Journal of Allergy and Clinical Immunology-In Practice最新文献

Background: Beta-lactam (BL) allergy work-up varies across studies due to methodological heterogeneity, which affects the estimated risk of BL resensitization after a negative allergy test. Consequently, controversy remains regarding recommendations for retesting.

Objective: This systematic review and meta-analysis aimed to quantify the prevalence, severity, and determinants of BL resensitization to support safe and individualized retesting strategies.

Methods: PubMed, EMBASE, Scopus, and CINAHL were searched from inception to August 4, 2024, in accordance with PRISMA. Eligible studies enrolled patients with documented BL allergy who achieved a negative initial standard evaluation (NISE) confirming tolerance and subsequently underwent retesting. Random-effects models generated pooled prevalence with 95% confidence intervals; subgroup analyses examined retest modality, reaction chronology, geography, and age. The strength of evidence was graded with GRADE.

Results: Thirty-two studies comprising 5,766 retests met eligibility criteria. The overall pooled resensitization rate was 3.80% (95% CI, 2.35-5.50; I² = 82.96%). Limiting to studies using sequential or direct drug provocation test (DPT) across 3,414 retesting evaluations, the resensitization rate was 2.44% (95% CI: 0.99-4.43; I²=86.08%), equivalent to 1 case detected per 41 retests. Severe reactions during retesting with these methods occurred at a rate of 0.32%; 95% CI, 0.18-0.58; I² = 0.0%). The overall strength of evidence for resensitization prevalence was graded as low.

Conclusions: In DPT-based studies, the pooled resensitization risk was low (approximately 1-4%) with substantial heterogeneity. Serious reactions during retesting were very rare. These findings do not support routine retesting after a negative evaluation, as the observed risk is in the range of de novo beta-lactam reactions in the general population.

Food allergy affects approximately 8% of children and 11% of adults in the United States. Available treatments, including oral immunotherapy and anti-IgE, are not known to lead to remission. There is now increasing evidence implicating the gut microbiome as a key regulator of allergic inflammation. Distinct microbial and metabolomic alterations characterize food-allergic individuals, and gnotobiotic mouse models show that fecal microbiota from food-allergic donors transfer allergic sensitization, whereas microbiota from healthy donors protect from anaphylaxis through induction of tolerogenic Foxp3⁺RORγt⁺ regulatory T cells (Tregs). Goblet cell-derived resistin-like molecule beta induces food allergy through modulation of the gut microbiome and depletion of indole-producing species. These findings have inspired the development of 5 microbial therapeutic approaches: probiotics, rationally defined bacterial consortia, fecal microbiota transplantation, metabolite-based approaches, and biologics targeting dysbiosis-associated pathways. Early-phase clinical studies support feasibility, yet long-term safety, durability, and reproducibility remain uncertain. Major challenges include interindividual variability, ecological complexity, and regulatory standardization. Microbiome-directed therapeutics hold promise to transform food allergy management from temporary desensitization toward remission and durable immune tolerance. The application of systems biology approaches integrating metabolomics, transcriptomics, and immune phenotyping will be essential to unravel the complex host-microbial interactions that underlie the efficacy of these approaches.

Background: The impact of treatable traits on clinical remission in asthma remains unclear, despite their recognition as potential therapeutic targets for personalized care.

Objective: This study investigated the association between treatable traits and clinical remission in asthma and identified specific traits influencing remission rates.

Methods: A multicenter, cross-sectional questionnaire survey was conducted at 26 centers in Japan between September and November 2021. Clinical remission was defined as an Asthma Control Test score ≥20, a forced expiratory volume in one second of at least 80%, no exacerbations, no oral corticosteroid use over the past year. Assessed treatable traits included a peripheral blood eosinophil count ≥300/μL, fractional exhaled nitric oxide ≥25 ppb, systemic allergic inflammation, obesity, depression, dysfunctional breathing, and current smoking.

Results: Among 2,154 participants, 1,350 were included in the final analysis, while 679 patients with missing data and 125 using biologics were excluded. The median number of treatable traits per patient was two. Clinical remission rates decreased significantly as the number of treatable traits increased (p<0.05, Cochran-Armitage test). Logistic regression identified the number of treatable traits as an independent risk factor for remission (odds ratio: 0.685, p<0.001). Peripheral blood eosinophil count, elevated fractional exhaled nitric oxide, and depression were also independent risk factors (odds ratio: 0.622, 0.617, 0.340, respectively; p <0.05).

Conclusion: In patients with non-biologic-treated bronchial asthma, a higher number of treatable traits was associated with lower clinical remission rates. Targeted treatment for type 2 inflammation and supportive care for depression may improve remission outcomes.

