A Real-world Pharmacovigilance Study Of FDA Adverse Event Reporting System (FAERS) Events For Gender Of Voriconazole Drugs

Abstract

Purpose

To detect the gender variations in adverse events (AEs) of voriconazole, promote personalised medicine.

Methods

A normalized dataset from Q1 2004 to Q4 2022 from the US Food and Drug Administrationʼs Adverse Event Reporting System (FAERS) was analyses. The reporting odds ratio (ROR), proportional reporting ratio (PRR), and P value were used to examine data from the FAERS database to detect risk signals and quantify the presence and extent of gender variations in voriconazole adverse events.

Results

A total of 7670 cases (female/male (2785/4885)) of adverse reactions to voriconazole were analysed, and drug interaction (ROR 1.30 (1.10,1.54)), death and sudden death (ROR 1.31 (1.06,1.61)), actinic keratosis (ROR 1.98 (1.10,3.57)) were found to be significantly more frequent in male patients than in female patients.

Conclusion

We found that gender was a determinant in voriconazole-related AEs using FAERS. Our results require future validation due to the inherent limits of this open data source, but they also identify potential contributing elements for a customised side effect profiling.

Keywords

voriconazole - gender differences - real-world study - FAERS - adverse events

Introduction

Voriconazole ((2r, 3 s)-2-(2, 4–2 fluorinated phenyl)-3-(5-fluoro-4-pyrimidine)-1-(1h-1, 4-trichlorobenzene triazole-1-base)-2-butanol) is the drug of choice for the prevention and treatment of aggressive fungal infections [1] [2]. Furthermore, they are advised for general antifungal prophylaxis or preventive treatment in patients undergoing solid organ and hematopoietic stem cell transplantation [3]. Generally speaking, triazole antifungals need to be used for weeks or months at a time [4], followed by long-term inhibitory therapy. In view of the difference in the therapeutic effect of voriconazole on different genders [5]. Unstudied, but possible, are gender variations in the incidence of adverse events (AEs). There was an important article published in Scientific Reports by Hideo Kato [6], In this article, regarding sex distribution, the groups except for two groups (voriconazole+risperidone and voriconazole+chlorpromazine) consisted of more men than women.

There were differences in the efficacy of voriconazole in the treatment of fungal infection between genders [5] [7] [8], and additionally, there can be variations in gender in the incidence of AEs. According to a randomised controlled research, nausea, separation, and dizziness were the most frequent adverse effects experienced by voriconazole patients. Additionally, men experienced an increased frequency of adverse events compared to women. Furthermore, research suggests that women are primarily affected by adverse occurrences in the nervous system [5]. Previous safe pharmacological studies between genders to support clinicians to prescribe different doses for men and women A more thorough and multisource description of the variations in AEs between genders is warranted due to the unclear nature of the role that gender plays in AE risk and the possible therapeutic implications of this understanding.

Reporting on the spur of the moment presents a potentially better way to investigate adverse events in practice. Retrospective pharmacovigilance analysis using the FDA Adverse Event Reporting System (FAERS) database was used in this study to assist clinically rational drug use and decision-making for treatment regimens of patients of different genders. Additionally, a signal analysis evaluation of gender differences in AEs in voriconazole drugs was carried out [9].

