Analyzing real-world adverse events of spironolactone with the FAERS database

Spironolactone is the first mineralocorticoid receptor antagonist developed and is widely used in the treatment of hypertension, primary hyperaldosteronism, and peripheral edema associated with heart failure, as well as other conditions related to aldosteronism [ 1 ]. As a synthetic 17-lactone, spironolactone is a non-selective mineralocorticoid receptor antagonist that has been in clinical use since its introduction in 1960, maintaining its relevance for over six decades [ 2 , 3 ]. In addition to its use in managing hypertension, spironolactone is also employed in the treatment of acne in women due to its antagonistic effects on both progesterone and androgen receptors [ 4 , 5 ]. Recently, spironolactone has gained attention for the treatment of resistant hypertension [ 6 ]. A study demonstrated that when added to regimens including diuretics or angiotensin-converting enzyme inhibitors, spironolactone significantly improved blood pressure control after 6 weeks and 6 months of treatment [ 7 ]. Due to its multifaceted therapeutic effects and favorable tolerability, spironolactone remains a commonly used drug in clinical practice, particularly in the management of hypertension, heart failure, and endocrine-related disorders. Despite the therapeutic benefits of spironolactone, it is associated with a range of adverse drug events (ADEs). The common ADE is menstrual irregularities (15%−30%), which are dose-dependent and can be alleviated with oral contraceptives or intrauterine devices [ 8 , 9 ]. Other infrequent ADEs include increased urination, lightheadedness, headaches, nausea, vomiting, breast discomfort, and breast enlargement [ 10 ]. As a potassium-retaining diuretic, elevated potassium levels (hyperkalemia) represent another possible side effect, especially in individuals with renal dysfunction or heart failure, and its occurrence is more common at higher dosages [ 11 ]. According to the prescribing information, routine monitoring of potassium levels is recommended for patients receiving spironolactone for Food and Drug Administration (FDA)-approved indications, including hypertension and heart failure. Additionally, there are reports of rare but severe adverse reactions. One study reported a case of granulocytopenia in a patient with cirrhotic ascites who was treated with spironolactone [ 12 ]. A case report described a male patient who developed a lupus-like skin reaction following spironolactone use [ 13 ]. Recognizing and delineating these ADEs is essential for enhancing patient safety and facilitating well-informed clinical choices. In contrast to laboratory studies and clinical trials, pharmacovigilance information offers a more accurate representation of real-world drug usage and is essential for post-market surveillance [ 14 ]. The FDA Adverse Event Reporting System (FAERS) is the publicly accessible repository for voluntarily reported ADEs, gathering information from healthcare providers, consumers, manufacturers, and other stakeholders. It plays a crucial role in notifying healthcare providers and the general public about possible drug-related hazards [ 15 , 16 ]. Data mining techniques, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and the empirical Bayesian geometric mean (EBGM) are widely used for signal detection in pharmacovigilance databases [ 17 , 18 ]. These approaches apply statistical methods to uncover associations or unanticipated events within extensive datasets. Many studies have utilized the FAERS database to investigate ADEs of various medications [ 19 – 24 ]. However, to date, no research has utilized the FAERS database to analyze the adverse reactions associated with spironolactone. The objective of this study is to thoroughly examine the risk of adverse reactions associated with spironolactone use through FAERS and to identify potential adverse reactions not specified in the drug labeling, providing valuable insights for clinical practice.

