
==== Front
BMC Pharmacol Toxicol
BMC Pharmacol Toxicol
BMC Pharmacology & Toxicology
2050-6511
BioMed Central London

789
10.1186/s40360-024-00789-9
Research
Stratified analysis of the association between anti-obesity medications and digestive adverse events: a real-world study based on the FDA adverse event reporting system database
Yang Qing 1
Wang Junyan 2
Wang Menghuan 1
Zhang Shuyu 1
He Qin-Qin heqinqin2022@wchscu.cn

2
1 https://ror.org/003xyzq10 grid.256922.8 0000 0000 9139 560X Department of Anesthesiology, Huaihe Hospital of Henan University, No. 8, Baobei Road, Gulou District, Kaifeng, 475000 China
2 https://ror.org/007mrxy13 grid.412901.f 0000 0004 1770 1022 Department of Anaesthesiology, Laboratory of Mitochondria and Metabolism, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
12 9 2024
12 9 2024
2024
25 6422 4 2024
6 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

Numerous digestive system adverse events (dsAEs) have been observed during the use of anti-obesity medications (AOMs), leading to concerns about the safety of these medications. However, most current studies are limited to the association of one class of drugs with specific digestive disorders, and there is no cascading analysis of AOMs in the digestive system. This study aims to use data from the United States Food and Drug Administration Adverse Event Reporting System (FAERS) for a stratified analysis of the reported associations between AOMs and dsAEs.

Methods

We analyzed adverse event reports submitted to FAERS between January 2015 and December 2023 related to obesity treatment. It is important to note that FAERS data cannot establish causality or incidence rates. Pharmacovigilance (PV) signals were detected by disproportionate analyses through proportionate reporting ratio (PRR), reporting odds ratios (ROR), and information components (IC) to detect dsAEs associated with AOMs. Reporting rates, severity, and response outcomes of digestive adverse events were compared across AOMs by multivariate logistic regression analysis.

Results

Among 34,396 adverse events (AEs) related to obesity treatment, 8844 dsAEs were analyzed. Comparing with semaglutide and liraglutide, tirzepatide exhibited fewer reported dsAEs while semaglutide and liraglutide showed a high correlation with non-lethal pancreatitis reports. Bupropion-naltrexone (31.65%) reported the highest number of dsAEs, and a PV signal was detected in mouth and lips AEs (ROR = 2.97, 95% CI: 2.42–3.6). Orlistat (ROR = 3.30, 95% CI: 3.08–3.55) exhibited the highest association with gastrointestinal AEs compared to other AOMs. PV signal for hepatobiliary AEs (ROR = 6.13, 95% CI: 3.45–10.88) with phentermine-topiramate still needs further clarification.

Conclusions

Tirzepatide may be considered for patients with a history of digestive system disease or an elevated risk of pancreatitis based on the pattern of reported dsAEs. Caution is needed for the orofacial AEs when using bupropion-naltrexone. Orlistat has a higher reporting rate of gastrointestinal AEs, but these events are typically less severe. Phentermine-topiramate’s association with liver impairment requires further clinical investigation. This article provides insights into the reported associations between AOMs and dsAEs, which may aid clinicians in making more informed decisions about individualizing medication and managing potential adverse events.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40360-024-00789-9.

Keywords

Obesity
Anti-obesity medications
Digestive adverse events
Pharmacovigilance
Disproportionality analysis
FDA adverse event reporting system database
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcBackground

According to the World Health Organization (WHO), overweight is defined as a BMI > 25 kg/m², and obesity is defined as a BMI > 30 kg/m² and these conditions are characterized by abnormal or excessive fat accumulation [1]. The prevalence of obesity has risen to pandemic proportions globally over the past 50 years. In 2016, more than 1.9 billion adults aged 18 years and older were categorized as overweight, more than 650 million adults were in the obese category, and approximately 13% of the global adult population [2]. World Obesity Atlas 2023, the latest publication from the World Obesity Federation, predicts that more than 4 billion people could be affected by overweight or obesity globally by 2035 compared with over 2.6 billion in 2020 [3], and overweight and obesity will cost the global economy over US$4 trillion of potential income in 2035, nearly 3% of current global gross domestic product (GDP) [4]. Currently, Obesity has now become a severe public health problem and is associated with an elevated health risk [1].

The rising prevalence of obesity is associated with an increased risk of a variety of diseases that lead to higher mortality rates, including type 2 diabetes mellitus, hyperlipidemia, non-alcoholic fatty liver disease, and certain types of cancers (e.g. colorectal cancer), etc. [5–7]. Therefore, amidst the persistent rise in global obesity rates, effective obesity management emerges as a critical imperative. Various guidelines have been devised in the USA [8], the UK [9], and Europe [10] to furnish healthcare professionals with a comprehensive framework for the effective management of obesity. These guidelines encompass three key components: lifestyle modifications involving dietary adjustments and heightened physical activity, pharmacological treatment, and surgical interventions when indicated. Lifestyle interventions are the cornerstone of the treatment of obesity but are of limited effectiveness and durability for the majority of the population [11, 12]. Following a period of rapid growth, there has been a gradual decline in the number of obese patients undergoing weight loss surgeries in recent years [13]. Surgery carries the risk of trauma, postoperative complications leading to reoperation (e.g. weight regain, anastomotic fistula, bowel obstruction, etc.), and even death [11, 14], despite surgical treatment being the most effective and widely adopted method for weight loss. In recent years, more and more weight-loss drugs have been approved for clinical use in the treatment of obesity, leading to a growing population of patients using these medications [15], so it is urgent to evaluate the safety of anti-obesity medications (AOMs).

