The real-world pharmacovigilance study based on the FAERS database analyzed the adverse drug events associated with hydroxychloroquine

The real-world pharmacovigilance study based on the FAERS database analyzed the adverse drug events associated with hydroxychloroquine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The real-world pharmacovigilance study based on the FAERS database analyzed the adverse drug events associated with hydroxychloroquine Yuan Shiwei, Yuan Yongchang, Lin Weifeng, Zhang Yuan, Zhong Yongying, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5951209/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Introduction : HCQ is an antimalarial and immunomodulatory drug widely used to treat autoimmune diseases and other conditions. Despite its significant efficacy, HCQ can cause adverse effects such as gastrointestinal issues, retinal toxicity, and cardiotoxicity. As the application of HCQ in immunotherapy expands, its safety and long-term effects need to be evaluated through big data and clinical observations. In a post-marketing surveillance study conducted from the first quarter of 2004 to the third quarter of 2024, we analyzed HCQ-related adverse events (AEs) from the FAERS database, aiming to provide clinical references for its use. Methods : This retrospective pharmacovigilance study, based on the FAERS database, aimed to explore the association between HCQ and adverse events (AEs). AE data from 2004 to 2024 were collected, with adverse event reports of the primary suspected (PS) drugs retrieved from the FAERS database. We filtered and analyzed reports related to HCQ use. Four different methods—ROR, PRR, MGPS, and BCPNN—were applied to perform disproportionality analysis on the AEs associated with HCQ. Results : The year 2020 had the highest number of AE reports, accounting for 20.44% of the total. In gender-based analysis, women were more likely to report adverse events such as rheumatoid arthritis, disease exacerbation, drug intolerance, nausea, and pain, while men were more prone to report ECG QT prolongation and acute kidney injury. The study highlighted the differences in AE distribution across age groups and genders and pointed out that most AEs occurred within one month of starting HCQ; however, the risk of AEs remained even after two years, emphasizing the importance of long-term monitoring. The findings provided a reference for healthcare professionals and policymakers in developing safer drug usage guidelines. Conclusion : This study emphasizes that HCQ-related adverse reactions are influenced by factors such as gender, age, and underlying diseases, revealing the potential risks associated with the widespread use of HCQ, particularly the risks related to severe adverse reactions. It underscores the importance of continuous drug safety monitoring and suggests the need for individualized risk assessments in clinical settings, especially for patients on long-term use or combination therapies. Biological sciences/Drug discovery Biological sciences/Drug discovery/Drug safety Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 1. Introduction Hydroxychloroquine (HCQ) is a synthetic derivative of chloroquine, with both antimalarial and immunomodulatory effects. As a weakly basic compound, it also exhibits antimalarial activity¹. In addition to its use in treating malaria, HCQ is widely employed for the treatment of autoimmune diseases, such as systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), through the inhibition of immune cell activation, particularly in regulating macrophages and T cells. During the process of immune modulation, HCQ interferes with antigen presentation, the release of inflammatory mediators, and the production of cytokines, thereby reducing the intensity of autoimmune responses, alleviating symptoms, and improving disease outcomes¹. In the treatment of SLE, HCQ effectively controls disease progression, alleviates joint pain, skin rashes, and other visceral damages, and slows the progression of the disease². For rheumatoid arthritis, HCQ exerts its anti-inflammatory effects to reduce joint swelling and pain, and it helps to slow the onset of joint damage³. The immunomodulatory properties of HCQ also suggest its potential application in other autoimmune diseases, such as Sjögren’s syndrome and dermatomyositis. HCQ has been widely approved for the treatment of the aforementioned conditions, and dosage adjustments based on the patient's specific condition are crucial to minimize side effects⁴. Although HCQ has demonstrated favorable therapeutic effects, it may also cause adverse reactions. Common side effects include gastrointestinal symptoms, such as nausea, vomiting, and diarrhea, which are generally mild and tend to resolve with prolonged use⁵. More serious side effects include retinal toxicity and cardiac toxicity. Long-term, high-dose use of HCQ may lead to retinal damage, manifested as blurred vision or color vision abnormalities, and in extreme cases, irreversible blindness. Therefore, regular ophthalmologic checkups are recommended, especially for long-term users. Cardiac toxicity, characterized by QT interval prolongation, may lead to fatal arrhythmias, particularly in patients with pre-existing heart conditions or those taking other medications that affect the QT interval. Special caution is needed in these cases. Additionally, HCQ may cause skin reactions, such as rashes and photosensitivity. Therefore, it should be used cautiously in patients with a history of allergies⁶. In clinical practice, adverse reactions to the drug should be managed through dose adjustments, supportive treatments (such as anti-nausea medications and ophthalmic examinations), and timely discontinuation of the drug when necessary. In order to ensure the safety and efficacy of HCQ in clinical applications, especially during its widespread use in immunomodulatory treatments, drug safety monitoring is crucial. As the user population expands, the long-term safety of HCQ still requires continuous clinical observation and big data analysis for evaluation. Real-time monitoring of adverse drug reactions can be conducted through various methods, including clinical trials, adverse event data reported by patients, and regulatory agency reporting systems (such as the FDA's Adverse Event Reporting System FAERS) 7 . The application of data mining technology enables the rapid identification of potential safety issues and undiscovered side effects after widespread use, thus providing more comprehensive treatment guidance for clinicians. Many researchers have delved into its mechanisms of action in an attempt to assess its potential therapeutic effects and side effects in different patient populations. Systematic drug safety monitoring conducted worldwide contributes to improving treatment protocols and enhancing the overall safety of drug use. Considering that HCQ is a versatile drug with significant efficacy in treating malaria and immune-related diseases, and the lack of evidence of HCQ adverse events in the real world, we conducted a post-marketing surveillance study to assess HCQ-related adverse events in patients using the drug from the first quarter of 2004 to the third quarter of 2024, based on FAERS data. We comprehensively analyzed the systemic-specific side effects of HCQ, their onset times, and gender-based differences. The findings of this study provide clinicians and health policymakers with some recommendations for monitoring drug adverse reactions and offer partial guidance for the safe clinical use of HCQ. 2. Methods 2.1 Study Design and Data Sources Data Source: A retrospective pharmacovigilance study was conducted based on the FAERS database to investigate the correlation between HCQ and potential adverse events (AEs). FAERS is an important database maintained by the U.S. Food and Drug Administration (FDA) to collect adverse event information reported by patients and healthcare professionals during drug use8. This study collected data from the FAERS database from the first quarter of 2004 to the third quarter of 2024. To ensure the specificity and accuracy of the study, the search was limited to the generic name "Hydroxychloroquine," brand names, and other names such as "Hydroxychloroquine Sulfate" and "Oxychlorochin" as the primary suspected drugs, using the search tool at https://www.ncbi.nlm.nih.gov/mesh . Data were collected, preprocessed, and cleaned using MySQL software (SAS) to ensure accuracy and completeness. Following the FDA-recommended method for removing duplicate reports, we selected the fields PRIMARYID, CASEID, and FDA_DT from the DEMO table. We first sorted by CASEID and FDA_DT, then by PRIMARYID. For reports with the same CASEID, we retained the report with the largest FDA_DT value. For reports with the same CASEID and FDA_DT, we retained the report with the largest PRIMARYID value 9 – 10 . After duplicate data removal, we deleted reports based on the CASEID listed in the removed reports list 11 . Subsequently, the data were mapped to RxNorm and MedDRA tools. Additionally, the Preferred Term (PT) was standardized and translated to ensure data consistency. To present the data, AE reports with the same PT were merged. Furthermore, using the System Organ Class (SOC) method, PTs were classified and organized to better summarize and analyze the characteristics of the AEs. After data preprocessing, we obtained 18,289,374 DEMO reports, 66,422,789 DRUG cases, and 53,463,446 REAC records (Fig. 1 ). 2.2 Statistical Analysis The drugs in the FAERS reports were categorized into four patterns: PS (primary suspect), SS (secondary suspect), C (concomitant), and I (interaction). To improve accuracy, only drugs with HCQ as the PS were retained in the AE action codes, resulting in 15,893 AE reports (HCQ-related AEs) 12 . The Medical Dictionary for Regulatory Activities (MedDRA) is a standardized medical terminology that facilitates AE data recording and reporting globally 13 – 14 . Its hierarchical structure includes multiple levels, ranging from lower-level terms to SOCs 15 . SOC is the highest-level term in MedDRA used to classify and report adverse events in drug safety monitoring and reporting systems. To summarize and analyze the AE characteristics in a structured manner, all the AEs we collected were coded using Preferred Terms (PT) and then mapped to the corresponding highest SOC level in MedDRA (version 26.0) 16 – 17 . A total of 61,799 PTs induced by HCQ were identified as PS (HCQ-related PTs). In pharmacovigilance research, disproportionality analysis is a tool used to identify and detect drug-related adverse event signals. To improve the reliability of the results, multiple disproportionality analysis methods were employed, with the Reporting Odds Ratio (ROR) 18 demonstrating good performance in early signal detection. The ROR and Proportional Reporting Ratio (PRR) methods are widely used to detect drug-related adverse event signals 19 . Additionally, Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-item Gamma-Poisson Shrinker (MGPS) 20 are also used. In cases of fewer drug adverse event reports, both MGPS and BCPNN methods still exhibit strong signal detection capabilities 21 – 22 . We chose ROR as the primary signal mining method and used the proportional imbalance measurement method from the 2×2 contingency table to report the adverse event data for HCQ and other drugs (Table 1 ). Subsequently, using the four statistical methods—ROR, PRR, BCPNN, and MGPS—combined with all four thresholds, positive signals that met the criteria were selected (Table 2 ). Furthermore, to identify disproportional signals between males and females after HCQ administration, we applied the formula for the ROR method. The ROR used here does not strictly adhere to the epidemiological definition of ROR for drug-related events. Based on the 2×2 contingency table, we calculated the p-value using the chi-square (χ2) test. A volcano plot was created using the R package "ggplot2" (version 4.3.0), with the log2-transformed ROR values on the x-axis and the -log10 transformed adjusted p-values on the y-axis, with the false discovery rate (FDR) method used for p-value adjustment. The Kruskal-Wallis test and Dunn's test were used to evaluate numerical differences between multiple groups. 