IFN-γ ELISpot-enabled machine learning for culprit drug identification in nonimmediate drug hypersensitivity

Chongpison, Yuda; Sriswasdi, Sira; Buranapraditkun, Supranee; Thantiworasit, Pattarawat; Rerknimitr, Pawinee; Mongkolpathumrat, Pungjai; Chularojanamontri, Leena; Srinoulprasert, Yuttana; Rerkpattanapipat, Ticha; Chanprapaph, Kumutnart; Disphanurat, Wareeporn; Chakkavittumrong, Panlop; Tovanabutra, Napatra; Srisuttiyakorn, Chutika; Sukasem, Chonlaphat; Tuchinda, Papapit; Pongcharoen, Padcha; Klaewsongkram, Jettanong

doi:10.1016/j.jaci.2023.08.026

Cited by 5 publications

(2 citation statements)

References 26 publications

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“…As discussed with the patient, the ELISpot assay exhibits the highest sensitivity and specificity in cases of DRESS, with a sensitivity of 61% and specificity of 97% [ 16 ]. However, the sensitivity and specificity of the ELISpot depend on factors such as Naranjo score, drug allergy phenotype, type of suspected drug, and underlying disease, as mentioned in Chongpison et al's [ 31 ] study. The confidence score calculated by machine learning for omeprazole was 0.80 (percentage of positive challenge 68.8), while for meropenem and ceftriaxone, it was 0.15 (percentage of positive challenge around 13.1) (as Figure 3 ).…”

Section: Discussionmentioning

confidence: 99%

Omeprazole Induced Rapid Drug Reaction with Eosinophilia, Systemic Symptoms, and Cross-Reactivity in Delayed-Type Hypersensitivity Associated with Proton-Pump Inhibitors: A Case Report and Literature Review

Pinyopornpanish,

Pinyopornpanish

et al. 2024

Case Reports in Immunology

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Background. Omeprazole, a proton pump inhibitor (PPI), is a widely used and generally safe agent for treating acid-related gastrointestinal conditions. However, drug reaction with eosinophilia and systemic symptoms (DRESSs) syndrome has been reported. Objectives. To report a case of omeprazole-induced rapid DRESS syndrome and to review the literature. Methods. Descriptive analysis of one new case and a case series from literature review. Results. We report a case of 82-year-old woman presenting with rapid-onset of DRESS syndrome. The condition was initially suspected to be caused by antibiotic, but the definite diagnosis was eventually omeprazole-induced DRESS syndrome as suggested by the enzyme-linked immune absorbent spot (ELISpot) assay along with the clinical picture. Previous literatures regarding cases of PPI-induced DRESS syndrome were pooled for descriptive analysis. Among 21 PPI cases pooled, esomeprazole was the most commonly implicated PPI (52.4%), followed by pantoprazole (19.1%), and omeprazole along with lansoprazole (both 14.3%). The issue of cross-reactivities amongst PPIs remains uncertain. Nonetheless, in situations in which a PPIs are deemed necessary, a prudent approach could be considering a switch to an alternative agent with distinct chemical structure. Conclusion. PPI is commonly used safely as an agent for acid-related gastrointestinal conditions. However, PPI-induced rapid DRESS syndrome can occur, particularly with prior exposure history. ELISpot is an in vitro test, useful in identifying the culprit agent in patients with delayed-type hypersensitivity reaction.

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Section: Discussionmentioning

confidence: 99%

Omeprazole Induced Rapid Drug Reaction with Eosinophilia, Systemic Symptoms, and Cross-Reactivity in Delayed-Type Hypersensitivity Associated with Proton-Pump Inhibitors: A Case Report and Literature Review

Pinyopornpanish,

Pinyopornpanish

et al. 2024

Case Reports in Immunology

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“…Thus, a DL-based approach has shown its utility in vancomycin treatment monitoring to deal with patients suffering critical illnesses, as demonstrated by its superior performance compared to other population pharmacokinetic models [52 ▪▪ ]. Finally, another ML model has recently achieved the highest precision in predicting NIR using IFN-γ ELISpot and clinical variables [53 ▪▪ ].…”

Section: Predictive Models In Drug Allergymentioning

confidence: 99%

Predictive models and applicability of artificial intelligence-based approaches in drug allergy

Núñez,

Doña,

Cornejo-García

2024

Current Opinion in Allergy &Amp; Clinical Immunology

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Purpose of review Drug allergy is responsible for a huge burden on public healthcare systems, representing in some instances a threat for patient's life. Diagnosis is complex due to the heterogeneity of clinical phenotypes and mechanisms involved, the limitations of in vitro tests, and the associated risk to in vivo tests. Predictive models, including those using recent advances in artificial intelligence, may circumvent these drawbacks, leading to an appropriate classification of patients and improving their management in clinical settings. Recent findings Scores and predictive models to assess drug allergy development, including patient risk stratification, are scarce and usually apply logistic regression analysis. Over recent years, different methods encompassed under the general umbrella of artificial intelligence, including machine and deep learning, and artificial neural networks, are emerging as powerful tools to provide reliable and optimal models for clinical diagnosis, prediction, and precision medicine in different types of drug allergy. Summary This review provides general concepts and current evidence supporting the potential utility of predictive models and artificial intelligence branches in drug allergy diagnosis.

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The Australasian Registry for Severe Cutaneous Adverse Reactions (AUS-SCAR) – Providing a roadmap for closing the diagnostic, patient, and healthcare gaps for a group of rare drug eruptions

James,

Goh,

Vogrin

et al. 2024

World Allergy Organization Journal

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IFN-γ ELISpot-enabled machine learning for culprit drug identification in nonimmediate drug hypersensitivity

Cited by 5 publications

References 26 publications

Omeprazole Induced Rapid Drug Reaction with Eosinophilia, Systemic Symptoms, and Cross-Reactivity in Delayed-Type Hypersensitivity Associated with Proton-Pump Inhibitors: A Case Report and Literature Review

Omeprazole Induced Rapid Drug Reaction with Eosinophilia, Systemic Symptoms, and Cross-Reactivity in Delayed-Type Hypersensitivity Associated with Proton-Pump Inhibitors: A Case Report and Literature Review

Predictive models and applicability of artificial intelligence-based approaches in drug allergy

The Australasian Registry for Severe Cutaneous Adverse Reactions (AUS-SCAR) – Providing a roadmap for closing the diagnostic, patient, and healthcare gaps for a group of rare drug eruptions

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