Background: Patients with asthma and elevated BMI have higher baseline exacerbation risk and vulnerability to corticosteroid adverse effects. Yet evidence on the utilization and efficacy of respiratory biologics, which reduce these risks, in patients with obesity is lacking.

Objective: To test the hypothesis that respiratory biologics are underutilized in eligible patients with obesity.

Methods: This is a retrospective observational analysis of adult patients with active, moderate-to-severe asthma, with BMI≥25kg/m² in the electronic health records of a large U.S. health system (2018-2023). We included patients meeting FDA-specified eligibility criteria. Primary outcomes were biologic prescription and time-to-prescription. Secondary outcomes were change in exacerbation rates and factors associated with biologic prescription. Exploratory outcomes were biologic eligibility using obesity-adjusted eosinophil counts (≥96cells/μL), and utilization compared to a healthy weight cohort.

Results: We included 5805 patients with asthma and overweight or obesity who were biologic- eligible. Of these, 11.9% were prescribed biologics. Of the biologic-eligible cohort, 59.8% had obesity and 10.4% of those patients were prescribed biologics. In adjusted analyses, obesity reduced prescription odds and time to initiation. Subspecialist care was the strongest prescription predictor. Annualized exacerbation rates significantly declined across T2-biologics users with obesity. Use of obesity-adjusted eosinophil criteria expanded biologics eligibility by 11.3% without clear exacerbation benefit.

Conclusion: Only a fraction of eligible patients with asthma and comorbid obesity receive biologics despite meeting T2 biomarker criteria, compared to patients with overweight or healthy weight. These data may substantially inform health services research and therapeutic interventions to improve asthma management.

Background: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pretest risk stratification may improve the safety and efficiency of drug provocation testing.

Objective: To develop a clinically interpretable risk stratification tool (nomogram + simplified score) for pediatric paracetamol and/or other NSAID hypersensitivity and to validate its performance against machine learning (ML) models.

Methods: We conducted a retrospective cohort study (2014-2025) of children evaluated for suspected paracetamol and/or other NSAID hypersensitivity. Analyses used the index reaction as the unit, classifying definitive outcomes as NSAID-hypersensitive or NSAID-tolerant. Independent predictors from multivariable logistic regression were used to develop a clinically interpretable risk stratification tool, implemented as a nomogram and a simplified point-based score. were trained. Eight ML models were trained using fivefold cross-validation under three data scenarios (original, matched, and Synthetic Minority Oversampling Technique for Nominal and Continuous Variables).

Results: Among 507 index reactions (from 487 children) evaluated for suspected paracetamol and/or other NSAID hypersensitivity, 90 of 507 (17.7%) had confirmed hypersensitivity. Independent predictors were age 82.5 months or older at the time of reaction, coexisting asthma and/or allergic rhinitis, latency between exposure and symptom onset of 60 minutes or less, having angioedema, respiratory symptoms, and hypotension or syncope during the index reaction. The nomogram and simplified point-based score showed strong discrimination (receiver operating characteristic [ROC] area under the curve [AUC] = 0.877) and bedside applicability. After class balancing (Synthetic Minority Oversampling Technique for Nominal and Continuous Variables), ensemble ML achieved top performance: gradient boosting ROC AUC = 0.955, recall = 0.895, and F1 = 0.896; random forest ROC AUC = 0.953, recall = 0.890, and F1 = 0.883; and AdaBoost ROC AUC = 0.940, recall = 0.873, and F1 = 0.874.

Conclusion: The nomogram and simplified point-based score provide practical pre-drug provocation testing risk stratification for children evaluated for suspected paracetamol and/or other NSAID hypersensitivity. Ensemble ML can complement the tool by improving sensitivity to minimize false negatives. Multicenter external validation and prospective impact studies are warranted before clinical implementation.

Background: The specific inhalation challenge (SIC) is the reference standard for diagnosing occupational asthma (OA) but is not widely used globally.

Objective: We aimed to develop a more practical clinical model to diagnose OA in workers exposed to low-molecular-weight (LMW) agents.

Methods: We conducted a diagnostic study using clinical interview variables and non-SIC tests as predictors. OA was defined by positive SIC. Retrospective data from Quebec and British Columbia were used to develop logistic models. External validation included centers with routine SIC (Finland, Poland) and expert-confirmed OA (Ontario, Turkey, England).

