Cardiotoxicity associated with different 5-HT3RAs: pharmacovigilance analysis of the FDA Adverse Event Reporting System database study and a pharmacokinetic study

Cardiotoxicity associated with different 5-HT3RAs: pharmacovigilance analysis of the FDA Adverse Event Reporting System database study and a pharmacokinetic study | 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 Research Article Cardiotoxicity associated with different 5-HT3RAs: pharmacovigilance analysis of the FDA Adverse Event Reporting System database study and a pharmacokinetic study Yijun Cai, Shaohong Luo, Shen Lin, Xiaoting Huang, Xiangzhen Wang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6213342/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose To comprehensively compare the risk of cardiotoxicity with 5-HT3RAs and to explore the underlying pharmacokinetic factors that might partially contribute to cardiotoxicity. Methods The FDA Adverse Event Reporting System (FAERS) data (January 2004 to March 2023) were extracted. Disproportionality analysis by calculating the relative odds ratio (ROR) and sensitivity analyses were conducted to assess cardiac risk signals of 5-HT3RAs. Additionally, various parameter distributions were tested for time-to-onset analysis to describe the latency of cardiac AEs induced by 5-HT3RAs. Physiologically based pharmacokinetic (PBPK) models were developed to study the drug distribution characteristics in cardiac tissues. Results A total of 1,174 reports of cardiotoxicity related to 5-HT3RAs (including ondansetron, granisetron and palonosetron) were identified in the FAERS database. Ondansetron had an electrocardiogram QT prolonged ROR 025 of 11.21, while that of granisetron and palonosetron were 1.07 and 3.42, respectively. Removing cases with diagnosed heart disease and electrolyte disorders at baseline, all cardiotoxicity signals persisted except the arrhythmia signal in palonosetron. The median onset time of cardiac AEs associated with 5-HT3RAs was 0.5 days (interquartile ranges (IQR): 0.5–7.5 days). Notably, palonosetron demonstrated a longer latency than ondansetron and granisetron, which exhibited similar time-to-onset (TTO) values. The PBPK model extrapolation results showed that ondansetron concentration in cardiac tissue was 2.3 times higher than that in plasma, which might support that it is more susceptible to cardiotoxicity. Conclusion It suggested prioritizing low cardiac toxicity 5-HT3RAs for patients especially for those with heart diseases, and strengthening the monitoring and management of cardiac toxicity further. FAERS database 5-HT3RAs PBPK model pharmacovigilance analysis cardiotoxicity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Nausea and vomiting are the most prevalent and distressing adverse events (AEs) experienced by cancer patients undergoing chemotherapy[ 1 ]. The drugs 5-HT3 receptor antagonists (5-HT3RAs), a class of commonly used clinical antiemetic agents, play a pivotal role in the prophylaxis of acute and delayed nausea and vomiting, including chemotherapy-induced nausea and vomiting (CINV), radiotherapy-related and postoperative nausea and vomiting[ 2 , 3 ]. However, as a commonly used adjuvant drug for cancer patients, the AEs of 5-HT3RAs receive insufficient attention, probably attributed to that people are more concerned about the response and toxicity of tumor treatment drugs[ 4 ]. According to FDA drug label, ondansetron and granisetron were categorized as high cardiotoxicity risk drugs in the Drug-Induced Cardiotoxicity Rank[ 5 ]. However, the warnings primarily emphasize the risk of QT interval prolongation, with a significant lack of evidence concerning other AEs in the cardiac system. Additionally, a series of case reports observed torsade de pointes (TdP), bradycardia and cardiac arrest after 5-HT3RAs infusion[ 6 – 8 ], which has drawn researcher attention to cardiotoxicity associated with 5-HT3RAs. As a vital organ of the body, heart damage may lead to grave even fatal adverse consequences, especially for those patients with heart disease. Currently, there appears to be a relative scarcity of comprehensive comparative research on the cardiotoxic AEs associated with different 5-HT3RAs on a significant scale. Given the widespread global use of 5-HT3RAs and the serious hazards of cardiac AEs, it is imperative to commit more detailed and specific comparisons for drugs among 5-HT3RAs, which might provide evidence-based reference for prescribing optimal 5-HT3RAs to patients. Generally, the target tissues or site-specific drug concentration is the most direct indicator of safety, which might partially explain some concentration-related adverse reactions. It is reported that ondansetron exerts a more pronounced inhibitory effect on human cardiac K + HERG channels than other 5-HT3RAs[ 9 ]. This enhanced blockade may contribute to prolonged cardiac repolarization, occurring with a concentration-dependent manner[ 9 ]. It is important to evaluate the exposure levels of 5-HT3RAs in cardiac tissues to further investigate the potential contributors of cardiotoxicity. Physiologically based pharmacokinetic (PBPK) model is an effective tool for surveying the time-varying process of drug exposure level in tissues and organs by simulating the absorption, distribution, metabolism, and excretion process of drugs in the body. This study aimed to investigate the signal of cardiotoxicity associated with 5-HT3RAs utilizing The FDA Adverse Event Reporting System (FAERS) database and examine the cardiotoxicity reasons from the perspective of pharmacokinetics by a PBPK model. 2 Methods 2.1 Overview First, we described the clinical features of cardiotoxicity AEs related to 5-HT3RAs by analyzing data from the FAERS database. Then, the association between 5-HT3RAs and cardiotoxicity was assessed by analyzing metrics such as time-to-onset (TTO) and disproportionality scores. Finally, PBPK modeling was constructed to extrapolate the drug concentration distribution profile of ondansetron, which showed the strongest signal in cardiotoxic AEs and thereby provided a comprehensive perspective of drug safety ( Graphical Abstract ). 2.2 Data sources and study design (FAERS) FAERS is a robust pharmacovigilance database designed to aid regulatory bodies and healthcare practitioners in surveilling and overseeing drug safety, identifying potential safety concerns associated with medications, and ensuring public medication safety. It contains AE reports from healthcare providers, pharmaceutical companies, and patients (https://fis.fda.gov/extensionS/FPD-QDE-FAERS/FPD-QDE-FAERS.html), which provide information about various adverse reactions triggered by drug use, drug misuse, and manufacturing problems. FAERS data from January 2004 to March 2023 were extracted and analyzed. The initiation time was selected based on the earliest time that relevant data were accessible in the FAERS database following FDA approval of the 5-HT3RAs medicines (including ondansetron, granisetron, palonosetron, dolasetron, and tropisetron)[10]. The flowchart of the FAERS analysis methodology is presented in Fig. 1 and additional files. 2.3 Definition of cases and drugs of interest The Medical Dictionary for Regulatory Activities (MedDRA) (version 26.0) Concept Libraries was used to standardize and map adverse drug reaction (ADR) descriptions within the FAERS database, employing preferred terms (PTs) for consistency. The detailed ADRs of interest are listed in Supplemental Table S3 . Both generic and brand names sourced from Drugbank were input as keywords for the database retrieval. Only 5-HT3RAs with over 100 AE reports in FAERS database were included for analysis[11] (tropisetron with only 15 AEs was excluded). To mitigate potential influence of confounders associated with non-cardiac AEs, our study exclusively focused on cases where 5-HT3RAs were designated as the 'primary suspect' for cardiotoxic AEs. 2.4 Data mining and statistical analysis A case/non-case method was applied to analyze the extracted cases. The reporting odds ratio (ROR) and information component (IC) were calculated to determine whether ADRs were reported more frequently for specific drugs than for others in the dataset [12]. A significant risk signal is generated when the number of reports exceeds three and the lower limit of 95% confidence interval (CI) of ROR 025 is greater than 1 or of IC 025 is greater than 0 (dolasetron was excluded because the number of single interested cardiac event less than 3, see Supplementary file)[13]. The magnitude of signal value reflected the strength of association between the suspected drug and ADR, namely, higher signal values suggest an increased likelihood of causing ADR. 2.5 Reported TTO analysis The Weibull, lognormal, gamma, and exponential distributions were tested for the TTO analysis, and the scale parameter α and shape parameter β were applied to characterize the parameter distributions[14]. The Akaike Information Criterion corrected (AIC), Bayesian information criterion (BIC), and -2 times the log-likelihood of the model (β) (-2*Log L(β)) for all candidate distributions were calculated, and the one with smallest AIC, BIC and -2*Log L(β) values was selected as the optimal parameter distribution model to describe the latency of cardiac AEs induced by 5-HT3RAs. 2.6 Sensitivity analyses Post-hoc sensitivity analyses directed at the primary outcome of ROR were conducted to find potential confounding factors that may skew the baseline analysis[15]. The ROR values were recalculated after adjusting the sample in two separate ways: (1) excluding cases with possible cardiac AEs at baseline, (2) excluding cases with potential risk factors such as electrolyte disorder that could cause QT interval prolongation. Furthermore, we delved into individual characteristics and explored sex-specific cardiac AEs associated with 5-HT3RAs, which was performed primarily for ondansetron because granisetron and palonosetron-associated cardiotoxic AEs≤3 in both sexes (Supplementary file). 