Data and methods

Data acquisition and preprocessing

The FAERS database contains more than 19 million case reports from throughout the world regarding potential pharmaceutical adverse effects. On April 1, 2023, patient data reported between Q1 2004 and Q4 2022 was obtained from the FAERS website (https://fis.fda.gov), because more than 20% of FAERS records have been duplicated [10]. Furthermore, unlike the AE words, which are MedDRA-standardized and coded [11] (http://www.meddra.org), FAERS does not normalise medication names. Alternatively, they could be trade names, full names, or abbreviations; spelling errors are also frequent, which makes the analysis process more difficult. In the past, the FAERS data was standardised into three phases [12]: Data de-duplication is the first phase, in which duplicate reports are removed in accordance with the FDAʼs recommended procedure; RxNorm is the second step in drug name normalisation [13], For clinical pharmaceuticals, a standard nomenclature that offers a standardised naming system was employed. MedEx, a prescription information extraction system, was used to map drug names, administration routes, and dose information to concept-unique identifiers in RxNorm [14]. Thirdly, medications were grouped into classes using NDF-RT 24, a RxNorm drug terminology dictionary, by matching the AE phrases to the chosen term code of MedDRA and classifying them into the MedDRA System Organ Class (SOC). Supplement 1 contains a list of drug search names. The FAERS database contains information with the following names: “INDI”, “DEMO”, “DRUG”, "REAC”, “OUTC”, “RPSR”, and “THER”. Typically, we use the three data listed below: 1) “DEMO” gives the reporterʼs case ID, gender, age, year, country, and kind of occupation; 2) “REAC” lists all possible side effects that each patient may have had from the medication they took; and 3) “Drug” gives the name, dose, indication, dosing, and date of withdrawal of each medication [15].

Signals were mined and evaluated from the level of Preferred Term (PT), and classified into different SOC, High-Level Group Term, and high-level group term (HLGT) to more precisely characterize the signals of voriconazole drug gender differences.

Statistical analysis

Analysis of disproportionality was used to find pertinent signals. The degree of disproportionality was determined using the proportionate reporting ratio (PRR) and reporting odds ratio (ROR) [16] [17] [18] [19], and the 95% confidence interval (CI) for voriconazole-related AEs was assessed [16]. It was determined that the association was statistically significant if the 95%CIʼs lower limit was more than 1.0. To analyses the data, the following formula was used:

Note: a is the number of AEs records for males; b is the number of other AEs for males; c is the number of AEs records for females; d is the number of other AE for females.

Microsoft Excel version 2023 and SAS version 9.4 were used for all data categorization and statistical calculations.

Results

[Fig. 1] shows a flowchart of the study. We retrieved 15,641 distinct patients who were administered voriconazole from Jan 2004 to Jun 2023. Of these, 7,971 duplicate cases, analysis set 7,670.

Fig. 1 Flowchart of the data collection process.

7,670 voriconazole adverse AEs with a female/male ratio of 2785/4885 were obtained by extracting the basic data from AEs. [Table 1] displays the clinical results of AEs patients, the reporting population, the age distribution, and the nation. It was discovered that whereas men reported a greater rate of severe clinical outcomes – including death – resulting from AEs, men reported a larger total number of AEs.

Table 1 Features of adverse event reports that were filed for voriconazole.

	Female	Percentage %	Male	Percentage %
Clinical outcome
Death	587	21	1078	22
Hospitalization	772	28	1326	27
Threat to life	125	4	197	4
Disability	32	1	72	1
Other	1261	45	2190	45
Reporting crowd
Medical workers	395	14	654	13
Consumer	562	20	762	16
Unknown	34	1	65	1
Age distribution
≤18	256	9	357	7
18~64	1120	40	1664	34
≥65	823	30	1557	32
Unknown		0		0
Country
USA	53	2	58	1
Others	2389	86	3956	81
Unknown	10	0	14	0
Total	2785		4885

Results of signal detection at the PT level indicated that medication interaction was one of the high-risk signals associated with voriconazole in men (ROR 1.30 (1.10,1.54)), death and sudden death (ROR 1.31(1.06,1.61)), Actinic keratosis (ROR1.98 (1.10,3.57)) etc. In men, high-risk signs included drug interaction, death and sudden death, actinic keratosis ([Table 2]).

Table 2 Detection results of gender difference risk signals for voriconazole.