3. Results 3.1 Basic Information on AE Reports Data from the FAERS database, spanning from the first quarter of 2004 to the third quarter of 2024, were extracted, resulting in a total of 21,838,627 AE reports. After data cleaning and drug screening, 15,839 HCQ-related AE reports were included for analysis. As shown in Table 3 , the majority of HCQ AE reports were from females, comprising 55.2% with 8,772 cases; males accounted for 23.7% with 3,766 cases. Among the reports, 3,355 cases did not specify gender, representing 21.1%. Regarding the provided age information, 5,865 cases lacked detailed age data, making up 36.9% of the reports. Among the reports with available age data, the most frequent AE cases occurred in the 18–64.9 years age group, with 6,748 cases, representing 42.5%. The 65–85 years age group had 2,615 cases, making up 16.5%; the under 18 years group had 521 cases, representing 3.3%; and the over 85 years group had 144 cases, representing 0.9%. In terms of the reporting population, pharmacists were the largest group, reporting 5,488 cases (34.5%); physicians were the second largest group, with 3,642 cases (22.9%); followed by consumers, with 2,847 cases (17.9%). The majority of AE cases (37%) came from the United States; Canada followed with 2,431 cases (15.3%); France ranked third with 1,356 cases (8.5%). Excluding data from the fourth quarter of 2024, from the first quarter of 2004 to the third quarter of 2024, the highest number of AE reports occurred in 2020, accounting for 20.44% of the total reports. The distribution of report years is shown in Fig. 2 . Regarding clinical outcomes, there were 999 deaths, representing 6.3%, with 18.8% of reports indicating initial or extended hospitalization, further highlighting the need for monitoring adverse drug reactions. 3.2 Signal Detection 3.2.1 Signal Detection Statistics Based on System Organ Class Levels Based on the four calculation methods, this study identified 27 HCQ-related AE signals within the SOC, as shown in Fig. 3 . Using the most stringent ROR method, the top three prominent categories were: Pregnancy, Puerperium, and Perinatal Conditions (n = 902, ROR 3.41), Eye Disorders (n = 2,555, ROR 2.09), and Musculoskeletal and Connective Tissue Disorders (n = 6,312, ROR 2.02). According to the number of reports, the top three SOCs with the highest report numbers were: General Disorders and Administration Site Conditions, Musculoskeletal and Connective Tissue Disorders, and Injury, Poisoning, and Procedural Complications, as shown in Fig. 4 . 3.2.2 Signal Detection at PTs Level After the use of HCQ, we organized the signal value distribution of the top 50 PTs (Preferred Terms) according to the ROR (95% CI) method and labeled the corresponding SOCs (Fig. 5 ) for comparison. The top three positive PTs were: Chondrodysplasia Punctata, Red Blood Cell Vacuolisation, and T-Cell Receptor Gene Rearrangement Test. In terms of the number of PT occurrences, the three most frequent PTs (Fig. 6 ) were: Rheumatoid Arthritis, Condition Aggravated, and Drug Intolerance. We also found that, except for Rheumatoid Arthritis, the ROR values for the top five PTs were all below 10. Using the four major algorithms—ROR, PRR, BCPNN, and MGPS—we selected four PTs that were positive according to all four algorithms. We then categorized the top five PTs by SOC (Table 4 ) and created visualizations (Fig. 7 ), as well as a cross-visualization of signal detection across the four algorithms (Fig. 8 ). 3.2.3 Time to Onset of Hydroxychloroquine-associated Adverse Events This database provides data on the onset time of HCQ-related adverse events. Among all reported adverse events, only 1,402 reports had detailed onset time information. We analyzed the available data (which may cause the data to deviate from the true proportion) as a reference, as shown in Fig. 9 . Our study found that the majority of adverse events (793 cases, 56.56%) occurred within one month of HCQ use. Additionally, the occurrence of AE was distributed as follows: 31–60 days (101 cases, 7.2%), 61–90 days (59 cases, 4.21%), 91–120 days (41 cases, 2.92%), 121–150 days (27 cases, 1.93%), 151–180 days (24 cases, 1.71%), 181–360 days (92 cases, 6.56%), and more than 360 days (265 cases, 18.9%). According to our statistics, even after two years of HCQ use, the probability of experiencing an adverse event is still above 15%. This highlights the importance of continued monitoring for adverse events even after two years of HCQ treatment. 3.3 Subgroup Analysis 3.3.1 Age Subgroup According to Fig. 10 , the most common PT in the <18 years age group is Drug Overdose, while in the ≥ 18 years, <65 years age group, the most common PT is Rheumatoid Arthritis, which may be related to the underlying disease. In the ≥ 65 years age group, the most common PT is Electrocardiogram QT Prolonged. We classified the top 15 PT signals in each age group in descending order based on ROR (95% CI). In the <18 years group, the top three signals with stronger associations are: Electrocardiogram QRS Complex Prolonged, Electrocardiogram QT Prolonged, and Ventricular Tachycardia. In the ≥ 18 years, <65 years age group, the top three signals with stronger associations are: Electrocardiogram QT Prolonged, Treatment Failure, and Rheumatoid Arthritis. In the ≥ 65 years age group, the top three signals with stronger associations are: Electrocardiogram QT Prolonged, Treatment Failure, and Rheumatoid Arthritis. 3.3.2 Gender Differences in Hydroxychloroquine-associated AEs To analyze whether gender affects HCQ-related adverse events, we compared the occurrence of PTs between males and females based on the number of occurrences from 1,179 PTs, selecting the top 25 PTs for each gender, from high to low, as shown in Fig. 11 . The results indicate an imbalance in the AE occurrence rate between males and females. Rheumatoid Arthritis, Condition Aggravated, Drug Intolerance, Nausea, and Pain occurred more frequently in females, while Electrocardiogram QT Prolonged, Condition Aggravated, Rheumatoid Arthritis, and Acute Kidney Injury were more likely to occur in males. Using the ROR method, we identified 50 patients with disproportionately high AE rates for both males and females and classified them by SOC. The results are shown in Fig. 12 . AEs such as Electrocardiogram QT Prolonged, Drug Interaction, Drug Ineffective For Unapproved Indication, Condition Aggravated, and Pneumonia were more common in males. Female high-risk AEs included Rheumatoid Arthritis, Drug Intolerance, Nausea, Pain, Arthralgia, Rash, Fatigue, Joint Swelling, Diarrhoea, Treatment Failure, and Drug Hypersensitivity. Each point in Fig. 13 represents a related AE, suggesting valuable information about gender-specific potential adverse events associated with HCQ. The vertical axis uses a -Log 10 (adjusted P-value) scale, and the horizontal axis uses a Log 2 ROR value scale. The closer a point is to the top of the vertical axis, the more significant the result; the farther a point is from the center of the horizontal axis, the greater the difference. We marked the AEs that were statistically significant. Six significant signals were observed in males, including Electrocardiogram QT Prolonged, Acute Kidney Injury, Haemolytic Anaemia, Drug Interaction, Hepatitis, and Methaemoglobinaemia. In females, six significant AEs were observed, including Alopecia, Fatigue, Systemic Lupus Erythematosus, Rheumatoid Arthritis, Headache, and Pain. 4. Discussion This study utilized a comprehensive dataset from the FAERS database, covering reports from the first quarter of 2004 to the third quarter of 2024, totaling 21,838,627 adverse event (AE) reports. After data cleaning and drug screening, 15,839 AE reports related to hydroxychloroquine (HCQ) were included for analysis. The data revealed several significant patterns related to HCQ in terms of population characteristics, clinical outcomes, and signal detection. Population Characteristics and Report Distribution: Regarding gender distribution, females dominated the AE reports, accounting for approximately 55.2%, while males represented 23.7%. This result is consistent with findings from some related literature, where females are more likely to use HCQ due to a higher incidence of autoimmune diseases 19 . Age distribution analysis showed that most reports (42.5%) occurred in individuals aged 18–64, which correlates with HCQ's primary use in the treatment of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), diseases commonly affecting adults in this age group. This finding is consistent with other studies, indicating that HCQ is mainly used in adults, particularly middle-aged and elderly individuals 20 . The proportion of missing age data was 36.9%, reflecting a common issue of incomplete reporting in adverse drug reaction databases. Geographical distribution showed that the majority of AE reports (37%) originated from the United States, followed by Canada and France, highlighting the significant reporting presence in these regions. The surge in reports in 2020 21 , likely corresponds to HCQ being widely discussed and used as a potential antiviral drug, especially during 2020–2021. This increase was mainly due to HCQ being proposed by some studies and doctors for COVID-19 treatment, leading to a sharp rise in its use, particularly with hundreds of times more heart-related reports 22 , compared to its pre-pandemic use for approved indications (e.g., lupus and RA). The pre-pandemic incidence was 0.011%, while during the pandemic it surged to 2.892%. This difference indicates that the use of HCQ in COVID-19 treatment during the pandemic greatly increased the risk of cardiac AEs 23 . The decline in reports by 2022 may be due to the reduction in HCQ use following changes in the COVID-19 pandemic situation, particularly with the widespread vaccination and development of new treatment methods. As HCQ use for COVID-19 treatment decreased, the number of adverse reports also declined. Additionally, with ongoing research into HCQ’s efficacy and safety, public health agencies in multiple countries and regions issued updated treatment guidelines, typically recommending more effective and safer drugs. These guideline changes likely led to a reduction in HCQ reliance by clinicians and patients. Clinical Outcomes and Severity: Regarding clinical outcomes, HCQ was associated with some AEs related to death, although these were rare. Literature studies 24 have shown that HCQ can prolong the QT interval, and prolonged QT interval increases the risk of arrhythmic death. Especially in severe COVID-19 cases, the risk of malignant arrhythmias (such as torsades de pointes and ventricular fibrillation) is high, which can lead to sudden death and further increase the mortality risk. Therefore, the severe adverse reactions of HCQ require continuous monitoring and management, particularly as death and hospitalization are not uncommon severe adverse events. Signal Detection and Drug Safety Insights: Signal detection was conducted through the System Organ Class (SOC) method, identifying 27 significant AE signals related to HCQ. The most prominent categories included Pregnancy, Puerperium, and Perinatal Conditions, Eye Disorders, and Musculoskeletal and Connective Tissue Disorders. These categories highlight the diversity of HCQ's side effects, from pregnancy-related issues to eye disorders and musculoskeletal/connective tissue disorders, which are common complications in patients on long-term HCQ therapy. The strong positive signal for constipation during pregnancy and the perinatal period (ROR 3.41) suggests that HCQ may cause more notable AEs in these specific populations, even though such AEs are not extensively discussed in the drug's labeling. Eye disorders are the most reported AEs associated with the drug, with an ROR value of 2.09, and this is clearly warned in the drug's prescribing information, indicating a potential association. Musculoskeletal and connective tissue disorders showed a relatively high report frequency (n = 6312), indicating that these AEs are frequently observed in clinical practice and require careful monitoring during drug use. Comparison with the FDA's HCQ prescribing information revealed that constipation during pregnancy, puerperal, and perinatal periods, as well as musculoskeletal and connective tissue disorders, were not explicitly listed but were identified as strong positive signals in this study. This finding suggests that certain AE signals have not received adequate attention in the current drug warnings, highlighting the need for enhanced focus on these symptoms in drug monitoring and risk assessment, particularly for high-risk populations. On the other hand, eye disorders, a well-known AE listed in the prescribing information, remain the most significant signal in this study, consistent with data in the literature, indicating that eye-related adverse reactions are one of the most concerning AEs in HCQ’s clinical use. However, AEs listed in the drug's prescribing information, such as psychiatric disorders and metabolic and nutritional disorders, did not show strong signals in this study. Their ROR values were 0.37 and 0.77, respectively, showing relatively low significance (PRR, EBGM, IC values were also insignificant). Although these potential AEs were listed in the prescribing information, no strong correlation was observed based on this data analysis. This result may reflect limitations of the reporting data or the rarity of these AEs, preventing them from being adequately represented in this study’s sample. Alternatively, these AEs might not be entirely dependent on HCQ but could be related to the patient’s underlying conditions or interactions with other drugs. Further research and more detailed patient subgroup analysis may help accurately identify these unassociated AEs. According to our incomplete statistics, the most common AEs in the categories of constipation during pregnancy, puerperium, and perinatal periods were premature delivery (123/403), followed by low birth weight (111/403), and spontaneous abortion (65/403). However, some literature 24 has shown that HCQ was found to be safe in asymptomatic or mildly infected pregnant women and postpartum women with no significant pregnancy-related, puerperal, or perinatal constipation reactions. The most frequently reported Preferred Terms (PTs) include chondrodysplasia punctata and red blood cell vacuolization, which are relatively rare adverse drug reactions in clinical practice. Chondrodysplasia punctata (CDP) is a rare genetic skeletal developmental abnormality, typically presenting as skeletal system development issues, especially during cartilage formation, leading to limb shortening, dwarfism, and disproportionate body proportions. Red blood cell vacuolization refers to the presence of vacuoles (fluid cavities or bubble-like structures) within red blood cells, indicating abnormal internal structure or function of the red blood cells. Therefore, signals for these reactions should be monitored closely and reported promptly. Time-to-event data provided key insights into the timing of HCQ-related AEs. 56.56% of AEs occurred within one month of HCQ use, but several cases occurred after a year, emphasizing the need for continuous monitoring even after long-term use of HCQ. The time distribution of these AEs suggests that sustained monitoring and early intervention strategies are necessary during long-term HCQ therapy to mitigate potential risks. Age and Gender Subgroup Differences: Subgroup analysis revealed different AE patterns. For example, in patients under 18, the most common preferred term was drug overdose. Notably, drug overdose reports were more frequent, indicating possible misuse or incorrect use of HCQ. Signal strength analysis for this age group revealed that the top three strong signal PTs were prolonged electrocardiogram QRS complex, prolonged electrocardiogram QT, and ventricular tachycardia. This suggests that ECG abnormalities, especially QT prolongation, and arrhythmias are significant signals in this group, potentially related to HCQ’s cardiac toxicity, especially in children and adolescents, where the cardiac system may be more sensitive to the drug. In elderly patients aged 65 and above, the most common adverse reactions were those related to prolonged QT on ECG, a known cardiac risk of HCQ. These findings highlight age-specific risks and emphasize the importance of personalized monitoring protocols for different age groups. Particularly in older patients and those with multiple comorbidities, AE risks may be further exacerbated by polypharmacy or physiological changes. The age subgroup analysis indicated that as age increases, HCQ-related cardiac AEs (especially QT prolongation) significantly increase, particularly in elderly patients, who may have compromised cardiac function, comorbidities, and organ dysfunction, making them more susceptible to HCQ's adverse effects. Additionally, "treatment failure" was noted in various age groups, particularly among adults and the elderly, possibly due to the slow onset of action of anti-rheumatic drugs, prompting clinicians to change treatment regimens. Regardless, this hypothesis warrants further pharmacological monitoring and individualized treatment strategies. Gender difference analysis shows that common adverse events (AEs) in women include rheumatoid arthritis (RA) and fatigue, while men are more likely to experience electrocardiogram (ECG) QT prolongation and acute kidney injury. Recent studies suggest that gender differences may significantly affect the incidence, severity, and treatment response of these adverse events. Women are more likely than men to experience exacerbations of RA. Research has found 25 that RA has a higher incidence in women, and HCQ, as a treatment for RA, may influence disease progression in women through immune modulation mechanisms. Moreover, women are more affected by sex hormones (such as estrogen) in RA, and estrogen’s immune-regulating effect may lead to overactivation of immune responses, exacerbating the disease, particularly in autoimmune disorders. Nausea is commonly reported as an adverse reaction to HCQ, especially during the early treatment stages, and women tend to be more sensitive to gastrointestinal (GI) reactions. This is related to differences in gastric acid secretion, gastrointestinal motility speed, and drug-metabolizing enzymes (such as CYP450) activity in women compared to men. Men are more prone to QT prolongation when using HCQ compared to women. QT interval prolongation increases the risk of arrhythmias and may lead to life-threatening cardiac events. This may be because men have a longer baseline heart rate and QT interval compared to women, and their QT interval is more susceptible to certain drugs (such as HCQ). Studies have shown that men have a higher incidence of acute kidney injury following HCQ use. Male renal function may bear a higher metabolic burden in drug metabolism, and men often have a higher baseline risk for kidney diseases (such as hypertension and diabetes), making them more susceptible to the effects of HCQ. The pharmacokinetic pathways in men differ from those in women, and this may increase the likelihood of drug-drug interactions. For example, interactions between HCQ and cardiovascular drugs, antiepileptic drugs, antibiotics, and others may cause adverse reactions in men, particularly with regard to the CYP450 enzyme system, potentially leading to an increased risk of drug interactions. The analysis of gender-specific adverse reactions further suggests that gender could be a key factor in drug safety assessments. This hypothesis may help promote the development of personalized treatment strategies and encourage more gender-sensitive drug safety evaluations, ultimately improving patient outcomes. Given these gender differences, clinicians should conduct individualized risk assessments for male and female patients when using HCQ 26 . For example, female patients should be particularly cautious about drug intolerance, nausea, and GI symptoms when using HCQ, while male patients should be monitored more closely for QT prolongation and acute kidney injury. Moreover, more high-quality clinical trials focusing on gender differences are needed to further clarify the mechanisms, incidence, and clinical impacts of HCQ's adverse reactions in different genders. Future research should focus on how gender regulates drug responses, especially with regard to the kidneys, cardiovascular system, and immune system. 5. Limitations This study analyzed HCQ-related adverse events (AEs) using the FAERS database. While important conclusions were drawn, the study has certain limitations: 1.Limitations of Data Sources: The study relies on adverse event report data from the FAERS database, where the quality and accuracy of reports may be influenced by several factors, such as the subjective judgment of the reporters, omissions in reporting, and differences in the definition of adverse events. Additionally, the data mainly come from voluntary reports, which could lead to reporting biases, especially for certain populations or specific adverse events, potentially not fully reflecting the experience of all patients. 