Post-marketing safety study of Eribulin: a real-world, retrospective pharmacovigilance study leveraging the FAERS database

Post-marketing safety study of Eribulin: a real-world, retrospective pharmacovigilance study leveraging the FAERS database | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 14 March 2025 V1 Latest version Share on Post-marketing safety study of Eribulin: a real-world, retrospective pharmacovigilance study leveraging the FAERS database Authors : Mengqiu Yan 0009-0000-9806-3605 [email protected] , Zhongyi Yang , Yiliu Wu , and dongmei chen Authors Info & Affiliations https://doi.org/10.22541/au.174194849.97303530/v1 314 views 162 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background and objective: Eribulin, a halichondrin, inhibits microtubule dynamics non-taxanely, which showed neuropathy and maintained effectiveness that had developed resistance to paclitaxel. This study evaluates Eribulin-related adverse events (AEs) in real-world settings using the Food and Drug Administration Adverse Event Reporting System (FAERS) data mining. Methods: Retrospectively query FAERS for Eribulin reports from 2010 Q4 to 2024 Q3. Use odds ratio, Bayesian neural networks, and multi-item γ Poisson IC to quantify adverse event signals. To identify and evaluate potential AEs in patients undergoing Eribulin, we used reported odds ratio (ROR) and proportional reported ratio (PRR). Univariable and multivariable logistic regression analyses were applied to investigate the effects of age, weight, and medication time on the occurrence of Eribulin-related AEs. Result: 3,684 Eribulin reports identified. AEs affected 26 organ systems and 100 significantly PTs identified by all four disproportionality methods. New AEs were Myelosuppression, Neutrophil Count Decreased, Interstitial Lung Disease, and Pulmonary Embolism. In females, we identified 37 drug related AEs and in males were total 128. We found there were 203 drug related AEs in the ≥ 65years old. The median time-to-onset was 13 days, and the Weibull distribution test revealed curve types were early failure. Univariate and multivariable logistic regression analysis showed medication time has significant impact on the risk of Blood and Lymphatic System Disorders. Conclusion: Our study validates common AEs and potential safety concerns with Eribulin, enhancing awareness of its toxicities, onset times, outcomes, and clinical priority. Supporting evidence aids clinicians in managing Eribulin safety issues. Post-marketing safety study of Eribulin: a real-world, retrospective pharmacovigilance study leveraging the FAERS database Mengqiu Yan 1†* , Zhongyi Yang 2 , Yiliu Wu 3 , Dongmei Chen 1 Author affiliations: 1 Department of Pharmacy, Xiaolan People’s Hospital of ZhongShan, Zhongshan, Guangdong, PR China 2 School Of Pharmacy, Hennan University, Kaifeng, Henan, PR China 3 Department of Pharmacy, Hengyang City Mental Health Center, Hengyang, Hunan, PR China † Mengqiu Yan and Zhongyi Yang are the first author of the paper. * Correspondence: * Mengqiu Yan, Department of Pharmacy, Xiaolan People’s Hospital of ZhongShan, Zhongshan, Guangdong, PR China; Email: [email protected] . Zhongyi Yang: [email protected] Yiliu Wu: [email protected] Dongmei Chen: [email protected] Background and objective: Eribulin, a halichondrin, inhibits microtubule dynamics non-taxanely, which showed neuropathy and maintained effectiveness that had developed resistance to paclitaxel. This study evaluates Eribulin-related adverse events (AEs) in real-world settings using the Food and Drug Administration Adverse Event Reporting System (FAERS) data mining. Methods: Retrospectively query FAERS for Eribulin reports from 2010 Q4 to 2024 Q3. Use odds ratio, Bayesian neural networks, and multi-item γ Poisson IC to quantify adverse event signals. To identify and evaluate potential AEs in patients undergoing Eribulin, we used reported odds ratio (ROR) and proportional reported ratio (PRR). Univariable and multivariable logistic regression analyses were applied to investigate the effects of age, weight, and medication time on the occurrence of Eribulin-related AEs. Result: 3,684 Eribulin reports identified. AEs affected 26 organ systems and 100 significantly PTs identified by all four disproportionality methods. New AEs were Myelosuppression, Neutrophil Count Decreased, Interstitial Lung Disease, and Pulmonary Embolism. In females, we identified 37 drug related AEs and in males were total 128. We found there were 203 drug related AEs in the ≥ 65years old. The median time-to-onset was 13 days, and the Weibull distribution test revealed curve types were early failure. Univariate and multivariable logistic regression analysis showed medication time has significant impact on the risk of Blood and Lymphatic System Disorders. Conclusion: Our study validates common AEs and potential safety concerns with Eribulin, enhancing awareness of its toxicities, onset times, outcomes, and clinical priority. Supporting evidence aids clinicians in managing Eribulin safety issues. Keywords: Eribulin, adverse drug event, FAERS, disproportionality analysis, pharmacovigilance, real world analysis 1 Introduction Breast cancer is the second most common malignant cancer worldwide, with a yearly growth rate of 11.6% in total cases, and it stands as the fourth primary cause of cancer deaths, responsible for 6.6% of all cancer-related fatalities [1] . Despite significant progress in breast cancer treatment, including breakthroughs in molecular medicine and a deeper understanding of tumor cell biology, systemic chemotherapy remains to play a crucial role in the treatment of metastatic breast cancer in women, especially those with hormone-refractory, hormone receptor-negative, or rapidly advancing metastatic disease [2] . Among the various chemotherapy options available, taxanes and anthracyclines are widely regarded as the most potent for treating breast cancer. However, despite their proven effectiveness, these agents are not universally effective for all patients and are associated with certain