Abstract
OBJECTIVE:
Etrasimod, a selective sphingosine-1-phosphate receptor modulator, is a new treatment for ulcerative colitis. This study aims to analyze the real-world distribution of adverse events (AEs) related to Etrasimod using the FDA Adverse Event Reporting System (FAERS) database, identify key AE signals, and provide a comprehensive safety assessment.
MATERIALS AND METHODS:
AE data related to Etrasimod from the FAERS database between Q4 2023 and Q1 2025 were analyzed using frequency-based and Bayesian methods, including reporting odds ratio (ROR), proportional reporting ratio, Bayesian confidence propagation neural network, and Empirical Bayesian Geometric Mean. Data from the FAERS were accessed on July 7, 2025. The authors did not have access to information that could identify individual participants during or after data collection, as FAERS provides only de-identified case reports.
RESULTS:
A total of 1284 AE reports were collected, of which 871 were Etrasimod related. Most reports (94.9%) came from the U.S. and primarily involved patients aged 18–65 (66.9%). The most common AEs were related to gastrointestinal disorders and general disorders, with “Drug Ineffective” and “Condition Aggravated” being prominent signals. Eye disorders, including diabetic eye disease and diabetic retinopathy (DR), were identified with high signal strength. New potential AEs such as Type 2 diabetes mellitus and diabetic eye disease were also identified. Severe events such as macular edema and blood cholesterol abnormal, although rare, showed high signal strength.
CONCLUSION:
Etrasimod’s safety risks primarily involve gastrointestinal issues, metabolic disorders, eye diseases, and reactions at the administration site. Most notably and unexpectedly, diabetes-related AEs constituted a prominent new safety signal, including type 2 diabetes, DR, and diabetic eye disease, and should be prioritized in early safety monitoring. Clinicians should monitor high-risk populations closely, especially in the early stages of treatment. Further research is needed to validate these findings and optimize safe use of Etrasimod.
Keywords: Adverse events, etrasimod, FDA Adverse Event Reporting System database, signal mining, ulcerative colitis
Introduction
Ulcerative colitis (UC) is a chronic, immune-mediated disease characterized by diffuse mucosal inflammation.[1] The pathophysiology of UC is complex, involving genetic susceptibility, environmental factors, and immune dysregulation, which together drive the recruitment and activation of leukocytes to the colonic mucosa. The treatment goals aim to alleviate clinical symptoms and repair mucosal inflammation, achieving endoscopic remission.[2] Over the past two decades, various biologics and small molecule drugs targeting inflammatory pathways have shown effective results in moderate to severe UC patients and have successfully maintained long-term remission. In addition to anti-TNF-α agents, the treatment strategies have continuously expanded to include anti-adhesion molecules, interleukin inhibitors, and JAK inhibitors. Moreover, recent advances in traditional Chinese medicine have promoted the exploration of herbal therapies for IBD. For example, Chaenomeles speciosa-derived triterpenoids and the herbal formula CDD-2103 showed protective effects in DSS-induced colitis models.[3,4] However, approximately 10% of patients still require colectomy, one-third show primary nonresponsiveness, and nearly 50% experience gradual treatment failure during follow-up.[5] Furthermore, most biologics require intravenous or subcutaneous administration, which is limited by high costs, pharmacokinetic half-lives, and immunogenicity. Therefore, there is a need for safe and effective oral treatment options for UC. As the first oral small molecule approved for UC, JAK inhibitors have garnered attention due to their pharmacokinetic advantages and low immunogenicity, although their use is also associated with an increased risk of viral infections.[6]
With the advancement of biotechnology, the regulation of the sphingosine-1-phosphate (S1P) signaling pathway has emerged as a new therapeutic target. S1P, a membrane-derived lysophospholipid signaling molecule, activates the S1P receptor subtypes S1P1-S1P5 expressed on the cell surface, participating in the pathophysiological processes by regulating the distribution of lymphocytes between the lymph nodes and the periphery. S1P1 receptor modulators reversibly block specific lymphocytes from exiting the lymph nodes into the circulation, thereby reducing immune cell infiltration in inflammatory sites (such as the colonic mucosa).[7] The first-generation nonselective S1P receptor modulator, Fingolimod, was approved in 2010 for the treatment of multiple sclerosis.[8]
On October 12, 2023, the U.S. Food and Drug Administration (FDA) granted accelerated approval for Etrasimod (brand name Velsipity®) for the treatment of adult patients with moderate to severe active UC. Etrasimod is the first nontitrated oral S1P receptor modulator approved for UC and is the only drug globally shown to be effective for isolated proctitis in phase III clinical trials.[9] This approval marks the beginning of a new era in UC treatment. However, as a novel drug, Etrasimod is also associated with certain safety risks in clinical applications. Notably, early clinical trials revealed that Etrasimod may cause adverse reactions such as infections, bradyarrhythmias, and macular edema.[10] The potential adverse reactions and associated risks of Etrasimod in large-scale postmarketing use urgently require comprehensive evaluation. The FDA Adverse Event Reporting System (FAERS) is a widely used pharmacovigilance database that compiles reports of adverse events (AEs) related to drug use globally, providing valuable clinical data for drug safety monitoring.[11,12,13,14,15,16,17,18,19] This study aims to mine and analyze the AEs of Etrasimod using the FAERS database to understand its safety profile in the real world.
