller observed-to-expected differences. Primary-suspect drug composition also shifted, and immune checkpoint inhibitor involvement increased substantially over time.

Conclusion
SJS/TEN demonstrated minimal seasonality despite strong seasonality in positive controls. These findings support a limited role for seasonal environmental exposures relative to host susceptibility and drug-specific risk, while highlighting the importance of evolving treatment patterns when interpreting pharmacovigilance trends. The increasing representation of ICIs among SJS/TEN reports further highlights the importance of evolving therapeutic landscapes when interpreting long-term pharmacovigilance trends.

Importance: Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe, potentially fatal hypersensitivity syndrome with 3% to 10% mortality, and lamotrigine, a first-line treatment for bipolar and seizure disorders, is among the top 5 causative agents of DRESS in the United States and globally. Commercial panels test HLA-B*15:02 and HLA-A*31:01 for risk of carbamazepine-associated severe cutaneous adverse reactions; however, these are not validated for lamotrigine-induced DRESS, and current reports from these commercial assays could therefore provide false reassurance. No HLA associations with lamotrigine-induced DRESS have been established in US populations.

Objective: To identify HLA genetic variants associated with lamotrigine-induced DRESS in a US population.

Design, Setting, and Participants: This matched case-control study was conducted at 2 US academic medical centers (Vanderbilt University Medical Center and Mass General Brigham). Patients with lamotrigine-induced DRESS confirmed by Registry of Severe Cutaneous Adverse Reactions (RegiSCAR) criteria (score ≥4) were prospectively enrolled between April 2016 and June 2025. Lamotrigine-tolerant controls were matched 10:1 from the Vanderbilt BioVU biobank on sex, self-reported race, and age. HLA typing included class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DPB1, HLA-DQA1, HLA-DQB1, and HLA-DRB1) loci for case (high-resolution typing) and control (imputed from genotyping array data) participants.

Main Outcomes and Measures HLA class I and II alleles and haplotypes were tested using logistic regression with Bonferroni correction for their association with lamotrigine-induced DRESS.

Results: This study included 29 patients with lamotrigine-induced DRESS (case participants; median [IQR] age, 33 [24-56] years; 25 female [86.2%]; 2 Asian [6.9%], 2 Black [6.9%], 23 White [79.3%], and 2 unknown race [6.9%]) and 290 matched control participants. HLA-A*32:01 was associated with lamotrigine-induced DRESS (41.4% [12 case participants] vs 4.1% [12 control participants]; odds ratio [OR], 16.4; 95% CI, 6.4-42.5; Bonferroni-corrected P < .001). No other alleles or class II loci showed significant associations after correction. The A*32:01 ~ B*44:02 haplotype was enriched (OR, 18.4; 95% CI, 4.6-83.8; Bonferroni-corrected P = .001) in lamotrigine-induced DRESS.

Conclusions and Relevance: In this case-control study, HLA-A*32:01 was associated with lamotrigine-induced DRESS in a US population. Given that HLA-A*32:01 is not included in existing commercial pharmacogenomic panels, adding this marker could improve preprescription DRESS risk identification for lamotrigine.

These updated EAACI guidelines aim to standardize skin testing methodologies for both immediate and non-immediate drug hypersensitivity reactions. For immediate reactions, the optimal testing window is 4-6 weeks post-reaction; whereas beyond 6 months, false-negative results increase. For chemotherapy-related reactions, earlier testing (within 2 weeks) remains necessary due to treatment urgency. The previously published multicenter ENDA study established the international reference method for positive immediate intradermal test reading: injection of exactly 0.02 mL with a wheal at 20 min measuring ≥ initial wheal +3 mm, representing a major standardization achievement. For patch testing, exact active ingredient concentrations must be systematically documented. When tablets are crushed and diluted at 30% in petrolatum, significant variability in final concentrations has been observed. The guidelines present validated nonirritant concentrations for major drug classes including antibiotics, contrast media, anesthetics, proton pump inhibitors, chemotherapies, and biologicals. Specific recommendations are based on negative controls demonstrating specificity, while conditional recommendations are provided when few or no negative controls are available. Risk stratification algorithms now allow direct drug provocation testing for mild maculopapular exanthema, bypassing preliminary skin tests. However, more severe reactions such as anaphylaxis require skin testing before considering drug provocation tests. For DRESS/AGEP/SJS/TEN, skin tests are useful and safe for identifying culprit drugs. These harmonized methods enable safe drug allergy delabeling while preserving diagnostic accuracy and patient safety. Strict adherence to these standardized protocols is essential to ensure reproducible results and safe clinical practice in drug hypersensitivity evaluation.