2.7 Establishment and evaluation of the PBPK model Due to the highest risk of cardiac toxicity associated with ondansetron, we investigated its pharmacokinetics to explore the possible factors. A publicly available PBPK model for ondansetron has effectively characterized its pharmacokinetic profile in healthy populations and demonstrated strong evaluative capability [16-18]. Building on this foundation, we further extended the PBPK framework to extrapolate the distribution characteristics of ondansetron in cardiac tissues using PK-Sim and MoBi software ( Supplemental Table S4 ). Based on the recommended dose range in clinical guidelines[19], we simulated ondansetron with single doses of 4 mg, 8 mg, 0.15 mg/kg administered intravenously and 8 mg orally in a population sample of 1,000 subjects with a 1:1 sex ratio to obtain the pharmacokinetic profiles of plasma and cardiac tissue for each dose regimen, respectively. To visually assess the model's performance, we compared the agreement between real human plasma concentrations of ondansetron measured in 12 experiments and the corresponding concentration-time curves extrapolation in our PBPK model. Furthermore, the accuracy of model was rigorously validated by examining whether the expected values (the key pharmacokinetic parameters C max and AUC t-end ) fell within 0.5 to 2 times the measured parameter values[16](see Supplementary file). This assessment approach ensured that the model possesses theoretical validity, high credibility, and strong generalization capability in practical applications. 2.8 Software FAERS data were extracted and plotted using SAS (version 9.4), and R statistical computing language version (4.3.1) was utilized for data processing. Additionally, the published drug concentration-time plots were digitized by GetData Graph Digitizer software (GetData Graph Digitizer V.2.26.0.20 ©, S. Fedorov) to obtain concentration data. The PBPK analysis was performed in the PK-Sim and MoBi modeling environment (version 9.0, https://open-systems-pharmacology.org/) 3 Results 3.1 Data from the FAERS analysis 3.1.1 Descriptive analysis After excluding duplicate and invalid entries, about 66,032 AEs associated with 5HT3RAs were identified in the FAERS database, of which 1,174 were cardiac AEs of interest ( Table 1). The incidence of cardiotoxic AEs presented a rising trend post-2012 and peaked in 2018 ( Fig. 2A ). Remarkably, the overwhelming majority (96.7%, n=1,135) of cardiac AEs were linked to ondansetron, and the most prevalent cardiotoxicity type was electrocardiogram QT prolonged ( Fig. 2B ). The median age was 49 years (interquartile ranges (IQR): 32-60 years), and females accounted for 51.45% of the cases ( Fig. 2C ). Healthcare professionals contributed to a significant proportion of the reporters (78.62%), and the United States was the primary reporting country (60.56%). Hospitalization (49.06%) emerged as the predominant outcome of these cardiac AEs ( Fig. 2E ). Table 1. Cases characteristics of 5-HT3RAs associated with cardiotoxic adverse events in the FAERS database, January 2004 - March 2023 Categories Ondansetron N(%) Granisetron N(%) Palonosetron N(%) Total N(%) Reports number 1135 24 15 1174 Sex Female 582 (51.3) 14 (58.3) 8 (40.0) 604 (51.4) Male 458 (40.4) 4 (16.7) 5 (25.0) 467 (39.8) Unknown 95 (8.4) 6 (25.0) 2 (10.0) 103 (8.8) Age category, years Median (IQR) 49 (33,60) 50 (22,68) 58 (42,65) 49 (32.25,60) <18 103 (9.1) 0 (0.0) 1 (6.7) 104 (8.9) 18-44 209 (18.4) 4 (16.7) 2 (13.3) 215 (18.3) 45-64 290 (25.6) 2 (8.3) 3 (20.0) 295 (25.1) 65-74 75 (6.6) 4 (16.7) 1 (6.7) 80 (6.8) ≥ 75 46 (4.1) 0 (0.0) 2 (13.3) 48 (4.1) Unknown 412 (36.3) 14 (58.3) 6 (40.0) 432 (36.8) Reporter country The USA 703 (61.9) 7 (29.2) 1 (6.7) 711 (60.6) United Kingdom 194 (17.1) 2 (8.3) 1 (6.7) 197 (16.8) Canada 43 (3.8) 0 (0.0) 0 (0.0) 43 (3.7) France 39 (3.4) 1 (4.2) 0 (0.0) 40 (3.4) Other country 125 (11.0) 11 (45.8) 13 (86.7) 149 (12.7) Unknown 31 (2.7) 3 (12.5) 0 (0.0) 34 (2.9) Reporter a Healthcare professional 904 (79.6) 4 (16.7) 15 (100.0) 923 (78.6) Non-healthcare professional 186 (16.4) 19 (79.2) 0 (0.0) 205 (17.5) Unknown 45 (4.0) 1 (4.2) 0 (0.0) 46 (3.9) Report year 2004-2010 72 (6.3) 9 (37.5) 2 (13.3) 83 (7.1) 2011-2015 156 (13.7) 3 (12.5) 6 (40.0) 165 (14.1) 2016-2020 694 (61.1) 6 (25.0) 3 (20.0) 703 (59.9) 2021-2023 213 (18.8) 6 (25.0) 4 (26.7) 223 (19.0) Outcomes b Death 186 (16.4) 9 (37.5) 1 (6.7) 196 (16.7) Life-threatening 356 (31.4) 13 (54.2) 4 (26.7) 373 (31.8) Hospitalization 566 (49.9) 6 (25.0) 4 (26.7) 576 (49.1) Disability 21 (1.9) 0 (0.0) 0 (0.0) 21 (1.8) Other serious condition 1015 (89.4) 9 (37.5) 11 (73.3) 1035 (88.2) Abbreviations: IQR: interquartile ranges, 5-HT3RAs: 5-HT3 receptor antagonists a Healthcare professional including reporters such as physicians and pharmacists; non-healthcare professionals including reporters such as consumers and lawyers b Since a case may experience different clinical outcomes during drug therapy, it is reasonable that the sum percentage of the outcome under this item may exceed 100% 3.1.2 Disproportionality analysis The disproportionality analysis results are depicted in Fig. 3. The analysis mainly included ondansetron, granisetron, and palonosetron. (tropisetron with only 15 AEs was excluded, and dolasetron was excluded because the number of single interested cardiac events was less than 3). Of which, ondansetron exhibited significantly higher signal values compared to other 5-HT3RAs, with a TdP ROR 025 of 22.94 and electrocardiogram QT prolonged ROR 025 of 11.21. 3.1.3 Reported TTO analysis After eliminating erroneous reports, 194 cardiac AEs were analyzed for TTO and the outcome is illustrated in Supplemental Fig. S1 . It indicated that the median onset time of cardiac AEs associated with 5-HT3RAs was 0.5 days (IQR: 0.5-7.5 days), and the majority of cases occurred within the first month of treatment initiation (92%, n=179), even 72% (n=140) happened within 5 days. Additionally, it is observed that the cardiac AEs associated with 5-HT3RAs appeared with similar probability within the 30 to 360-day period throughout the year, with the exception of a particularly high incidence in the first month. This suggests that AEs could occur at any stage of treatment, underscoring the importance of continuous monitoring, especially during the early phase. The results of the goodness-of-fit tests indicated that the lognormal model best described the latency of cardiac AEs associated with 5-HT3RAs ( Supplemental Table S5 ). Accordingly, granisetron was classified as a random failure type, while ondansetron and palonosetron were categorized as wear-out failure type. In the TTO analysis based on parameter distributions and the valid cases, the IQR for cardiac AEs associated with ondansetron, palonosetron, and granisetron were 0.5 (0.5-7.5, n=173), 4.5 (1-395.5, n=11), and 0.5 (0.5-2.5, n=10), respectively ( Supplemental Table S6 ). 3.1.4 Sensitivity analysis Supplemental Fig. S2 displayed the outcomes of sensitivity analyses. Removing cases with heart disease diagnosis and electrolyte disorders at baseline, the arrhythmia signal in palonosetron disappeared with original ROR 025 =1.36 (removal of cardiac disease diagnosis ROR 025 =0.61, and removal of electrolyte disorders ROR 025 =0.60), while the other signals persisted. In Supplemental Fig. S3 , each point indicates ondansetron related-AEs and specifically highlights the PT names of AE signals that are significant ( P ＜0.05) at both Log 2 (ROR) values and -Log 10 (adjusted P values). Interestingly, despite the higher number of total ondansetron AE cases in females ( Supplemental Table S8 ), male patients showed stronger signals for cardiac AEs such as electrocardiogram QT prolonged, arrhythmia, pericardial effusion, myocardial infarction and cardiomyopathy. 3.2 Characterization of ondansetron distribution in cardiac organs Given that ondansetron exhibited a stronger signal intensity for cardiotoxic AEs among the 5-HT3RAs and was associated with a broad range of AEs, a PBPK model was established to simulate the drug concentration-time curve of ondansetron based on clinical demographic characteristics and dosing regimens ( Supplemental Fig. S4 ). The results demonstrated that 76.3% of the clinically measured drug concentration-time points fell within the 95% CI of the simulated value. Goodness-of-fit plots revealed that most extrapolate values were within a 2.0-fold error range of the measured values ( Fig. 4, Supplemental Table S9) . The fold errors between extrapolated and observed values of ondansetron pharmacokinetic parameters (AUC, Cmax) were within the 2.0 range ( Supplemental Table S10 ). These findings indicated that the PBPK model possessed high accuracy for extrapolating the plasma and tissue concentrations of ondansetron. The pharmacokinetic profiles of ondansetron in plasma and cardiac tissue were explored in four different doses, which are recommended by the guidelines[19]（ Fig. 5 ）. The AUC of single intravenous or oral doses of ondansetron is approximately 1.4 times higher than those in plasma. Notably, the maximum concentration of ondansetron in cardiac tissue was up to 2.3 times greater than that in plasma following a single intravenous dose ( Supplemental Table S11) . 4 Discussion This study specifically investigated and compared cardiotoxic AEs associated with different 5-HT3RAs based on the FAERS database. As a commonly used adjuvant drug for cancer patients, the safety of 5-HT3RAs has received insufficient attention. Notably, cardiotoxicity, a rare but significantly detrimental ADR of 5-HT3RAs, calls for further research. Current studies predominantly concentrated on a single AE associated with a specific drug or under particular circumstances[20], lacking a comprehensive comparative evaluation cardiac safety of these 5-HT3RAs. The study revealed that different drugs of 5-HT3RAs presented varying degrees and types of cardiotoxicity, among which ondansetron exhibited the highest cardiotoxicity signals, followed by palonosetron, and finally granisetron. The result might provide evidence-based recommendations to prescribe low cardiac toxicity 5-HT3RAs for patients with heart diseases, and to enhance monitoring practices. Furthermore, it might raise public awareness regarding the safety of adjuvant oncology medications. To our knowledge, this is the first study integrating pharmacokinetic into pharmacovigilance analyses to explore the potential underlying pharmacokinetic factors of AEs. We initially described the clinical characteristics of patients who experienced cardiotoxic reactions after 5-HT3RAs treatment in FAERS database. Notably, the number of reported cardiotoxic AEs remained relatively stable from 2004 to 2012, yet with a significant increase in cases following 2012. The FDA issued a safety bulletin regarding ondansetron potentially prolonging the QT interval and resulting in lethal arrhythmias in 2012. It is reasonable to assume that the announcement of safety bulletin heightened awareness of 5-HT3RAs-related cardiac AEs among the medical community and public, subsequently, increasing the reporting frequency. Patients over 60 years of age who were associated with cardiotoxic AEs related to 5-HT3RAs accounted for 26.4% of the non-missing age data in the FAERS database, which