Materials and Methods
Data source
The data for this study were obtained from the FAERS database, which includes all AE reports from the fourth quarter of 2023 to the first quarter of 2025. The dataset encompasses several categories of records: demographic information (DEMO), drug utilization information (DRUG), treatment outcome information (OUTC), AE information (REAC), report source information (RPSR), and treatment duration information (THER).
Data processing
“Etrasimod” was used as the target drug for retrieval, with the brand name “Velsipity” included to ensure comprehensive coverage. Spelling variations and potential spelling errors were addressed by including common variations. Following the FDA-recommended method of eliminating duplicate reports, we selected the PRIMARYID, CASEID, and FDA_DT fields from the DEMO table. Reports were then sorted by CASEID, FDA_DT, and PRIMARYID. For reports with the same CASEID, the report with the latest FDA_DT value was retained. Furthermore, for reports with identical CASEID and FDA_DT, the report with the highest PRIMARYID value was kept. Since the fourth quarter of 2023, each quarterly data package includes a list of deleted reports. After removing duplicates, we excluded reports listed in the deleted report list based on their CASEID. The classification and description of AE reports were based on the System Organ Class (SOC) and Preferred Term (PT) from the MedDRA 26.0 AE terminology set,[20] where SOC represents the category of the AE, and PT is the standard name for the AE.
Data analysis
Signal mining was performed using disproportionality analysis methods, primarily including frequency-based and Bayesian methods. The frequency-based methods encompass reporting odds ratio (ROR) and proportional reporting ratio (PRR), whereas the Bayesian methods include bayesian confidence propagation neural network (BCPNN), and empirical bayesian geometric mean (EBGM).[21,22,23,24] The ROR helps minimize bias in events that are reported less frequently, whereas PRR stands out due to its greater specificity compared to ROR. BCPNN excels in integrating and cross-validating multisource data, and Multivariate Gamma Poisson Shrinker (MGPS) is particularly effective in detecting signals from infrequent events. This study combines ROR, PRR, BCPNN, and MGPS, leveraging their individual strengths to enhance the detection and validation range from different perspectives. This integrated approach allows for more accurate identification of safety signals, reduces false positives through cross-validation, and refines the detection of rare AEs by adjusting thresholds and variance. All four methods are based on proportional imbalance metrics using 2 × 2 tables, as shown in Table 1. To reduce bias introduced by individual algorithms, this study integrates these four methods, with the specific formulas outlined in Table 2.
Table 1.
Four grid table
| Target AEs | Non-target AEs | Total | |
|---|---|---|---|
| Etrasimod | a | b | a+b |
| Nonetrasimod | c | d | c+d |
| Total | a + c | b + d | n=a + b+c + d |
AEs=Adverse events
Table 2.
Reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and empirical Bayesian geometric mean methods, formulas, and thresholds
| Method | Formula | Threshold |
|---|---|---|
| ROR |
|
A ≥3 and 95% CI (lower limit) >1 |
| PRR |
|
A ≥3 and 95% CI (lower limit) >1 |
| BCPNN |
|
IC025>0 |
| EBGM |
|
EBGM05>2 |
CI=Confidence interval, ROR=Reporting odds ratio, PRR=Proportional reporting ratio, BCPNN=Bayesian confidence propagation neural network, EBGM=Empirical Bayesian geometric mean, IC=Information component
Results
Distribution of adverse events reports for etrasimod
The AE reports related to Etrasimod from the FAERS database showed that 46.5% of the reports were from female patients, slightly higher than the 42.3% from male patients, while 11.3% of gender information was missing. The age group of 18–64.9 years accounted for 66.9% of the reports, with the second-largest group being 65–85 years, comprising 11.4%. In terms of reporting years, the number of reports in 2024 significantly increased, accounting for 68.9% of the total reports. Regarding report sources, the majority (44.7%) of the reports were submitted by patients or their family members, followed by reports from doctors (32.0%), reflecting the high concern for drug safety among the patient population. Geographically, most reports (94.9%) were from the United States, with relatively fewer reports from Canada, Puerto Rico, Australia, and Austria. Concerning the outcome of the AEs, 0.1% (1 case) resulted in death, 0.2% (2 cases) resulted in disability, and 5.1% led to hospitalization. Most AEs occurred within 30 days of medication use (2.5%), and the incidence of AEs decreased with the extension of the medication period, with only 0.1% of AEs occurring after 360 days of use [Table 3].