We referred to the American Gastroenterological Association (AGA) Clinical Practice Guideline on Pharmacological Interventions for Adults with Obesity to select six commonly used anti-obesity medications approved by the United States Food and Drug Administration (FDA) [16]. GLP-1 receptor agonists (GLP-1 RAs) semaglutide and liraglutide, which act in the hypothalamus to suppress appetite, delay gastric emptying, increase glucose-dependent insulin release, and decrease glucagon secretion [17]; Orlistat, a pancreatic lipase inhibitor that prevents triglyceride hydrolysis and thus reduces free fatty acid absorption [18]; Bupropion-naltrexone, which reduces response to food signaling and ameliorates dysregulation of dietary control in the limbic pathway of the midbrain [19]; Additionally, there are phentermine-topiramate and phentermine, where phentermine reduces appetite by enhancing norepinephrine release and blocking norepinephrine reuptake, but the exact mechanism of topiramate is still unclear [20]. Simultaneously, we have included the latest FDA-approved weight loss medication for clinical use, tirzepatide (a glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 RA [21]).According to the literature, obese patients, whether with or without diabetes, exhibit a correlation between the use of GLP-1 RAs and gastrointestinal adverse reactions [22, 23]. Meanwhile, A descriptive analysis of adverse events (AEs) of AOMs in the United States Food and Drug Administration Adverse Event Reporting System (FAERS) found that nausea and vomiting were the most common adverse events [24]. So, it is really necessary to explore the association between different AOMs and digestive adverse events (dsAEs).

Currently, there is a lack of stratified profiling of AOM-related adverse events in the digestive system. Therefore, in this study, we classified the AEs in the digestive system into the digestive tract, digestive glands, and specific digestive organs, and utilized the data in the FAERS database to analyze in detail the PVs, reporting rates, severity, and outcomes of the adverse events in each stratum, so as to provide substantial references for the use of clinical medications, the individualization of medications, and the alleviation of patients’ discomfort during the treatment period.

Methods

Data source and study design

FAERS is the public database used by the FDA to collect all AE information and medication error information and has been an important infrastructure for post-marketing safety studies of drugs in recent years [25]. Healthcare professionals and consumers voluntarily submit information such as AE and medication error reports, which are managed by the FDA and evaluated by clinical reviewers from the Center for Drug Evaluation and Research and the Center for Biologics Evaluation and Research [26]. All information is available on the official FDA website. (https://open.fda.gov/data/downloads/).

In this study, we primarily collected information: safety report ID (“safetyreportid”), nationality, weight, sex, and age at the time of reporting (“primarysourcecountry”, “patientweight”, “patientsex” and “patientonsetage”), AE (“actionmeddrapt”), severity of adverse reaction (“serious”), AE response outcome (“actionoutcome”), drug name (“activesubstancename”), and the reason for taking the drug (“drugindication”), where the severity of the adverse reaction also includes whether it was fatal (“seriousnessdeath”). We then analyzed reports of dsAEs related to the treatment of obesity in adults submitted to FAERS from January 2015 to December 2023, totaling 59,179,740 entries. Data on the treatment of obesity (44,179 in total) were screened, and then duplicate reports, anonymized drug reports, and reports of unknown AEs were sequentially deleted, along with an incredible number of ages, and weights were converted to “unknown” values, ultimately reducing the number of reports to 34,396. In addition, we retained only adverse reaction reports from persons 16 years of age or older. Because FAERS is a publicly available anonymized database, informed consent and review approval by the institutional review board was waived for this study.

Drugs of interest

We retrieved relevant suspect drugs from the drug directory using the generic names of the medications [16]. We selected 6 guideline-recommended FDA-approved AOMs based on the AGA Clinical Practice Guidelines for Pharmacologic Interventions for Obesity in Adults, including: liraglutide, semaglutide, orlistat, bupropion-naltrexone, phentermine-topiramate, and phentermine along with one recently FDA-approved anti-obesity drug for clinical use, tirzepatide.

Definition of adverse event of interest

In FAERS, suspected AEs are described using the 27 system organ classifications (SOC) and preferred terms (PT) from the Medical Dictionary for Regulatory Activities (MedDRA) [27]. Severe adverse events (SAEs) are defined to indicate any of the following criteria, including death, life-threatening, leading to/prolonged hospitalization, disability/incapacity, congenital anomalies/birth defects, and other medically significant symptoms. Otherwise, the case is not considered severe. The severity of patient outcomes is graded on a scale of 1 to 5: 1 = Recovered/Resolved, 2 = Partial recovery/Resolution, 3 = Not Recovered/Not Resolved, 4 = Recovered/Resolved with sequelae, and 5 = Fatal [28]. In this study, we mainly investigated the AEs in the broader digestive system (i.e., including the oral cavity, esophagus, stomach, small and large intestines, liver, gallbladder, and pancreas [29]) and further subdivided the digestive system by counting the digestive tract and digestive glands AEs separately (Table S4). Finally, individual investigations were conducted on specific digestive organs (including mouth and lips, gastrointestinal tract, hepatobiliary, and pancreas).