tolerability issues, including cardiomyopathy with prolonged anthracycline use and cumulative neurotoxicity with taxane treatment [3] . Until recently, in the United States and Europe, capecitabine was the only chemotherapeutic agent approved for monotherapy to treat metastatic breast cancer that is resistant to both taxanes and anthracyclines. In some other countries, ixabepilone is the sole approved agent for patients whose cancer is resistant to taxanes, anthracyclines, and capecitabine [4] . Therefore, patients with locally advanced or metastatic breast cancer, particularly those with late-stage disease refractory to treatment, urgently require more effective and well-tolerated treatment options. Most importantly, there remains a critical unmet need for treatments that can offer a survival benefit to these patients with refractory late-stage disease. Eribulin mesilate (E7389) belongs to the halichondrin class of antineoplastic drugs and functions as a non-taxane inhibitor of microtubule dynamics. It is a synthetic compound structurally derived from halichondrin B, which is a naturally occurring substance extracted from the rare Japanese marine sponge Halichondria okadai [5, 6] . Eribulin exhibits a unique action mechanism that differs from other tubulin-targeting agents, such as paclitaxel, epothilones and vinca alkaloids as it specifically inhibits the growth phase of microtubules without impacting the shortening phase, leading to the sequestration of tubulin into non-functional aggregates [7] . In preclinical trials, Eribulin was found to cause less neuropathy compared to paclitaxel, and it maintained effectiveness in cell lines that had developed resistance to paclitaxel due to β-tubulin mutations. Therefore, Eribulin has the potential to be effective in patients whose disease is resistant to other tubulin-targeting therapies [8] . The efficacy of intravenous Eribulin for the management of patients with locally advanced, recurrent, or metastatic breast cancer, who have extensively been pretreated, has been thoroughly assessed through numerous clinical trials. In early non-comparative phase I studies enrolling less than 40 patients with advanced solid tumors, which included women with advanced breast cancer, intravenous Eribulin, when administered according to various dosing schedules, showed promising initial therapeutic effects and displayed a predictable and well-tolerated safety profile [9] . In larger phase II trials (n = 299) enrolling patients with locally advanced or metastatic breast cancer previously treated with anthracyclines, taxanes, and capecitabine, Eribulin demonstrated antitumor activity [10] . The promising results from these studies led to the evaluation of Eribulin in a large phase III trial, known as EMBRACE (Eisai Metastatic Breast Cancer Study Assessing Physician’s Choice Versus E7389; study E7389-G000-305). This trial, which focused on patients with metastatic breast cancer, is the main subject of this section. Recently, Eribulin has been approved in the US and the EU for treating patients with locally advanced or metastatic breast cancer (for more details, see section 6) [11] . Additionally, in Japan, Eribulin is approved for the treatment of inoperable and recurrent breast cancer. Given the recognized limitations and observed bias in a single clinical trial when it comes to fully evaluating the safety profile of Eribulin, it is especially necessary and valuable to conduct comprehensive and systematic pharmacovigilance studies based on a real - world large - sample database of AEs for Eribulin when detecting rare, unexpected, and delayed adverse events [12] . Therefore, in order to provide a reference for clinicians and pharmacists to be vigilant in managing safety issues, we carried out this pharmacovigilance study. The purpose was to assess the post-marketing safety profile of Eribulin by conducting a disproportional analysis through data mining of the FDA Adverse Event Reporting System (FAERS). FAERS is one of the largest pharmacovigilance repositories. It has collected more than 15 million unsolicited reports and almost covers a global population (the associated area also includes serious reports from the EU and other non- US countries). This publicly available archive has attracted great interest among clinicians for drug safety assessment [13, 14] . 2 Methods 2.1 Study Design and Data Sources Based on prior experience, an retrospective observational analysis with a non-proportional design mirroring the case/non-case study design was employed to evaluate whether there could be an association between Eribulin and specific AEs [15, 16] . Adverse events related to Eribulin were recognized as more common signals compared to background information in relation to other drug events in the database. All reports submitted to FAERS from the fourth quarter of 2010 (when Eribulin was FDA - approved) to the third quarter of 2024 (the most recent update of the FAERS database during the study) were incorporated into our study. The data is downloaded from FAERS quarterly Data Extract Files, available at https://fs.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html. And provides data in two formats (ASCII packets and XML packets) for downloading. In this study, the original ASCII packets are downloaded for data mining and statistical analysis. The original data is imported into SAS 9.4 software and weighed in accordance with the official weighting guidelines recommended by the FDA [17] . 