Table 3.
Basic information on adverse events related to Etrasimod
| Factors | Number of events (%) |
|---|---|
| Gender | |
| Female | 405 (46.5) |
| Male | 368 (42.3) |
| Unknown | 98 (11.3) |
| Age | |
| <18 | 8 (0.9) |
| 18–64.9 | 583 (66.9) |
| 65–85 | 99 (11.4) |
| >85 | 1 (0.1) |
| Reporter | |
| Consumer | 389 (44.7) |
| Health professional | 191 (21.9) |
| Physician | 279 (32.0) |
| Pharmacist | 12 (1.4) |
| Reported Countries | |
| United States | 827 (94.9) |
| Canada | 28 (3.2) |
| Puerto Rico | 4 (0.5) |
| Australia | 3 (0.3) |
| Austria | 2 (0.2) |
| Report year | |
| 2023 | 13 (1.5) |
| 2024 | 600 (68.9) |
| 2025 | 258 (29.6) |
| Serious outcomes | |
| Death | 1 (0.1) |
| Disability | 2 (0.2) |
| Hospitalization-Initial or Prolonged | 44 (5.1) |
| AE occurrence time-medication date (days) | |
| 0–30 | 22 (2.5) |
| 31–60 | 8 (0.9) |
| 61–90 | 8 (0.9) |
| 91–120 | 1 (0.1) |
| 181–360 | 3 (0.3) |
| >360 | 1 (0.1) |
AE=Adverse event
Signal mining
From the fourth quarter of 2023 to the first quarter of 2025, a total of 1284 AE reports were collected, with 871 related to Etrasimod. Through signal mining, 25 SOC and 40 preferred terms (PT) were identified. Table 4 ranks the SOCs by report count, with gastrointestinal disorders (n = 493, ROR 1.7, PRR 1.51, IC 0.6, EBGM 1.51) having the most reports, followed by general disorders and administration site conditions (n = 360, ROR 2.63, PRR 2.32, information component [IC] 1.21, EBGM 2.32) and nervous system disorders (n = 159, ROR 1.2, PRR 1.19, IC 0.25, EBGM 1.19). Based on the EBGM values, eye disorders (n = 139, ROR 3.75, PRR 3.55, IC 1.83, EBGM 3.55), metabolism and nutrition disorders (n = 92, ROR 2.52, PRR 2.45, IC 1.29, EBGM 2.45), and general disorders and administration site conditions (n = 360, ROR 2.63, PRR 2.32, IC 1.21, EBGM 2.32) ranked in the top three. Notably, in addition to the AEs clearly mentioned in the drug label, several other frequently occurring AEs were identified, such as metabolism and nutrition disorders (n = 92, ROR 2.52, PRR 2.45, IC 1.29, EBGM 2.45), skin and subcutaneous tissue disorders (n = 66, ROR 0.61, PRR 0.62, IC-0.69, EBGM 0.62), and musculoskeletal and connective tissue disorders (n = 55, ROR 0.56, PRR 0.57, IC −0.8, EBGM 0.57), which require clinical attention. Reports on neoplasms benign, malignant, and unspecified (Including Cysts and Polyps) (n = 7), social circumstances (n = 2), and congenital, familial and genetic disorders (n = 1) were less frequent, and their EBGM values was much lower than that of other systems, suggesting lower risk for these systems. In summary, AEs related to Etrasimod primarily affect the gastrointestinal system, while also impacting other systems and organs to some extent.
Table 4.