Data mining and statistical analysis

We utilized data submitted to FAERS to assess the correlation between the usage of AOMs and dsAEs. The application of disproportionality analysis is limited to the examination of pharmacovigilance signals pertaining to anti-obesity drugs and their impact on the digestive system of obese patients. Disproportionality analysis was conducted to compare the observed reporting frequency and the expected reporting frequency of weight loss drugs concerning adverse events in the digestive system. Disproportionality analysis can be categorized into two forms: the frequency analysis method and the Bayesian analysis method. In this study, the frequency analysis method (Proportional Reporting Ratio [PRR], Reporting Odds Ratio [ROR]) and Bayesian analysis method (Information Component [IC]) were regarded as statistical indicators for disproportionality analysis [30–32]. As the correlation between specific drugs and adverse events strengthens, the corresponding indicator values increase. Once a predefined threshold is surpassed, the detection of a Pharmacovigilance (PV) signal is considered. In other words, a PV signal is suggested under the following conditions: (1) Number of cases ≥ 3, PRR ≥ 2, and χ2 analysis (χ2) ≥ 4; (2) The lower limit of the 95% confidence interval (CI) for ROR is > 1; (3) IC025 is > 0. The calculation formula, including χ2 and the 95% CI, is provided below [33]:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$PRR=\frac{{a/\left( {a+c} \right)}}{{b/\left( {b+d} \right)}}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$PRR95\% CI={e^{\ln \left( {PRR} \right) \pm 1.96\sqrt {\frac{1}{a} - \frac{1}{{a+c}}+\frac{1}{b} - \frac{1}{{b+d}}} }}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ROR=\frac{{\left( {a/c} \right)}}{{\left( {b/d} \right)}}=\frac{{ad}}{{bc}}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ROR95\% CI={e^{\ln \left( {ROR} \right) \pm 1.96\sqrt {\frac{1}{a}+\frac{1}{b}+\frac{1}{c}+\frac{1}{d}} }}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$X_{{yates}}^{2}=\frac{{\left( {a+b+c+d} \right)\cdot{{\left( {\left| {\left( {a \times d} \right) - \left( {b \times c} \right)} \right| - \left( {a+b+c+d} \right)/2} \right)}^2}}}{{\left( {a+c} \right)\cdot\left( {a+b} \right)\cdot\left( {b+d} \right)\cdot\left( {d+c} \right)}}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Information\,component\left( {IC} \right)=lo{g_2}\frac{{a+0.5}}{{{a_{exp}}+0.5}}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${a_{exp}}=\frac{{\left( {a+b} \right)\cdot\left( {a+c} \right)}}{{\left( {a+b+c+d} \right)}}$$\end{document}

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$I{C_{025}}=IC - 3.3{\left( {a+0.5} \right)^{ - \frac{1}{2}}} - 2{\left( {a+0.5} \right)^{ - \frac{3}{2}}}$$\end{document}

a = The number of reports of the drug of interest with the adverse event of interest. b = The number of reports of all other drugs with the adverse event of interest. c = The number of reports of the drug of interest with all other adverse events. d = The number of reports of all other drugs with all other adverse events.

For continuous variables, a normality test was conducted. If the data followed a normal distribution, the mean ± standard deviation was used for description; if not, the median and interquartile range (IQR) were used. For categorical variables, frequency and percentage were used for description. We used multivariate logistic regression to compare the reporting rate of serious digestive adverse events among all adverse events caused by different anti-obesity drugs. Additionally, ordinal logistic regression was used to compare the severity of reaction outcomes in ordinal multi-categorical data among reporters of digestive system adverse events. All regressions were adjusted for age and gender (patient_onsetage = Age at time of response/event in obese patients; gender = Gender of obese patients, Male = 0, Female = 1). We did not exclude covariates that were not significant in the final model. Information on covariates in the model are presented in Tables S5 and S6. All analyzes were performed in Stata 17.0 MP software. P < 0.05 was considered significant.

Results

Descriptive statistics

From January 2015 to December 2023, the FAERS database documented a total of 44,179 adverse events associated with the treatment of obesity. Following the exclusion of some incomplete data, a total of 8,844 cases were ultimately identified as adverse events related to the digestive system. Among the cohort experiencing dsAEs, 68.83% of female patients with obesity reported encountering these incidents, with a median age (IQR) of 51 (40–61) years and a median weight (IQR) of 93 (80–113) kg, and the majority of reporters were from the United States (56.35%). Table 1 summarizes the baseline characteristics of these reports. We further classified into two subcategories: digestive tract AEs (6731 cases) are nearly six times more prevalent than glandular AEs (1015 cases). However, both were reported by obese females with a higher incidence of AEs (69.22% and 64.63%), with similar median ages (52 and 50 years) and median weights of 93 kg. Reporters of digestive tract AEs are primarily from the United States (59.83%), whereas reporters of glandular AEs are more geographically dispersed in other countries (65.32%). Finally, detailed baseline data of the digestive tract, digestive glands, and digestive organs are presented in Table S1.