2.Bias in Gender and Age Groups: Although the study shows that gender and age groups have a significant impact on adverse event reports, this analysis did not consider baseline differences in these groups regarding HCQ use. For instance, men and women have differences in immune systems, disease types, and underlying pathologies, which may affect their drug responses. Furthermore, age-related effects may vary depending on other diseases or concomitant medications, and these factors were not sufficiently controlled in the analysis. 3.Insufficient Evaluation of Clinical Outcomes: The study recorded 999 death events and noted their association with HCQ, but the causal relationship between these deaths and HCQ remains unclear. This analysis is based solely on adverse event report data and lacks detailed clinical background and treatment history for each case. Therefore, it is difficult to determine whether these deaths were directly related to HCQ use or influenced by other factors such as underlying diseases or concomitant medications. 4.Lack of Consideration of Drug Interactions: Although men are more prone to drug interactions, the study did not explore the specific role of drug interactions in adverse events. Drug-drug interactions may increase the risk of AEs in certain populations, particularly in patients on multiple medications. The lack of a detailed analysis of drug interactions limits the understanding of the mechanisms of adverse events. 5.Inadequate Focus on Specific Populations: Although pregnancy, postpartum period, and perinatal constipation showed strong positive signals, safety evaluations in these specific populations remain insufficient. Despite the potential higher risk in these groups, the lack of more detailed clinical data prevents a precise evaluation of HCQ's safety in these populations. 6.Temporal Issues with the Data: The study found that 2020 had the highest number of reports, which could be related to the widespread discussion and use of HCQ during the COVID-19 pandemic. However, the pandemic’s unique context may have affected the representativeness of the data, particularly for non-COVID-19 patient groups. Therefore, the results may have some bias and may not fully represent all HCQ users. 7.Lack of Support from Randomized Controlled Trials (RCTs): While this study provides valuable information regarding HCQ-related AEs, the lack of data from randomized controlled trials (RCTs) means that other potential confounding factors influencing adverse events cannot be ruled out. Future studies should incorporate more rigorous designs, such as RCTs, to validate the reliability and universality of the findings. Declarations Ethics approval and consent to participate No ethical approval was required for this study as it only involved publicly available data and no human participants were involved. Consent for publication As the data used in this study were anonymized and obtained from publicly available sources, no consent was required from individual participants. Data Availability The data used in this study are available upon request from the corresponding author. Competing interest The authors declare that they have no competing interests. Funding This study was funded by the Health Project of Longyan City Science and Technology Innovation Joint Fund (2024LYF17120; 2024LYF17123) support. Authors' contributions Yuan Shiwei, Yuan Yongchang, Lin Weifeng,Zhang Yuan, Zhong Yongying, Luo XiuQing, Chen Dongco-authored the paper and collected data，Guo Wei, Liu Siyujointly reviewed and revised the paper. Acknowledgements The authors would like to thank FDA for providing the data used in this study. References Arachchillage, D. J., Laffan, M. & Pericleous, C. Hydroxychloroquine as an Immunomodulatory and Antithrombotic Treatment in Antiphospholipid Syndrome. Int. J. Mol. Sci. 24 (2), 1331. https://doi.org/10.3390/ijms24021331 (2023). Shippey, E. A., Wagler, V. D., Collamer, A. N. & Hydroxychloroquine An Old Drug with New Relevance. Clevel. Clin. J. Med. 85 (6), 459–467. https://doi.org/10.3949/ccjm.85a.17034 (2018). Feng, Y. et al. Innovative Lipid Nanoparticles Co-Delivering Hydroxychloroquine and siRNA for Enhanced Rheumatoid Arthritis Therapy. Pharmaceutics 17 (1), 45. https://doi.org/10.3390/pharmaceutics17010045 (2025). Largest Global Study on Hydroxychloroquine Safety Finds Increased Cardiovascular Risk with Azithromycin | University of Oxford . https://www.ox.ac.uk/news/2020-08-24-largest-global-study-hydroxychloroquine-safety-finds-increased-cardiovascular-risk (accessed 2025-02-01). Botelho, M. S. et al. Nunes-Nogueira, V. dos S. Systematic Review and Meta-Analysis of the Safety of Chloroquine and Hydroxychloroquine from Randomized Controlled Trials on Malarial and Non-Malarial Conditions. Syst. Rev. 10 (1), 294. (2021). https://doi.org/10.1186/s13643-021-01835-x Barailler, H. et al. Delayed Hypersensitivity Skin Reaction to Hydroxychloroquine: Successful Short Desensitization. J. Allergy Clin. Immunol. -Pract . 7 (1), 307–308. https://doi.org/10.1016/j.jaip.2018.04.041 (2019). Baroukhian, J., Seiffert-Sinha, K., Attwood, K. & Sinha, A. A. Evaluation of Link between COVID-19 Adjacent Spike in Hydroxychloroquine Use and Increased Reports of Pemphigus: A Disproportionality Analysis of the FDA Adverse Event Reporting System. Front. Immunol. 15 , 1470660. https://doi.org/10.3389/fimmu.2024.1470660 (2024). Sakaeda, T., Tamon, A., Kadoyama, K. & Okuno, Y. Data Mining of the Public Version of the FDA Adverse Event Reporting System. Int. J. Med. Sci. 10 (7), 796–803. https://doi.org/10.7150/ijms.6048 (2013). Shu, Y. et al. Version of FDA Adverse Event Reporting System. Clin. Epidemiol. 14 , 789–802. https://doi.org/10.2147/CLEP.S365513 (2022). Disproportionality Analysis of Olaparib: Data Mining of the Public. Wang, Y., Zhao, B., Yang, H., Wan, Z. A. & Real-World Pharmacovigilance Study of FDA Adverse Event Reporting System Events for Sildenafil. Andrology 12 (4), 785–792. https://doi.org/10.1111/andr.13533 (2024). Cui, Z. et al. A Pharmacovigilance Study of Etoposide in the FDA Adverse Event Reporting System (FAERS) Database, What Does the Real World Say? Front. Pharmacol. 14 , 1259908. https://doi.org/10.3389/fphar.2023.1259908 (2023). Ji, C., Bai, J., Zhou, J., Zou, Y. & Yu, M. Adverse Event Profiles of PCSK9 Inhibitors Alirocumab and Evolocumab: Data Mining of the FDA Adverse Event Reporting System. Br. J. Clin. Pharmacol. 88 (12), 5317–5325. https://doi.org/10.1111/bcp.15460 (2022). Brown, E. G. Using MedDRA - Implications for Risk Management. Drug Saf. 27 (8), 591–602. https://doi.org/10.2165/00002018-200427080-00010 (2004). Singh, J. International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use. J. Pharmacol. Pharmacother. 6 (3), 185–187. (2015). https://doi.org/10.4103/0976-500X.162004 Brown, E. G. Methods and Pitfalls in Searching Drug Safety Databases Utilising the Medical Dictionary for Regulatory Activities (MedDRA). Drug Saf. 26 (3), 145–158. https://doi.org/10.2165/00002018-200326030-00002 (2003). Wang, L., Jiang, G., Li, D. & Liu, H. Standardizing Adverse Drug Event Reporting Data. J. Biomed. Semant. 5 , 36. https://doi.org/10.1186/2041-1480-5-36 (2014). Zhou, Q. et al. Adverse Events of Epidiolex: A Real-World Drug Safety Surveillance Study Based on the FDA Adverse Event Reporting System (FAERS) Database. Asian J. Psychiatr . 90 , 103828. https://doi.org/10.1016/j.ajp.2023.103828 (2023). Li, Z., Zou, W., Yuan, J., Zhong, Y. & Fu, Z. Gender Differences in Adverse Events Related to Osimertinib: A Real-World Pharmacovigilance Analysis of FDA Adverse Event Reporting System. Expert Opin. Drug Saf. 23 (6), 763–770. https://doi.org/10.1080/14740338.2023.2243220 (2024). Barragan-Martinez, C. et al. Gender Differences in Latin-American Patients With Rheumatoid Arthritis. Gend. Med. 9 (6), 490–510. https://doi.org/10.1016/j.genm.2012.10.005 (2012). Rúa-Figueroa, Í. et al. Multidisciplinary Consensus on the Use of Hydroxychloroquine in Patients with Systemic Lupus Erythematosus. Reumatol Clin. (Engl Ed) . 20 (6), 312–319. https://doi.org/10.1016/j.reumae.2024.03.002 (2024). Cui, C. et al. Review on the Clinical Pharmacology of Hydroxychloroquine Sulfate for the Treatment of COVID-19. Curr. Drug Metab. 21 (6), 427–435. https://doi.org/10.2174/1389200221666200610172929 (2020). Gérard, A. et al. Off-Label Use of Hydroxychloroquine, Azithromycin, Lopinavir-Ritonavir and Chloroquine in COVID-19: A Survey of Cardiac Adverse Drug Reactions by the French Network of Pharmacovigilance Centers. Therapies 75 (4), 371–379. https://doi.org/10.1016/j.therap.2020.05.002 (2020). Romani, S. et al. the French Pharmacovigilance Network. Insights on the Evidence of Cardiotoxicity of Hydroxychloroquine Prior and During COVID‐19 Epidemic. Clin. Translational Sci. 14 (1), 163–169. https://doi.org/10.1111/cts.12883 (2021). Yamin, M. & Demili, A. U. Prevention of Ventricular Arrhythmia and Sudden Cardiac Death in COVID-19 Patients. Acta Med. Indones. 52 (3), 290 (2020). van Vollenhoven, R. F. Sex Differences in Rheumatoid Arthritis: More than Meets the Eye… BMC Med 2009, 7 , 12. https://doi.org/10.1186/1741-7015-7-12. Klein, S. L. & Morgan, R. The Impact of Sex and Gender on Immunotherapy Outcomes. Biology Sex. Differences . 11 (1), 24. https://doi.org/10.1186/s13293-020-00301-y (2020). Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 Apr, 2025 Reviews received at journal 03 Apr, 2025 Reviewers agreed at journal 03 Apr, 2025 Reviews received at journal 01 Apr, 2025 Reviewers agreed at journal 21 Mar, 2025 Reviewers invited by journal 19 Mar, 2025 Submission checks completed at journal 19 Mar, 2025 First submitted to journal 18 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5951209","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":431070127,"identity":"cdfa36dd-4b53-41b5-a470-de9af4098e05","order_by":0,"name":"Yuan Shiwei","email":"","orcid":"","institution":"Longyan Hospital of Traditional Chinese Medicine Affiliated to Xiamen University, Xiamen Unive rsity","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Shiwei","suffix":""},{"id":431070128,"identity":"1eee2de5-99ea-413d-bf79-2ad3a8067aa4","order_by":1,"name":"Yuan 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reports\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/4b6363962c5c57a07969ee0b.jpg"},{"id":79119292,"identity":"d623e6d1-4205-4b29-9329-49a05cd2d965","added_by":"auto","created_at":"2025-03-24 15:47:32","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":403243,"visible":true,"origin":"","legend":"\u003cp\u003eshows the distribution of signal values for the first 50 PT according to the ROR (95%CI) method\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/63c52021f5685fecd2674c4b.jpg"},{"id":79120108,"identity":"7c8e8acf-ece0-45e7-b14f-b1d3416f46c6","added_by":"auto","created_at":"2025-03-24 15:55:34","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":327874,"visible":true,"origin":"","legend":"\u003cp\u003eVisualizing the occurrence of the top 50 PT\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/6c7a79473481242351eed727.jpg"},{"id":79120112,"identity":"a6bc0a38-6009-4a12-a3d9-ad09bca96da9","added_by":"auto","created_at":"2025-03-24 15:55:34","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":350073,"visible":true,"origin":"","legend":"\u003cp\u003ePT that meets ROR, PRR, BCPNN, and MGPS are all positive, and can be summarized according to SOC.