Volume 11,Issue 1
Real-World Safety Signals of Drug-Induced Proteinuria: A Two-Decade Pharmacovigilance Study Using Multi-Indicator Detection and Multivariate Correction
Proteinuria is a critical biomarker for kidney damage and a key indicator in drug safety assessment. However, existing pharmacovigilance studies are often limited by single adverse event term detection and confounding factors inherent in spontaneous reporting systems, making it difficult to accurately identify the true risk of drug-induced proteinuria. We retrospectively analyzed data from the U.S. FDA Adverse Event Reporting System (FAERS) from the first quarter of 2004 through the fourth quarter of 2024. A multi-indicator detection framework was constructed using 17 MedDRA Preferred Terms related to proteinuria, encompassing 5,688 unique case reports. Signal-positive drugs were screened using four disproportionality analysis methods (ROR, PRR, EBGM, IC) with Bonferroni correction. Multivariable logistic regression models were applied to adjust for confounding factors including demographics, comorbidities, and concomitant medications. A total of 16 signal-positive drugs were identified. Antineoplastic agents accounted for the largest proportion (n = 8), with bevacizumab having the highest number of reported cases (n = 451) and tenofovir disoproxil showing the strongest disproportionality signal (ROR = 24.28). Immunomodulators (e.g., pembrolizumab, tacrolimus) and antiviral agents also demonstrated significant associations. The study population had a mean age of 53.7 years with a balanced sex distribution (50.7% male vs. 48.7% female). Antineoplastic and immunomodulatory agents are the primary risk sources for drug-induced proteinuria. The methodological framework proposed in this study, combining multi-indicator signal detection with multivariate correction, effectively enhances the reliability and accuracy of pharmacoepidemiological signals. Clinical monitoring of urinary protein is recommended for patients using high-risk medications to facilitate early identification of renal injury.
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