SOC	HLGT	PT	Men	Women	ROR(95% CI)	PRR (95% CI)
General disorders and administration site conditions	Therapeutic and nontherapeutic effects (excl toxicity)	Drug ineffective	967	352	0.98 (0.86,1.11)	0.98 (0.86,1.11)
	Therapeutic and nontherapeutic effects (excl toxicity)	Drug interaction	643	177	1.30 (1.10,1.54)	1.30 (1.10,1.54)
	Fatal outcomes	Death and sudden death	412	113	1.31 (1.06,1.61)	1.31 (1.06,1.60)
	General system disorders NEC	Condition aggravated	321	99	1.16 (0.92,1.45)	1.16 (0.92,1.45)
	Therapeutic and nontherapeutic effects (excl toxicity)	Drug resistance	198	60	1.18 (0.88,1.58)	1.18 (0.88,1.58)
Injury, poisoning and procedural complications	Off label uses and intentional product misuses/use issues	Off label uses and intentional product misuses/use issues	413	139	1.06 (0.87,1.29)	1.06 (0.87,1.28)
	Medication errors and other product use errors and issues	Product use in unapproved indication	159	47	1.21 (0.87,1.67)	1.21 (0.87,1.67)
	Medication errors and other product use errors and issues	Product use issue	146	56	0.93 (0.68,1.87)	0.93 (0.68,1.87)
	Exposures, chemical injuries and poisoning	Toxicity to various agents	124	45	0.98 (0.70,1.38)	0.98 (0.70,1.37)
	Injuries NEC	Drop attacks	59	31	0.68 (0.44,1.05)	0.68 (0.44,1.05)
Skin and subcutaneous tissue disorders	Epidermal and dermal conditions	Photosensitivity reaction	249	72	1.24 (0.95,1.61)	1.24 (0.95,1.61)
	Epidermal and dermal conditions	Rash	110	38	1.03 (0.71,1.49)	1.03 (0.71,1.48)
	Cornification and dystrophic skin disorders	Actinic keratosis	72	13	1.98 (1.10,3.57)	1.98 (1.10,3.57)
	Epidermal and dermal conditions	Administration site erythema	70	28	0.89 (0.57,1.38)	0.89 (0.57,1.38)
	Epidermal and dermal conditions	Administration site pruritus	46	23	0.71 (0.43,1.18)	0.71 (0.43,1.18)
Total			3989	1293

Note: SOC: System Organ Class; PT: Preferred Term; HLGT: High-Level Group Term.

A “volcano plot” was made to visualise the results of the signal detection process. The visualisation and understanding of the gender-specific AEs signals linked to voriconazole were made easier by this analytical method. The results are displayed in [Fig. 2] and were obtained using the values of -Log₁₀ P for the volcano diagramʼs vertical axis and Log₂ ROR for its horizontal axis as scales. The figure showed that in male patients, the rates of drug ineffectiveness, drug interaction, off-label usage, death, worsening of illness, and photosensitivity reaction were much greater than in female patients.

Fig. 2 Volcanic map of gender difference risk signal for Voriconazole Note: The graphʼs dots each reflect a possible drug-adverse event combination; female patients,potential AEs are indicated by red dots, while male patients,potential AEs are indicated by blue dots. Additionally labelled are AEs signals with substantial Log₂ ROR values and -Log₁₀ P values. P 0.05 is indicated by the dashed line.

Discussion

Hailong Li et al. [20] found that regardless of gender, the FAERS data suggest that voriconazole and periostitis may be related.

The reported country distribution is relatively fragmented, possibly due to the long time the drug has been on the market and its widespread use.

While there are clear physical and physiological variations between the sexes, gender differences in adverse events are rarely taken into account in clinical treatment [21]. One of the primary causes can be doctors,ignorance. A survey has revealed that the current curriculum of US medical schools does not properly incorporate information about gender issues of medicine [8]. Yue Yu et al. asked two general practitioners to determine whether the twenty drug-event combinations for diabetes mellitus and twenty drug-event combinations for hypertension had AEs associated with gender disparities. Neither doctor was aware of any gender disparities in these gender differences were linked to AEs in twenty drug-event combinations for hypertension and in drug-event combinations for diabetes mellitus [22].

Lin Cheng et al. [5] found that the proportion of female patients in the hypokalemia group was higher than that in the nonhypokalemia group, as was the proportion of patients receiving intravenous VCZ. hypokalemia is more likely to occur in females, in patients receiving intravenous VCZ, and in patients with the combined use of antibiotics. Hyponatremia is more likely to occur in patients older than 47 years who have been using VCZ for a long time and have higher VCZ C₀ values. This study is the same as ours.