2.2 Data Extraction and Descriptive Analysis Patients who were included in the analysis and used the target drug were analyzed and described statistically in the patient dimension, in addition, a patient who had multiple adverse events at the same time was counted as only one event. Each report contains orthogonal data regarding patient demographics (age, sex, country), drug/biological information (one or more drugs regarded as suspicious or concomitant), AEs (response to one or more drugs), indication for drug use, start/end date of drug treatment, and serious AEs outcomes. [18-20] . To guarantee the uniqueness of the report, a deduplication process was carried out before the statistical analysis. In line with the method of duplicate-report elimination recommended by FDA, if CASEIDs were the same, the most recent FDA_DT was chosen; if CASEIDs and FDA_DTs were the same, the higher PRIMARYID was chosen In addition, the FDA lists these removals cases every quarter for a variety of reasons. In this study, only reports with the most recent FDA acceptance date were chosen, and the duplicate records were removed by using the CASEIDs as a vital filtering criterion. Additionally, we manually deleted the records that had the same PRIMARYID, patient details, and PTs with a case ID [21, 22] . In the FAERS database, all adverse event names are coded according to the standardized Medical Dictionary for Regulatory Activities (MedDRA® 27.1). Simply put, this means that each adverse event is assigned a specific code determined by the standard terms in MedDRA® 27.0, ensuring that information in the database can be identified and managed uniformly and accurately. Since the adverse event names in the FAERS database are described using the preferred term (PT) in MedDRA, which is updated annually in March and September, each update involves adjustments to the hierarchy of PT and changes in the corresponding system organ classification (SOC), consequently, the PT names in the FAERS database are recalibrated using the latest version of the MedDRA dictionary. The terminology features a five-level hierarchy, with SOC at the apex and the most specific terms at the base, enabling flexible data retrieval based on the desired level of detail. Our studies concentrated on the commonly utilized PT and SOC levels. Whenever data were accessible, we meticulously compiled detailed information encompassing patient demographics, reporting nations, indications, outcomes (both serious and non-serious), time to onset (TTO), concurrent medications, and the year of reporting. Figure 1 displays a flowchart outlining the multi-step procedure for data extraction, processing, and analysis. Statistical analysis was conducted using SAS 9.4 for all data processing, and the SAS software is one of the statistical analysis software recommended by the FDA website for FDA FAERS database mining [23, 24] . 2.3 Statistical Analysis ROR, algorithm and PRR algorithms are both frequency (non-Bayesian) algorithms, compared with the PRR algorithm, the advantage of the ROR algorithm is that it can correct the bias caused by the small number of reports of some events [25] . The advantage of PRR over ROR is that it is less affected by the omission of adverse events. In summary, the non-Bayesian approach, also known as frequency method, is straightforward and exhibits high sensitivity; however, it carries a significant risk of false positives when the number of adverse events is low. The BCPNN and MGPS algorithms are both Bayesian algorithms [26] . BCPNN excels in integrating data originating from multiple sources and performing cross-validation, while MGPS has the advantage of detecting signals stemming from rare events. The Bayesian approach exhibits stability by taking account of the uncertainty in disproportionate rates when dealing with a small number of reports [27] . It reduces the risk of false positives and is applied for pattern recognition in higher dimensions. However, it is computationally intensive and associated with a relatively delayed signal detection time [28] . Therefore, this study applys a combination of multiple algorithms, leveraging the strengths of each to broaden the detection scope, and validates the results through multiple perspectives to ensure the identification of more comprehensive and reliable safety signals. In this study, PTs reporting counts of 3 or more were chosen for the preliminary screening. The thresholds for signal detection in each algorithm were established based on authoritative methods, with the specific formulas and thresholds outlined in Table 1. Based on the 2 by 2 contingency table, we determined the p-value using the chi-square (χ 2 ) test as showed in Table2. We display a volcano plot where the horizontal axis represents the log2-transformed ROR values and the vertical axis represents the -log10-transformed adjusted p-values (P.adj, corrected by FDR), using the R package “ggplot2”(version 3.5.1). Under the criterion that the volcano plot generates differential signals with a significance level of p<0.05, in order to identify signals with greater statistical differences. In the FAERS, reports were categorized as either serious or non-serious upon submission. The listings of severe and non-severe cases were separated to elucidate the results of identified significant signals and to evaluate the potential risk factors (gender, age, and reporters) in patients [29, 30] . To investigate the factors influencing the occurrence of adverse reactions to Eribulin in the real world, we analyzed the relationships between adverse reactions and various variables, including age categories (<18 [pediatric and adolescent], 18-44 [adult], 45-64 [middle-aged], ≥65 [elderly]), gender (male and female), report type (serious and non-serious), and reporter type (consumer and healthcare professional). We utilized Pearson’s Chi-squared test or Fisher’s exact test to compare proportions, while the Mann-Whitney U test was employed for analyzing continuous data with non-normal distributions. Data analysis was conducted using SPSS (version 22.0, IBM Corp., Armonk, NY, USA), with statistical significance determined at p < 0.05 and R 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria). 