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/236218ea84cf70d3405c896a.jpg"},{"id":79120103,"identity":"d300ab9c-82e8-4f22-8220-3d31874a59d7","added_by":"auto","created_at":"2025-03-24 15:55:33","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":83547,"visible":true,"origin":"","legend":"\u003cp\u003eCross visualization of positive signals of the four algorithms.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/cecb8537fb3844fbdeef491d.jpg"},{"id":79119305,"identity":"bc7d6054-698e-4246-b104-e6b92f06e866","added_by":"auto","created_at":"2025-03-24 15:47:33","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":50794,"visible":true,"origin":"","legend":"\u003cp\u003eTime to induce adverse reactions.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/bc5db40db76c091071ec73ef.jpg"},{"id":79119325,"identity":"610b1069-f8d3-49b2-b686-a62967c6224e","added_by":"auto","created_at":"2025-03-24 15:47:34","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":335107,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent age groups are listed in descending order according to the number of PT\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/ab8ded2e43829a4e33593552.jpg"},{"id":79119295,"identity":"aa1abdbd-3249-44f0-911f-d5b345298abe","added_by":"auto","created_at":"2025-03-24 15:47:32","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":278729,"visible":true,"origin":"","legend":"\u003cp\u003eThe sexes are listed in descending order of the number of PT .\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/05fbf1ad275d8b4cf9e1815a.jpg"},{"id":79119318,"identity":"75cacebe-e7de-4f4d-9e04-a2e524da2f4b","added_by":"auto","created_at":"2025-03-24 15:47:34","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":290225,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of male to female occurrence in the top 50 patients with PT was observed using ROR (95%CI) method.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/b42086cc68522e9c0a5e12ab.jpg"},{"id":79119342,"identity":"878ea429-3cca-4c1a-b4ab-dac08387f373","added_by":"auto","created_at":"2025-03-24 15:47:35","extension":"jpg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":146317,"visible":true,"origin":"","legend":"\u003cp\u003eSex difference risk signal volcano map.P.adj, the p-value is adjusted with false discovery rate(FDR) method.Red points indicate potential adverse events in female patients, while blue points denote those in male patients.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951209/v1/0f94d216357c7b0020046ed1.jpg"},{"id":79120526,"identity":"a20fd479-680f-4746-81f2-ff41628a2e79","added_by":"auto","created_at":"2025-03-24 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Introduction","content":"\u003cp\u003eHydroxychloroquine (HCQ) is a synthetic derivative of chloroquine, with both antimalarial and immunomodulatory effects. As a weakly basic compound, it also exhibits antimalarial activity\u0026sup1;. In addition to its use in treating malaria, HCQ is widely employed for the treatment of autoimmune diseases, such as systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), through the inhibition of immune cell activation, particularly in regulating macrophages and T cells. During the process of immune modulation, HCQ interferes with antigen presentation, the release of inflammatory mediators, and the production of cytokines, thereby reducing the intensity of autoimmune responses, alleviating symptoms, and improving disease outcomes\u0026sup1;. In the treatment of SLE, HCQ effectively controls disease progression, alleviates joint pain, skin rashes, and other visceral damages, and slows the progression of the disease\u0026sup2;. For rheumatoid arthritis, HCQ exerts its anti-inflammatory effects to reduce joint swelling and pain, and it helps to slow the onset of joint damage\u0026sup3;. The immunomodulatory properties of HCQ also suggest its potential application in other autoimmune diseases, such as Sj\u0026ouml;gren\u0026rsquo;s syndrome and dermatomyositis. HCQ has been widely approved for the treatment of the aforementioned conditions, and dosage adjustments based on the patient\u0026apos;s specific condition are crucial to minimize side effects⁴.\u003c/p\u003e\n\u003cp\u003eAlthough HCQ has demonstrated favorable therapeutic effects, it may also cause adverse reactions. Common side effects include gastrointestinal symptoms, such as nausea, vomiting, and diarrhea, which are generally mild and tend to resolve with prolonged use⁵. More serious side effects include retinal toxicity and cardiac toxicity. Long-term, high-dose use of HCQ may lead to retinal damage, manifested as blurred vision or color vision abnormalities, and in extreme cases, irreversible blindness. Therefore, regular ophthalmologic checkups are recommended, especially for long-term users. Cardiac toxicity, characterized by QT interval prolongation, may lead to fatal arrhythmias, particularly in patients with pre-existing heart conditions or those taking other medications that affect the QT interval. Special caution is needed in these cases. Additionally, HCQ may cause skin reactions, such as rashes and photosensitivity. Therefore, it should be used cautiously in patients with a history of allergies⁶. In clinical practice, adverse reactions to the drug should be managed through dose adjustments, supportive treatments (such as anti-nausea medications and ophthalmic examinations), and timely discontinuation of the drug when necessary.\u003c/p\u003e\n\u003cp\u003eIn order to ensure the safety and efficacy of HCQ in clinical applications, especially during its widespread use in immunomodulatory treatments, drug safety monitoring is crucial. As the user population expands, the long-term safety of HCQ still requires continuous clinical observation and big data analysis for evaluation. Real-time monitoring of adverse drug reactions can be conducted through various methods, including clinical trials, adverse event data reported by patients, and regulatory agency reporting systems (such as the FDA\u0026apos;s Adverse Event Reporting System FAERS)\u003csup\u003e7\u003c/sup\u003e. The application of data mining technology enables the rapid identification of potential safety issues and undiscovered side effects after widespread use, thus providing more comprehensive treatment guidance for clinicians. Many researchers have delved into its mechanisms of action in an attempt to assess its potential therapeutic effects and side effects in different patient populations. Systematic drug safety monitoring conducted worldwide contributes to improving treatment protocols and enhancing the overall safety of drug use.\u003c/p\u003e\n\u003cp\u003eConsidering that HCQ is a versatile drug with significant efficacy in treating malaria and immune-related diseases, and the lack of evidence of HCQ adverse events in the real world, we conducted a post-marketing surveillance study to assess HCQ-related adverse events in patients using the drug from the first quarter of 2004 to the third quarter of 2024, based on FAERS data. We comprehensively analyzed the systemic-specific side effects of HCQ, their onset times, and gender-based differences. The findings of this study provide clinicians and health policymakers with some recommendations for monitoring drug adverse reactions and offer partial guidance for the safe clinical use of HCQ.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study Design and Data Sources\u003c/h2\u003e\n \u003cp\u003eData Source: A retrospective pharmacovigilance study was conducted based on the FAERS database to investigate the correlation between HCQ and potential adverse events (AEs). FAERS is an important database maintained by the U.S. Food and Drug Administration (FDA) to collect adverse event information reported by patients and healthcare professionals during drug use8. This study collected data from the FAERS database from the first quarter of 2004 to the third quarter of 2024. To ensure the specificity and accuracy of the study, the search was limited to the generic name \u0026quot;Hydroxychloroquine,\u0026quot; brand names, and other names such as \u0026quot;Hydroxychloroquine Sulfate\u0026quot; and \u0026quot;Oxychlorochin\u0026quot; as the primary suspected drugs, using the search tool at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/mesh\u003c/span\u003e\u003c/span\u003e. Data were collected, preprocessed, and cleaned using MySQL software (SAS) to ensure accuracy and completeness. Following the FDA-recommended method for removing duplicate reports, we selected the fields PRIMARYID, CASEID, and FDA_DT from the DEMO table. We first sorted by CASEID and FDA_DT, then by PRIMARYID. For reports with the same CASEID, we retained the report with the largest FDA_DT value. For reports with the same CASEID and FDA_DT, we retained the report with the largest PRIMARYID value\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. After duplicate data removal, we deleted reports based on the CASEID listed in the removed reports list\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Subsequently, the data were mapped to RxNorm and MedDRA tools. Additionally, the Preferred Term (PT) was standardized and translated to ensure data consistency. To present the data, AE reports with the same PT were merged. Furthermore, using the System Organ Class (SOC) method, PTs were classified and organized to better summarize and analyze the characteristics of the AEs. After data preprocessing, we obtained 18,289,374 DEMO reports, 66,422,789 DRUG cases, and 53,463,446 REAC records (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eThe drugs in the FAERS reports were categorized into four patterns: PS (primary suspect), SS (secondary suspect), C (concomitant), and I (interaction). To improve accuracy, only drugs with HCQ as the PS were retained in the AE action codes, resulting in 15,893 AE reports (HCQ-related AEs)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The Medical Dictionary for Regulatory Activities (MedDRA) is a standardized medical terminology that facilitates AE data recording and reporting globally\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Its hierarchical structure includes multiple levels, ranging from lower-level terms to SOCs\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. SOC is the highest-level term in MedDRA used to classify and report adverse events in drug safety monitoring and reporting systems. To summarize and analyze the AE characteristics in a structured manner, all the AEs we collected were coded using Preferred Terms (PT) and then mapped to the corresponding highest SOC level in MedDRA (version 26.0)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. A total of 61,799 PTs induced by HCQ were identified as PS (HCQ-related PTs).