Top 10 system organ class-level adverse events reported with etrasimod, ranked by report numbers
| SOC | Case reports | ROR (95% CI) | PRR (χ2) | EBGM (EBGM05) | IC (IC025) |
|---|---|---|---|---|---|
| Gastrointestinal disorders | 493 | 1.7 (1.53–1.88) | 1.51 (104.04) | 0.6 (0.45) | 1.51 (1.37) |
| General disorders and administration site conditions | 360 | 2.63 (2.35–2.95) | 2.32 (294.64) | 1.21 (1.04) | 2.32 (2.07) |
| Nervous system disorders | 159 | 1.2 (1.02–1.42) | 1.19 (5.01) | 0.25 (0.01) | 1.19 (1.01) |
| Investigations | 145 | 1.36 (1.15–1.61) | 1.33 (12.58) | 0.41 (0.16) | 1.33 (1.12) |
| Eye disorders | 139 | 3.75 (3.16–4.46) | 3.55 (259.76) | 1.83 (1.55) | 3.55 (2.98) |
| Metabolism and nutrition disorders | 92 | 2.52 (2.04–3.11) | 2.45 (80.29) | 1.29 (0.96) | 2.45 (1.98) |
| Infections and infestations | 79 | 0.66 (0.53–0.82) | 0.67 (13.47) | −0.57 (−0.9) | 0.67 (0.54) |
| Skin and subcutaneous tissue disorders | 66 | 0.61 (0.48–0.78) | 0.62 (16.09) | −0.69 (−1.04) | 0.62 (0.49) |
| Musculoskeletal and connective tissue disorders | 55 | 0.56 (0.43–0.73) | 0.57 (18.51) | −0.8 (−1.19) | 0.57 (0.44) |
| Injury, poisoning and procedural complications | 51 | 0.17 (0.13–0.22) | 0.19 (201.66) | −2.38 (−2.76) | 0.19 (0.15) |
SOC=System organ class, CI=Confidence interval, ROR=Reporting odds ratio, PRR=Proportional reporting ratio, EBGM=Empirical Bayesian geometric mean, IC=Information component
According to the data in Table 5, the use of Etrasimod was closely associated with various AEs. PTs in Table 5 were ranked by the number of reports (n); accordingly, the most frequently reported AEs included drug ineffective (n = 158, ROR = 4.84, PRR = 4.52, EBGM = 4.51, IC = 2.17), condition aggravated (n = 77, ROR = 6.86, PRR = 6.62, EBGM = 6.61, IC = 2.72), which are noteworthy as they are not typical AEs but may reflect poor treatment outcomes or disease progression related to medication use in certain patient populations. Other significant events included headache (n = 54, ROR = 3.36, PRR = 3.29, EBGM = 3.29, IC = 1.72), dizziness (n = 45, ROR = 3.66, PRR = 3.59, EBGM = 3.59, IC = 1.84), vision blurred (n = 22, ROR = 6.18, PRR = 6.12, EBGM = 6.11, IC = 2.61), heart rate decreased (n = 12, ROR = 11.13, PRR = 11.06, EBGM = 11.03, IC = 3.46), bradycardia (n = 10, ROR = 8.72, PRR = 8.68, EBGM = 8.66, IC = 3.12), macular edema (n = 10, ROR = 78.54, PRR = 78.12, EBGM = 76.54, IC = 6.26), and blood cholesterol abnormal (n = 5, ROR = 32.44, PRR = 32.36, EBGM = 32.09, IC = 5.00), which are consistent with clinical observations and the drug’s labeling. After excluding AEs unrelated to the drug (such as those related to surgery, medical procedures, and social circumstances) and those associated with FDA-approved indications and disease progression, this study identified new, clinically valuable potential ADE signals, including Type 2 diabetes mellitus (n = 66, ROR = 62.52, PRR = 60.36, EBGM = 59.42, IC = 5.89), diabetic eye disease (n = 52, ROR = 7988.01, PRR = 7767.33, EBGM = 2522.54, IC = 11.3), diabetic retinopathy (DR) (n = 9, ROR = 118.49, PRR = 117.93, EBGM = 114.35, IC = 6.84), eye disorder (n = 6, ROR = 6.21, PRR = 6.19, EBGM = 6.19, IC = 2.63), blood iron decreased (n = 4, ROR = 8.13, PRR = 8.12, EBGM = 8.10, IC = 3.02), and Vitamin D decreased (n = 3, ROR = 13.2, PRR = 13.18, EBGM = 13.14, IC = 3.72). These symptoms may suggest risks of drug-induced metabolic disturbances and related eye diseases, warranting further clinical research.
Table 5.