is consistent with the literature findings[6-8]. Given that older cancer patients, who are also the main recipients of 5-HT3RAs, often have multiple comorbidities and polypharmacy[21], they may face an elevated risk of cardiac AEs. Notably, serious fatal cases were also predominantly observed in older patients[7], highlighting the need for caution when using medications in this population. Next, in our sensitivity analyses, we found that electrolyte imbalances and the presence of underlying cardiac disease significantly impact cardiac safety, particularly with the use of drugs such as palonosetron. Hypokalemia could lead to QT interval prolongation and TdP[22] by enhancing cardiomyocyte excitability. This condition often coexists with hypomagnesemia and hyperphosphatemia, further increasing the risk of cardiac AEs[23]. Crucially, underlying cardiac disease and electrolyte disturbances may augment susceptibility to drug-induced cardiotoxicity and potentially mask or exacerbate medicine-related cardiac issues. The results of sensitivity analyses excluding cases with baseline cardiac diseases and electrolyte disturbances showed that the arrhythmia signal associated with palonosetron became insignificant, suggesting that palonosetron-related arrhythmia may be primarily attributed to the patient's pre-existing cardiac risk factors. This finding emphasizes the importance of evaluating a patient's baseline cardiac status before administrating palonosetron, facilitating a more precise risk assessment to mitigate the risks. Furthermore, this study found that ondansetron exhibited significantly higher signal values of QT interval prolongation and TdP compared to granisetron and palonosetron. QT interval prolongation is a critical indicator of cardiotoxicity, which may precipitate serious arrhythmias and ultimately result in sudden cardiac death[22]. The evidence that ondansetron prolongs QT interval is compelling and has been confirmed by prospective studies and meta-analyses[24,25]. Our PBPK model showed a significant accumulation of ondansetron drug concentrations in cardiac tissue, which may exacerbate its' effects on blocking potassium channels, thus leading to a prolongation of the QT interval and TdP. The finding sustained the cardiotoxicity of ondansetron from the pharmacokinetic perspective. In contrast, the QT interval prolongation of palonosetron and granisetron is somewhat controversial. Kim, H. J et al reported that palonosetron may cause a slight intraoperative QTc interval increase while without statistical significance[26], and Morganroth J deemed that palonosetron does not influence QTc interval[27]. Several research disclosed that the association between granisetron and QT interval prolongation is weak and usually presented as transient or minimal cardiac AEs[28]. It is undeniable that differences in study designs may affect drug evaluation outcomes, hence, comprehensive prospective studies using uniform methodologies to assess the effects of three 5-HT3RAs on QT interval prolongation are warranted. Our results indicated a clear association between granisetron (with an ROR 025 of 1.07) and palonosetron with QT interval prolongation (with an ROR 025 of 3.42). In summary, physicians should be cautious in prescribing 5-HT3RAs especially ondansetron, particularly for patients with existing cardiac conditions or those concurrently taking medications that may prolong the QT interval. Regular electrocardiogram monitoring is essential to promptly identify and assess any changes in these patients. We further explored whether different 5-HT3RAs induce cardiotoxicity through a common mechanism. It is hypothesized that a similar mechanism may lead to a consistent pathological pattern during treatment. TTO analysis categorized granisetron as a random failure type, while palonosetron and ondansetron were classified as wear-off. A random failure model implies that the hazard of the AEs remains constant over time, whereas a wear-out failure model indicates that the hazard of the AEs increases over time. These findings indicated that a single mechanism could not fully account for the association between different 5-HT3RAs and onset time of cardiotoxicity,[29] underscoring the complexity of their relationship and the need for a nuanced understanding of the underlying mechanisms of AEs. Further analysis manifested that palonosetron (4.5 days, IQR:1-395.5days) had a significantly longer latency compared with ondansetron (0.5 days, IQR:0.5-7.5days) and granisetron (0.5 days, IQR:0.5-2.5days). The PBPK model displayed that intracardiac ondansetron concentrations peaked rapidly, approximately 0.8 hours after oral administration (Fig. 5D) , which partially supported the finding that the latency of ondansetron cardiotoxic AEs was short. We examined individual cases of cardiotoxicity associated with palonosetron by analyzing raw data from the FAERS database, and observed that patients exhibited significant cardiotoxic reactions after long-term use. It is reported that cardiotoxicity induced by 5-HT3RAs may occur following prolonged use of the medication [30]. Palonosetron exhibits a 30- to 100-fold higher affinity for the 5-HT3 receptor than ondansetron and granisetron, and its long half-life [31] results in its' slower distribution and metabolism within the body, which implies that it takes more time to raise concentrations to the threshold of triggering cardiotoxic AEs, and therefore has an extended latency. Additionally, palonosetron shows allosteric interactions and positive cooperativity with the receptor, which is not presented in ondansetron and granisetron[32]. These findings suggest that palonosetron may possess a diverse pharmacokinetics mechanism of cardiotoxicity compared to other 5-HT3RAs, necessitating a longer duration of exposure to detect its toxic effects. Our subgroup analysis revealed gender-specific disparities in the cardiotoxicity associated with 5-HT3RAs. Research revealed that females generally engage in more frequent drug use compared to males, which may elevate the risk of drug interactions[33]. Besides, the notable sex differences in pharmacokinetics also contribute to a higher incidence of AEs in females[34]. This is partially reflected in total ondansetron-related AEs, with a proportion of females and males were 53.77% and 38.79, respectively. However, in terms of ondansetron-related cardiotoxic AEs, the case is slightly different. The cardiotoxic AEs such as electrocardiogram QT prolonged, arrhythmia, pericardial effusion, myocardial infarction and cardiomyopathy were stronger in males than in females with statistical significance( P ＜0.05). Literature has demonstrated that estrogen estradiol exhibits significant cardioprotective effects, including the prevention of apoptosis, reduction of myocardial injury during ischemia and reperfusion, enhancement of mitochondrial function, and diminishments of oxidative stress[35,36]. However, it cannot rule out that the observed sex differences may arise from reporting biases, further research is needed to clarify whether men are generally at greater risk for cardiotoxicity to help clinicians better comprehend and predict drug responses in patients of different sexes. In drug safety assessments, the AEs of a drug are closely associated with its concentration in specific target tissues. Among 5-HT3RAs, ondansetron exhibits significant cardiac-related signals, prompting to develop PBPK model to explore the pharmacokinetic factors. Traditionally, PBPK models pose challenges to parameterization due to the need to estimate the tissue-plasma partition coefficient and tissue protein binding ratio[37]. Fortunately, this issue has effectively been addressed by computer simulations of tissue composition, including neutral lipids, phospholipids, and water[38]. We further developed a validated PBPK model to extrapolate cardiac drug concentration, which showed that ondansetron concentrations in cardiac tissue were 2.3 times higher than that in plasma, probably due to its lipophilic properties[16] and an apparent volume of distribution[39]. Moreover, the abundance of 5-HT3 receptors in cardiac mitochondria promotes selective accumulation of ondansetron in these regions, owing to its high receptor affinity[40]. The greater accumulation of the drug in the heart may potentially contribute to its cardiotoxic effects. We acknowledged that there are several inherent limitations in this study. First, the spontaneous reporting nature of FAERS database implies that AEs under-reporting may occur, and thus the number of reports may not comprehensively reflect the safety landscape of 5-HT3RAs. To mitigate under-reporting, we extended the data collection period to maximize the sample size, enabling a more comprehensive analysis of AEs and improving the robustness of our findings. Second, data from longitudinal studies are likely to offer richer evidence than voluntarily submitted pharmacovigilance information. Nonetheless, our study conducted extensive sensitivity analyses to eliminate the impact of underlying diseases on disproportionate signals detection, making the result more reliable and credible than those based solely on spontaneous reporting[11]. Finally, it is hard to measure true concentrations in human tissue level, which results in the difficulties of verifying the PBPK simulation analysis. However, we compared the consistency between the concentration-time curves extrapolated in our model and the corresponding real human plasma concentrations of ondansetron in literature. Utilizing PK-Sim and MoBi software, which provide a precise physiological foundation for accurately extrapolating organ concentrations[41], further supports this study. Based on the above mentions, we inferred that the concentration in the heart might also be free of significant bias. Overall, despite the limitations, this study effectively quantified 5-HT3RAs-related cardiac AE risks. However, our PBPK model currently includes only ondansetron and has not yet compared the pharmacokinetics of other 5-HT3RAs, which will be developed in the future. 