2.4 TTO Analysis The time interval of Eribulin administration and the occurrence of AEs was defined as the onset time of the AE. Prior to analysis, we conducted a deduplication process and removed any invalid data. In our study, we assessed the characteristics of TTO using the median (with Inter-quartile Range [IQR]), minimum-maximum values and Weibull shape parameter to comprehensively assess TTO characteristics in our study. The Weibull distribution test, characterized by scale (α) and shape (β) parameters, can be utilized to identify and predict changes in the risk incidence of ADEs over time. In this research, our primary focus is on the parameter β. If the shape parameter β is less than 1, and its 95% confidence interval (CI) also falls below 1, it indicates that the risk of adverse effects diminishes over time, suggesting an early failure-type curve. In contrast, if β is roughly equal to 1 and its 95% CI includes the value of 1, the risk is expected to remain consistent over time, indicating a random failure-type curve. Lastly, if β exceeds 1 and its 95% CI does not include the value of 1, the hazard is understood to be escalating over time, typical of a wear-out failure-type curve. All WSP analyses were conducted using Minitab statistical software, version 20.0 (Minitab LLC, State College, PA, USA). 2.5 Univariable and multivariable logistic regression analyses We conducted univariable and multivariable logistic regression analyses to examine the effects of age, gender, and medication time on the occurrence of Eribulin-related AEs. After excluding irrelevant variables, variables were finally included in the univariate logistic regression analyses. The strength of the associations between these variables was quantified using the odds ratio (OR) with a 95% confidence interval (CI). Variables that showed a significant association with with p values <.05 in the univariate analyses were included in the multivariable regression analysis. A significant difference was defined as a two-tailed p value < .05. 3 Results 3.1 General characteristics From 2010 Q4 to 2024 Q3, the FAERS database documented a total of 19,120,845 reports during the surveillance period. 3,684 case reports related to Eribulin medication were analyzed after removing duplicates. Table 3 provides comprehensive demographic and clinical details. Among the 3,600 patients with available gender information, females experienced a significantly higher proportion of AEs, accounting for 90.10%, in contrast to males. Among the 1981 case reports with clear weight information, patients weighing between 50 and 100 kg (40.70%) accounted for a larger proportion than others. In terms of age distribution, patients whose age were between 45 and 64 years accounted for a higher proportion of Eribulin-related AEs (45.28%) than patients under 45 years old and patients whose age over 64 years old. Additionally, a substantial number of patients, 91.58% (n=3,374), suffered serious outcomes, such as hospitalizations (n=1770 cases, 48.0%), deaths (n=491 cases, 16.0%), and life-threatening conditions (n=165 cases, 4.50%), based on available follow-up information. Concerning reporting sources, 62.10% of AEs reports were submitted by 2,289 physicians, 5.80% of AEs-related Eribulin were reported by pharmacists, and other health professionals (7.70%). In contrast, 52.41% of AEs were reported by 5,278 consumers, while 1.90% were reported by 70 unknown individuals. Table 3 reveals that the United States reported the highest number of AEs cases related to Eribulin, totaling 1,153 and accounting for 31.30% of the overall cases. China followed with 632 cases (17.20%), and United States with 519 cases (14.10%). Breast Cancer was the most reported indication (35.00%), followed by Breast Cancer Metastatic (20.60%). As shown in Figure 2, most cases occurred within the first month (n = 1,681, 66.49%) with Eribulin administration. The number of AEs decreased over time, with 324 AEs (12.82%) occurring in the second month and 168 AEs (6.65%) in the third month. Notably, in 1.86% of cases, adverse drug events could still occur even after 1 year of treatment with Eribulin. Figure 3 shows the annual distribution of Eribulin-related ADE reports. The lowest and highest number of reports were documented in 2022 (42 reports) and in 2013 (397 reports), respectively. The annual distribution of Eribulin-related ADE reports showed The number of AEs reported were increasing year by year since 2015. These results highlight the widespread clinical use and efficacy of Eribulin and emphasize the significance of enhancing the identification of Eribulin-related adverse drug reactions for its association with serious adverse events in clinical practice. 3.2 The proportion of suspected adverse events under SOC level with Eribulin Table 4 and Figure 4 presents the report on signal strengths of Eribulin at the System Organ Class level. Our analysis revealed that Eribulin-induced AEs affected a total of 26 organ systems, which suggested that Eribulin-related ADRs were relatively common. Ranked by frequency of AEs occurrence, the top five SOCs were Blood and Lymphatic System Disorders (n = 1853, 24.32%), General Disorders and Administration Site Conditions (n = 836, 10.97%), Investigations (n = 734, 9.63%), Gastrointestinal Disorders (n = 651, 8.54%), Respiratory, Thoracic and Mediastinal Disorders (n = 616, 8.08%). The four criteria were met by the SOCs of Blood and lymphatic system disorders and Hepatobiliary disorders. To improve visualization, we present with a forest plot format, arranged in ROR and its 95% confidence interval for Eribulin-associated SOC signal strength. 