Top 10 preferred terms ranked by report numbers
| SOC | PTs | Case reports | ROR (95% CI) | PRR (χ2) | EBGM (EBGM05) | IC (IC025) |
|---|---|---|---|---|---|---|
| General disorders and administration site conditions | Drug ineffective | 158 | 4.84 (4.11–5.7) | 4.52 (440.41) | 4.51 (3.83) | 2.17 (1.9) |
| General disorders and administration site conditions | Condition aggravated | 77 | 6.86 (5.46–8.61) | 6.62 (368.7) | 6.61 (5.26) | 2.72 (2.29) |
| Metabolism and nutrition disorders | T2DM | 66 | 62.52 (48.81–80.08) | 60.36 (3794.02) | 59.42 (46.39) | 5.89 (4.63) |
| Nervous system disorders | Headache | 54 | 3.36 (2.56 4.41) | 3.29 (86.96) | 3.29 (2.51) | 1.72 (1.26) |
| Eye disorders | Diabetic eye disease | 52 | 7988.01 (4946.77–12,899.01) | 7767.33 (131,104.45) | 2522.54 (1562.14) | 11.3 (5.18) |
| Nervous system disorders | Dizziness | 45 | 3.66 (2.72 –4.91) | 3.59 (84.66) | 3.59 (2.67) | 1.84 (1.33) |
| Gastrointestinal disorders | Colitis ulcerative | 38 | 15.77 (11.43–21.75) | 15.47 (512.85) | 15.41 (11.17) | 3.95 (3.02) |
| Gastrointestinal disorders | Haematochezia | 29 | 14.77 (10.23–21.34) | 14.56 (365.24) | 14.51 (10.05) | 3.86 (2.79) |
| General disorders and administration site conditions | Drug interaction | 26 | 6.86 (4.66–10.11) | 6.78 (128.15) | 6.77 (4.6) | 2.76 (1.92) |
| Gastrointestinal disorders | Colitis | 22 | 16.02 (10.51–24.41) | 15.84 (304.84) | 15.78 (10.35) | 3.98 (2.66) |
PTs=Preferred terms, SOC=System organ class, CI=Confidence interval, ROR=Reporting odds ratio, PRR=Proportional reporting ratio, EBGM=Empirical Bayesian geometric mean, IC=Information component, T2DM=Type 2 diabetes mellitus
Based on the data in Table 6, eye-related diseases are particularly prominent among the main AE signals associated with Etrasimod. At the PT level, AEs in Table 6 were ranked by signal strength using EBGM. Notably, diabetic eye disease (n = 52, ROR = 7988.01, PRR = 7767.33, EBGM = 2522.54, IC = 11.30), DR (n = 9, ROR = 118.49, PRR = 117.93, EBGM = 114.35, IC = 6.84), and macular edema (n = 10, ROR = 78.54, PRR = 78.12, EBGM = 76.54, IC = 6.26) exhibited the most significant signals. Type 2 diabetes mellitus (n = 66, ROR = 62.52, PRR = 60.36, EBGM = 59.42, IC = 5.89) also showed high EBGM values, despite not being listed in the current label for Etrasimod. In addition to these primary signals, less common AEs such as Herpes Simplex (n = 3, ROR = 15.71, PRR = 15.69, EBGM = 15.63, IC = 3.97), Escherichia infection (n = 3, ROR = 11.02, PRR = 11.00, EBGM = 10.98, IC = 3.46), and thyroid disorder (n = 5, ROR = 10.14, PRR = 10.12, EBGM = 10.10, IC = 3.34) also showed high EBGM values, suggesting that these less frequent AEs, while rare, are of clinical significance and warrant attention in clinical practice. Enhanced pharmacovigilance monitoring is needed for these AEs.
Table 6.
Top 10 signal strength of adverse events of Etrasimod ranked by empirical Bayesian geometric mean at the preferred terms level
| SOC | PTs | Case reports | ROR (95% CI) | PRR (χ2) | EBGM (EBGM05) | IC (IC025) |
|---|---|---|---|---|---|---|
| Eye disorders | Diabetic eye disease | 52 | 7988.01 (4946.77–12,899.01) | 7767.33 (131,104.45) | 2522.54 (1562.14) | 11.3 (5.18) |
| Gastrointestinal disorders | Proctitis ulcerative | 5 | 228.3 (92.45–563.79) | 227.7 (1063.68) | 214.67 (86.93) | 7.75 (1.33) |
| Eye disorders | DR | 9 | 118.49 (60.93–230.42) | 117.93 (1011.5) | 114.35 (58.8) | 6.84 (2.28) |
| Eye disorders | Macular Oedema | 10 | 78.54 (41.92–147.15) | 78.12 (745.81) | 76.54 (40.85) | 6.26 (2.4) |
| Metabolism and nutrition disorders | T2DM | 66 | 62.52 (48.81–80.08) | 60.36 (3794.02) | 59.42 (46.39) | 5.89 (4.63) |
| Gastrointestinal disorders | Inflammatory bowel disease | 7 | 34.38 (16.31–72.47) | 34.26 (223.99) | 33.96 (16.11) | 5.09 (1.7) |
| Investigations | Blood cholesterol abnormal | 5 | 32.44 (13.44–78.33) | 32.36 (150.66) | 32.09 (13.29) | 5 (1.19) |
| Gastrointestinal disorders | Mucous stools | 7 | 25.01 (11.88–52.66) | 24.92 (159.67) | 24.76 (11.76) | 4.63 (1.61) |
| Gastrointestinal disorders | Defaecation urgency | 9 | 23.16 (12.01–44.67) | 23.05 (188.73) | 22.92 (11.88) | 4.52 (1.93) |
| Investigations | Faecal calprotectin increased | 4 | 20.7 (7.74–55.37) | 20.66 (74.43) | 20.55 (7.68) | 4.36 (0.77) |
PTs=Preferred terms, SOC=System organ class, CI=Confidence interval, ROR=Reporting odds ratio, PRR=Proportional reporting ratio, EBGM=Empirical Bayesian geometric mean, IC=Information component, T2DM=Type 2 diabetes mellitus, DR=Diabetic retinopathy
Discussion
As the first nontitrated oral S1P receptor modulator approved for the treatment of UC and the only drug globally shown to be effective for isolated proctitis in phase III clinical trials, although the exact mechanism by which Etrasimod exerts its therapeutic effect in UC remains unclear, it is likely that the long-term depletion of S1PR on the cell membrane inhibits lymphocytes from exiting the lymph nodes and may reduce T-cell migration in the colon, thereby improving colonic inflammation in UC patients.[25] Current phase I, II, and III clinical trials have confirmed that Etrasimod has good safety and efficacy in adult patients with moderate-to-severe active UC.[9] However, given the associated AEs in clinical use and the limitations of trial data, further clinical trials and research are needed to comprehensively evaluate its efficacy and safety to ensure its effectiveness and reliability in real-world applications. This study provides an in-depth analysis of the AEs associated with Etrasimod in real-world settings using data from the FAERS database. The findings are discussed as follows:
