Attitudes of caregivers of children labeled with drug allergy after delabeling by provocation tests
Jul 1, 2026·
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Şeyma Kaya Ağargün
Besim Fazil Agargun
Ayşe Süleyman
Sophia Tsabouri
Zeynep Ülker Altınel
Cevdet Ozdemir
Abstract
Mislabeling children as drug-allergic leads to suboptimal, costly, and potentially harmful treatments. Although drug provocation tests (DPTs) are the gold standard for excluding drug hypersensitivity, the impact of these interventions on caregivers’ willingness to reuse delabeled drugs remains elusive. We evaluated DPT outcomes and post-DPT drug use and caregiver attitudes in pediatric patients. We analyzed children who underwent DPTs for suspected drug allergy at a tertiary pediatric allergy center between January 2019 and June 2023. Demographic and clinical data were reviewed, and caregivers were contacted ≥6 months after DPT to assess subsequent drug use and concerns. A total of 254 DPTs were performed in 198 children (55.1% male; median age: 58 months). Drug allergy was confirmed in 25.3% of patients (50/198), corresponding to 22.0% of tests (56/254). Among 162 negative DPTs with follow-up, the suspected drug was reused in 56.8% of cases; 92.4% were tolerated while 7.6% resulted in mild reactions. Multivariable logistic regression identified predictors of drug reuse: paracetamol (aOR: 7.40; 95% CI: 1.73-31.63; p = .007), concomitant allergic disease (aOR: 2.51; 95% CI: 1.12-5.64; p = .026), self-referral (aOR: 3.81; 95% CI: 1.12-12.95; p = .032), and younger age (aOR per month: 0.99; 95% CI: 0.98-1.00; p = .017). Anaphylaxis at index reaction was associated with reduced reuse likelihood (aOR: 0.21; 95% CI: 0.06-0.76; p = .018). Despite negative DPT results, almost half of caregivers did not reuse the suspected drug, mostly due to fear or miscommunication. These findings highlight the importance of post-DPT education and structured follow-up to optimize delabeling outcomes.
Type
Publication
Pediatric Allergy and Immunology

Authors
Gastroenterology Fellow
Gastroenterology and hepatology fellow at Istanbul University, Istanbul Faculty of Medicine.
My clinical work centres on inflammatory bowel disease and diagnostic and therapeutic endoscopy;
my research combines real-world cohorts with natural-language processing and AI-assisted analytics —
including an NLP programme over more than 11,000 colonoscopy reports and the ELASTIBD transient
elastography study of liver fibrosis and steatosis in IBD. I am also a PhD candidate in clinical trials.