5 Conclusion The results indicated that different 5-HT3RAs exhibit varying degrees and types of cardiotoxicity. Noteworthy, the cardiotoxicity signal associated with ondansetron was significantly higher than that of palonosetron and granisetron. The PBPK simulation analysis demonstrated that the concentration of ondansetron in cardiac tissues was considerably higher than that in plasma, supporting that ondansetron may pose a high risk of cardiotoxicity. Overall, it highlights the importance of enhancing monitor and assessment of cardiac-related AEs when administering 5-HT3RAs. Declarations Funding No funding was received for conducting this study. Conflict of interest The authors have no competing interests to declare that are relevant to the content of this article. Author's contributions Yijun Cai: software, writing-original draft; Shaohong Luo: methodology, writing-original draft; Shen Lin: formal analysis, data curation; Xiaoting Huang: investigation; Xiangzhen Wang, Lijing Yang: validation; Xiongwei Xu, Xiuhua Weng: conceptualization, writing-reviewing and editing. All authors read and approved the final manuscript. Availability of data and materials Pharmacovigilance data can be found at https://fis.fda.gov/extensionS/FPD-QDE-FAERS/FPD-QDE-FAERS.html. PBPK model data were derived from published studies. Acknowledgments The authors thank FAERS. References Ning, C., Yan, Y., Wang, Y., Li, R., Liu, W., Qiu, L., Sun, L., & Yang, Y. (2024). Research trends on chemotherapy induced nausea and vomiting: a bibliometric analysis. Frontiers In Pharmacology , 15 , 1369442. https://doi.org/10.3389/fphar.2024.1369442 Herrstedt, J., Clark-Snow, R., Ruhlmann, C. H., Molassiotis, A., Olver, I., Rapoport, B. L., Aapro, M., Dennis, K., Hesketh, P. J., Navari, R. M., Schwartzberg, L., Affronti, M. L., Garcia-Del-Barrio, M. A., Chan, A., Celio, L., Chow, R., Fleury, M., Gralla, R. J., & Giusti, R. … participants of the, M. E. C. C. E. a. c. e. o. (2024). 2023 MASCC and ESMO guideline update for the prevention of chemotherapy- and radiotherapy-induced nausea and vomiting. 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Impact of physiologically based pharmacokinetic models on regulatory reviews and product labels: Frequent utilization in the field of oncology. Clinical Pharmacology And Therapeutics , 101 (5), 597–602. https://doi.org/10.1002/cpt.622 Le Merdy, M., Spires, J., Tan, M. L., Zhao, L., & Lukacova, V. (2024). Clinical Ocular Exposure Extrapolation for a Complex Ophthalmic Suspension Using Physiologically Based Pharmacokinetic Modeling and Simulation. Pharmaceutics , 16 (7). https://doi.org/10.3390/pharmaceutics16070914 Griddine, A., & Bush, J. S. (2024). Ondansetron. In StatPearls . https://www.ncbi.nlm.nih.gov/pubmed/29763014 Wang, Q., Zhang, H., Xu, H., Guo, D., Shi, H., Li, Y., Zhang, W., & Gu, Y. (2016). 5-HTR3 and 5-HTR4 located on the mitochondrial membrane and functionally regulated mitochondrial functions. Scientific Reports , 6 , 37336. https://doi.org/10.1038/srep37336 Geci, R., Gadaleta, D., de Lomana, M. G., Ortega-Vallbona, R., Colombo, E., Serrano-Candelas, E., Paini, A., Kuepfer, L., & Schaller, S. (2024). Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans. Archives Of Toxicology , 98 (8), 2659–2676. https://doi.org/10.1007/s00204-024-03764-9 Additional Declarations No competing interests reported. Supplementary Files SupplementalDataFile.docx Onlinefloatimage1.png Cite Share Download PDF Status: Posted Version 1 posted 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-6213342","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":435071091,"identity":"7e7645ef-0cf4-413a-b37d-4b6cc2c7508a","order_by":0,"name":"Yijun Cai","email":"","orcid":"","institution":"Mengchao Hepatobiliary Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yijun","middleName":"","lastName":"Cai","suffix":""},{"id":435071094,"identity":"1f356d1f-f998-4e0a-8373-3e814954eb8d","order_by":1,"name":"Shaohong Luo","email":"","orcid":"","institution":"the First Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shaohong","middleName":"","lastName":"Luo","suffix":""},{"id":435071095,"identity":"ff72df03-f9d8-4571-927c-ce6230e05c14","order_by":2,"name":"Shen Lin","email":"","orcid":"","institution":"the First Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shen","middleName":"","lastName":"Lin","suffix":""},{"id":435071097,"identity":"adb42af7-9e0b-40ec-b9df-b91a081e2998","order_by":3,"name":"Xiaoting Huang","email":"","orcid":"","institution":"the First Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoting","middleName":"","lastName":"Huang","suffix":""},{"id":435071099,"identity":"1a23cf4f-f6bd-4cfd-9d7c-1ed6aba972c3","order_by":4,"name":"Xiangzhen Wang","email":"","orcid":"","institution":"Mengchao Hepatobiliary Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiangzhen","middleName":"","lastName":"Wang","suffix":""},{"id":435071101,"identity":"a27cef0b-9941-4cb2-b28c-7ab459844aa7","order_by":5,"name":"Lijing Yang","email":"","orcid":"","institution":"Mengchao Hepatobiliary Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lijing","middleName":"","lastName":"Yang","suffix":""},{"id":435071102,"identity":"0f693c22-a381-4f42-9dc7-f1b4a5206d14","order_by":6,"name":"Xiongwei Xu","email":"","orcid":"","institution":"the First Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiongwei","middleName":"","lastName":"Xu","suffix":""},{"id":435071103,"identity":"da37b796-ff0e-414d-95f0-ce3f5a9b12d8","order_by":7,"name":"Xiuhua Weng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYFACHoYDCQY2/IwNIA4bcVoYH3woSJNsJEULs+GMD4clwTqI0mJwI/eYNI/BeQnmaWcMGD6UHWbgn91AQMuZc2lALbclGGfnGDDOOHeYQeLOAfxazI73mIG01IG0MPO2HWYwkEggoOUwD0jLObAtzH+J0nK8x9hwhsEBiBZGYrTYnzlj+OCDQTJQS1rBwZ5z6TwSNwhokZyRY3Ag4Y+dhOHs5I0PfpRZy/HPIKAFDgwbGBgOMIASA9FAnnilo2AUjIJRMNIAAJvPQtxqbQ1CAAAAAElFTkSuQmCC","orcid":"","institution":"Mengchao Hepatobiliary Hospital of Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xiuhua","middleName":"","lastName":"Weng","suffix":""}],"badges":[],"createdAt":"2025-03-12 15:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6213342/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6213342/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79830803,"identity":"fba9ee61-faf7-4772-ac42-41aefe51950e","added_by":"auto","created_at":"2025-04-03 10:28:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":258821,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart of the FAERS database processing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eFAERS: US Food and Drug Administration Adverse Event Reporting System; DEMO: demographics; DRUG drug; REAC: reaction; INDI: indication; RPSR: reporting source; THER: therapy; OUTC: outcome;5-HT3RAs: 5-HT3 receptor antagonists; AEs: adverse events; PTs: preferred terms\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003eAll seven tables above are from the FAERS data file; “n” is the number of adverse drug reaction records in the FAERS database\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/d8cfde43226b6fe34fb0a2ef.jpg"},{"id":79830804,"identity":"1c3e827f-68c2-4562-88a8-bf4c42bf8441","added_by":"auto","created_at":"2025-04-03 10:28:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":147912,"visible":true,"origin":"","legend":"\u003cp\u003eInformation about 1174 cases with cardiac adverse events associated with 5-HT3RAs (A) Distribution of occurrence years (B) Types of cardiac adverse events (C) Distribution of sex (D) Distribution of age (E) Distribution of adverse events outcomes\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/b654361798b9fb830dc8a889.jpg"},{"id":79830807,"identity":"538978ca-fc67-42a5-88f5-651e6bf866f4","added_by":"auto","created_at":"2025-04-03 10:28:40","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217801,"visible":true,"origin":"","legend":"\u003cp\u003e(A) ROR of cardiac AEs associated with 5-HT3RAs (B) The spectrum of cardiac AEs in different 5-HT3RAs\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e “a”: the reports number of cardiac AEs associated with 5-HT3RA; “b”: the reports number of 5-HT3RA AEs other than cardiac AEs; ROR: reporting odds ratio; IC\u003csub\u003e025\u003c/sub\u003e: the lower end of the 95% confidence interval of the information component; PT: preferred term; 5-HT3RA: 5-HT3 receptor antagonist; AEs: adverse events; CI: confidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e The numbers in blocks represent the value of IC\u003csub\u003e025\u003c/sub\u003e of each cardiac AEs induced by target 5-HT3RAs\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/cd21438e05faf303f8b2bfe4.jpg"},{"id":79830806,"identity":"0a3bd23d-ffcb-41cf-82fc-f6e701f5b841","added_by":"auto","created_at":"2025-04-03 10:28:40","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":261230,"visible":true,"origin":"","legend":"\u003cp\u003eThe goodness of fit plots of final model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e The black line signifies that the observed concentrations are equal to the predicted ones. Black and grey dotted lines were obtained by scaling the observed concentrations by a factor of 2 and 1.25, respectively. Different colours represent concentrations measured in different studies（More detailed information can be found in the supplementary document）\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/61f7e9b1e0891b8ea62ecc46.jpg"},{"id":79830816,"identity":"72109726-bf65-47cc-85a9-d2c88907b6bd","added_by":"auto","created_at":"2025-04-03 10:28:40","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":193055,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration time curve of ondansetron in heart intracellular, heart tissue, and peripheral venous blood-plasma\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e iv: intravenous injection; po: oral medication\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/806f8ea65b00239ace4bd59f.jpg"},{"id":80670518,"identity":"2ee94ddb-9bd8-4d2d-974c-0629cbf017f1","added_by":"auto","created_at":"2025-04-15 19:31:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2286647,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/9b226d82-51c3-4c0c-8074-a58f0f490004.pdf"},{"id":79831476,"identity":"93f7cc07-d5ed-4e4b-a855-18d8e82dd1a1","added_by":"auto","created_at":"2025-04-03 10:36:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3383279,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalDataFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/04497183b385a4c3cc62f97e.docx"},{"id":79830814,"identity":"1e19fb94-7dcc-4e22-91ca-62d007c3b441","added_by":"auto","created_at":"2025-04-03 10:28:40","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":300879,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6213342/v1/97ebd977fb901519772b38e8.