\u003c/p\u003e\n \u003cp\u003eIn pharmacovigilance research, disproportionality analysis is a tool used to identify and detect drug-related adverse event signals. To improve the reliability of the results, multiple disproportionality analysis methods were employed, with the Reporting Odds Ratio (ROR)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e demonstrating good performance in early signal detection. The ROR and Proportional Reporting Ratio (PRR) methods are widely used to detect drug-related adverse event signals\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Additionally, Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-item Gamma-Poisson Shrinker (MGPS)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e are also used. In cases of fewer drug adverse event reports, both MGPS and BCPNN methods still exhibit strong signal detection capabilities\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. We chose ROR as the primary signal mining method and used the proportional imbalance measurement method from the 2\u0026times;2 contingency table to report the adverse event data for HCQ and other drugs (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Subsequently, using the four statistical methods\u0026mdash;ROR, PRR, BCPNN, and MGPS\u0026mdash;combined with all four thresholds, positive signals that met the criteria were selected (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFurthermore, to identify disproportional signals between males and females after HCQ administration, we applied the formula for the ROR method. The ROR used here does not strictly adhere to the epidemiological definition of ROR for drug-related events. Based on the 2\u0026times;2 contingency table, we calculated the p-value using the chi-square (\u0026chi;2) test. A volcano plot was created using the R package \u0026quot;ggplot2\u0026quot; (version 4.3.0), with the log2-transformed ROR values on the x-axis and the -log10 transformed adjusted p-values on the y-axis, with the false discovery rate (FDR) method used for p-value adjustment. The Kruskal-Wallis test and Dunn\u0026apos;s test were used to evaluate numerical differences between multiple groups.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Basic Information on AE Reports\u003c/h2\u003e\n \u003cp\u003eData from the FAERS database, spanning from the first quarter of 2004 to the third quarter of 2024, were extracted, resulting in a total of 21,838,627 AE reports. After data cleaning and drug screening, 15,839 HCQ-related AE reports were included for analysis. As shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the majority of HCQ AE reports were from females, comprising 55.2% with 8,772 cases; males accounted for 23.7% with 3,766 cases. Among the reports, 3,355 cases did not specify gender, representing 21.1%. Regarding the provided age information, 5,865 cases lacked detailed age data, making up 36.9% of the reports. Among the reports with available age data, the most frequent AE cases occurred in the 18\u0026ndash;64.9 years age group, with 6,748 cases, representing 42.5%. The 65\u0026ndash;85 years age group had 2,615 cases, making up 16.5%; the under 18 years group had 521 cases, representing 3.3%; and the over 85 years group had 144 cases, representing 0.9%. In terms of the reporting population, pharmacists were the largest group, reporting 5,488 cases (34.5%); physicians were the second largest group, with 3,642 cases (22.9%); followed by consumers, with 2,847 cases (17.9%). The majority of AE cases (37%) came from the United States; Canada followed with 2,431 cases (15.3%); France ranked third with 1,356 cases (8.5%). Excluding data from the fourth quarter of 2024, from the first quarter of 2004 to the third quarter of 2024, the highest number of AE reports occurred in 2020, accounting for 20.44% of the total reports. The distribution of report years is shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Regarding clinical outcomes, there were 999 deaths, representing 6.3%, with 18.8% of reports indicating initial or extended hospitalization, further highlighting the need for monitoring adverse drug reactions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Signal Detection\u003c/h2\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1 Signal Detection Statistics Based on System Organ Class Levels\u003c/h2\u003e\n \u003cp\u003eBased on the four calculation methods, this study identified 27 HCQ-related AE signals within the SOC, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Using the most stringent ROR method, the top three prominent categories were: Pregnancy, Puerperium, and Perinatal Conditions (n\u0026thinsp;=\u0026thinsp;902, ROR 3.41), Eye Disorders (n\u0026thinsp;=\u0026thinsp;2,555, ROR 2.09), and Musculoskeletal and Connective Tissue Disorders (n\u0026thinsp;=\u0026thinsp;6,312, ROR 2.02). According to the number of reports, the top three SOCs with the highest report numbers were: General Disorders and Administration Site Conditions, Musculoskeletal and Connective Tissue Disorders, and Injury, Poisoning, and Procedural Complications, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.2 Signal Detection at PTs Level\u003c/h2\u003e\n \u003cp\u003eAfter the use of HCQ, we organized the signal value distribution of the top 50 PTs (Preferred Terms) according to the ROR (95% CI) method and labeled the corresponding SOCs (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) for comparison. The top three positive PTs were: Chondrodysplasia Punctata, Red Blood Cell Vacuolisation, and T-Cell Receptor Gene Rearrangement Test. In terms of the number of PT occurrences, the three most frequent PTs (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e) were: Rheumatoid Arthritis, Condition Aggravated, and Drug Intolerance. We also found that, except for Rheumatoid Arthritis, the ROR values for the top five PTs were all below 10. Using the four major algorithms\u0026mdash;ROR, PRR, BCPNN, and MGPS\u0026mdash;we selected four PTs that were positive according to all four algorithms. We then categorized the top five PTs by SOC (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e) and created visualizations (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e), as well as a cross-visualization of signal detection across the four algorithms (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.3 Time to Onset of Hydroxychloroquine-associated Adverse Events\u003c/h2\u003e\n \u003cp\u003eThis database provides data on the onset time of HCQ-related adverse events. Among all reported adverse events, only 1,402 reports had detailed onset time information. We analyzed the available data (which may cause the data to deviate from the true proportion) as a reference, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e. Our study found that the majority of adverse events (793 cases, 56.56%) occurred within one month of HCQ use. Additionally, the occurrence of AE was distributed as follows: 31\u0026ndash;60 days (101 cases, 7.2%), 61\u0026ndash;90 days (59 cases, 4.21%), 91\u0026ndash;120 days (41 cases, 2.92%), 121\u0026ndash;150 days (27 cases, 1.93%), 151\u0026ndash;180 days (24 cases, 1.71%), 181\u0026ndash;360 days (92 cases, 6.56%), and more than 360 days (265 cases, 18.9%). According to our statistics, even after two years of HCQ use, the probability of experiencing an adverse event is still above 15%. This highlights the importance of continued monitoring for adverse events even after two years of HCQ treatment.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Subgroup Analysis\u003c/h2\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.1 Age Subgroup\u003c/h2\u003e\n \u003cp\u003eAccording to Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e, the most common PT in the \u0026amp;lt;18 years age group is Drug Overdose, while in the \u0026ge;\u0026thinsp;18 years, \u0026amp;lt;65 years age group, the most common PT is Rheumatoid Arthritis, which may be related to the underlying disease. In the \u0026ge;\u0026thinsp;65 years age group, the most common PT is Electrocardiogram QT Prolonged. We classified the top 15 PT signals in each age group in descending order based on ROR (95% CI). In the \u0026amp;lt;18 years group, the top three signals with stronger associations are: Electrocardiogram QRS Complex Prolonged, Electrocardiogram QT Prolonged, and Ventricular Tachycardia. In the \u0026ge;\u0026thinsp;18 years, \u0026amp;lt;65 years age group, the top three signals with stronger associations are: Electrocardiogram QT Prolonged, Treatment Failure, and Rheumatoid Arthritis. In the \u0026ge;\u0026thinsp;65 years age group, the top three signals with stronger associations are: Electrocardiogram QT Prolonged, Treatment Failure, and Rheumatoid Arthritis.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.2 Gender Differences in Hydroxychloroquine-associated AEs\u003c/h2\u003e\n \u003cp\u003eTo analyze whether gender affects HCQ-related adverse events, we compared the occurrence of PTs between males and females based on the number of occurrences from 1,179 PTs, selecting the top 25 PTs for each gender, from high to low, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e. The results indicate an imbalance in the AE occurrence rate between males and females. Rheumatoid Arthritis, Condition Aggravated, Drug Intolerance, Nausea, and Pain occurred more frequently in females, while Electrocardiogram QT Prolonged, Condition Aggravated, Rheumatoid Arthritis, and Acute Kidney Injury were more likely to occur in males.\u003c/p\u003e\n \u003cp\u003eUsing the ROR method, we identified 50 patients with disproportionately high AE rates for both males and females and classified them by SOC. The results are shown in Fig. \u003cspan class=\"InternalRef\"\u003e12\u003c/span\u003e. AEs such as Electrocardiogram QT Prolonged, Drug Interaction, Drug Ineffective For Unapproved Indication, Condition Aggravated, and Pneumonia were more common in males. Female high-risk AEs included Rheumatoid Arthritis, Drug Intolerance, Nausea, Pain, Arthralgia, Rash, Fatigue, Joint Swelling, Diarrhoea, Treatment Failure, and Drug Hypersensitivity.\u003c/p\u003e\n \u003cp\u003eEach point in Fig. \u003cspan class=\"InternalRef\"\u003e13\u003c/span\u003e represents a related AE, suggesting valuable information about gender-specific potential adverse events associated with HCQ. The vertical axis uses a -Log 10 (adjusted P-value) scale, and the horizontal axis uses a Log 2 ROR value scale. The closer a point is to the top of the vertical axis, the more significant the result; the farther a point is from the center of the horizontal axis, the greater the difference. We marked the AEs that were statistically significant. Six significant signals were observed in males, including Electrocardiogram QT Prolonged, Acute Kidney Injury, Haemolytic Anaemia, Drug Interaction, Hepatitis, and Methaemoglobinaemia. In females, six significant AEs were observed, including Alopecia, Fatigue, Systemic Lupus Erythematosus, Rheumatoid Arthritis, Headache, and Pain.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study utilized a comprehensive dataset from the FAERS database, covering reports from the first quarter of 2004 to the third quarter of 2024, totaling 21,838,627 adverse event (AE) reports. After data cleaning and drug screening, 15,839 AE reports related to hydroxychloroquine (HCQ) were included for analysis. The data revealed several significant patterns related to HCQ in terms of population characteristics, clinical outcomes, and signal detection.