3.2 Signal detections at prefer terms level During the study, four algorithms were utilized to investigate adverse drug reactions and determine if they satisfied the filtering criteria of all four methods. Figure 5 and Supplementary Table S1 present the 100 most significantly disproportionate PTs, identified simultaneously by all four disproportionality analysis methods and ranked by the number of cases. Among them, 20 PTs including Neutropenia(n = 414, ROR 53.83, IC025 5.51), Febrile Neutropenia (n = 414, ROR 53.83, IC025 5.51), Leukopenia (n = 197, ROR 33.87, IC025 4.83), Anaemia (n = 121, ROR 5.09, IC025 2.07), Thrombocytopenia (n = 78, ROR 5.89, IC025 2.22), Mucosal Inflammation (n = 48, ROR 15.46, IC025 3.52), Pneumonia (n = 118, ROR 2.92, IC025 1.26), Sepsis (n = 90, ROR 6.62, IC025 2.41) and so on were consistent with the drug instructions published by FDA. Interestingly, there were 80 new and unexpected Eribulin-associated AEs that statistically met four algorithms, such as Myelosuppression (n = 347, ROR 118.07, IC025 6.63), Neutrophil Count Decreased (n = 207, ROR 42.08, IC025 5.14), Interstitial Lung Disease (n = 168, ROR 29.58, IC025 4.62), Pulmonary Embolism (n = 49, ROR 4.26, IC025 1.67). Furthermore, the top 30 positive signal of these PTs of Eribulin were grouped by SOC and ranked the PTs in descending order according to the ROR, as shown in Table 5 and Supplementary Figure 1. Next, to improve visualization, we present the 10 PT signals with a volcano plot, arranged in descending order of case number, highlighting those with higher risk significance. We ranked the detected ADE signals by their signal strength according to the magnitudes of the ROR values and the χ 2 values. As shown in the Figure 6, the larger the circle, the greater the number of events, the closer to the upper right corner, the greater the ROR and chi-square, and the stronger the signal, which that contains Myelosuppression (n = 347, ROR 118.07, χ 2 37758.26), Febrile Neutropenia (n = 414, ROR 53.83, χ 2 20134.7), Neutropenia (n = 559, ROR 35.05, χ 2 17045.56) Neutrophil Count Decreased (n = 207, ROR 42.08, χ 2 8022.41), Malignant Neoplasm Progression (n = 305, ROR 24.88, χ 2 6683.83) and so on. 3.3 Subgroup analysis of signals for preferred terms To investigate the influence of gender on the adverse effects of Eribulin, we applied the ROR method and identified 167 PTs with a disproportionate incidence of AEs between males and females, classified by SOC. The findings are illustrated in Figure 7A, and the complete data set is provided in Supplementary Table S2. The study found that males are more prone to develop Leukopenia, Interstitial Lung Disease, Dyspnoea, Platelet Count Decreased, Oedema Peripheral, Muscular Weakness, Confusional State, Drug Ineffective, Dysphagia, Dysphagia and Peripheral Sensory Neuropathy, while females are more prone to suffer from Nausea, Fatigue, Vomiting, Alopecia, Mucosal Inflammation, Dizziness, Dehydration and Cough. Of note, both males and females commonly suffer from Neutropenia and Febrile Neutropenia, however, males are at a higher risk of developing hematologic ADEs, whereas females show a stronger association with gastrointestinal disorders compared to males. To investigate gender differences in the adverse event signals identified for Eribulin, we created a ”volcano diagram” to visually represent the signals and analyze the results of gender-specific AEs signal extraction for Eribulin (Figure 7B). The volcano plot performs the -Log10p-value scale on the y-axis and the Log2ROR value scale on the x-axis. Each point on the plot represents a specific pairing of the drug and an adverse reaction. Blue dots on the plot signify potential adverse event signals in female patients, whereas purple dots signify potential adverse event signals in male patients. Additionally, Figure 7 emphasizes significant adverse event signals that exhibit notable Log2ROR and -Log10p values, complete data set is showed in Supplementary Table S3. In the analysis of the four age subgroups (Figure 7C and D), at the same time,we divided all the cases into ≥ 65years old and < 65 years old, ROR was used to assess the risk of age specific ADRs, and we found that there were 203 drug related AEs in the ≥ 65years old group, such as Neutropenia, Febrile Neutropenia, Interstitial Lung Disease, Leukopenia, Decreased Appetite, Sepsis. While Malignant Neoplasm Progression, Myelosuppression, Pyrexia, White Blood Cell Count Decreased, Asthenia, Neutrophil Count Decreased, Nausea was more likely to occur in < 65 years old group. In addition, according to the WHO age classification standard, we made age-differentiated risk signal heat map for Eribulin related AEs. The darker the circle color, the greater the risk of a specific AEs. As shown in Fig.4E, there are 13 AEs to occur in in people of all ages, including Respiratory Failure, Pyrexia, Pneumothorax, Pleural Effusion, Peripheral Sensory Neuropathy, Neutropenia, Myelosuppression, Malignant Neoplasm Progression, Febrile Neutropenia, Fatigue, Dehydration, C-Reactive Protein increased, Bacteraemia. Noteblely, Pneumothorax, Peripheral Sensory Neuropathy, Neutropenia, Myelosuppression, Malignant Neoplasm Progression, Febrile Neutropenia were likely to occur in patients over the age of 75. And Under 18 patients were high-risk population for adverse reactions. All in all, combining this information would be essential for enhancing clinical management, enabling clinical decision-makers to customize treatments based on the unique characteristics of specific subgroups (Figure 7). 3.4 TTO Analysis After excluding reports with inaccurate, missing, or unknown onset information, 2,528 Eribulin-associated reports contained time-to-onset data were collected, Kaplan-Meier curves to explore the time to onset of five age groups (<18 years old, 18-44 years old, 45-64 years old, 65-74 years old, ≥75 years old) in response Eribulin based on data from the FAERS in Figure 8. The log-rank test indicated cumulative incidence statistically significant differences between the five age groups treated with Eribulin (log-rank test, P< .0001). To assess whether the risk of AEs associated with Eribulin changes over time, we performed Weibull distribution tests on the overall patient population as well as on different age subgroups (Table 6). Overall, the median time-to-onset was 13 days (interquartile range [IQR] 7-19 days), the calculated shape parameter (β) was 0.70 and the upper limit of its 95% confidence interval (CI) was 0.72. Both values were below 1, indicating a decline in the prevalence of AEs over time. In the subgroup analyses based on age, it is noteworthy that β values were below 1 for five age groups. Additionally, the Weibull distribution test indicated that all curves exhibited early failure characteristics. Detailed statistical descriptions for the various TTO subgroups can be found in Table 6. 