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cardiotoxicity associated with different 5-HT3RAs: pharmacovigilance analysis of the FDA Adverse Event Reporting System database study and a pharmacokinetic study","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eNausea and vomiting are the most prevalent and distressing adverse events (AEs) experienced by cancer patients undergoing chemotherapy[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The drugs 5-HT3 receptor antagonists (5-HT3RAs), a class of commonly used clinical antiemetic agents, play a pivotal role in the prophylaxis of acute and delayed nausea and vomiting, including chemotherapy-induced nausea and vomiting (CINV), radiotherapy-related and postoperative nausea and vomiting[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, as a commonly used adjuvant drug for cancer patients, the AEs of 5-HT3RAs receive insufficient attention, probably attributed to that people are more concerned about the response and toxicity of tumor treatment drugs[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. According to FDA drug label, ondansetron and granisetron were categorized as high cardiotoxicity risk drugs in the Drug-Induced Cardiotoxicity Rank[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the warnings primarily emphasize the risk of QT interval prolongation, with a significant lack of evidence concerning other AEs in the cardiac system. Additionally, a series of case reports observed torsade de pointes (TdP), bradycardia and cardiac arrest after 5-HT3RAs infusion[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], which has drawn researcher attention to cardiotoxicity associated with 5-HT3RAs. As a vital organ of the body, heart damage may lead to grave even fatal adverse consequences, especially for those patients with heart disease. Currently, there appears to be a relative scarcity of comprehensive comparative research on the cardiotoxic AEs associated with different 5-HT3RAs on a significant scale. Given the widespread global use of 5-HT3RAs and the serious hazards of cardiac AEs, it is imperative to commit more detailed and specific comparisons for drugs among 5-HT3RAs, which might provide evidence-based reference for prescribing optimal 5-HT3RAs to patients.\u003c/p\u003e \u003cp\u003eGenerally, the target tissues or site-specific drug concentration is the most direct indicator of safety, which might partially explain some concentration-related adverse reactions. It is reported that ondansetron exerts a more pronounced inhibitory effect on human cardiac K\u003csup\u003e+\u003c/sup\u003e HERG channels than other 5-HT3RAs[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This enhanced blockade may contribute to prolonged cardiac repolarization, occurring with a concentration-dependent manner[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It is important to evaluate the exposure levels of 5-HT3RAs in cardiac tissues to further investigate the potential contributors of cardiotoxicity. Physiologically based pharmacokinetic (PBPK) model is an effective tool for surveying the time-varying process of drug exposure level in tissues and organs by simulating the absorption, distribution, metabolism, and excretion process of drugs in the body. This study aimed to investigate the signal of cardiotoxicity associated with 5-HT3RAs utilizing The FDA Adverse Event Reporting System (FAERS) database and examine the cardiotoxicity reasons from the perspective of pharmacokinetics by a PBPK model.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Overview\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, we described the clinical features of cardiotoxicity AEs related to 5-HT3RAs by analyzing data from the FAERS database. Then, the association between 5-HT3RAs and cardiotoxicity was assessed by analyzing metrics such as time-to-onset (TTO) and disproportionality scores. Finally, PBPK modeling was constructed to extrapolate the drug concentration distribution profile of ondansetron, which showed the strongest signal in cardiotoxic AEs and thereby provided a comprehensive perspective of drug safety (\u003cstrong\u003eGraphical Abstract\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data sources and study design (FAERS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFAERS is a robust pharmacovigilance database designed to aid regulatory bodies and healthcare practitioners in surveilling and overseeing drug safety, identifying potential safety concerns associated with medications, and ensuring public medication safety. It contains AE reports from healthcare providers, pharmaceutical companies, and patients (https://fis.fda.gov/extensionS/FPD-QDE-FAERS/FPD-QDE-FAERS.html), which provide information about various adverse reactions triggered by drug use, drug misuse, and manufacturing problems.\u003c/p\u003e\n\u003cp\u003eFAERS data from January 2004 to March 2023 were extracted and analyzed. The initiation time was selected based on the earliest time that relevant data were accessible in the FAERS database following FDA approval of the 5-HT3RAs medicines (including ondansetron, granisetron, palonosetron, dolasetron, and tropisetron)[10]. The flowchart of the FAERS analysis methodology is presented in \u003cstrong\u003eFig. 1\u0026nbsp;\u003c/strong\u003eand additional files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Definition of cases and drugs of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Medical Dictionary for Regulatory Activities (MedDRA) (version 26.0) Concept Libraries was used to standardize and map adverse drug reaction (ADR) descriptions within the FAERS database, employing preferred terms (PTs) for consistency. The detailed ADRs of interest are listed in \u003cstrong\u003eSupplemental Table S3\u003c/strong\u003e. Both generic and brand names sourced from Drugbank were input as keywords for the database retrieval. Only 5-HT3RAs with over 100 AE reports in FAERS database were included for analysis[11] (tropisetron with only 15 AEs was excluded). To mitigate potential influence of confounders associated with non-cardiac AEs, our study exclusively focused on cases where 5-HT3RAs were designated as the \u0026apos;primary suspect\u0026apos; for cardiotoxic AEs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Data mining and statistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA case/non-case method was applied to analyze the extracted cases. The reporting odds ratio (ROR) and information component (IC) were calculated to determine whether ADRs were reported more frequently for specific drugs than for others in the dataset [12]. A significant risk signal is generated when the number of reports exceeds three and the lower limit of 95% confidence interval (CI) of ROR\u003csub\u003e025\u003c/sub\u003e is greater than 1 or of IC\u003csub\u003e025\u003c/sub\u003e is greater than 0 (dolasetron was excluded because the number of single interested cardiac event less than 3, see Supplementary file)[13]. The magnitude of signal value reflected the strength of association between the suspected drug and ADR, namely, higher signal values suggest an increased likelihood of causing ADR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Reported TTO analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Weibull, lognormal, gamma, and exponential distributions were tested for the TTO analysis, and the scale parameter \u0026alpha; and shape parameter \u0026beta; were applied to characterize the parameter distributions[14]. The Akaike Information Criterion corrected (AIC), Bayesian information criterion (BIC), and -2 times the log-likelihood of the model (\u0026beta;) (-2*Log L(\u0026beta;)) for all candidate distributions were calculated, and the one with smallest AIC, BIC and -2*Log L(\u0026beta;) values was selected as the optimal parameter distribution model to describe the latency of cardiac AEs induced by 5-HT3RAs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Sensitivity analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Post-hoc sensitivity analyses directed at the primary outcome of ROR were conducted to find potential confounding factors that may skew the baseline analysis[15]. The ROR values were recalculated after adjusting the sample in two separate ways: (1) excluding cases with possible cardiac AEs at baseline, (2) excluding cases with potential risk factors such as electrolyte disorder that could cause QT interval prolongation. Furthermore, we delved into individual characteristics and explored sex-specific cardiac AEs associated with 5-HT3RAs, which was performed primarily for ondansetron because granisetron and palonosetron-associated cardiotoxic AEs\u0026le;3 in both sexes (Supplementary file).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Establishment and evaluation of the PBPK model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the highest risk of cardiac toxicity associated with ondansetron, we investigated its pharmacokinetics to explore the possible factors. A publicly available PBPK model for ondansetron has effectively characterized its pharmacokinetic profile in healthy populations and demonstrated strong evaluative capability [16-18]. Building on this foundation, we further extended the PBPK framework to extrapolate the distribution characteristics of ondansetron in cardiac tissues using PK-Sim and MoBi software (\u003cstrong\u003eSupplemental\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Table S4\u003c/strong\u003e). Based on the recommended dose range in clinical guidelines[19], we simulated ondansetron with single doses of 4 mg, 8 mg, 0.15 mg/kg administered intravenously and 8 mg orally in a population sample of 1,000 subjects with a 1:1 sex ratio to obtain the pharmacokinetic profiles of plasma and cardiac tissue for each dose regimen, respectively. To visually assess the model\u0026apos;s performance, we compared the agreement between real human plasma concentrations of ondansetron measured in 12 experiments and the corresponding concentration-time curves\u0026nbsp;extrapolation\u0026nbsp;in our PBPK model. Furthermore, the accuracy of model was rigorously validated by examining whether the expected values (the key pharmacokinetic parameters C\u003csub\u003emax\u003c/sub\u003e and AUC\u003csub\u003et-end\u003c/sub\u003e) fell within 0.5 to 2 times the measured parameter values[16](see Supplementary file). This assessment approach ensured that the model possesses theoretical validity, high credibility, and strong generalization capability in practical applications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 Software\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFAERS data were extracted and plotted using SAS (version 9.4), and R statistical computing language version (4.3.1) was utilized for data processing. Additionally, the published drug concentration-time plots were digitized by GetData Graph Digitizer software (GetData Graph Digitizer V.2.26.0.20 \u0026copy;, S. Fedorov) to obtain concentration data. The PBPK analysis was performed in the PK-Sim and MoBi modeling environment (version 9.0, https://open-systems-pharmacology.org/)\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Data from the FAERS analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.1 Descriptive analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter excluding duplicate and invalid entries, about 66,032 AEs associated with 5HT3RAs were identified in the FAERS database, of which 1,174 were cardiac AEs\u0026nbsp;of interest (\u003cstrong\u003eTable 1).