Table 1 Characteristics of AOM-associated digestive system adverse events (January 1, 2015–December 31, 2023)

Characteristics	Total
(n = 8844)	Liraglutide
(n = 1524)	Semaglutide
(n = 1506)	Tirzepatide
(n = 167)	Bupropion-naltrexone
(n = 2799)	Orlistat
(n = 1991)	Phentermine-topiramate
(n = 21)	Phentermine
(n = 74)	
Gender, n (%)	
 Male	1052 (11.90%)	264 (17.32%)	435 (28.88%)	27 (16.16%)	222 (7.93%)	273 (13.71%)	3 (14.29%)	10 (13.51%)	
 Female	6087 (68.83%)	1235 (81.03%)	1014 (67.33%)	135 (80.84%)	1811(64.70%)	1400 (70.32%)	13 (61.90%)	61 (82.43%)	
 Unknown	1255 (14.19%)	25 (1.64%)	57 (3.78%)	5 (2.99%)	766 (28.37%)	318 (15.97%)	5 (23.81%)	3 (4.05%)	
Age, Median (IQR)	51 (40–61)	48 (38–58)	53 (42–64)	47 (34–57)	52 (42–60)	51 (38–60)	52 (38–59)	46 (35–59)	
Weight, Median (IQR)	93 (80–113)	93 (81–115)	95 (81–114)	81 (76–93)	94 (82–113)	94 (80–118)	98 (73–113)	78 (70–90)	
Reporting region, n (%)	
 United States	4984 (56.35%)	621 (40.75%)	754 (50.07%)	160 (95.80%)	1183 (42.27%)	1822 (91.51%)	21 (100%)	61 (82.43%)	
 Other countries	3830 (43.31%)	897 (58.86%)	752 (49.93%)	7 (4.19%)	1616 (57.73%)	168 (8.44%)	0	7 (9.46%)	
 Unknown	30 (0.34%)	6 (0.93%)	0	0	0	1 (0.05%)	0	6 (8.11%)	
Seriousness, n (%)	
 Serious	4725 (53.43%)	1106 (72.57%)	944 (62.68%)	20 (11.98%)	1749 (62.49%)	250 (12.56%)	14 (66.67%)	46	
 Not serious	4119 (46.57%)	418 (27.43%)	562 (37.32%)	147 (88.02%)	1050 (37.51%)	1741 (87.44%)	7 (33.33%)	28	
Severity of reaction outcome, n (%)	
 1	3429 (38.77%)	630 (41.34%)	598 (39.71%)	37 (22.16%)	1078 (38.51%)	870 (43.70%)	9 (42.86%)	33 (62.16%)	
 2	773 (8.74%)	181 (11.88%)	153 (10.16%)	20 (11.98%)	248 (8.86%)	84 (4.22%)	0	6 (37.84%)	
 3	2173 (24.57%)	357 (23.43%)	368 (24.44%)	22 (13.17%)	962 (34.37%)	339 (17.03%)	1 (4.76%)	17 (44.59%)	
 4	52 (0.59%)	16 (1.05%)	11 (0.73%)	0	4 (0.14%)	5 (0.25%)	0	0	
 5	39 (0.44%)	10 (0.66%)	8 (0.53%)	0	3 (0.11%)	1 (0.05%)	1 (4.76%)	1 (1.35%)	
 Unknown	2378 (26.89%)	330 (21.65%)	377 (25.03%)	88 (52.69%)	504 (18.01%)	755 (37.92%)	10 (47.62%)	17 (22.97%)	
Abbreviations The reaction outcomes were graded on a scale of 1 to 5 depending on the severity of the patient’s outcome: 1 = recovered/resolved, 2 = recovering/resolving, 3 = not recovered/not resolved, 4 = recovered/resolved with sequelae, and 5 = fatal

The top three AOMs with the highest reported dsAEs are bupropion-naltrexone (31.65%), orlistat (22.51%), and liraglutide (17.23%) and the most common sea is nausea (1,658, 18.75%), followed by vomiting (8.53%) and diarrhea (8.21%). The three drugs most frequently reported for gastrointestinal AEs are bupropion-naltrexone (34.90%), orlistat (23.70%), and semaglutide (15.57%), the most frequently occurring gastrointestinal AEs were consistent with the above. On the other hand, the drug most frequently reported for glandular digestive system adverse events is liraglutide (33.30%), followed by semaglutide (26.90%), and then orlistat and bupropion-naltrexone (10.94%). The reported rates of glandular adverse events are Cholelithiasis (11.72%), Pancreatitis (11.63%), and Hepatic enzyme increased (5.42%). The top 10 most common adverse events are shown in Figs. 1 and S1. The most common AOMs varied in different digestive organs, with bupropion-naltrexone being the most common in the orofacial and gastrointestinal regions (62.24% and 33.34%), and liraglutide being the most common in the hepatobiliary and pancreatic regions (28.96% and 48.12%).

Fig. 1 Top 10 most reported number of digestive adverse events. The bar plot shows statistics for the top 10 reported adverse events for the digestive system (orange), digestive tract (blue), and digestive glands (green). The colors indicate the corresponding categories of adverse events. Percentage values labeled in the figure represent the proportion of cases of that adverse event that occurred in obese patients taking anti-obesity medications out of the total number of cases of that category of adverse events

