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Drug-associated Porphyria: A Pharmacovigilance Study

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Abstract Background: The potentially fatal attacks experienced by carriers of porphyria are triggered by various porphyrinogenic drugs; however, it is difficult to determine the safety of a particular drug. Mothed: we retrospectively used the FDA’s Adverse Event Reporting System (FAERS) to determine drugs associated with porphyria as an adverse event (AE). Reports with porphyria as an AE were extracted from FAERS data from January 2004 to March 2022. Search terms used to identify the AEs included “Porphyria,” “Porphyria screen,” “Porphyria non-acute,” “Porphyria acute,” “Acquired porphyria,” and “Pseudoporphyria.” Signal mining analysis was performed to identify the association between drugs and AEs by four algorithms “ROR,” “PRR,” “BCPNN,” and “MGPS.” Results: FAERS reported 1470 cases of porphyria-related AEs and 406 drugs were obtained after combining trade and generic names of the same drug. Fifty-two drugs with signals were identified by all four algorithms. The characteristics of all the reports and signaling drugs were analyzed. Conclusions: This is the first report of drug-associated porphyria analysis, that provides critical information on drug porphyrogenicity, thus allowing rational and evidence-based prescribing of drugs and improving the accuracy of predicted porphyrogenicity by model algorithms. In addition, this study provides references for clinicians to ensure that porphyrinogenic drugs are not prescribed to carriers of porphyria genetic mutations.
Title: Drug-associated Porphyria: A Pharmacovigilance Study
Description:
Abstract Background: The potentially fatal attacks experienced by carriers of porphyria are triggered by various porphyrinogenic drugs; however, it is difficult to determine the safety of a particular drug.
Mothed: we retrospectively used the FDA’s Adverse Event Reporting System (FAERS) to determine drugs associated with porphyria as an adverse event (AE).
Reports with porphyria as an AE were extracted from FAERS data from January 2004 to March 2022.
Search terms used to identify the AEs included “Porphyria,” “Porphyria screen,” “Porphyria non-acute,” “Porphyria acute,” “Acquired porphyria,” and “Pseudoporphyria.
” Signal mining analysis was performed to identify the association between drugs and AEs by four algorithms “ROR,” “PRR,” “BCPNN,” and “MGPS.
” Results: FAERS reported 1470 cases of porphyria-related AEs and 406 drugs were obtained after combining trade and generic names of the same drug.
Fifty-two drugs with signals were identified by all four algorithms.
The characteristics of all the reports and signaling drugs were analyzed.
Conclusions: This is the first report of drug-associated porphyria analysis, that provides critical information on drug porphyrogenicity, thus allowing rational and evidence-based prescribing of drugs and improving the accuracy of predicted porphyrogenicity by model algorithms.
In addition, this study provides references for clinicians to ensure that porphyrinogenic drugs are not prescribed to carriers of porphyria genetic mutations.

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