\u003c/strong\u003e The incidence of cardiotoxic AEs presented a rising trend post-2012 and peaked in 2018 (\u003cstrong\u003eFig. 2A\u003c/strong\u003e). Remarkably, the overwhelming majority (96.7%, n=1,135) of cardiac AEs were linked to ondansetron, and the most prevalent cardiotoxicity type was electrocardiogram QT prolonged (\u003cstrong\u003eFig. 2B\u003c/strong\u003e). The median age was 49 years (interquartile ranges (IQR): 32-60 years), and females accounted for 51.45% of the cases (\u003cstrong\u003eFig. 2C\u003c/strong\u003e). Healthcare professionals contributed to a significant proportion of the reporters (78.62%), and the United States was the primary reporting country (60.56%). Hospitalization (49.06%) emerged as the predominant outcome of these cardiac AEs (\u003cstrong\u003eFig. 2E\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eCases characteristics of 5-HT3RAs associated with cardiotoxic adverse events in the FAERS database, January 2004 - March 2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"657\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOndansetron N(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGranisetron N(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePalonosetron N(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReports number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e1135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e1174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e582 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e14 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e8 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e604 (51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e458 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e5 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e467 (39.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e95 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e6 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e2 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e103 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge category, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e49 (33,60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e50 (22,68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e58 (42,65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e49 (32.25,60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e103 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e104 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e209 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e215 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e45-64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e290 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e2 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e295 (25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e65-74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e75 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e80 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u003c/strong\u003e\u003cstrong\u003e75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e46 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e48 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e412 (36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e14 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e6 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e432 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReporter country\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThe USA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e703 (61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e7 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e711 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnited Kingdom\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e194 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e2 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e197 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCanada\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e43 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e43 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e39 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e1 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e40 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther country\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e125 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e11 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e13 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e149 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e31 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e3 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e34 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReporter\u003c/strong\u003e\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare professional\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e904 (79.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e15 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e923 (78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-healthcare professional\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e186 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e19 (79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e205 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e45 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e1 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e46 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReport year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004-2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e72 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e9 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e83 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011-2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e156 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e3 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e6 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e165 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016-2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e694 (61.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e6 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e703 (59.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021-2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e213 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e6 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e4 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e223 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e186 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e9 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e196 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLife-threatening\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e356 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e13 (54.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e4 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e373 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e566 (49.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e6 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e4 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e576 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e21 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e21 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25.1142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther serious condition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7215%;\"\u003e\n \u003cp\u003e1015 (89.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7869%;\"\u003e\n \u003cp\u003e9 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.7002%;\"\u003e\n \u003cp\u003e11 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6773%;\"\u003e\n \u003cp\u003e1035 (88.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e IQR: interquartile ranges, 5-HT3RAs: 5-HT3 receptor antagonists\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eHealthcare professional including reporters such as physicians and pharmacists; non-healthcare professionals including reporters such as consumers and lawyers\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u0026nbsp;\u003c/sup\u003eSince a case may experience different clinical outcomes during drug therapy, it is reasonable that the sum percentage of the outcome under this item may exceed 100%\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDisproportionality analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe disproportionality analysis results are depicted in \u003cstrong\u003eFig. 3.\u0026nbsp;\u003c/strong\u003eThe analysis mainly included ondansetron, granisetron, and palonosetron. (tropisetron with only 15 AEs was excluded, and dolasetron was excluded because the number of single interested cardiac events was less than 3). Of which, ondansetron exhibited significantly higher signal values compared to other 5-HT3RAs, with a TdP ROR\u003csub\u003e025\u003c/sub\u003e of 22.94 and electrocardiogram QT prolonged ROR\u003csub\u003e025\u003c/sub\u003e of 11.21.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.3 Reported TTO analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter eliminating erroneous reports, 194 cardiac AEs were analyzed for TTO and the outcome is illustrated in \u003cstrong\u003eSupplemental\u003c/strong\u003e \u003cstrong\u003eFig. S1\u003c/strong\u003e. It indicated that the median onset time of cardiac AEs associated with 5-HT3RAs was 0.5 days (IQR: 0.5-7.5 days), and the majority of cases occurred within the first month of treatment initiation (92%, n=179), even 72% (n=140) happened within 5 days. Additionally, it is observed that the cardiac AEs associated with 5-HT3RAs appeared with similar probability within the 30 to 360-day period throughout the year, with the exception of a particularly high incidence in the first month. This suggests that AEs could occur at any stage of treatment, underscoring the importance of continuous monitoring, especially during the early phase.