Results: The clinical interview model included male sex, isocyanate exposure, work-related rhinoconjunctivitis, smoking status, and exposure duration <10 years. The clinical interview model can correctly discriminate a positive from a negative SIC in 65% of the cases (AUC=0.65). Adding diagnostic tests to the clinical interview model improved the AUC to 0.73 for the nonspecific bronchial hyperreactivity (NSBHR), 0.80 for the serial peak expiratory flow (PEF), and 0.81 for NSBHR plus serial PEF. Combining the clinical interview with serial PEF was the model of choice, showing strong internal validity (shrinkage 0.93) and adequate calibration (Hosmer-Lemeshow p>0.05). In Finland/Poland, AUCs were 0.61 for the clinical interview alone and 0.72 with serial PEF; in England, 0.73 and 0.81; and in Ontario/Turkey, 0.60 and 0.68, respectively. Calibration was adequate in all centers.

Conclusion: A novel model, comprising clinical features and serial PEFs, can predict positive SIC caused by LMW agents. It can guide referrals or diagnosis when SIC is unavailable or unnecessary.

Background: Dupilumab is approved for moderate-to-severe asthma with an eosinophilic phenotype in the United States (US) and for severe asthma with type 2 inflammation in ex-US countries. Tezepelumab is globally approved for severe asthma. However, their long-term relative efficacy is unknown.

Objective: To estimate the long-term relative efficacy of dupilumab versus tezepelumab using an unanchored matching-adjusted indirect comparison.

Methods: Individual patient data for dupilumab from TRAVERSE (N=1,368) and associated parent randomized controlled trials (RCTs) were re-weighted to match aggregate tezepelumab data from DESTINATION (N=475) and associated parent RCTs for prognostic factors and treatment effect modifiers. Outcomes included annualized exacerbation rate (AER) of all asthma exacerbations, AER of asthma exacerbations leading to hospitalization and/or emergency room (ER) visits (baseline of RCTs until the end of TRAVERSE/DESTINATION), and change from baseline (CFB) in pre-bronchodilator forced expiratory volume in 1s (pre-BD FEV₁) (baseline of RCTs to Week 100/104). Sensitivity analysis (SA) explored key characteristics from the primary analysis.

Results: Dupilumab demonstrated a significantly lower AER of all asthma exacerbations (mean difference [MD]: -0.269, 95%CI: -0.372; -0.166, p<0.0001) and a comparable AER of asthma exacerbations leading to hospitalization and/or ER visits (MD: 0.006, 95%CI: -0.016; 0.027, p=0.62) compared with tezepelumab. Dupilumab exhibited numerically greater improvement in pre-BD FEV₁ (MD: -0.064L, 95%CI: -0.132; 0.005, p=0.07), with a significantly higher CFB in SA (MD: -0.153L; 95%CI: -0.207; -0.099, p<0.0001).

Conclusion: In the matched cohort, long-term dupilumab treatment resulted in a lower AER of all asthma exacerbations relative to tezepelumab, with lung function improvements observed in SA.

Background: There is no consensus on the approach to maintenance oral corticosteroid (mOCS) withdrawal in severe asthma (SA) in the presence of hypothalamic-pituitary-adrenal-axis (HPA-axis) suppression.

Objectives: To identify the prevalence of persistent HPA-axis suppression after long-term follow-up and factors that predictively correlate to persistent HPA-axis suppression. The secondary objective is to validate the morning cortisol cut points using short synacthen test (SST) results and evaluate the use of dynamic testing.

Methods: Retrospective analysis was carried out on data from Northern Ireland patients registered to the United Kingdom Severe Asthma Registry (UKSAR).

Results: At baseline, 83% (95%CI 76-88%, 149/180) of the cohort demonstrated adrenal insufficiency. After a median test time of 58.5 (33.5-78.5) months, 48/180 (27%) had persistent adrenal insufficiency and of these, 32/48 (66.7%) had complete adrenal insufficiency. Of those with adrenal insufficiency at baseline, 68% (95%CI 60-75%, 101/149) achieved HPA-axis recovery. Median time from baseline to most recent test in those who recovered was 21 (6-40) months. Those with persistent adrenal insufficiency had a significantly lower baseline cortisol than those who achieved HPA-axis recovery. (43nmol/L(1.56 μg/dL) (IQR 21.5-105nmol/L) vs 165nmol/L(5.98 μg/dL) (IQR 77-222nmol/L),p<0.0001).

Conclusion: A proportion of patients with severe asthma withdrawing from mOCS will have persistent adrenal insufficiency. These patients are asymptomatic and if not identified through serial biochemical assessment, will be at risk of harm. This data also has implications for other diseases treated with long-term OCS.