HLA class I alleles confer a striking risk for T cell–mediated drug hypersensitivity, yet positive predictive values are low—typically under 10% and as low as 0.12% for some drug–HLA pairs. We propose that persistent, human-adapted pathogens—notably herpesviruses—focus postnatal immune memory on conserved epitopes in the tissue niches where viral control occurs (the Keystone Epitope Theory). The phylogenetic basis for this proposal is that herpesviruses and their vertebrate hosts have co-adapted over hundreds of millions of years, and that this co-evolutionary relationship is replayed ontogenetically as each individual acquires these infections and builds tissue-specific immune memory. When a drug-altered self-peptide approximates the geometry of such a target and is presented by the same risk HLA in the same niche at sufficient density, pre-existing tissue-resident memory T cells (TRM) may be recruited, breaching local regulatory equilibria and driving immunopathology. We synthesize three strands of evidence: (i) heterologous immunity, in which virus-imprinted TRM cross-recognize drug-modified self; (ii) antigen presentation in the same tissue where antiviral memory already resides, which helps explain why injury is tissue-restricted; and (iii) public and private TCR solutions that bridge viral and self-targets. Beginning with T cell–mediated drug hypersensitivity as an empirical anchor, we extend this framework to EBV-associated multiple sclerosis and transplant rejection and conclude with proposed experimental validation strategies that may be applicable more broadly to T cell–mediated hypersensitivity and autoimmunity. From keystone protection to clinical misdirection. Postnatal immune focusing concentrates durable tissue-resident memory on conserved peptide–HLA targets in specific niches. Modified self-peptides (drug-altered or post-translationally modified) that approximate this geometry, presented by the same risk HLA in the same tissue, can recruit entrenched antiviral programs and, when mimicking ligand burden is sufficient, exceed local inhibitory set-points. The clinical result is high NPV but low PPV for HLA risk alleles. Abbreviations: TRM, tissue-resident memory T cell; PTM, post-translational modification.

As the original authors of the PEN-FAST penicillin allergy clinical decision rule,1 we have received frequent questions since publication regarding its applicability across certain patient populations and penicillin allergy phenotypes. PEN-FAST is a validated clinical decision rule that uses 4 criteria to identify low-risk penicillin allergy phenotypes that may be eligible for evaluation with direct penicillin challenge without prior skin testing. With a scoring range of 0 to 5, a PEN-FAST score of less than 3 is used to identify low-risk allergy phenotypes. Despite global implementation among broad stakeholder groups2 and external validation in immediate hypersensitivity3,4 and specialty populations (eg, pregnancy), clinicians ask whether PEN-FAST retains its negative predictive value (NPV) in immunocompromised hosts, older adults, and delayed (nonimmediate) reactions.

To address these clinical questions, we performed subgroup analyses based on age, immune status, and reaction phenotype using the PEN-FAST development cohort published in JAMA Internal Medicine.1 In brief, the initial PEN-FAST was developed to identify predictors of positive allergy testing results in a prospective cohort of 622 participants (development cohort) and externally validated in 3 retrospective data sets from independent international clinical sites. Using the same development cohort, we have now performed additional subgroup analyses evaluating the distribution of PEN-FAST scores and its diagnostic performance within each subgroup. This includes sensitivity, specificity, positive and negative predictive values, and area under receiver-operating characteristics curve, using a cutoff of less than 3 to classify as low risk as suggested in the main study. Performance was compared between subgroups using Fisher exact test and χ2 test. All results are reported with 95% CI. Analysis was performed using Stata 18 (StataCorp LLC, College Station, Tex).

