Purine Antimetabolites associated Pneumocystis Jiroveci Pneumonia

by Selleckchem | Oct 20 2023

Purpose: To detect the possible safety signal of purine antimetabolites associated with pneumocystis jiroveci pneumonia through disproportionality analysis in the FDA Adverse Event Reporting System (FAERS) Database.

Methods: A 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.

Results: A total of 7073 reports associated with pneumocystis jiroveci 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)] CONCLUSIONS: Our 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.

Comments:

Title: Detection of Safety Signal for Pneumocystis jiroveci Pneumonia with Purine Antimetabolites: FAERS Database Analysis

Abstract: This study aimed to identify a possible safety signal for pneumocystis jiroveci pneumonia (PJP) associated with purine antimetabolites through a retrospective disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) database. Four models were developed to evaluate the signal strength among different populations, considering potential confounding factors. The data mining algorithms, Reporting Odds Ratio (ROR), and Proportional Reporting Ratio (PRR) were employed, with a threshold for a signal set at ROR-1.96SE>1 and PRR≥2, accompanied by an associated X2 value of 4 or more.

Results: A total of 7,073 reports related to PJP were identified in the FAERS database, out of which 899 reports were associated with the use of purine antimetabolites. The crude signal strength for purine antimetabolites and PJP was determined as ROR 15.76 (14.70-16.91). Notably, the highest signal strengths were observed with fludarabine and thioguanine, with RORs of 19.63 (17.42-22.13) and 19.45 (13.21-28.63), respectively. Stratifying the cases based on autoimmune disorders and the cancer population revealed RORs of 3.33 (2.46-4.50) and 2.93 (2.26-3.79), respectively. Amongst the analyzed populations, children exhibited the highest risk of PJP associated with purine antimetabolites, with a nearly twofold increased risk compared to adults, with an ROR of 11.57 (9.16-14.62).

Conclusions: This study provides evidence of an association between PJP and the use of purine antimetabolites in patients with autoimmune disorders and cancer. The analysis identified signals for PJP with azathioprine, mercaptopurine, thioguanine, cladribine, fludarabine, and clofarabine. However, further research employing superior epidemiological study designs within well-defined populations is necessary to validate these findings.