Agreement Among Different Scales for Causality Assessment in Drug-Induced Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis
Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net..
BACKGROUND AND OBJECTIVE: Identification of the offending drug is crucial and challenging in cases of severe cutaneous adverse drug reactions (CADR) like Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Poor reproducibility and varying levels of agreement have been observed among different causality assessment tools (CATs) in assessing severe CADRs. This study was conducted to examine the agreement among four different CATs in assessing cases of drug-induced SJS, TEN and SJS/TEN overlap.
METHODS: All cases of drug-induced SJS, TEN and SJS/TEN overlap, which were reported between January 2012 and January 2020, were identified from the ADR register at an ADR monitoring centre. Causality assessment was done in these reported cases using the following CATs: The World Health Organization-Uppsala Monitoring Centre (WHO-UMC) scale, Naranjo algorithm, Liverpool algorithm and Algorithm of drug causality for epidermal necrolysis (ALDEN). Weighted kappa (κw) test was used to evaluate the agreement among four CATs.
RESULTS: A total of 30 cases of drug-induced SJS, TEN and SJS/TEN overlap were included in our analyses. The most common offending groups of drugs were anticonvulsants (46.7%), antimicrobials (40%) and nonsteroidal anti-inflammatory drugs (13.3%). Of the anticonvulsants, phenytoin (13.3%), carbamazepine (10%), and valproate (10%) were the commonly reported offending drugs. Poor agreement was observed among the four different causality assessment scales.
CONCLUSION: Discrepancies were observed among four different CATs in assessing drug-induced SJS and TEN. A CAT, which is more specific to drug-induced SJS and TEN, simple, user-friendly with limited subjective interpretation, incorporating new immunological and pharmacogenetic markers, is necessary.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2022 |
---|---|
Erschienen: |
2022 |
Enthalten in: |
Zur Gesamtaufnahme - volume:17 |
---|---|
Enthalten in: |
Current drug safety - 17(2022), 1 vom: 26., Seite 40-46 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Sivagourounadin, Kiruthika [VerfasserIn] |
---|
Links: |
---|
Anmerkungen: |
Date Completed 10.05.2022 Date Revised 31.05.2022 published: Print Citation Status MEDLINE |
---|
doi: |
10.2174/1574886316666210611160123 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM326747591 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM326747591 | ||
003 | DE-627 | ||
005 | 20231225195250.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231225s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.2174/1574886316666210611160123 |2 doi | |
028 | 5 | 2 | |a pubmed24n1089.xml |
035 | |a (DE-627)NLM326747591 | ||
035 | |a (NLM)34126908 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Sivagourounadin, Kiruthika |e verfasserin |4 aut | |
245 | 1 | 0 | |a Agreement Among Different Scales for Causality Assessment in Drug-Induced Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis |
264 | 1 | |c 2022 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 10.05.2022 | ||
500 | |a Date Revised 31.05.2022 | ||
500 | |a published: Print | ||
500 | |a Citation Status MEDLINE | ||
520 | |a Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net. | ||
520 | |a BACKGROUND AND OBJECTIVE: Identification of the offending drug is crucial and challenging in cases of severe cutaneous adverse drug reactions (CADR) like Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Poor reproducibility and varying levels of agreement have been observed among different causality assessment tools (CATs) in assessing severe CADRs. This study was conducted to examine the agreement among four different CATs in assessing cases of drug-induced SJS, TEN and SJS/TEN overlap | ||
520 | |a METHODS: All cases of drug-induced SJS, TEN and SJS/TEN overlap, which were reported between January 2012 and January 2020, were identified from the ADR register at an ADR monitoring centre. Causality assessment was done in these reported cases using the following CATs: The World Health Organization-Uppsala Monitoring Centre (WHO-UMC) scale, Naranjo algorithm, Liverpool algorithm and Algorithm of drug causality for epidermal necrolysis (ALDEN). Weighted kappa (κw) test was used to evaluate the agreement among four CATs | ||
520 | |a RESULTS: A total of 30 cases of drug-induced SJS, TEN and SJS/TEN overlap were included in our analyses. The most common offending groups of drugs were anticonvulsants (46.7%), antimicrobials (40%) and nonsteroidal anti-inflammatory drugs (13.3%). Of the anticonvulsants, phenytoin (13.3%), carbamazepine (10%), and valproate (10%) were the commonly reported offending drugs. Poor agreement was observed among the four different causality assessment scales | ||
520 | |a CONCLUSION: Discrepancies were observed among four different CATs in assessing drug-induced SJS and TEN. A CAT, which is more specific to drug-induced SJS and TEN, simple, user-friendly with limited subjective interpretation, incorporating new immunological and pharmacogenetic markers, is necessary | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Adverse drug reactions | |
650 | 4 | |a causality assessment tool | |
650 | 4 | |a drug-induced Stevens-Johnson syndrome | |
650 | 4 | |a drug-induced toxic epidermal necrolysis | |
650 | 4 | |a liverpool algorithm | |
650 | 4 | |a naranjo scale | |
650 | 7 | |a Anti-Inflammatory Agents, Non-Steroidal |2 NLM | |
650 | 7 | |a Anticonvulsants |2 NLM | |
650 | 7 | |a Phenytoin |2 NLM | |
650 | 7 | |a 6158TKW0C5 |2 NLM | |
700 | 1 | |a Rajendran, Priyadharsini |e verfasserin |4 aut | |
700 | 1 | |a Selvarajan, Sandhiya |e verfasserin |4 aut | |
700 | 1 | |a Ganesapandian, Mahalakshmi |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Current drug safety |d 2006 |g 17(2022), 1 vom: 26., Seite 40-46 |w (DE-627)NLM181475790 |x 2212-3911 |7 nnns |
773 | 1 | 8 | |g volume:17 |g year:2022 |g number:1 |g day:26 |g pages:40-46 |
856 | 4 | 0 | |u http://dx.doi.org/10.2174/1574886316666210611160123 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 17 |j 2022 |e 1 |b 26 |h 40-46 |