\u003c/p\u003e\n\u003cp\u003eThe results of the goodness-of-fit tests indicated that the lognormal model best described the latency of cardiac AEs associated with 5-HT3RAs (\u003cstrong\u003eSupplemental\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable S5\u003c/strong\u003e). Accordingly, granisetron was classified as a random failure type, while ondansetron and palonosetron were categorized as wear-out failure type. In the TTO analysis based on parameter distributions and the valid cases, the IQR for cardiac AEs associated with ondansetron, palonosetron, and granisetron were 0.5 (0.5-7.5, n=173), 4.5 (1-395.5, n=11), and 0.5 (0.5-2.5, n=10), respectively (\u003cstrong\u003eSupplemental\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable S6\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.4 Sensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental Fig. S2\u0026nbsp;\u003c/strong\u003edisplayed the outcomes of sensitivity analyses. Removing cases with heart disease diagnosis and electrolyte disorders at baseline, the arrhythmia signal in palonosetron disappeared with original ROR\u003csub\u003e025\u003c/sub\u003e=1.36 (removal of cardiac disease diagnosis ROR\u003csub\u003e025\u003c/sub\u003e=0.61, and removal of electrolyte disorders ROR\u003csub\u003e025\u003c/sub\u003e=0.60), while the other signals persisted.\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003eSupplemental Fig. S3\u003c/strong\u003e, each point indicates ondansetron related-AEs and specifically highlights the PT names of AE signals that are significant (\u003cem\u003eP\u003c/em\u003e＜0.05)\u0026nbsp;at both Log\u003csub\u003e2\u003c/sub\u003e (ROR) values and -Log\u003csub\u003e10\u003c/sub\u003e (adjusted P values). Interestingly, despite the higher number of total ondansetron AE cases in females (\u003cstrong\u003eSupplemental\u003c/strong\u003e \u003cstrong\u003eTable S8\u003c/strong\u003e), male patients showed stronger signals for cardiac AEs such as electrocardiogram QT prolonged, arrhythmia, pericardial effusion, myocardial infarction and cardiomyopathy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Characterization of ondansetron distribution in cardiac organs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven that ondansetron exhibited a stronger signal intensity for cardiotoxic AEs among the 5-HT3RAs and was associated with a broad range of AEs, a PBPK model was established to simulate the drug concentration-time curve of ondansetron based on clinical demographic characteristics and dosing regimens (\u003cstrong\u003eSupplemental Fig. S4\u003c/strong\u003e). The results demonstrated that 76.3% of the clinically measured drug concentration-time points fell within the 95% CI of the simulated value. Goodness-of-fit plots revealed that most extrapolate values were within a 2.0-fold error range of the measured values (\u003cstrong\u003eFig. 4, Supplemental Table S9)\u003c/strong\u003e. The fold errors between extrapolated and observed values of ondansetron pharmacokinetic parameters (AUC, Cmax) were within the 2.0 range (\u003cstrong\u003eSupplemental\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable S10\u003c/strong\u003e). These findings indicated that the PBPK model possessed high accuracy for extrapolating the plasma and tissue concentrations of ondansetron.\u003c/p\u003e\n\u003cp\u003eThe pharmacokinetic profiles of ondansetron in plasma and cardiac tissue were explored in four different doses, which are recommended by the guidelines[19]（\u003cstrong\u003eFig. 5\u003c/strong\u003e）. The AUC of single intravenous or oral doses of ondansetron is approximately 1.4 times higher than those in plasma. Notably, the maximum concentration of ondansetron in cardiac tissue was up to 2.3 times greater than that in plasma following a single intravenous dose (\u003cstrong\u003eSupplemental Table S11)\u003c/strong\u003e.\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study specifically investigated and compared cardiotoxic AEs associated with different 5-HT3RAs based on the FAERS database. As a commonly used adjuvant drug for cancer patients, the safety of 5-HT3RAs has received insufficient attention. Notably, cardiotoxicity, a rare but significantly detrimental ADR of 5-HT3RAs, calls for further research. Current studies predominantly concentrated on a single AE associated with a specific drug or under particular circumstances[20], lacking a comprehensive comparative evaluation cardiac safety of these 5-HT3RAs. The study revealed that different drugs of 5-HT3RAs presented varying degrees and types of cardiotoxicity, among which ondansetron exhibited the highest cardiotoxicity signals, followed by palonosetron, and finally granisetron. The result might provide evidence-based recommendations to prescribe low cardiac toxicity 5-HT3RAs for patients with heart diseases, and to enhance monitoring practices. Furthermore, it might raise public awareness regarding the safety of adjuvant oncology medications.\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this is the first study integrating pharmacokinetic into pharmacovigilance analyses to explore the potential underlying pharmacokinetic factors of AEs. We initially described the clinical characteristics of patients who experienced cardiotoxic reactions after 5-HT3RAs treatment in FAERS database. Notably, the number of reported cardiotoxic AEs remained relatively stable from 2004 to 2012, yet with a significant increase in cases following 2012. The FDA issued a safety bulletin regarding ondansetron potentially prolonging the QT interval and resulting in lethal arrhythmias in 2012. It is reasonable to assume that the announcement of safety bulletin heightened awareness of 5-HT3RAs-related cardiac AEs among the medical community and public, subsequently, increasing the reporting frequency. Patients over 60 years of age who were associated with cardiotoxic AEs related to 5-HT3RAs accounted for 26.4% of the non-missing age data in the FAERS database, which is consistent with the literature findings[6-8]. Given that older cancer patients, who are also the main recipients of 5-HT3RAs, often have multiple comorbidities and polypharmacy[21], they may face an elevated risk of cardiac AEs. Notably, serious fatal cases were also predominantly observed in older patients[7], highlighting the need for caution when using medications in this population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, in our sensitivity analyses, we found that electrolyte imbalances and the presence of underlying cardiac disease significantly impact cardiac safety, particularly with the use of drugs such as palonosetron. Hypokalemia could lead to QT interval prolongation and TdP[22] by enhancing cardiomyocyte excitability. This condition often coexists with hypomagnesemia and hyperphosphatemia, further increasing the risk of cardiac AEs[23]. Crucially, underlying cardiac disease and electrolyte disturbances may augment susceptibility to drug-induced cardiotoxicity and potentially mask or exacerbate medicine-related cardiac issues. The results of sensitivity analyses excluding cases with baseline cardiac diseases and electrolyte disturbances showed that the arrhythmia signal associated with palonosetron became insignificant, suggesting that palonosetron-related arrhythmia may be primarily attributed to the patient's pre-existing cardiac risk factors. This finding emphasizes the importance of evaluating a patient's baseline cardiac status before administrating palonosetron, facilitating a more precise risk assessment to mitigate the risks.\u003c/p\u003e\n\u003cp\u003eFurthermore, this study found that ondansetron exhibited significantly higher signal values of QT interval prolongation and TdP compared to granisetron and palonosetron. QT interval prolongation is a critical indicator of cardiotoxicity, which may precipitate serious arrhythmias and ultimately result in sudden cardiac death[22]. The evidence that ondansetron prolongs QT interval is compelling and has been confirmed by prospective studies and meta-analyses[24,25]. Our PBPK model showed a significant accumulation of ondansetron drug concentrations in cardiac tissue, which may exacerbate its' effects on blocking potassium channels, thus leading to a prolongation of the QT interval and TdP. The finding sustained the cardiotoxicity of ondansetron from the pharmacokinetic perspective. In contrast, the QT interval prolongation of palonosetron and granisetron is somewhat controversial. Kim, H. J \u003cem\u003eet al\u003c/em\u003e reported that palonosetron may cause a slight intraoperative QTc interval increase while without statistical significance[26], and Morganroth J deemed that palonosetron does not influence QTc interval[27]. Several research disclosed that the association between granisetron and QT interval prolongation is weak and usually presented as transient or minimal cardiac AEs[28]. It is undeniable that differences in study designs may affect drug evaluation outcomes, hence, comprehensive prospective studies using uniform methodologies to assess the effects of three 5-HT3RAs on QT interval prolongation are warranted. Our results indicated a clear association between granisetron (with an ROR\u003csub\u003e025\u003c/sub\u003e of 1.07) and palonosetron with QT interval prolongation (with an ROR\u003csub\u003e025\u003c/sub\u003e of 3.42). In summary, physicians should be cautious in prescribing 5-HT3RAs especially ondansetron, particularly for patients with existing cardiac conditions or those concurrently taking medications that may prolong the QT interval. Regular electrocardiogram monitoring is essential to promptly identify and assess any changes in these patients.\u003c/p\u003e\n\u003cp\u003eWe further explored whether different 5-HT3RAs induce cardiotoxicity through a common mechanism.