Importance Antiepileptic drugs (AEDs) are frequently implicated in Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), which are the most severe type of drug hypersensitivity reaction, with a mortality rate up to 50%. However, the overall proportion of these cases attributed to AEDs has not been systematically reviewed. Objective To evaluate the proportion of AED-associated SJS/TEN. Data Sources The MEDLINE and Embase databases were searched from inception through March 17, 2026, with results limited to English-language publications and human participants. Study Selection All experimental and observational studies that reported patient-level triggers of SJS/TEN were included. Data Extraction and Synthesis Two reviewers independently screened studies and extracted data using a predefined template. To estimate the proportion of AED-associated SJS/TEN, a random-effects meta-analysis was performed, calculating the pooled proportions with 95% CIs. Subgroup analyses by age group (children vs adults) and geographic region were performed to explore heterogeneity. Main Outcomes and Measures To estimate the proportion of AED-associated SJS/TEN. Results This systematic review and meta-analysis included 50 studies with 4403 patients that reported patient-level triggers of SJS/TEN. Single-drug triggers accounted for 88% (95% CI, 83-92) of cases. The pooled proportion of SJS/TEN cases attributed to AEDs was 23% (95% CI, 19-26). Nearly all AED-associated cases were due to aromatic AEDs (96%; 95% CI, 92-99), most commonly carbamazepine (39%; 95% CI, 29-50), followed by phenytoin (19%; 95% CI, 11-28), and lamotrigine (15%; 95% CI, 8-22). Nonaromatic AEDs were rarely implicated (2%; 95% CI, 0-4). Significant geographic variation was observed in the proportion of AED-associated SJS/TEN, ranging from 42% (95% CI, 26-59) in West Asia to 10% (95% CI, 0-33) in Africa (P < .001). The proportion of AED-associated SJS/TEN cases was significantly higher in children (35%; 95% CI, 22-48) than in adults (23%; 95% CI, 20-27). Conclusions and Relevance In this systematic review and meta-analysis of observational studies, AEDs accounted for nearly one-quarter of SJS/TEN cases reported worldwide, predominantly involving aromatic AEDs, such as carbamazepine, phenytoin, and lamotrigine. These findings suggest aromatic AEDs as leading contributors to SJS/TEN and support the preferential use of nonaromatic AEDs when clinically appropriate.

Background
Inaccurate multiple antibiotic allergy labels to first-line agents (penicillins, cephalosporins, and sulfonamides) restrict optimal therapy and often require sequential evaluations across multiple visits, delaying delabeling and increasing loss to follow-up.

Objective
To conduct a comparative effectiveness study of the Multiple Antibiotic Allergy Evaluation Strategy (MAAES), comparing its effectiveness, safety, and patient-reported outcomes (PRO) to traditional sequential evaluation (non-MAAES).

Methods
This retrospective cohort study (2014–2024) compared same-day multi-antibiotic testing (MAAES) with non-MAAES in patients with ≥2 low-risk labels. Multivariable regression adjusted for baseline differences and testing era. Inverse probability of treatment weighting (IPTW) and a restricted post-2020 subcohort analysis addressed selection bias and temporal shifts. Outcomes included delabeling efficacy, time to complete delabeling, loss to follow-up, relabeling, adverse events (AEs), and PRO.

Results
Baseline differences were present between the MAAES and non-MAAES groups, including penicillin anaphylaxis (1.4%vs.6.6%, p=0.002), angioedema (12.4%vs.19.1%, p=0.049), maculopapular rash (13.1%vs.24.3%, p=0.002), and unknown sulfonamide history (9.5%vs.3.7%, p=0.03). MAAES removed 97.4% of labels vs 79.6% for non-MAAES (adjusted odds ratio(aOR) 9.41, 95%CI 5.22-16.95, p<0.001). MAAES achieved faster complete delabeling (log-rank χ2=42.4, p<0.001), with 84.9%vs.21.1% delabeled at the initial visit (restricted mean survival time difference: 2.1 months). Results remained robust in post-2020 and IPTW models. Loss to follow-up (1.3%vs.17.2%; aOR 0.06, 95%CI 0.03–0.13; p<0.001) and AEs (<1%vs.2.8%; aOR 0.26, 95%CI 0.09–0.78; p=0.02) were significantly lower with MAAES. Favorable PRO was sustained, with no significant differences between groups.

Conclusions
A consolidated multi-drug evaluation strategy substantially improves effectiveness of first-line antibiotic allergy delabeling while maintaining excellent safety profiles and PRO.

Paramyxoviruses comprise a diverse family of viruses that threaten global human health through direct infection and zoonotic transmission. Understanding adaptive immune responses to these viruses is critical for characterizing host-pathogen interactions and evaluating vaccine performance. Here, we systematically map human CD4+ T cell epitopes across Nipah and measles viruses, two prototypic members of the Paramyxoviridae family. We identify broad epitope repertoires, including 186 Nipah and 288 measles epitopes recognized in multiple donors. Epitopes are characterized for HLA binding and inferred restrictions, and broader HLA binding correlates with immunodominance. We observe overlapping T cell targets between viruses, with N and F proteins immunodominant in both and L additionally dominant in Nipah. We define conserved T cell epitope regions (CTERs) in Nipah virus that encompass 17% of the proteome, capture over 50% of T cell responses, show high conservation across different Henipaviruses, and elicit broadly cross-reactivity, supporting broad population coverage.
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•Systematic mapping reveals broad CD4+ T cell epitopes in Nipah and measles•HLA binding promiscuity correlates with epitope immunodominance•Conserved T cell epitope regions (CTERs) capture over 50% of Nipah T cell responses•CTERs elicit cross-reactive T cells across diverse Paramyxoviruses
Tarke et al. systematically map CD4+ T cell epitopes in measles and Nipah viruses, revealing broad and overlapping immune targets. They define conserved T cell epitope regions (CTERs) that drive cross-reactive T cell responses across Paramyxoviruses, providing a framework for vaccine strategies that enhance population coverage and pandemic preparedness.

