Purine antimetabolites associated Pneumocystis jirovecii pneumonia

Abstract

PurposeTo detect the possible safety signal of purine antimetabolites associated with Pneumocystis jirovecii pneumonia through disproportionality analysis in the FDA Adverse Event Reporting System (FAERS) Database.MethodsA case/non‐case retrospective disproportionality analysis was performed in the publicly available FAERS database using AERSmine (2004Q1–2021Q3). Four models were developed to explore the signal strength of PAs among different populations with possible confounding factors. Reporting odds ratio (ROR) and Proportional reporting ratio (PRR) was used as the data mining algorithm for the analysis. A value of ROR‐1.96SE > 1 and PRR ≥ 2 with an associated X2 value of 4 or more was considered the threshold for a signal.ResultsA total of 7073 reports associated with Pneumocystis jirovecii pneumonia were present in the database, of which 899 reports were associated with purine antimetabolites. A crude signal strength of ROR 15.76(14.70–16.91) was obtained for purine antimetabolites associated PJP, with the highest signal strength reported with fludarabine and thioguanine [ROR 19.63(17.42–22.13); 19.45(13.21–28.63)]. Stratifying the cases based on autoimmune disorders and the cancer population revealed an ROR of 3.33(2.46–4.50) and 2.93(2.26–3.79) respectively. The highest risk of PJP with use of PAs was observed amongst children with a higher risk of nearly 2 times than the adult population [ROR 11.57(9.16–14.62)].ConclusionsOur study provided evidence on the occurrence of PJP with the use of purine antimetabolites among the autoimmune and cancer population. We identified signals for PJP with azathioprine, mercaptopurine, thioguanine, cladribine, fludarabine, and clofarabine. More research with a superior epidemiological study design of a defined population is required to validate these findings.