\u0026nbsp;It is hypothesized that a similar mechanism may lead to a consistent pathological pattern during treatment. TTO analysis categorized granisetron as a random failure type, while palonosetron and ondansetron were classified as wear-off. A random failure model implies that the hazard of the AEs remains constant over time, whereas a wear-out failure model indicates that the hazard of the AEs increases over time. These findings indicated that a single mechanism could not fully account for the association between different 5-HT3RAs and onset time of cardiotoxicity,[29] underscoring the complexity of their relationship and the need for a nuanced understanding of the underlying mechanisms of AEs. Further analysis manifested that palonosetron (4.5 days, IQR:1-395.5days) had a significantly longer latency compared with ondansetron (0.5 days, IQR:0.5-7.5days) and granisetron (0.5 days, IQR:0.5-2.5days). The PBPK model displayed that intracardiac ondansetron concentrations peaked rapidly, approximately 0.8 hours after oral administration\u003cstrong\u003e\u0026nbsp;(Fig. 5D)\u003c/strong\u003e, which partially supported the finding that the latency of ondansetron cardiotoxic AEs was short. We examined individual cases of cardiotoxicity associated with palonosetron by analyzing raw data from the FAERS database, and observed that patients exhibited significant cardiotoxic reactions after long-term use. It is reported that cardiotoxicity induced by 5-HT3RAs may occur following prolonged use of the medication [30]. Palonosetron exhibits a 30- to 100-fold higher affinity for the 5-HT3 receptor than ondansetron and granisetron, and its long half-life [31] results in its' slower distribution and metabolism within the body, which implies that it takes more time to raise concentrations to the threshold of triggering cardiotoxic AEs, and therefore has an extended latency. Additionally, palonosetron shows allosteric interactions and positive cooperativity with the receptor, which is not presented in ondansetron and granisetron[32]. These findings suggest that palonosetron may possess a diverse pharmacokinetics mechanism of cardiotoxicity compared to other 5-HT3RAs, necessitating a longer duration of exposure to detect its toxic effects.\u003c/p\u003e\n\u003cp\u003eOur subgroup analysis revealed gender-specific disparities in the cardiotoxicity associated with 5-HT3RAs. Research revealed that females generally engage in more frequent drug use compared to males, which may elevate the risk of drug interactions[33]. Besides, the notable sex differences in pharmacokinetics also contribute to a higher incidence of AEs in females[34]. This is partially reflected in total ondansetron-related AEs, with a proportion of females and males were 53.77% and 38.79, respectively. However, in terms of ondansetron-related cardiotoxic AEs, the case is slightly different. The cardiotoxic AEs such as electrocardiogram QT prolonged, arrhythmia, pericardial effusion, myocardial infarction and cardiomyopathy were stronger in males than in females with statistical significance(\u003cem\u003eP\u003c/em\u003e＜0.05). Literature has demonstrated that estrogen estradiol exhibits significant cardioprotective effects, including the prevention of apoptosis, reduction of myocardial injury during ischemia and reperfusion, enhancement of mitochondrial function, and diminishments of oxidative stress[35,36]. However, it cannot rule out that the observed sex differences may arise from reporting biases, further research is needed to clarify whether men are generally at greater risk for cardiotoxicity to help clinicians better comprehend and predict drug responses in patients of different sexes.\u003c/p\u003e\n\u003cp\u003eIn drug safety assessments, the AEs of a drug are closely associated with its concentration in specific target tissues.\u0026nbsp;Among 5-HT3RAs, ondansetron exhibits significant cardiac-related signals, prompting to develop PBPK model to explore the pharmacokinetic factors. Traditionally, PBPK models pose challenges to parameterization due to the need to estimate the tissue-plasma partition coefficient and tissue protein binding ratio[37]. Fortunately, this issue has effectively been addressed by computer simulations of tissue composition, including neutral lipids, phospholipids, and water[38]. We further developed a validated PBPK model to extrapolate cardiac drug concentration, which showed that ondansetron concentrations in cardiac tissue were 2.3 times higher than that in plasma, probably due to its lipophilic properties[16] and an apparent volume of distribution[39]. Moreover, the abundance of 5-HT3 receptors in cardiac mitochondria promotes selective accumulation of ondansetron in these regions, owing to its high receptor affinity[40]. The greater accumulation of the drug in the heart may potentially contribute to its cardiotoxic effects.\u003c/p\u003e\n\u003cp\u003eWe acknowledged that there are several inherent limitations in this study. First, the spontaneous reporting nature of FAERS database implies that AEs under-reporting may occur, and thus the number of reports may not comprehensively reflect the safety landscape of 5-HT3RAs. To mitigate under-reporting, we extended the data collection period to maximize the sample size, enabling a more comprehensive analysis of AEs and improving the robustness of our findings. Second, data from longitudinal studies are likely to offer richer evidence than voluntarily submitted pharmacovigilance information. Nonetheless, our study conducted extensive sensitivity analyses to eliminate the impact of underlying diseases on disproportionate signals detection, making the result more reliable and credible than those based solely on spontaneous reporting[11]. Finally, it is hard to measure true concentrations in human tissue level, which results in the difficulties of verifying the PBPK simulation analysis. However, we compared the consistency between the concentration-time curves extrapolated in our model and the corresponding real human plasma concentrations of ondansetron in literature. Utilizing PK-Sim and MoBi software, which provide a precise physiological foundation for accurately extrapolating organ concentrations[41], further supports this study. Based on the above mentions, we inferred that the concentration in the heart might also be free of significant bias. Overall, despite the limitations, this study effectively quantified 5-HT3RAs-related cardiac AE risks. However, our PBPK model currently includes only ondansetron and has not yet compared the pharmacokinetics of other 5-HT3RAs, which will be developed in the future.\u0026nbsp;\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThe results indicated that different 5-HT3RAs exhibit varying degrees and types of cardiotoxicity. Noteworthy, the cardiotoxicity signal associated with ondansetron was significantly higher than that of palonosetron and granisetron. The PBPK simulation analysis demonstrated that the concentration of ondansetron in cardiac tissues was considerably higher than that in plasma, supporting that ondansetron may pose a high risk of cardiotoxicity. Overall, it highlights the importance of enhancing monitor and assessment of cardiac-related AEs when administering 5-HT3RAs.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for conducting this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026apos;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYijun Cai: software, writing-original draft; Shaohong Luo: methodology, writing-original draft; Shen Lin: formal analysis, data curation; Xiaoting Huang: investigation; Xiangzhen Wang, Lijing Yang: validation; Xiongwei Xu, Xiuhua Weng: conceptualization, writing-reviewing and editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePharmacovigilance data can be found at https://fis.fda.gov/extensionS/FPD-QDE-FAERS/FPD-QDE-FAERS.html. PBPK model data were derived from published studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank FAERS.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNing, C., Yan, Y., Wang, Y., Li, R., Liu, W., Qiu, L., Sun, L., \u0026amp; Yang, Y. (2024). 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Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans. \u003cem\u003eArchives Of Toxicology\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e(8), 2659\u0026ndash;2676. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00204-024-03764-9\u003c/span\u003e\u003cspan address=\"10.1007/s00204-024-03764-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"FAERS database, 5-HT3RAs, PBPK model, pharmacovigilance analysis, cardiotoxicity","lastPublishedDoi":"10.21203/rs.3.rs-6213342/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6213342/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo comprehensively compare the risk of cardiotoxicity with 5-HT3RAs and to explore the underlying pharmacokinetic factors that might partially contribute to cardiotoxicity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe FDA Adverse Event Reporting System (FAERS) data (January 2004 to March 2023) were extracted. Disproportionality analysis by calculating the relative odds ratio (ROR) and sensitivity analyses were conducted to assess cardiac risk signals of 5-HT3RAs. Additionally, various parameter distributions were tested for time-to-onset analysis to describe the latency of cardiac AEs induced by 5-HT3RAs. Physiologically based pharmacokinetic (PBPK) models were developed to study the drug distribution characteristics in cardiac tissues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,174 reports of cardiotoxicity related to 5-HT3RAs (including ondansetron, granisetron and palonosetron) were identified in the FAERS database. Ondansetron had an electrocardiogram QT prolonged ROR\u003csub\u003e025\u003c/sub\u003e of 11.21, while that of granisetron and palonosetron were 1.07 and 3.42, respectively. Removing cases with diagnosed heart disease and electrolyte disorders at baseline, all cardiotoxicity signals persisted except the arrhythmia signal in palonosetron. The median onset time of cardiac AEs associated with 5-HT3RAs was 0.5 days (interquartile ranges (IQR): 0.5–7.5 days). Notably, palonosetron demonstrated a longer latency than ondansetron and granisetron, which exhibited similar time-to-onset (TTO) values. The PBPK model extrapolation results showed that ondansetron concentration in cardiac tissue was 2.3 times higher than that in plasma, which might support that it is more susceptible to cardiotoxicity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt suggested prioritizing low cardiac toxicity 5-HT3RAs for patients especially for those with heart diseases, and strengthening the monitoring and management of cardiac toxicity further.\u003c/p\u003e","manuscriptTitle":"Cardiotoxicity associated with different 5-HT3RAs: pharmacovigilance analysis of the FDA Adverse Event Reporting System database study and a pharmacokinetic study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-03 10:28:35","doi":"10.21203/rs.3.rs-6213342/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"22c57fa6-5ea3-405b-a245-23cfaa984b6b","owner":[],"postedDate":"April 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-15T19:23:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-03 10:28:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6213342","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6213342","identity":"rs-6213342","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}