Disproportionate analysis

In the disproportionate analysis, Initially, we studied dsAEs among 7 AOMs (Table 2). The results revealed PV signals for dsAEs in semaglutide (PRR = 1.28, 95% CI: 1.23–1.34; χ2 = 105.07; ROR = 1.41, 95% CI: 1.32–1.51; IC = 0.30, IC025 = 0.22), liraglutide (PRR = 1.45, 95% CI: 1.39–1.52; χ2 = 238.37; ROR = 1.7, 95% CI: 1.59–1.82; IC = 0.46, IC025 = 0.37), and orlistat (PRR = 2.12, 95% CI: 2.04–2.21; χ2 = 1234.07; ROR = 3.16, 95% CI: 2.96–3.38; IC = 0.90, IC025 = 0.83), whereas no PV signals were detected in other AOMs. We further detected PV signals in the digestive tracts and glands and found that PV signals were detected in both the tract and glands for semaglutide and liraglutide, but orlistat (PRR = 2.27, 95% CI: 2.17–2.38; χ2 = 1074.64; ROR = 3.07, 95% CI: 2.86–3.29; IC = 0.98, IC025 = 0.89) exhibited PV signal only in the tract. Intriguingly, we found PV signals in the glands for Phentermine-topiramate (PRR = 5.33, 95% CI: 3.28–8.66; χ2 = 50.06; ROR = 6.13, 95% CI: 3.45–10.88; IC = 2.20, IC025 = 1.30). As to the digestive organ (Table S2), only bupropion-naltrexone (PRR = 2.93, 95% CI: 2.39–3.59; χ2 = 118.65; ROR = 2.97, 95% CI: 2.42–3.65; IC = 0.79, IC025 = 0.58) exhibited a PV signal in mouth & lip-related AEs. PV signals for gastrointestinal AEs were detected in semaglutide, liraglutide, and orlistat, while PV signals for hepatobiliary AEs were detected in semaglutide, liraglutide, and phentermine-topiramate. Finally, we performed a detailed analysis of the pancreas and detected PV signals in semaglutide and liraglutide, which is consistent with non-lethal pancreatitis. These findings suggest that, in comparison to other investigated AOMs, semaglutide and liraglutide exhibit a stronger correlation with overall dsAEs, orlistat is more closely correlated with gastrointestinal AEs, and phentermine-topiramate shows a higher correlation with glandular AEs, particularly in hepatobiliary events.

Table 2 Disproportionate analysis of anti-obesity medication-associated digestive system, tract and gland adverse events

Events	Drugs	a	b	c	d	PRR (95%CI)	ROR (95% CI)	χ²	P	IC	IC025	
Digestive system	Liraglutide	1524	7320	2791	22,761	1.45 (1.39, 1.52)	1.7 (1.59, 1.82)	238.37	<0.001	0.46	0.37	
Semaglutide	1506	7338	3237	22,315	1.28 (1.23, 1.34)	1.41 (1.32, 1.51)	105.07	<0.001	0.30	0.22	
Tirzepatide	167	8677	441	25,111	1.07 (0.94, 1.22)	1.10 (0.92, 1.31)	1.00	0.318	0.09	−0.16	
Bupropion-naltrexone	2799	6045	9580	15,972	0.82 (0.79, 0.86)	0.77 (0.73, 0.81)	97.39	<0.001	−0.19	−0.25	
Orlistat	1991	6853	2149	23,403	2.12 (2.04, 2.21)	3.16 (2.96, 3.38)	1234.07	<0.001	0.90	0.83	
Phentermine/topiramate	21	8823	69	25,483	0.91 (0.62, 1.32)	0.88 (0.54, 1.43)	0.27	0.605	−0.14	−0.87	
Phentermine	74	8770	635	24,917	0.4 (0.32, 0.50)	0.33 (0.26, 0.42)	88.43	<0.001	−1.29	−1.68	
Digestive tract	Liraglutide	1009	5722	3306	24,359	1.23 (1.16, 1.30)	1.30 (1.20, 1.40)	45.61	<0.001	0.26	0.15	
Semaglutide	1048	5683	3695	23,970	1.15 (1.09, 1.22)	1.20 (1.11, 1.29)	22.31	<0.001	0.18	0.07	
Tirzepatide	137	6594	471	27,194	1.15 (0.99, 1.34)	1.20 (0.99, 1.45)	3.45	0.063	0.2	−0.08	
Bupropion-naltrexone	2349	4382	10,030	17,635	0.95 (0.91, 1.00)	0.94 (0.89, 1.00)	4.33	0.038	−0.04	−0.11	
Orlistat	1595	5136	2545	25,120	2.27 (2.17, 2.38)	3.07 (2.86, 3.29)	1074.64	<0.001	0.98	0.89	
Phentermine/topiramate	7	6724	83	27,582	0.40 (0.19, 0.81)	0.35 (0.16, 0.75)	7.97	0.005	−1.27	−2.57	
Phentermine	59	6672	650	27,015	0.42 (0.33, 0.54)	0.37 (0.28, 0.48)	58.19	<0.001	−1.23	−1.66	
Digestive gland	Liraglutide	338	677	3977	29,404	3.48 (3.07, 3.95)	3.69 (3.23, 4.22)	410.66	<0.001	1.40	1.23	
Semaglutide	273	742	4470	28,911	2.30 (2.01, 2.63)	2.38 (2.06, 2.74)	151.14	<0.001	0.96	0.76	
Tirzepatide	11	1004	597	32,784	0.61 (0.34, 1.10)	0.60 (0.33, 1.10)	2.82	0.093	−0.68	−1.71	
Bupropion-naltrexone	111	904	12,268	21,113	0.22 (0.18, 0.27)	0.21 (0.17, 0.26)	284.96	<0.001	−1.71	−2.03	
Orlistat	111	904	4029	29,352	0.90 (0.74, 1.09)	0.89 (0.73, 1.09)	1.20	0.274	−0.14	−0.45	
Phentermine/topiramate	14	1001	76	33,305	5.33 (3.28, 8.66)	6.13 (3.45, 10.88)	50.06	<0.001	2.20	1.30	
Phentermine	7	1008	702	32,679	0.33 (0.16, 0.69)	0.32 (0.15, 0.68)	9.75	0.002	−1.51	−2.82	
Abbreviations a = The number of reports of the drug of interest with the adverse event of interest; b = The number of reports of all other drugs with the adverse event of interest; c = The number of reports of the drug of interest with all other adverse events; d = The number of reports of all other drugs with all other adverse events; PRR = proportional reporting ratio; ROR = reporting odds ratio; IC = information component