Distribution of adverse events and clinical significance
This study delved into the distribution characteristics of Etrasimod’s AEs based on data from the FAERS database. The data revealed that slightly more female patients (46.5%) reported AEs than male patients (42.3%), suggesting a relatively balanced distribution of AEs between genders. The age group of 18–64 years, which constitutes 66.9% of the reports, aligns with the epidemiological characteristics of UC, indicating that clinicians should pay special attention to the safety of Etrasimod in this age group. Geographically, most reports (94.9%) came from the United States, which is likely due to the drug’s primary market. Regarding outcomes, 5.1% of the events led to hospitalization. Although the absolute numbers were low, this still warrants caution; death (0.1%) and disability (0.2%) events, while rare, should not be overlooked due to their potential risks. The majority of AEs occurred within the first 30 days of medication use (2.5%), which may suggest that most AEs related to Etrasimod manifest early in treatment, possibly related to acute immune-modulatory responses. The highest proportion of reports (44.7%) came from patients or their families, followed by doctors (32.0%) and other healthcare professionals (21.9%), reflecting high concerns for drug safety from both patients and professionals, and potentially signaling high expectations for UC treatment. Patient or family education, particularly about potential risks, would be beneficial in raising awareness and improving treatment adherence.
Known adverse events
Currently, research on the long-term safety and efficacy of Etrasimod in repeated treatments remains relatively limited. In three clinical trials associated with Etrasimod, a total of 345 patients reported AEs related to the drug. The most common AEs included headaches, liver dysfunction, dizziness, joint pain, hypertension, urinary tract infections, nausea, hypercholesterolemia, herpes simplex virus infections, bradycardia, and iron-deficiency anemia.[26,27,28] This study found that gastrointestinal disorders, general disorders, administration site conditions, and nervous system disorders were the most reported AEs, which is consistent with the drug’s labeling. Clinicians should prioritize monitoring these events when using Etrasimod. Notably, although “drug ineffective” and “condition aggravated” were high-frequency and EBGM-abnormal PTs in the AE reports, these categories are more likely to reflect dissatisfaction with the drug’s efficacy, disease progression, or adherence factors, rather than traditional “toxic” AEs. In addition, high-signal AEs such as Macular Oedema and Blood Cholesterol Abnormal are also mentioned in the labeling, underscoring the importance of monitoring vision and cholesterol levels. Other common AEs include heart rate decreased and bradycardia. These relatively mild events, although, may impact patient quality of life, warranting attention and possible adjustment of treatment based on patient tolerance. In summary, the results of this study are largely consistent with existing drug safety data and further quantify the adverse reaction risk levels, providing support for clinical drug monitoring.
New potential adverse events
This study also revealed several potential new AE signals that may be associated with the use of Etrasimod. These AEs were not explicitly listed in the current product labeling for Etrasimod, but some signals showed high strength, suggesting that their potential risks warrant further clinical attention.
Metabolic and endocrine system abnormalities
In this study, several metabolic or endocrine-related AE signals that were not explicitly listed during Etrasimod treatment were observed, including Type 2 diabetes mellitus (T2DM), thyroid disorder, iron deficiency anemia, blood iron decreased, and Vitamin D decreased. Among these, Type 2 diabetes mellitus showed the highest report frequency and signal strength. Previous studies have indicated that an elevated neutrophil-to-lymphocyte ratio is strongly associated with an increased risk of developing T2DM,[29] and that HDL-C and LDL-C partly mediate the association between B lymphocyte ratio (BLR) and T2DM risk.[30] Given that Etrasimod affects lymphocyte migration and may also impact lipid metabolism, the findings of this study suggest that it may interfere with metabolic and endocrine homeostasis beyond immune regulation pathways. In addition, the presence of iron deficiency anemia and blood iron decreased suggests that Etrasimod may affect iron metabolism, as existing research has shown that iron homeostasis is tightly regulated by the hepcidin–ferroportin axis, but can be significantly disrupted during immune responses such as infection.[31] Iron imbalance can lead to immune deficiencies or alter immune cell functions, and iron plays a crucial role in the activation and differentiation of Th1, Th2, and Th17 cells, cytotoxic T lymphocytes (CTLs), and in the antibody responses of B cells.[32] Moreover, studies have shown that iron can influence the S1P/S1PR signaling axis involved in bone loss during chronic iron overload.[33] Thus, whether Etrasimod indirectly mediates iron metabolism abnormalities through its effects on lymphocyte function and the S1P signaling pathway requires further investigation to clarify the mechanism. Therefore, during Etrasimod treatment, especially in patients with underlying metabolic diseases or older populations, dynamic monitoring of blood glucose levels, thyroid function, and nutritional status (e.g., iron and Vitamin D levels) should be enhanced to reduce potential risks and optimize treatment safety.
