Pharmacoepidemiology and drug safety · 2021
Biases associated with epidermal necrolysis reporting in pharmacovigilance: An exploratory analysis using World Health Organization VigiBase.
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Bettuzzi Thomas, Ingen-Housz-Oro Saskia, Maison Patrick, de Prost Nicolas, Wolkenstein Pierre, Lebrun-Vignes Bénédicte, Sbidian Emilie
Аннотация
BACKGROUND: Possible biases in pharmacovigilance reporting may impact epidermal necrolysis (EN) and drugs associations.
OBJECTIVES: To assess biases associated with EN-reporting.
METHODS: Using VigiBase, the World Health Organization-pharmacovigilance database, among drugs associated with EN between 2016 and 2020, we used an unsupervised clustering including reports characteristics, that is, reporter quality, time from drug intake to EN onset, and only one suspected drug in the report.
RESULTS: Among 152 drugs, three clusters were identified. Cluster 1 (n = 41) exhibited drugs frequently reported within a time from intake to onset longer than 4 days, in 57 ± 13% of reports. It corresponded to well-reported drugs and was composed mainly of antivirals and antiepileptics. Cluster 2 (n = 42) exhibited drugs frequently reported within a time from drug intake to onset shorter than 4 days, in 31 ± 12% of reports. It corresponded to drugs with a high risk of protopathic bias and was composed of nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics, and antibiotics. Cluster 3 (n = 69) exhibited drugs frequently reported with an unavailable time from drug intake to reaction, in 66 ± 11% of reports, and reported by a high frequency of consumers (9 ± 9%). It corresponded to drugs reported with a high risk of classification bias, and was composed of anticancer therapies and cardiovascular drugs.
CONCLUSION: Protopathic and classification biases impact EN-reporting and should be considered regarding associations with antibiotics, NSAIDs, analgesics, anticancer therapies, and cardiovascular drugs.
OBJECTIVES: To assess biases associated with EN-reporting.
METHODS: Using VigiBase, the World Health Organization-pharmacovigilance database, among drugs associated with EN between 2016 and 2020, we used an unsupervised clustering including reports characteristics, that is, reporter quality, time from drug intake to EN onset, and only one suspected drug in the report.
RESULTS: Among 152 drugs, three clusters were identified. Cluster 1 (n = 41) exhibited drugs frequently reported within a time from intake to onset longer than 4 days, in 57 ± 13% of reports. It corresponded to well-reported drugs and was composed mainly of antivirals and antiepileptics. Cluster 2 (n = 42) exhibited drugs frequently reported within a time from drug intake to onset shorter than 4 days, in 31 ± 12% of reports. It corresponded to drugs with a high risk of protopathic bias and was composed of nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics, and antibiotics. Cluster 3 (n = 69) exhibited drugs frequently reported with an unavailable time from drug intake to reaction, in 66 ± 11% of reports, and reported by a high frequency of consumers (9 ± 9%). It corresponded to drugs reported with a high risk of classification bias, and was composed of anticancer therapies and cardiovascular drugs.
CONCLUSION: Protopathic and classification biases impact EN-reporting and should be considered regarding associations with antibiotics, NSAIDs, analgesics, anticancer therapies, and cardiovascular drugs.