P < 0.05 was considered to be of significant significance

Percentages of digestive adverse events in all adverse events caused by AOMs

Concerning the overall digestive system, orlistat exhibited a significant increase in AEs, whereas phentermine demonstrated a noteworthy decrease in AEs when compared to the other AOMs. Semaglutide (OR = 0.85, 95% CI: 0.76–0.94) and tirzepatide (OR = 0.57, 95% CI: 0.45–0.74) exhibited a significantly lower incidence of dsAEs compared to liraglutide, and tirzepatide (OR = 0.68, 95% CI: 0.53–0.87) also demonstrated a significant reduction compared to semaglutide. Additionally, the combination therapy of phentermine-topiramate (OR = 1.98, 95% CI: 1.06–3.71) significantly increases compared to phentermine monotherapy (Fig. 2a). Focusing further on the digestive tract and glands, there were no statistically differences in digestive tract AEs among the three drugs, but semaglutide (OR = 5.22,95% CI: 2.13–12.75) and liraglutide (OR = 6.37,95% CI: 2.6–15.54) digestive gland AEs were significantly increased compared to tirzepatide. Compared to phentermine alone, phentermine-topiramate (OR = 13.99, 95% CI: 4.81–40.65) combination was significantly increased in the gland (Fig. 2b). Surprisingly, phentermine-topiramate shows a significant increase in hepatobiliary AEs compared to the others. Additionally, in the pancreas, AEs with liraglutide are significantly higher than semaglutide and tirzepatide, but there is no statistical difference between semaglutide and tirzepatide (Fig. S2).

Fig. 2 Comparison of the percentages of digestive adverse events and reporting rate of severe adverse events caused by anti-obesity medications. (a) Percentages of digestive system adverse events. (b) Percentages of digestive tract adverse events (upper right) and percentages of digestive glands adverse events (lower left). (c) Reporting rate of severe digestive system adverse events. (d) Reporting rate of severe digestive tract adverse events and incidence of severe digestive gland adverse events. Odds ratio for percentages of adverse events and Incidence of severe adverse events. Numbers in parentheses indicate 95% credible intervals (95% CrIs). Relatively dark colors represent OR > 1, relatively light colors represent OR < 1, and no color indicates no statistical significance. (c) and (d) are adjusted for age and gender. All tables are in alphabetical order, but liraglutide, semaglutide and tirzepatide are listed together for ease of comparison

Reporting rate of severe digestive adverse events between AOMs

Throughout the digestive system, semaglutide (OR = 22.02, 95% CI: 11.23–43.1) and liraglutide (OR = 19.74, 95% CI: 10.11–38.56) had significantly higher rates of SAEs compared with tirzepatide, but there was no statistical difference between semaglutide and liraglutide. Meanwhile, there was also no statistical difference in the incidence of SAEs in the digestive system with the phentermine-topiramate combination compared to phentermine alone (Fig. 2c).

Whether in the digestive tract or glands, the incidence of SAEs is significantly increased for semaglutide and liraglutide compared to tirzepatide. However, there is no statistical difference in the digestive tract between semaglutide and liraglutide, while in the digestive glands, semaglutide (OR = 4.86, 95% CI: 1.05–22.51) significantly elevates the reporting rate of SAEs compared to liraglutide (Fig. 2d).

Subsequently, through multifactorial logistic regression analysis, we found that the occurrence rate of SAEs in the tract for the other five weight-loss drugs was significantly lower than that in the glands, except for phentermine-topiramate and phentermine, for which statistics were not available (Table S3). Then, tirzepatide only had a significantly lower reporting rate of SAEs in the gastrointestinal tract than the others (Fig. S3). Overall, among the studied drugs, the incidence of SAEs in the digestive tract is significantly lower than in the digestive glands, with tirzepatide having the lowest incidence, particularly in the gastrointestinal tract.

Severity of digestive adverse events reaction outcome between AOMs

Statistical analyzes revealed no statistically significant difference in the risk of severe reaction outcomes in the digestive system among liraglutide, semaglutide and tirzepatide, but in the digestive glands there was a significantly increased risk of a more severe reaction outcome with liraglutide (OR = 1.86, 95% CI: 1.28–2.71) than with semaglutide. Similar results were found only in the hepatobiliary, where liraglutide (OR = 2.43, 95% CI: 1.55–3.82) resulted in a significantly higher risk of more serious hepatobiliary adverse reaction outcomes, and there was no statistical difference between the two in any of the other digestive organs. Remarkably, phentermine-topiramate combination therapy and phentermine monotherapy showed no statistically significant difference in the entire digestive system and the digestive tract, but phentermine-topiramate (OR = 0.06, 95% CI: 0.003–0.79) exhibited a significantly reduced risk of more severe reaction outcomes compared to phentermine in the digestive gland. (Fig. S4)

Discussion

This study innovatively conducts a continuous stratification of dsAEs, comparing the digestive tract and digestive glands, and finally focusing on different digestive organs, and is a PV study that analyses AOMs-associated dsAEs based on real-world data from the FAERS database. Through disproportionality analysis, we detected PV signals for these seven drugs, and regression analysis was employed to explore the reporting rate, severity, and reaction outcomes. A comprehensive understanding of dsAEs caused by AOMs can alert clinicians to weigh the pros and cons when selecting and prescribing diet pills, facilitating personalized treatment.