3.5 Univariate and multivariable logistic regression analysis In the analysis of Eribulin related AEs at the System Organ Class SOC level, Blood and Lymphatic System Disorders met four algorithms, the most frequent Eribulin related AE and the most intense ROR signal. After deduplication and filtering with “role_cod=PS” (primary suspect drug), all reports with missing values in age, gender, or duration of use were removed. We manually reviewed each report to ensure the completeness and rationality of the information, thereby ensuring the reliability of the data. After excluding mixed data interference, Eribulin was included in 1,534 cases. Therefore, univariate and multivariate logistical regression analyses were employed to determine the odds ratio (OR) of Blood and Lymphatic System Disorders associated with Eribulin under gender, age and medication time exposure factors. Finally, the univariate logistic regression analysis results showed no significant differences in gender and age (p < 0.05), while compared to the medication time less than 7 days, 8 ≤ days < 30 (OR, 0.63; CI, 0.47 - 0.85, p = 0.002 ), 30 ≤ days < 90 (OR, 0.46; CI, 0.35 - 0.60, p < 0.001), 90 ≤ days < 180 (OR, 0.45; CI, 0.32 - 0.63, p < 0.001) were significantly associated with the risk of Blood and Lymphatic System Disorders, and the risk of adverse reactions significantly reduced along with prolonged administration. Then only medication time was included in the multivariable logistic regression analysis. The results were consistent with the univariate logistic regression analysis, 8 ≤ days < 30, 30 ≤ days < 90, 90 ≤ days < 180 have a significant impact on the risk of Blood and Lymphatic System Disorders. The results indicated patients with the administration in a short time were more likely to develop Blood and Lymphatic System Disorders. The OR values were 0.63,0.6,0.46 and 0.45 respectively, the 95%CI did not include 1, further confirming the influence of medication time on the AE, and the effect remained stable after controlling for other factors. However, because age and gender showed no significant difference in the multivariate model, they cannot evaluate the effect on Blood and Lymphatic System Disorders in the multivariate level, but from the univariate logistic regression analysis results, they had no significant effect on the AE. In conclusion, univariate logistic regression analysis showed that medication time affected the risk of Blood and Lymphatic System Disorders. The results of this study can provide a reference for clinical medication and adverse reaction prevention, especially the effect of medication time on the risk of adverse reactions. 4 Discussion The efficacy of intravenous eribulin in the treatment of patients with extensively pretreated locally advanced/recurrent or metastatic breast cancer has been evaluated in several clinical trials. There is a lack of comprehensive studies on the possible adverse events associated with Eribulin yet. This study is the first pharmacovigilance study of Eribulin-related AEs based on real-world data from the FAERS database. Using the full FAERS database as a comparator, we identified new and unexpected adverse events that were highly relevant to the treatment of Eribulin by disproportionality analysis, explored the clinical characteristics of the reports in which such adverse reactions occurred, investigate the risk of adverse reactions occurring at different ages, genders, and medication times, explored risk factors of Eribulin related AEs by logistic regression analysis and supplement the onset profiles of Eribulin associated AEs. Our analysis revealed that Eribulin-induced AEs affected a total of 26 organ systems, significant SOCs identified by the four algorithms included Blood and Lymphatic System Disorders (n = 1853, 23.32%), Hepatobiliary disorders (n = 192, 2.52%), which was either reported in clinical trials or indicated in the drug label. During the study, 100 PTs were identified as significantly disproportionate satisfied all four methods of disproportionality analysis concurrently. Among them, 20 PTs including Neutropenia(n = 414, ROR 53.83, IC025 5.51), Febrile Neutropenia (n = 414, ROR 53.83, IC025 5.51), Leukopenia (n = 197, ROR 33.87, IC025 4.83), Anaemia (n = 121, ROR 5.09, IC025 2.07), Thrombocytopenia (n = 78, ROR 5.89, IC025 2.22), Mucosal Inflammation (n = 48, ROR 15.46, IC025 3.52), Pneumonia (n = 118, ROR 2.92, IC025 1.26), Sepsis (n = 90, ROR 6.62, IC025 2.41) and so on were consistent with the drug instructions published by FDA. This finding was validated in our study, further demonstrating the reliability of our results. It must be mentioned that there were 80 new and unexpected Eribulin-associated AEs that statistically met four algorithms, such as Myelosuppression (n = 347, ROR 118.07, IC025 6.63), Pneumonia (n = 118, ROR 2.92, IC025 1.26), Interstitial Lung Disease (n = 168, ROR 29.58, IC025 4.62), Pulmonary Embolism (n = 49, ROR 4.26, IC025 1.67). A post-marketing observational study was conducted to evaluate the real-world efficacy and safety of Eribulin in Japanese patients with Soft Tissue Sarcomas (STSs), categorized by subtype (L-type and non-L-type), over a 2-year follow-up period. The safety profile observed in this study aligns with the established safety profile of Eribulin, with the primary adverse drug reactions being related to myelosuppression [31] . In compliance with this, the California Cancer Consortium completed a Phase I trial in patients with advanced Solid Tumors of Eribulin was to determine the pharmacodynamics and pharmacokinetics. The trial results indicated that E7389 was well-tolerated, with myelosuppression being the primary toxicity observed. In vivo, toxicology studies of E7389 given i.v. once daily on days 1, 5, and 9 produced bone marrow depression in dogs and rats, intestinal toxicity in dogs, and liver toxicity in rats. Reversible myelosuppression occurred in dogs given 0.03 mg/kg/day (0.6 mg/m²/day) on days 1, 5, and 9 [31] . Besides, A single arm, phase two study of low‑dose