\u003c/p\u003e\n\u003cp\u003ePopulation Characteristics and Report Distribution: Regarding gender distribution, females dominated the AE reports, accounting for approximately 55.2%, while males represented 23.7%. This result is consistent with findings from some related literature, where females are more likely to use HCQ due to a higher incidence of autoimmune diseases\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Age distribution analysis showed that most reports (42.5%) occurred in individuals aged 18\u0026ndash;64, which correlates with HCQ\u0026apos;s primary use in the treatment of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), diseases commonly affecting adults in this age group. This finding is consistent with other studies, indicating that HCQ is mainly used in adults, particularly middle-aged and elderly individuals\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The proportion of missing age data was 36.9%, reflecting a common issue of incomplete reporting in adverse drug reaction databases. Geographical distribution showed that the majority of AE reports (37%) originated from the United States, followed by Canada and France, highlighting the significant reporting presence in these regions. The surge in reports in 2020\u003csup\u003e21\u003c/sup\u003e, likely corresponds to HCQ being widely discussed and used as a potential antiviral drug, especially during 2020\u0026ndash;2021. This increase was mainly due to HCQ being proposed by some studies and doctors for COVID-19 treatment, leading to a sharp rise in its use, particularly with hundreds of times more heart-related reports\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, compared to its pre-pandemic use for approved indications (e.g., lupus and RA). The pre-pandemic incidence was 0.011%, while during the pandemic it surged to 2.892%. This difference indicates that the use of HCQ in COVID-19 treatment during the pandemic greatly increased the risk of cardiac AEs\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The decline in reports by 2022 may be due to the reduction in HCQ use following changes in the COVID-19 pandemic situation, particularly with the widespread vaccination and development of new treatment methods. As HCQ use for COVID-19 treatment decreased, the number of adverse reports also declined. Additionally, with ongoing research into HCQ\u0026rsquo;s efficacy and safety, public health agencies in multiple countries and regions issued updated treatment guidelines, typically recommending more effective and safer drugs. These guideline changes likely led to a reduction in HCQ reliance by clinicians and patients.\u003c/p\u003e\n\u003cp\u003eClinical Outcomes and Severity: Regarding clinical outcomes, HCQ was associated with some AEs related to death, although these were rare. Literature studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e have shown that HCQ can prolong the QT interval, and prolonged QT interval increases the risk of arrhythmic death. Especially in severe COVID-19 cases, the risk of malignant arrhythmias (such as torsades de pointes and ventricular fibrillation) is high, which can lead to sudden death and further increase the mortality risk. Therefore, the severe adverse reactions of HCQ require continuous monitoring and management, particularly as death and hospitalization are not uncommon severe adverse events.\u003c/p\u003e\n\u003cp\u003eSignal Detection and Drug Safety Insights: Signal detection was conducted through the System Organ Class (SOC) method, identifying 27 significant AE signals related to HCQ. The most prominent categories included Pregnancy, Puerperium, and Perinatal Conditions, Eye Disorders, and Musculoskeletal and Connective Tissue Disorders. These categories highlight the diversity of HCQ\u0026apos;s side effects, from pregnancy-related issues to eye disorders and musculoskeletal/connective tissue disorders, which are common complications in patients on long-term HCQ therapy. The strong positive signal for constipation during pregnancy and the perinatal period (ROR 3.41) suggests that HCQ may cause more notable AEs in these specific populations, even though such AEs are not extensively discussed in the drug\u0026apos;s labeling. Eye disorders are the most reported AEs associated with the drug, with an ROR value of 2.09, and this is clearly warned in the drug\u0026apos;s prescribing information, indicating a potential association. Musculoskeletal and connective tissue disorders showed a relatively high report frequency (n\u0026thinsp;=\u0026thinsp;6312), indicating that these AEs are frequently observed in clinical practice and require careful monitoring during drug use.\u003c/p\u003e\n\u003cp\u003eComparison with the FDA\u0026apos;s HCQ prescribing information revealed that constipation during pregnancy, puerperal, and perinatal periods, as well as musculoskeletal and connective tissue disorders, were not explicitly listed but were identified as strong positive signals in this study. This finding suggests that certain AE signals have not received adequate attention in the current drug warnings, highlighting the need for enhanced focus on these symptoms in drug monitoring and risk assessment, particularly for high-risk populations. On the other hand, eye disorders, a well-known AE listed in the prescribing information, remain the most significant signal in this study, consistent with data in the literature, indicating that eye-related adverse reactions are one of the most concerning AEs in HCQ\u0026rsquo;s clinical use. However, AEs listed in the drug\u0026apos;s prescribing information, such as psychiatric disorders and metabolic and nutritional disorders, did not show strong signals in this study. Their ROR values were 0.37 and 0.77, respectively, showing relatively low significance (PRR, EBGM, IC values were also insignificant). Although these potential AEs were listed in the prescribing information, no strong correlation was observed based on this data analysis. This result may reflect limitations of the reporting data or the rarity of these AEs, preventing them from being adequately represented in this study\u0026rsquo;s sample. Alternatively, these AEs might not be entirely dependent on HCQ but could be related to the patient\u0026rsquo;s underlying conditions or interactions with other drugs. Further research and more detailed patient subgroup analysis may help accurately identify these unassociated AEs.\u003c/p\u003e\n\u003cp\u003eAccording to our incomplete statistics, the most common AEs in the categories of constipation during pregnancy, puerperium, and perinatal periods were premature delivery (123/403), followed by low birth weight (111/403), and spontaneous abortion (65/403). However, some literature\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e has shown that HCQ was found to be safe in asymptomatic or mildly infected pregnant women and postpartum women with no significant pregnancy-related, puerperal, or perinatal constipation reactions.\u003c/p\u003e\n\u003cp\u003eThe most frequently reported Preferred Terms (PTs) include chondrodysplasia punctata and red blood cell vacuolization, which are relatively rare adverse drug reactions in clinical practice. Chondrodysplasia punctata (CDP) is a rare genetic skeletal developmental abnormality, typically presenting as skeletal system development issues, especially during cartilage formation, leading to limb shortening, dwarfism, and disproportionate body proportions. Red blood cell vacuolization refers to the presence of vacuoles (fluid cavities or bubble-like structures) within red blood cells, indicating abnormal internal structure or function of the red blood cells. Therefore, signals for these reactions should be monitored closely and reported promptly.\u003c/p\u003e\n\u003cp\u003eTime-to-event data provided key insights into the timing of HCQ-related AEs. 56.56% of AEs occurred within one month of HCQ use, but several cases occurred after a year, emphasizing the need for continuous monitoring even after long-term use of HCQ. The time distribution of these AEs suggests that sustained monitoring and early intervention strategies are necessary during long-term HCQ therapy to mitigate potential risks.\u003c/p\u003e\n\u003cp\u003eAge and Gender Subgroup Differences: Subgroup analysis revealed different AE patterns. For example, in patients under 18, the most common preferred term was drug overdose. Notably, drug overdose reports were more frequent, indicating possible misuse or incorrect use of HCQ. Signal strength analysis for this age group revealed that the top three strong signal PTs were prolonged electrocardiogram QRS complex, prolonged electrocardiogram QT, and ventricular tachycardia. This suggests that ECG abnormalities, especially QT prolongation, and arrhythmias are significant signals in this group, potentially related to HCQ\u0026rsquo;s cardiac toxicity, especially in children and adolescents, where the cardiac system may be more sensitive to the drug. In elderly patients aged 65 and above, the most common adverse reactions were those related to prolonged QT on ECG, a known cardiac risk of HCQ. These findings highlight age-specific risks and emphasize the importance of personalized monitoring protocols for different age groups. Particularly in older patients and those with multiple comorbidities, AE risks may be further exacerbated by polypharmacy or physiological changes.\u003c/p\u003e\n\u003cp\u003eThe age subgroup analysis indicated that as age increases, HCQ-related cardiac AEs (especially QT prolongation) significantly increase, particularly in elderly patients, who may have compromised cardiac function, comorbidities, and organ dysfunction, making them more susceptible to HCQ\u0026apos;s adverse effects. Additionally, \u0026quot;treatment failure\u0026quot; was noted in various age groups, particularly among adults and the elderly, possibly due to the slow onset of action of anti-rheumatic drugs, prompting clinicians to change treatment regimens. Regardless, this hypothesis warrants further pharmacological monitoring and individualized treatment strategies.\u003c/p\u003e\n\u003cp\u003eGender difference analysis shows that common adverse events (AEs) in women include rheumatoid arthritis (RA) and fatigue, while men are more likely to experience electrocardiogram (ECG) QT prolongation and acute kidney injury. Recent studies suggest that gender differences may significantly affect the incidence, severity, and treatment response of these adverse events. Women are more likely than men to experience exacerbations of RA. Research has found\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e that RA has a higher incidence in women, and HCQ, as a treatment for RA, may influence disease progression in women through immune modulation mechanisms. Moreover, women are more affected by sex hormones (such as estrogen) in RA, and estrogen\u0026rsquo;s immune-regulating effect may lead to overactivation of immune responses, exacerbating the disease, particularly in autoimmune disorders. Nausea is commonly reported as an adverse reaction to HCQ, especially during the early treatment stages, and women tend to be more sensitive to gastrointestinal (GI) reactions. This is related to differences in gastric acid secretion, gastrointestinal motility speed, and drug-metabolizing enzymes (such as CYP450) activity in women compared to men.