Currently, the safety and efficacy of GLP-1 in treating obesity are widely scrutinized [34]. In our study, we did find that tirzepatide (a dual GIP/GLP-1 receptor co-agonist) lacked a PV signal throughout the digestive system, and its AEs composition and severity rate were significantly lower than liraglutide and semaglutide. A meta-analysis of a RCT measuring weight loss by mean difference indicates that, compared to weekly subcutaneous injections of 2.4 mg semaglutide (mean difference of 5.1%; 95% CI, 0.6–9.8%) and daily subcutaneous injections of 3 mg liraglutide (mean difference of 13.0%; 95% CI, 8.8–17.4%), the relationship between weekly intake of 15 mg tirzepatide and weight loss is more significant [35]. Preliminarily, tirzepatide was preferred over the commonly used single GLP-1 RAs among those studied, and this result can guide prescribers in decision-making when considering the use of GLP-1 RAs, provided it is sold at a reasonable, cost-effective price.

GLP-1 RAs have AEs in both the digestive tract and digestive glands. A recent cohort study based on the PharMetrics Plus database indicates that, compared to naltrexone-bupropion, the use of GLP-1 RAs is associated with an increased risk of pancreatitis (HR, 9.09 [95% CI, 1.25–66.00]), and gastroparesis (HR, 3.67 [95% CI, 1.15–11.90]) [22]. Moreover, existing research indicates that GLP-1 RAs, stimulate adenylate cyclase, increase gastric mucosal cyclic adenosine monophosphate levels, inhibit muscle contraction through protein kinase A, resulting in slowed gastric emptying [36]. Simultaneously, they may influence immune and inflammatory responses, potentially leading to pancreatitis, although the specific mechanisms remain unclear [37].Hence, further comparison between the digestive tract and glands is essential. In the horizontal comparison, the reporting rates of SAEs of liraglutide and semaglutide are significantly higher than tirzepatide in the digestive tract, simultaneously the percentage of AEs and the reporting rate of SAEs are in the order of liraglutide > semaglutide > tirzepatide in the digestive glands. In the longitudinal comparison, the number of AEs was higher in the digestive tract than in the gland, but the reporting rate of SAEs was significantly lower in the tract than in the gland for three drugs. Focusing on the gastrointestinal and pancreatic events (including non-fatal pancreatitis), both liraglutide and semaglutide show PV signals, but tirzepatide does not. Tirzepatide simultaneously activates GLP-1 and GIP receptors (a gut insulinotropic peptide responsible for most of the gut insulinotropic effects, with important additional functions distinct from GLP-1), reducing the occurrence of gastrointestinal and pancreatic AEs compared to the mechanism of solely GLP-1 RAs, which still needs exploration.

Bupropion-naltrexone (31.65%) and orlistat (22.51%) reported the highest reporting rate of adverse events, with the most common being nausea (18.75%), vomiting (8.53%), and diarrhea (8.21%). During PV analysis, although Bupropion-naltrexone reported the highest number of dsAEs, the composition of dsAEs is relatively low compared to liraglutide (OR = 0.52,95%CI: 0.47–0.57), semaglutide (OR = 0.61,95%CI: 0.55–0.67) and Orlistat (OR = 0.36,95%CI: 0.33–0.40), which detect PV signals, hence not meeting PV criteria. The most commonly reported AE in multicenter, randomized, double-blind, placebo-controlled, phase 3 clinical trials (COR-I) was nausea (29.2–42.3%), and headache, dizziness, and insomnia were also the most common AEs leading to discontinuation [38]. Since oral naltrexone and bupropion are both absorbed in the gastrointestinal tract at a rate of 90% and reduce appetite by acting on the nigrostriatal system of the hypothalamus (appetite-regulating centers) and on the limbic dopamine circuitry of the midbrain (the reward pathway) to effect weight loss [19], naltrexone and bupropion should be used with caution in patients with pre-existing digestive and neurological disorders. It is worth noting that bupropion-naltrexone only detected PV signals in the lips. In the second Phase 3 clinical trial (COR-II), dry mouth (9.1%) was also a common AE [39], but the detailed reasons for causing this AE are not yet understood. Clinicians should remind users to pay attention to lip protection to prevent strong discomfort caused by dry mouth. Regarding orlistat, the first FDA-approved treatment for obesity in 1999, it is a reversible inhibitor of gastric and pancreatic lipases. When taken with fatty meals, it partially inhibits the hydrolysis of triglycerides, reducing the absorption of glycerol esters and free fatty acids, thereby assisting in weight maintenance and reduction [40]. Interestingly orlistat detects PV signaling only in the digestive tract, and we did detect PV signaling in the gastrointestinal tract, while we found significantly more AEs in the gastrointestinal tract than other AOMs. The AGA guidelines have clearly stated that orlistat is not recommended for use where available due to its modest weight loss effect and gastrointestinal adverse effects [16]. This is highly consistent with our findings.

