Causative drugs for drug-induced cutaneous reactions in central China: a 608-case analysis

Zhao, Jun; Hu, Lei; Zhang, Lihua; Zhou, Maojun; Gao, Lichen; Cheng, Lin

doi:10.1016/j.abd.2019.01.007

Cited by 16 publications

(18 citation statements)

References 20 publications

(19 reference statements)

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“…For example, using a highly sensitive method first may capture the most true positive cases (eg, algorithmic approach), followed by a highly specific method to rule out the greatest number of true negatives (eg., probabilistic method). 3,30,31 Investigations: Lab-Based, Pharmacogenomic and Confirmatory Testing…”

Section: Causality Assessment Methodsmentioning

confidence: 99%

Methods for Identifying Culprit Drugs in Cutaneous Drug Eruptions: A Scoping Review

et al. 2021

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Background Cutaneous drug eruptions are a significant source of morbidity, mortality, and cost to the healthcare system. Identifying the culprit drug is essential; however, despite numerous methods being published, there are no consensus guidelines. Objectives Conduct a scoping review to identify all published methods of culprit drug identification for cutaneous drug eruptions, compare the methods, and generate hypotheses for future causality assessment studies. Eligibility criteria Peer-reviewed publications involving culprit drug identification methods. Sources of evidence Medline, Embase, and Cochrane Central Register of Controlled Trials. Charting methods Registered PRISMA-ScR format protocol on Open Science Forum. Results In total, 109 studies and 26 reviews were included comprising 656,635 adverse drug events, most of which were cutaneous. There were 54 methods of culprit drug identification published, categorized as algorithms, probabilistic approaches, and expert judgment. Algorithms had higher sensitivity and positive predictive value, but lower specificity and negative predictive value. Probabilistic approaches had lower sensitivity and positive predictive value, but higher specificity and negative predictive value. Expert judgment was subjective, less reproducible, but the most frequently used to validate other methods. Studies suggest that greater accuracy may be achieved by specifically assessing cutaneous drug eruptions and using combinations of causality assessment categories. Conclusions Culprit drug identification for adverse drug reactions remains a challenge. Many methods have been published, but there are no consensus guidelines. Using causality assessment methods specifically for cutaneous drug eruptions and combining aspects of the different causality assessment categories may improve efficacy. Further studies are needed to validate this hypothesis.

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Section: Causality Assessment Methodsmentioning

confidence: 99%

Methods for Identifying Culprit Drugs in Cutaneous Drug Eruptions: A Scoping Review

et al. 2021

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“…3 Obat penyebab tersering adalah obat antiinflamasi nonsteroid (OAINS), 4,5 golongan sulfa, 6,7 antibiotik laktam, antikonvulsan (misalnya karbamazepin, fenobarbital, dan fenitoin), antiretrovirus, agen kontras, alopurinol, dan lainlain. 8,9 Kerusakan jaringan pada NE terjadi akibat apoptosis sel keratinosit yang diinduksi oleh stimulus stres, kerusakan DNA, dan sitokin intraselular. 2,3 Insidens terjadinya SSJ diperkirakan 1-6,5 kasus per juta orang per tahun.…”

Section: Pendahuluanunclassified

Faktor Risiko Prediktor Bakteremia pada Pasien Nekrolisis Epidermal: Evidence-Based Case Report