A total of 17,947,757 ADE reports were recorded in the FAERS database from Q1 2004 to Q3 2024 ( Fig 2 ). Of these, 8,566 reports listed spironolactone as the main suspect drug, covering 2,409 PTs. A greater number of reports were submitted by females (4,292 reports, 50.11%) compared to males (3,542 reports, 41.35%). The age group most frequently affected was individuals aged 75 years and older (2,653 reports, 30.97%). Physicians contributed the largest proportion of reports (2,580 reports, 30.12%), with the United States being the leading country for case submissions (2,441 reports, 28.50%). Regarding clinical outcomes, the most frequent result was hospitalization (3,954 reports, 44.39%), followed by other serious outcomes (3,421 reports, 38.41%). Further information is available in Table 3 . Abbreviations: ADEs, adverse drug events; FAERS, FDA Adverse Event Reporting System. Curve plot of the adverse reaction reports for spironolactone over the years. Signal detection was performed at the SOC level. Based on statistical analysis, spironolactone-related ADEs primarily impacted 25 distinct SOCs. Among these, the SOC with the highest frequency of ADEs was “general disorders and administration site conditions” (n = 3,555, ROR 0.7, PRR 0.74, IC −0.44, EBGM 0.74). However, the “metabolism and nutrition disorders” (n = 3,234, ROR 6.06, PRR 5.45, IC 2.44, EBGM 5.44) and “reproductive system and breast disorders” (n = 913, ROR 4.11, PRR 4.01, IC 2, EBGM 4) showed the highest ROR values, suggesting robust correlations across all four statistical methods. Several of these findings were consistent with well-known ADEs mentioned in the drug labeling, further reinforcing the credibility of the data. Notably, certain SOCs were linked to significant ADEs not previously documented in the drug inserts, including “congenital, familial and genetic disorders” (n = 160, ROR 1.88, PRR 1.87, IC 0.9, EBGM 1.87), “ear and labyrinth disorders” (n = 141, ROR 1.18, PRR 1.18, IC 0.24, EBGM 1.18), and “pregnancy, puerperium, and perinatal conditions” (n = 86, ROR 0.72, PRR 0.72, IC −0.47, EBGM 0.72) ( Table 4 ). *Indicating statistical significance Abbreviations: ROR, reporting odds ratio; PRR, proportional reporting ratio; CI, confidence interval; χ2, chi-squared; IC, Information Component. Table 5 presents the top 30 ADEs associated with spironolactone, ranked according to their signal strength. Notably, hyperkalemia (n = 1,308; ROR 90.35, PRR 86.01, IC 6.36, EBGM 82.41) and nipple pain (n = 42; ROR 46.19, PRR 46.12, IC 5.49, EBGM 45.07) exhibited significantly higher frequency rates and signal magnitudes. Additionally, ADEs such as male endometriosis (n = 7; ROR 13,615.84, PRR 13,612.3, IC 10.73, EBGM 1,702.41), 5-alpha-reductase deficiency (n = 5; ROR 1,620.81, PRR 1,620.51, IC 9.79, EBGM 884.37), congenital bulbospinal muscular atrophy (n = 6; ROR 402.42, PRR 402.33, IC 8.38, EBGM 333.53), and double-hit lymphoma (n = 5; ROR 243.12, PRR 243.08, IC 7.76, EBGM 216.18) were recognized as potential new ADE signals that were not included in the drug’s labeling. Abbreviations: ROR, reporting odds ratio; PRR, proportional reporting ratio; CI, confidence interval; χ2, chi-squared; IC, Information Component.

In conclusion, this study performed a comprehensive assessment of spironolactone’s safety profile using the FAERS database. While certain adverse reactions, such as male endometriosis, 5-alpha-reductase deficiency, congenital bulbospinal muscular atrophy, and double-hit lymphoma, are rare, they represent significant signals that warrant further investigation.