This study used the FAERS databaseʼs signal detection capability to investigate gender-related differences in AEs associated with voriconazole. This study provided insightful information that can help medical professionals create treatment strategies that take gender variations into consideration, thereby improving drug safety. However, the study did not control for relevant variables that could have an impact on the AEs signals, such as polypharmacy and concomitant illnesses. To confirm and build upon these findings, more thorough evaluations, confirmatory research, and long-term follow-ups are necessary.

Sarah Allegra [5] found out through experiments that in a cohort of 330 Italian patients treated with voriconazole, with readings greater than 1000 ng/mL, males reported a far higher drug concentration than females did. Furthermore, a strong association between concentration and advancing age was discovered in the univariate study. The plasma drug concentration is highly variable in clinical practice, which can lead to inconsistent or inadequate dosing in many patients. It is also connected with the effectiveness of treatment and the incidence of adverse events [23]. Gender has a significant influence on blood exposure. Considering the gender effect on drug exposure, they found that, when comparing individuals taking IV and oral VRC, men had greater median VRC Trough values than women. Female sex also turned out to be a poor predictor of medication plasma levels adjusted for dose/kg when administered by IV [24] [25] [26]. Moreover, a noteworthy variation in medication dosage has been documented in every patient who was recruited. These imply that variations in dosages per kilogram of body weight may account for gender disparities. To prevent female underexposure, patient sex should be considered while determining the appropriate weight-based VRC dosage. Sexual hormones,impact on medication absorption, variations in fat percentage – age in body composition, and sex differences in CYP-mediated metabolism could all contribute to the gender effect on drug concentrations. Regretfully, the lack of information about female hormonal phase and impedance analysis – which cannot be found in a retrospective study – limits our research.

We summary of key RCTs evaluating ADRs associated with Voriconazole, see the [Table 3]. In head-to-head comparative trials, voriconazole appeared to be as efficacious as amphotericin B for the treatment of invasive aspergillosis and the empiric treatment of fungal infections in patients with febrile neutropenia. In clinical studies, it was as efficacious as fluconazole for the treatment of oropharyngeal and esophageal candidiasis. The results of in vitro susceptibility studies and case reports suggested that voriconazole may be useful against fluconazole- and/or itraconazole-resistant strains of Candida. Although voriconazole may be associated with a lower incidence of serious systemic adverse effects compared with amphotericin B (13.4% vs 24.3% in 1 pivotal clinical study; P=NS), major adverse effects associated with voriconazole include visual abnormalities ( approximately 30%), skin reactions ( approximately 20%), and elevations in hepatic enzymes (<or=20%) [27].

Table 3 Summary of Key RCTs Evaluating Adverse Drug Reactions (ADRs) Associated with Voriconazole

Author	Diease	Comparison	ADRs	Conclusion
Herbrecht et al. (2002) [1]	Invasive Aspergillosis	Voriconazole vs. amphotericin B.	Visual disturbances: 44% (transient, resolving without intervention) vs. 4% in amphotericin B. Hepatotoxicity: Elevated liver enzymes (13% vs. 5%). Renal toxicity: Lower incidence with voriconazole (no specific rates provided).	Voriconazole had fewer renal and infusion-related reactions but higher rates of reversible visual and hepatic effects.
Walsh et al. (2002) [2]	Febrile Neutropenia	Voriconazole vs. liposomal amphotericin B.	Visual disturbances: 23% (voriconazole) vs. 1% (amphotericin B). Hepatotoxicity: 9% liver enzyme elevation. Skin reactions: Rash (6%). Renal toxicity: Significantly lower with voriconazole (14% nephrotoxicity in amphotericin B group).	Voriconazole showed comparable efficacy with fewer renal complications but more transient visual/hepatic effects.
Kullberg et al. (2005) [3]	Candidemia in Non-Neutropenic Patients	Voriconazole vs. amphotericin B followed by fluconazole.	Visual disturbances: 23%. Hepatotoxicity: 16% liver enzyme elevation.	Similar efficacy between regimens, with voriconazoleʼs safety profile dominated by visual and hepatic ADRs.