\u003c/p\u003e\n\u003cp\u003eMen are more prone to QT prolongation when using HCQ compared to women. QT interval prolongation increases the risk of arrhythmias and may lead to life-threatening cardiac events. This may be because men have a longer baseline heart rate and QT interval compared to women, and their QT interval is more susceptible to certain drugs (such as HCQ). Studies have shown that men have a higher incidence of acute kidney injury following HCQ use. Male renal function may bear a higher metabolic burden in drug metabolism, and men often have a higher baseline risk for kidney diseases (such as hypertension and diabetes), making them more susceptible to the effects of HCQ. The pharmacokinetic pathways in men differ from those in women, and this may increase the likelihood of drug-drug interactions. For example, interactions between HCQ and cardiovascular drugs, antiepileptic drugs, antibiotics, and others may cause adverse reactions in men, particularly with regard to the CYP450 enzyme system, potentially leading to an increased risk of drug interactions.\u003c/p\u003e\n\u003cp\u003eThe analysis of gender-specific adverse reactions further suggests that gender could be a key factor in drug safety assessments. This hypothesis may help promote the development of personalized treatment strategies and encourage more gender-sensitive drug safety evaluations, ultimately improving patient outcomes.\u003c/p\u003e\n\u003cp\u003eGiven these gender differences, clinicians should conduct individualized risk assessments for male and female patients when using HCQ\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. For example, female patients should be particularly cautious about drug intolerance, nausea, and GI symptoms when using HCQ, while male patients should be monitored more closely for QT prolongation and acute kidney injury. Moreover, more high-quality clinical trials focusing on gender differences are needed to further clarify the mechanisms, incidence, and clinical impacts of HCQ\u0026apos;s adverse reactions in different genders. Future research should focus on how gender regulates drug responses, especially with regard to the kidneys, cardiovascular system, and immune system.\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eThis study analyzed HCQ-related adverse events (AEs) using the FAERS database. While important conclusions were drawn, the study has certain limitations:\u003c/p\u003e\n\u003cp\u003e1.Limitations of Data Sources: The study relies on adverse event report data from the FAERS database, where the quality and accuracy of reports may be influenced by several factors, such as the subjective judgment of the reporters, omissions in reporting, and differences in the definition of adverse events. Additionally, the data mainly come from voluntary reports, which could lead to reporting biases, especially for certain populations or specific adverse events, potentially not fully reflecting the experience of all patients.\u003c/p\u003e\n\u003cp\u003e2.Bias in Gender and Age Groups: Although the study shows that gender and age groups have a significant impact on adverse event reports, this analysis did not consider baseline differences in these groups regarding HCQ use. For instance, men and women have differences in immune systems, disease types, and underlying pathologies, which may affect their drug responses. Furthermore, age-related effects may vary depending on other diseases or concomitant medications, and these factors were not sufficiently controlled in the analysis.\u003c/p\u003e\n\u003cp\u003e3.Insufficient Evaluation of Clinical Outcomes: The study recorded 999 death events and noted their association with HCQ, but the causal relationship between these deaths and HCQ remains unclear. This analysis is based solely on adverse event report data and lacks detailed clinical background and treatment history for each case. Therefore, it is difficult to determine whether these deaths were directly related to HCQ use or influenced by other factors such as underlying diseases or concomitant medications.\u003c/p\u003e\n\u003cp\u003e4.Lack of Consideration of Drug Interactions: Although men are more prone to drug interactions, the study did not explore the specific role of drug interactions in adverse events. Drug-drug interactions may increase the risk of AEs in certain populations, particularly in patients on multiple medications. The lack of a detailed analysis of drug interactions limits the understanding of the mechanisms of adverse events.\u003c/p\u003e\n\u003cp\u003e5.Inadequate Focus on Specific Populations: Although pregnancy, postpartum period, and perinatal constipation showed strong positive signals, safety evaluations in these specific populations remain insufficient. Despite the potential higher risk in these groups, the lack of more detailed clinical data prevents a precise evaluation of HCQ\u0026apos;s safety in these populations.\u003c/p\u003e\n\u003cp\u003e6.Temporal Issues with the Data: The study found that 2020 had the highest number of reports, which could be related to the widespread discussion and use of HCQ during the COVID-19 pandemic. However, the pandemic\u0026rsquo;s unique context may have affected the representativeness of the data, particularly for non-COVID-19 patient groups. Therefore, the results may have some bias and may not fully represent all HCQ users.\u003c/p\u003e\n\u003cp\u003e7.Lack of Support from Randomized Controlled Trials (RCTs): While this study provides valuable information regarding HCQ-related AEs, the lack of data from randomized controlled trials (RCTs) means that other potential confounding factors influencing adverse events cannot be ruled out. Future studies should incorporate more rigorous designs, such as RCTs, to validate the reliability and universality of the findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eNo ethical approval was required for this study as it only involved publicly available data and no human participants were involved.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eAs the data used in this study were anonymized and obtained from publicly available sources, no consent was required from individual participants.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe data used in this study are available upon request from the corresponding author.\u003c/p\u003e\n\u003cp\u003eCompeting interest\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Health Project of Longyan City Science and Technology Innovation Joint Fund (2024LYF17120; 2024LYF17123) support.\u003c/p\u003e\n\u003cp\u003eAuthors' contributions\u003c/p\u003e\n\u003cp\u003eYuan Shiwei, Yuan Yongchang, Lin Weifeng,Zhang Yuan, Zhong Yongying, Luo XiuQing, Chen Dongco-authored the paper and collected data，Guo Wei, Liu Siyujointly reviewed and revised the paper.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank FDA for providing the data used in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArachchillage, D. 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Differences\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (1), 24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13293-020-00301-y\u003c/span\u003e\u003cspan address=\"10.1186/s13293-020-00301-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5951209/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5951209/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eIntroduction\u003c/b\u003e: HCQ is an antimalarial and immunomodulatory drug widely used to treat autoimmune diseases and other conditions. Despite its significant efficacy, HCQ can cause adverse effects such as gastrointestinal issues, retinal toxicity, and cardiotoxicity. As the application of HCQ in immunotherapy expands, its safety and long-term effects need to be evaluated through big data and clinical observations. In a post-marketing surveillance study conducted from the first quarter of 2004 to the third quarter of 2024, we analyzed HCQ-related adverse events (AEs) from the FAERS database, aiming to provide clinical references for its use.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e: This retrospective pharmacovigilance study, based on the FAERS database, aimed to explore the association between HCQ and adverse events (AEs). AE data from 2004 to 2024 were collected, with adverse event reports of the primary suspected (PS) drugs retrieved from the FAERS database. We filtered and analyzed reports related to HCQ use. Four different methods\u0026mdash;ROR, PRR, MGPS, and BCPNN\u0026mdash;were applied to perform disproportionality analysis on the AEs associated with HCQ.\u003c/p\u003e \u003cp\u003e\u003cb\u003eResults\u003c/b\u003e: The year 2020 had the highest number of AE reports, accounting for 20.44% of the total. In gender-based analysis, women were more likely to report adverse events such as rheumatoid arthritis, disease exacerbation, drug intolerance, nausea, and pain, while men were more prone to report ECG QT prolongation and acute kidney injury. The study highlighted the differences in AE distribution across age groups and genders and pointed out that most AEs occurred within one month of starting HCQ; however, the risk of AEs remained even after two years, emphasizing the importance of long-term monitoring. The findings provided a reference for healthcare professionals and policymakers in developing safer drug usage guidelines.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e: This study emphasizes that HCQ-related adverse reactions are influenced by factors such as gender, age, and underlying diseases, revealing the potential risks associated with the widespread use of HCQ, particularly the risks related to severe adverse reactions. It underscores the importance of continuous drug safety monitoring and suggests the need for individualized risk assessments in clinical settings, especially for patients on long-term use or combination therapies.\u003c/p\u003e","manuscriptTitle":"The real-world pharmacovigilance study based on the FAERS database analyzed the adverse drug events associated with hydroxychloroquine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-24 15:47:26","doi":"10.21203/rs.3.rs-5951209/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-04T05:36:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-03T13:40:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167598378328753297437971128569867705824","date":"2025-04-03T09:18:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-01T08:22:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54197033791973375643372440336191351404","date":"2025-03-22T02:51:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-19T13:13:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T07:16:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-18T15:30:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7749120b-e9ea-48fa-afa2-b10ad5929307","owner":[],"postedDate":"March 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":45913473,"name":"Biological sciences/Drug discovery"},{"id":45913474,"name":"Biological sciences/Drug discovery/Drug safety"}],"tags":[],"updatedAt":"2025-04-24T17:08:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-24 15:47:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5951209","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5951209","identity":"rs-5951209","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}