The FAERS database is a spontaneous reporting system that gathers ADE reports from a wide range of sources, including patients, healthcare providers, and pharmaceutical companies. It supports post-market surveillance and aims to enhance public health by aggregating and analyzing safety data, which is particularly beneficial for managing long-term conditions [ 25 ]. In this study, we conducted a retrospective pharmacovigilance analysis using FAERS data from the first quarter (Q1) of 2004 to the third quarter (Q3) of 2024. We also extracted patient demographic and clinical details, such as sex, age, reporting region, type of reporter, date of report, and outcomes associated with spironolactone-related ADEs. In accordance with the Medical Dictionary for Regulatory Activities (MedDRA) (Version 26.1), ADEs were classified using Preferred Terms (PTs) from the FAERS database. Each PT can be linked to multiple High-Level Terms, High-Level Group Terms, and System Organ Classes (SOCs). Within the FAERS database, a single ADE case may be reported multiple times, resulting in several entries for the same patient. Therefore, data cleaning procedures were implemented prior to analysis. Specifically, duplicate entries were identified and removed using unique identifiers in FAERS, such as the CASEID (which uniquely identifies each case) and ISR (Individual Safety Report) number (which tracks updates to the same case). For example, if multiple reports shared the same CASEID but different ISR numbers (indicating updates or revisions), only the report with the latest submission date (i.e., the most recent ISR version) was retained. This process ensured that each case was represented by its most updated clinical information, eliminating redundant data from initial reports and subsequent amendments. It is important to note that drug names in FAERS are typically reported in free-text format, which may include both generic and brand names, as well as research codes, with potential for spelling inconsistencies. To address this, a comprehensive drug name reference was applied, encompassing all known generic names, brand names, and study codes for FDA-approved spironolactone. PRR, ROR, BCPNN, and EBGM [ 18 , 26 – 28 ] are commonly employed techniques in pharmacovigilance for detecting ADE signals. While PRR measures relative risk, it tends to be highly sensitive and vulnerable to false positives, particularly when the number of reported incidents is small. In contrast, ROR offers more reliable estimates of risk or hazard ratios, with smaller deviations compared to other methods, and we applied a threshold of ROR ≥ 3 and 95% CI lower limit > 1 as recommended by Rothman et al [ 18 ]. BCPNN is recognized for its robustness, even with a limited number of reports, using an information component lower limit (IC025) > 0 as validated by Bate et al [ 27 ], while EBGM is particularly effective at identifying signals for rare events with a threshold of EBGM05 > 2 following Dumouchel [ 28 ]. For PRR, we adopted a criterion of PRR ≥ 2 and 95% CI lower limit > 1 as described by Evans et al [ 26 ]. This study integrated these methods to broaden detection scope and validate findings across statistical frameworks. A signal was deemed significant only when all four algorithms met their thresholds (e.g., ROR ≥ 3, PRR ≥ 2, IC025 > 0, EBGM05 > 2), a strategy designed to minimize false positives through cross-validation. Discordant results—where one method met criteria but others did not—were not prioritized to ensure consistency in identifying genuine associations. Detailed workflows for signal detection, including 2 × 2 contingency table construction and threshold evaluations, are provided in S1 Table , enhancing methodological transparency. The combined approach ensures reliable identification of potential rare ADEs by balancing sensitivity and specificity. The combined use of these algorithms ensures cross-validation, minimizes false positive rates, and enhances the identification of potential rare ADEs by adjusting thresholds and variances. Each method utilizes a 2x2 contingency table ( Table 1 ), with detailed formulas and cutoff values presented in Table 2 . A higher value indicates a stronger signal, suggesting a more significant association between the drug of interest and the ADEs. Ultimately, effective ADEs detection requires the fulfillment of positive signal criteria set by the four algorithms mentioned. Data related to spironolactone were meticulously processed and statistically analyzed using tools such as Excel and R Studio (Version 4.3.1, https://www.r-project.org/ ). The overall research approach is depicted in the flowchart ( Fig 1 ). Abbreviations: ADEs, adverse drug events. Abbreviations: ROR, Reporting Odds Ratio; PRR, Proportional Reporting Ratio; BCPNN, Bayesian Confidence Propagation Neural Network; EBGM, Empirical Bayesian Geometric Mean; SE, Standard Error; CI, Confidence Interval; IC, Information Component. The flow diagram of selecting spironolactone-related ADEs from FAERS database. Abbreviations: DEMO, demographic; REAC, Reporting Event Adverse Condition; PTs, Preferred Terms; PS, Primary Suspect; ROR, Reporting Odds Ratio; PRR, Proportional Reporting Ratio; BCPNN, Bayesian Confidence Propagation Neural Network; MGPS, multi-item gamma poisson shrinker.

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