Due to the small sample sizes and AE reporting rates for phentermine (0.84%) and phentermine-topiramate (0.24%), the FAERS reports could only be evaluated as indirect evidence. We detected a PV signal for hepatobiliary AEs (ROR = 6.13, 95% CI: 3.45–10.88) with phentermine-topiramate. Direct effects of both on the liver have not been retrieved from the literature, but several instances of acute liver injury have been linked to topiramate monotherapy in patients with seizure disorders. Topiramate is metabolized by the cytochrome P450 system and is known to induce CYP3A4 activity. This can result in alterations to the blood concentration of specific anticonvulsant metabolites (e.g., sodium valproate [41]), which may in turn lead to hepatic injury [42]. By itself, topiramate has not been linked to severe hepatic injury. Currently phentermine is approved for short-term weight management (typically < 3 months), whereas the phentermine-topiramate combination is only approved for long-term weight management in the USA [43], whether long-term use of the phentermine-topiramate combination affects liver function still requires prolonged clinical trials for verification.

Our research has certain limitations. First, the FAERS database is a global, spontaneous reporting system that suffers from a number of inherent selection biases, such as missing data (age, weight, etc.), timing of approval of different medications, and level of public awareness of specific AEs. Second, FAERS-based disproportionate analyzes show neither causality nor quantitative risk, but only an assessment of signal strength, which is a statistical association [44]. As in other PV studies, Frequentist and Bayesian are indicators of increased risk in AE reports, and further validation of whether a causal relationship exists is required by robust pharmacologic and biological studies. There are inherent biases in databases and analytical methods that we can’t avoid, although they may make our results slightly different from the real world. Third, we selected AEs caused by the treatment of obesity based solely on the indication for medication (‘’drugindication’’) and did not convert weight into BMI to accurately organize the data according to the WHO definitions of overweight and obesity because we did not collect data on the height of the reporters. Finally, because we could not accurately assign the few AEs to specific digestive organs and could not be stratified in particular detail for each digestive organ, our study did not point to an association between a particular drug and a particular organ. Therefore, it is not detailed enough, further clinical trials or observational studies are needed to supplement our results for specific digestive disease.

Conclusions

In conclusion, this study stratified the correlations between the seven AOMs and dAEs by disproportionate analysis based on real data from the FAERS database. Tirzepatide had the smallest risk of dsAEs and reporting rate of SAE, while liraglutide had the greatest risk of dsAEs. Moreover, we found that liraglutide had more pancreatic AEs, especially nonfatal pancreatitis, than semaglutide. Bupropion-naltrexone (31.65%) reported the highest number of dsAEs, with a higher correlation with orofacial AEs. Orlistat demonstrated the highest correlation with AEs throughout the digestive system compared to the other six AOMs, particularly showing the highest correlation with digestive tract AEs, especially those related to the gastrointestinal AEs (ROR = 3.30, 95% CI: 3.08–3.55). For phentermine-topiramate (ROR = 7.48, 95% CI: 4.14–13.53) the high correlation with hepatobiliary AEs still needs to be validated by further clinical and basic trials. A comprehensive understanding of dsAEs caused by AOMs can alert clinicians to prescribe medications more judiciously and tailor treatment to individuals, thereby alleviating patient distress during the treatment process. A variety of novel AOMs are emerging, and continued research on adverse events in AOMs will be beneficial in the future.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2. Top 10 most reported number of digestive organs adverse events

Supplementary Material 3. Comparison of the percentages of digestive organs adverse events caused by anti-obesity medications

Supplementary Material 4. Comparison of the reporting rate of severe digestive organs adverse events

Supplementary Material 5. Severity of Reaction Outcome for Patients With digestive adverse events

Supplementary Material 6. Characteristics of AOM-associated digestive tract, gland and digestive organs adverse events

Supplementary Material 7. Disproportionate analysis of anti-obesity medication-associated digestive organs adverse events

Supplementary Material 8. Comparisons of the reporting rate of digestive tract and gland SAEs with the same medications

Supplementary Material 9. Overview of Outcome Classification According to the Medical Dictionary for Regulatory Activities (MedDRA)

Supplementary Material 10. Independent variables associated with reporting rate of severe digestive adverse events

Supplementary Material 11. Independent variables associated with severity of digestive adverse events reaction outcome

Acknowledgements

Not applicable.

Author contributions

Q.Y., J.W. and Q.-Q.H. contributed to conception and design of the study. Q.Y., J.W. and M.W. organized the database and performed the statistical analysis. Q.Y., M.W. and S.Z. wrote the original draft of the manuscript. Q.-Q.H. revised the manuscript and approved the final version.

Funding

No Funding.

Data availability

The datasets analysed during the current study are available in the FDA Adverse Event Reporting System repository, [https://open.fda.gov/data/downloads/].

Declarations

Ethics approval and consent to participate

Ethical approval was not provided for this study on human participants because FAERS (FDA Adverse Event Reporting System) is publicly available and anonymous database.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Abbreviations

AOMs Anti-obesity medications

AEs Adverse events

dsAEs Digestive system adverse events

SAEs Severe adverse events

FDA Food and Drug Administration

FAERS Food and Drug Administration Adverse Event Reporting System

WHO World Health Organization

AGA American Gastroenterological Association

SOC System organ classifications

PT Preferred terms

MedDRA Medical Dictionary for Regulatory Activities

GLP-1 RAs GLP-1 receptor agonists

GIP Glucose-dependent insulinotropic polypeptide

PV Pharmacovigilance

PRR Proportionate Reporting Ratio

ROR Reporting Odds Ratio

IC Information components

IQR Interquartile range

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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