Anindya¹,

Muhammad²,

Budianti³

2022

J. Kdokt Meditek

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Nekrolisis epidermal (NE) yang terbagi atas Sindrom Stevens-Johnson (SSJ) dan nekrolisis epidermal toksik (NET) merupakan reaksi simpang obat berat dengan mortalitas tinggi. Penyebab kematian terbanyak pada NE adalah sepsis, namun gejala sepsis tidak spesifik pada NE dan hasil kultur darah membutuhkan waktu lama. Oleh karena itu penting mengetahui prediktor yang berpengaruh terhadap peningkatan risiko bakteremia pada pasien dengan NE. Evidence-based case report ini bertujuan mengetahui faktor prediktor terjadinya bakteremia pada pasien NE berdasarkan literatur. Pencarian artikel menggunakan basis data PubMed, Cochrane, dan Scopus yang relevan dengan pertanyaan klinis untuk kemudian ditelaah. Didapatkan dua artikel kohort yang sesuai. Studi Koh dkk. mendapatkan tiga prediktor yang berpengaruh terhadap kejadian bakteremia pada pasien NE; yaitu hemoglobin ≤ 10 g/dL (odds ratio [OR] 2,4; interval kepercayaan [IK] 95% 2,2-2,6), luas epidermolisis ≥ 10% (OR 14,3; IK 95% 13,4-15,2) dan penyakit komorbid kardiovaskular (OR 2,1; IK 95% 2,0-2,3). Studi De Prost dkk. mendapatkan tiga prediktor yaitu usia > 40 tahun (hazard ratio [HR] 2,5; IK 95% 1,35-4,63), leukosit > 10.000/mm3 (HR 1,9; IK 95% 0,96-3,61), serta LPB ≥ 30% (HR 2,5; IK 95% 1,13-5,47). Epidermolisis yang lebih luas merupakan faktor prediktor terjadinya bakteremia pada NE di kedua studi. Faktor risiko lainnya memerlukan penelitian lebih lanjut.

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“…A study by Yampayon et al reported that omeprazole comedication was strongly associated with phenytoininduced DRESS in Thai patients [59]. A study by Zhao et al showed that patients taking multiple-drug combinations and with a complex medication history, which greatly contributed to the development of SCARs [64]. The use of multiple drugs results in the accumulation of drugs, reactive metabolites, and drug interaction because of excessive demands on enzyme systems for oxidation or acetylation of multiple drugs [65].…”

Section: Non-genetic Factors For Scarsmentioning

confidence: 99%

GenotypingHLAalleles to predict the development of Severe cutaneous adverse drug reactions (SCARs): state-of-the-art

Jantararoungtong

Tempark

Koomdee

et al. 2021

Expert Opinion on Drug Metabolism & Toxicology

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Introduction: Pharmacogenomics has great potential in reducing drug-induced severe cutaneous adverse drug reactions (SCARs). Pharmacogenomic studies have revealed an association between HLA genes and SCARs including acute generalized exanthematous pustulosis (AGEP), drug reaction with eosinophilia and systemic symptoms (DRESS), Stevens-Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN). Areas covered: Pharmacogenomics-guided therapy could prevent severe drug hypersensitivity reactions. The US Food and Drug Administration (FDA), Clinical Pharmacogenetics Implementation Consortium (CPIC), and Dutch Pharmacogenetics Working Group (DPWG) provided guidelines in the translation of clinically relevant and evidence-based SCARs pharmacogenomics research into clinical practice. In this review, we intended to summarize the significant HLA alleles associated with SCARs induced by different drugs in different populations. We also summarize the SCARs associated with genetic and non-genetic factors and the cost-effectiveness of screening tests. Expert opinion: The effectiveness of HLA screening on a wider scale in clinical practice requires significant resources, including state-of-the-art laboratory; multidisciplinary team approach and health care provider education and engagement; clinical decision support alert system via electronic medical record (EMR); laboratory standards and quality assurance; evidence of cost-effectiveness; and cost of pharmacogenomics tests and reimbursement.

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Causative drugs for drug-induced cutaneous reactions in central China: a 608-case analysis

Cited by 16 publications

References 20 publications

Methods for Identifying Culprit Drugs in Cutaneous Drug Eruptions: A Scoping Review

Methods for Identifying Culprit Drugs in Cutaneous Drug Eruptions: A Scoping Review

Faktor Risiko Prediktor Bakteremia pada Pasien Nekrolisis Epidermal: Evidence-Based Case Report

GenotypingHLAalleles to predict the development of Severe cutaneous adverse drug reactions (SCARs): state-of-the-art

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