metronomic Eribulin in metastatic breast cancer was conducted, all patients were treated with metronomic Eribulin (0.9 mg/m 2 ) administered intravenously on days 1, 8, and 15 of a 28-day cycle.) . The result revealed that metronomic weekly low dose eribulin is an active and tolerable regimen with signifcantly less myelosuppression, alopecia, and peripheral neuropathy than is seen with the approved dose and schedule, allowing longer duration of use and disease control, with similar outcomes compared to the standard dose regimen [32] . These views were consistent with our findings. Although the drug label of Eribulin has not makered this AE, we cannot ignore the possible negative impact of Eribulin on the blood and lymphatic system. There is no denying that it has become a class of AEs that needs to be paid sufficient attention, and It is essential to conduct further research to explore the importance of this adverse event and its correlation with Eribulin. In addition, a real-world pharmacovigilance study of the FDA Adverse Event Reporting System about Drug-induced interstitial lung disease showed eribulin were one of the highest strengths of association with interstitial lung disease [33] , this study findings are in line with ours. As mentioned earlier in the baseline profile description, we observed proportional variations in the gender distribution of AEs. Indeed, it is imperative to take into account the analysis of gender differences when evaluating drug safety, as this enables more accurate management of AEs [34] . Our findings show that Eribulin-related AEs occur more frequently in females (90.10%) than in females (7.60%). This can be attributed to Eribulin is indicated for the treatment of patients with metastatic breast cancer who have previously received at least two chemotherapeutic regimens for the treatment of metastatic disease. Female breast cancer is the most commonly diagnosed cancer (11.7% of total cases) and accounts for 1 in 4 cancer cases and for 1 in 6 cancer deaths [2, 35] . In terms of age distribution, patients whose age were between 45 and 64 years accounted for a higher proportion of Eribulin-related AEs (45.28%) than patients under 45 years old and patients whose age over 64 years old. In the Subgroup analysis, we identified 37 drug related AEs. High-risk AEs in males total 128, included Febrile Neutropenia, Leukopenia, Pyrexia, Interstitial Lung Disease, Pneumonia, Dyspnoea and so on. we found that there were 203 drug related AEs in the ≥ 65years old group, such as Neutropenia, Febrile Neutropenia, Interstitial Lung Disease were likely to occur in < 65 years old group. This may be due to the concentration of breast cancer incidence at 45-64 years old. in China, breast cancer is most frequently diagnosed in the 40–50-year age group with a mean age of 48–49, which is more than 10 years younger than that reported in Western countries [36] . In China, the incidence of female breast cancer is closely linked to age. The rate is relatively low among women up to 30 years old and then rises rapidly, reaching a peak at the beginning of the fifth decade. Of the breast cancer cases admitted in China, about two-thirds are diagnosed in women aged 40-59, while only a small proportion (approximately 6%) are diagnosed in those aged 70 and over [37, 38] . The occurrence rate of adverse events after the commencement of treatment depends on the drug’s mechanism of action and may fluctuate over time. In the evaluation of drug safety, it is essential to assess the interval between drug administration and the occurrence of AEs. This examination can elucidate the mechanisms behind AEs, pinpoint specific time windows of risk during treatment, and enable earlier intervention or diagnosis of adverse reactions [39] . 2,528 Eribulin-associated reports contained time-to-onset data were collected, Overall, the median time-to-onset was 13 days (interquartile range [IQR] 7-19 days), the calculated shape parameter (β) was 0.70 and the upper limit of its 95% confidence interval (CI) was 0.72. Both values were below 1, indicating a decline in the prevalence of AEs over time. Additionally, the Weibull distribution test revealed that all curve types were early failure. However, AEs continued to occur over time in both the subgroup of individuals under 18 years old and the subgroup of those over 77 years old. This suggests that ongoing monitoring for Eribulin-related AEs is particularly necessary in these two subgroups. The WSP test revealed that the adverse drug reaction associated with Eribulin was characterized by an early failure-type profile, suggesting that the risk of Eribulin-associated AEs increased at an earlier stage of treatment and then gradually decreased over time. These results emphasize the importance of clinicians closely observing patients during the early stages of treatment to promptly identify immune responses or organ impairment. In conclusion, our findings stress the necessity for ongoing vigilance in clinical settings. Logistic regression results showed that medication time affected the risk of Blood and Lymphatic System Disorders, whereas the univariate logistic regression analysis results showed no significant differences in gender and age. These findings demonstrate a significant correlation between course of treatment and adcerse events of Eribulin, offering valuable information for future research. Nonetheless, because of the inherent limitations of the FAERS database including incomplete data and reporting bias, further verification through prospective studies is required. The timing of administration in relation to the risk of developing adverse reactions is vital for evaluating drug safety, as it helps pinpoint specific risk windows. This allows clinicians to assess the individual risk associated with Eribulin, make sound clinical decisions, and provide patients with the best possible treatment. This study, for the first time, comprehensively documented and evaluated the safety of post-marketing administration of Erubulin based on the largest sample of