Eye-related adverse events
Notably, this study also observed several eye-related AEs, including DR, diabetic eye disease, macular edema, Vision Blurred, and eye disorder. These events not only had relatively high report frequencies but also showed higher signal strength. Except for macular edema, which is already explicitly mentioned in the Etrasimod product labeling, the remaining reactions have not been mentioned in previous clinical studies or the product label. It is hypothesized that these eye-related AEs may be related to the mechanism by which Etrasimod influences sphingosine metabolism. Sphingosine, as a precursor of sphingolipids, is the most abundant sphingolipid in the retina and is an essential component of cell membranes and organelle membranes.[34] Etrasimod’s immune-regulating action through S1P receptors might also affect retinal sphingolipid metabolism and function, although further studies are needed to confirm this.
In addition, recent research on the retinal lymphatic system has shown increasing evidence that adaptive immune cells, such as T cells, play an essential role in the development of DR. In diabetic patients, peripheral lymphocytes can be observed infiltrating and activating in the retinal region.[35] Given that Etrasimod affects lymphocyte migration, it is important to investigate whether it could promote inflammatory infiltration and accelerate retinal damage in these individuals. Clinical monitoring, particularly for diabetic patients, should involve regular eye exams and vigilant monitoring of vision changes during Etrasimod treatment.
Seasonal allergic reactions
This study also identified seasonal allergy as a possible new AE. Although the report count was relatively low (n = 4), its signal strength was statistically significant. Considering that Etrasimod regulates lymphocyte migration, it may enhance an individual’s immune response to environmental allergens, leading to seasonal allergy symptoms. This finding suggests that during pollen season or in individuals with a history of allergies, caution should be exercised when using Etrasimod, and preventive measures may be necessary to reduce the risk of allergic reactions.
In conclusion, while these AEs have not yet been included in Etrasimod’s product labeling, this study’s real-world data mining highlights their potential significance. These findings suggest potential associations and warrant further validation and evaluation in subsequent drug safety monitoring and prospective clinical studies.
Recommendations for etrasimod safety monitoring
Despite Etrasimod showing good efficacy in the ELEVATE UC phase III clinical trials and the overall safety being consistent with prior data, its safety should also be interpreted in the broader UC treatment landscape. According to product labeling, anti-TNF agents (e.g., infliximab/adalimumab) highlight serious infections and cytopenias, vedolizumab commonly reports cutaneous reactions, ustekinumab frequently reports upper respiratory infections, and upadacitinib carries warnings for MACE and thromboembolism; in our FAERS analysis of etrasimod, these event clusters were not prominent (only three reports of Escherichia infection were identified). This study, based on real-world database mining, identified several known and potential new AE signals, highlighting the need for enhanced safety monitoring in clinical applications.
Recommendations for etrasimod safety monitoring based on known risks
First, for known AEs, clinicians should pay special attention to gastrointestinal, systemic, and nervous system-related AEs, particularly common symptoms such as headache, dizziness, hypertension, bradycardia, liver dysfunction, and abnormal cholesterol levels. Although most of these symptoms are relatively mild, some may impact patient quality of life, requiring dynamic adjustments to treatment regimens based on individual tolerance. In addition, high-signal AEs such as macular oedema and blood cholesterol abnormalities, while covered in the labeling, still suggest the need for regular monitoring of vision and cholesterol levels to ensure risks remain manageable.
Recommendations for etrasimod safety monitoring based on new signals
For the potential new AEs revealed in this study, dynamic assessments of metabolism, endocrine, eye, and immune systems should be enhanced, particularly in patients with underlying metabolic diseases. Regular monitoring of blood glucose levels, thyroid function, and nutritional status should be performed, especially in older patients. For eye-related AEs (e.g., DR, blurred vision), it is recommended to conduct regular fundus examinations before and during treatment, especially in high-risk populations with diabetes, to identify and intervene in potential retinal damage at an early stage.