Large language models (LLMs) have emerged as transformative technologies, revolutionising natural language understanding and generation across various domains, including medicine. In this study, we investigated the capabilities, limitations, and generalisability of Generative Pre-trained Transformer (GPT) models in analysing unstructured patient notes from large healthcare datasets to identify immune-related adverse events (irAEs) associated with the use of immune checkpoint inhibitor (ICI) therapy.
We evaluated the performance of GPT-3.5, GPT-4, and GPT-4o models on manually annotated datasets of patients receiving ICI therapy, sampled from two electronic health record (EHR) systems and seven clinical trials. A zero-shot prompt was designed to exhaustively identify irAEs at both the patient level (main analysis) and the note level (secondary analysis). The LLM-based system followed a multi-label classification approach to identify any combination of irAEs associated with individual patients or clinical notes. System evaluation was conducted for each available irAE as well as for broader categories of irAEs classified at the organ level.
Our analysis included 442 patients across three institutions. The most common irAEs manually identified in the patient datasets included pneumonitis (N = 64), colitis (N = 56), rash (N = 32), and hepatitis (N = 28). The GPT models demonstrated generalisable abilities in identifying irAEs across EHRs and clinical trial reports. Overall, the models achieved relatively high sensitivity and specificity but only moderate positive predictive values, reflecting a potential bias towards overpredicting irAE outcomes. GPT-4o achieved the highest F1 and micro-averaged F1 scores for both patient-level and note-level evaluations. Highest performance was observed in the haematological (F1 range = 1.0–1.0), gastrointestinal (F1 range = 0.81–0.85), and musculoskeletal and rheumatologic (F1 range = 0.67–1.0) irAE categories. Error analysis uncovered substantial limitations of GPT models in handling textual causation, where adverse events should not only be accurately identified in clinical text but also causally linked to immune checkpoint inhibitors.
This study demonstrated that GPT models can automate the detection of immune related adverse events in varied healthcare datasets, reducing the burden on physicians and other healthcare professionals by limiting the need for manual review. This capability will accelerate the generation of safety insights across large healthcare datasets and facilitate the characterisation of patient-level drivers of toxicities, thus enhancing safety monitoring and ultimately improving patient care.
National Institutes of Health, Roche, National Health and Medical Research Council of Australia, Stevens-Johnson Syndrome Foundation, Angela Anderson Research Fund, Larry L Hillblom Foundation and UCSF Research Allocation Program.

A label of betalactam (BL) allergy is estimated in around 10% of the population in their medical records. Second-line choices carry significant negative consequences, including reduced efficacy, effectiveness, and safety. This study aimed to develop a new highly specific score constructed by selecting variables assisted by artificial intelligence to identify low-risk BL-allergic patients.
In this study, derivation and validation of the BL-predictor score were performed on a retrospective cohort of 2207 patients who underwent penicillin allergy testing at Málaga University Hospital (Spain). The development of the BL-predictor encompassed expert drafting and a two-step variable selection process consisting of univariate analysis and variable filtering, followed by stepwise logistic regression with resampling. To assess the efficiency, a multicentric retrospective external validation was performed in 4261 patients from six populations: Salamanca and Madrid, Spain; Nashville, United States of America; Verona, Italy; Paris, France; and Copenhagen, Denmark.
The definitive questionnaire consisted of eight items and risk points were computed from the logistic regression model as follows: +1 for reactions after first dose or in less than 1 h (ITEM-1), +2 for anaphylaxis (ITEM-2); +1 for previous reaction with the culprit (ITEM-3); -1 for resolution in > 24 h (ITEM-4); +2 for spontaneous resolution (ITEM-5); -2 for unknown symptoms (ITEM-6); -2 for reaction occurred > 5 years (ITEM-7), and -1 for another reported drug allergy (ITEM-8). After establishing a threshold of ≤ 0 points to classify individuals with low risk, internal validation showed a specificity of 86% and a negative predictive value (NPV) of 83%. Overall multicenter external validation showed a specificity of 93%, which implies a 25% increase in specificity compared to the previously published BL decision tool.
This score would simplify diagnostic procedures in low-risk patients, enabling rapid delabeling, potentially in non-specialty settings, and reducing diagnostic costs and the negative consequences associated with incorrect antibiotic allergy labels.