realworld data to date. However, some limitations remain.Firstly, the FAERS has inherent limitations due to underreporting, incomplete data, and biased reporting. Milder or more common adverse events might not be reported as frequently, whereas more severe or rare events could be over-reported. [40, 41] . Therefore, when interpreting the results, it is essential to carefully consider potential biases inherent in the data. Secondly, the lack of detailed clinical information on patients, including comorbidities, the severity of underlying disease, and concomitant medications, further complicates the control for confounding factors. [42] . Thirdly, disproportionality analyses are limited to evaluate signal strength and establishing statistical correlations; they are unable to quantify risk or determine causality [43, 44] . Despite the inherent limitations of using the FAERS database for pharmacovigilance studies, a comprehensive characterization of ADEs related to Erubulin in this study may provide insightful evidence for safe use and further clinical studies. 5 Conclusion In conclusion, our comprehensive and systematic pharmacovigilance analysis of the FAERS database identified several common and rare side effects of Eribulin use and their associated timing. It is recommended to carefully monitor all patient populations and assess the risk of these adverse reactions. While our study provides valuable safety evidence for Eribulin, it is essential to thoroughly consider the inherent limitations of the FAERS database, along with potential confounders and biases. This calls for a more cautious interpretation of our analysis results. Furthermore, future prospective clinical trials and epidemiological studies will provide a more accurate evaluation of the safety risks associated with Eribulin. Data availability statement The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed at the corresponding author. Ethics statement There are no ethical issues involved in this study. Author contributions MY and ZY contributed to the design of the study protocol. YW performed the statistical analysis. ZY and DC drew the picture. MY, ZY and YW contributed to the writing of the study protocol and made the final corrections to this manuscript. MY and ZY finally corrected the manuscript. All authors read and approved of the final manuscript. Funding No funding supported. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. References [1] SUNG H, FERLAY J, SIEGEL R L, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries [J]. 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A real-world disproportionality analysis of Rucaparib: Post-marketing Pharmacovigilance Data [J]. BMC Cancer, 2023, 23(1): 745.[44] JI C, BAI J, ZHOU J, et al. Adverse event profiles of PCSK9 inhibitors alirocumab and evolocumab: Data mining of the FDA adverse event reporting system [J]. Br J Clin Pharmacol, 2022, 88(12): 5317-25. Figure 1. Flowchart for obtaining data on target adverse drug reactions. Figure 2. Time onset (TTO) analysis (counted in days) of Eribulin-related AEs at the overall level. The line chart illustrates the distribution of TTO reports across various time periods. Figure 3. Distribution of ADEs of Eribulin from 2011 Q3 to 2024 Q4. Figure 4. The frest plot of positive signal for Eribulin related AEs at the System Organ Class SOC level. *Indicates statistically significant signals in algorithm. Figure 5. The Venn diagram of Eribulin related AEs at the PT level conforming to the four algorithms. Figure 6. The High-risk signal volcano plot. Figure 7. Analysis of gender/age differentiated risk signals in Eribulin. (A)The forest plot of reporting odds ratios (ROR) with 95% CI for all positive gender-related AEs. (B) Gender-differentiated risk signal volcano plot forEribulin.(C) The forest plot of reporting odds ratios (ROR) with 95% CI for all positive age-related AEs ( divided into > 65years old and > 65 years old) .(D) Age-differentiated risk signal volcano plot for Eribulin. (E) According to the WHO age classification standard, age-differentiated risk signal heat map for Eribulin. The horizontal coordinate shows the log2 ROR value and the vertical coordinate indicates the adjusted p-value after -log10 conversion. Significant signals are highlighted and annotated in prominent colors. The p-value is adjusted with false discovery rate (FDR) method. Figure 8. Cumulative distribution function of Eribulin by time-to-onset. This figure demonstrates the cumulative time to onset of AEs associated with oral administration of Eribulin as well as the median time to onset. Significant difference was observed in the cumulative incidence of AEs between patients treated with Eribulin (log-rank test, P <0.0001). Supplementary Material File (table1.docx) Download 12.39 KB File (table2.docx) Download 11.51 KB File (table3.docx) Download 17.23 KB File (table4.docx) Download 18.01 KB File (table5.docx) Download 16.61 KB File (table6.docx) Download 16.76 KB File (table7.docx) Download 17.55 KB Information & Authors Information Version history V1 Version 1 14 March 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords adverse drug reactions clinical pharmacology drug regulation drug safety pharmacovigilance Authors Affiliations Mengqiu Yan 0009-0000-9806-3605 [email protected] Zhongshan Xiaolan Renmin Hospital View all articles by this author Zhongyi Yang Henan University School of Pharmacy View all articles by this author Yiliu Wu Hengyang City Mental Health Center View all articles by this author dongmei chen Zhongshan Xiaolan Renmin Hospital View all articles by this author Metrics & Citations Metrics Article Usage 314 views 162 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Mengqiu Yan, Zhongyi Yang, Yiliu Wu, et al. Post-marketing safety study of Eribulin: a real-world, retrospective pharmacovigilance study leveraging the FAERS database. Authorea . 14 March 2025. DOI: https://doi.org/10.22541/au.174194849.97303530/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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