[1] R. Herbrecht, D.W. Denning, T.F. Patterson, J.E. Bennett, R.E. Greene, J.W. Oestmann, W.V. Kern, K.A. Marr, P. Ribaud, O. Lortholary, R. Sylvester, R.H. Rubin, J.R. Wingard, P. Stark, C. Durand, D. Caillot, E. Thiel, P.H. Chandrasekar, M.R. Hodges, H.T. Schlamm, P.F. Troke, B. de Pauw, R. Invasive Fungal Infections Group of the European Organisation for, C. Treatment of, G. the Global Aspergillus Study, Voriconazole versus amphotericin B for primary therapy of invasive aspergillosis, N Engl J Med, 347 (2002) 408-415.10.1056/NEJMoa020191

[2] T.J. Walsh, P. Pappas, D.J. Winston, H.M. Lazarus, F. Petersen, J. Raffalli, S. Yanovich, P. Stiff, R. Greenberg, G. Donowitz, M. Schuster, A. Reboli, J. Wingard, C. Arndt, J. Reinhardt, S. Hadley, R. Finberg, M. Laverdiere, J. Perfect, G. Garber, G. Fioritoni, E. Anaissie, J. Lee, A. National Institute of, G. Infectious Diseases Mycoses Study, Voriconazole compared with liposomal amphotericin B for empirical antifungal therapy in patients with neutropenia and persistent fever, N Engl J Med, 346 (2002) 225-234.10.1056/NEJM200201243460403

[3] B.J. Kullberg, J.D. Sobel, M. Ruhnke, P.G. Pappas, C. Viscoli, J.H. Rex, J.D. Cleary, E. Rubinstein, L.W. Church, J.M. Brown, H.T. Schlamm, I.T. Oborska, F. Hilton, M.R. Hodges, Voriconazole versus a regimen of amphotericin B followed by fluconazole for candidaemia in non-neutropenic patients: a randomised non-inferiority trial, Lancet, 366 (2005) 1435-1442.10.1016/s0140-6736(05)67490-9

Conclusions

Our results have further enriched the observations from existing clinical and real-world studies, uncovering AEs signals for voriconazole. The findings of our investigation validated the presence of gender disparities in AEs linked to voriconazole usage, indicating that these inequalities had to be included into clinical practice to maximise treatment results.

Limitations

Male and female causation cannot be established by FAERS. Recent media coverage and publishing of AEs in the literature may influence reporting practices. Comorbidities and co-occurring medications masked the association between a medication and an AEs. The FDA asserts that no medical expert has reviewed the information that was supplied. FAERS data submission is available to consumers, healthcare providers, and manufacturers. A submissionʼs source needs to be considered. FAERS contains missing or incomplete data. In other cases, the medication names were spelt improperly, or the age was not stated. Given the lack of information regarding the patientʼs medication dosage, it is not feasible to rule out the bias in delirium caused by different drug dosages. Not all product-related AEs or medication errors were reported to the FDA. Furthermore, ROR looked into an elevated risk of adverse events reporting rather than an overall chance of adverse events occurring. One benefit of the FAERS database is its large sample size. Finding novel and uncommon AEs is crucial, despite several drawbacks.

Authorsʼ contributions

Conceptualization: Qiong Xu

Investigation: Xu Sun, Jing Zhao

Methodology: Hongxia Cheng, Qiong Xu

Formal analysis: Yan Liang, Lingyu Ji

Writing – original draft: Yan Liang, Qiong Xu, Yingying Chen

Writing – review & editing: Lingyu Ji, Yan Liang.

Funding Statement
This research received no external funding.

Ethics committee or institutional review

Ethical approval was not necessary because there is no data to be approved by the Ethics Committee in this document.

Data Availability Statement

This study analysed publicly available data sets. This data can be found in the following locations: https://research.cchmc.org/aers/explore.jsp.

Conflict of Interest

The author reports no conflicts of interest in this work.

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Publication History

Received: 01 January 2025

Accepted: 31 March 2025

Article published online:
28 April 2025