Finally, to further ensure the safety of patients using Etrasimod, a systematic AE monitoring mechanism should be established during clinical use, and patient education should be reinforced. Patients should be encouraged to report adverse experiences to improve their drug expectations and enhance adherence. For long-term or repeated medication users, individualized risk management and intervention strategies should be developed, combining imaging, laboratory indicators, and behavioral assessments. Future prospective clinical studies should continue to validate the causality and clinical significance of these potential signals and continually improve the safety profile of Etrasimod.
Limitations
This study, based on the FAERS database, has certain limitations. First, the FAERS data are primarily sourced from voluntary reports, which may introduce selection bias and incomplete information. In addition, mild or common AEs may be underreported, potentially leading to an underestimation of their true reporting burden. Moreover, because FAERS does not provide denominator data (e.g., the total number of exposed patients), incidence rates cannot be calculated, and the findings should be interpreted as disproportionality signals rather than risk estimates. Notably, the strong geographic concentration of reports (94.9% originating from the U.S.) may introduce systematic bias in the observed AE profile and limit its generalizability to other regions. Specifically, prescribing patterns and patient selection may differ across countries (e.g., positioning of etrasimod relative to biologics/JAK inhibitors, reimbursement restrictions, and baseline disease severity), which can shift the spectrum of reported events toward particular comorbidity clusters. In addition, monitoring intensity and clinical practice are not uniform: regulatory labels emphasize pretreatment and on-treatment assessments (e.g., ECG for bradyarrhythmia/conduction abnormalities and other baseline evaluations), which may increase detection and reporting of cardiovascular or laboratory-related abnormalities in settings where such monitoring is routinely implemented. Furthermore, population background risks and genetic predispositions vary by geography; for instance, the U. S. carries a high baseline burden of metabolic disease (adult obesity 40.3% in 2021–2023; diabetes 12.0% in 2023), which could increase the likelihood of reporting metabolism-or eye-related events and complicate attribution when underlying disease is common. Finally, cross-country differences in pharmacovigilance systems and reporting behaviors may affect what gets captured in FAERS and how promptly, further distorting apparent disproportionality patterns. Finally, cross-country differences in pharmacovigilance systems and reporting behaviors may affect what gets captured in FAERS and how promptly, further distorting apparent disproportionality patterns. Second, the database lacks detailed clinical background information about patients, such as their medical history and concomitant medications, which may affect the AEs association analysis. Therefore, concomitant medications and comorbidities may confound AE attribution, and some reported events may not be solely attributable to Etrasimod. Furthermore, signal mining methods can only identify statistical associations and cannot establish causality. Accordingly, the mechanistic explanations proposed for newly detected AEs (e.g., diabetic eye disease/DR, and iron metabolismyssality events) remain speculative at this stage. Future studies should therefore validate these signals and pathways through targeted preclinical experiments and well-designed clinical investigations, ideally complemented by randomized clinical trials when feasible. While this study provides insights into the AEs related to Etrasimod through FAERS database analysis, its limitations should be acknowledged. Due to the reliance on spontaneous reporting, FAERS data may suffer from reporting biases, including issues with completeness, accuracy, and timeliness, and may not comprehensively capture all real-world AEs. Since the data in FAERS are based on observational reports, causal relationships cannot be directly determined from these data. Reported AEs may be related to Etrasimod or may be caused by other factors. In addition, this study does not include detailed clinical analyses, such as case reviews or combined drug analyses. Future research should incorporate these detailed analyses to provide a more comprehensive understanding of Etrasimod’s safety profile.
Conclusion
As an innovative nontitrated oral S1P receptor modulator, Etrasimod offers new hope for UC treatment. However, this study, based on AE data from the FAERS database, demonstrates that Etrasimod presents certain safety risks in clinical applications, primarily concerning gastrointestinal disorders, general disorders, and administration site conditions, and nervous system disorders. Diabetic eye disease is the most prominent AE, characterized by microaneurysm formation and retinal hemorrhage. The newly identified potential AEs, including Type 2 diabetes mellitus, thyroid disorder, DR, and diabetic eye disease, suggest that Etrasimod may have profound effects on the metabolic, endocrine, eye, and immune systems in certain patients. Therefore, to ensure the safe use of Etrasimod, clinicians should strengthen AE monitoring in high-risk populations and conduct regular check-ups. In addition, patient education on the potential risks of the drug is crucial to improving treatment adherence. Although this study highlights some safety concerns for Etrasimod in the real world, further large-scale prospective studies and clinical trials are necessary to comprehensively assess its long-term safety.
Conflicts of interest
There are no conflicts of interest.
Acknowledgments
This study was performed using the FAERS source that was provided by the FDA. The information, results, or interpretation of the current study do not represent any opinion of the FDA.
Funding Statement
The work is supported by the Natural Science Foundation of Jiangsu Province (BK20231146), Yanzhen Talent Program for Emerging Academic Leaders (YZ-HBDTR-SJ-2025).
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