Skip to main content
Download PDF

Effect of survodutide, a glucagon and GLP-1 receptor dual agonist, on weight loss: a meta-analysis of randomized controlled trials

Diabetology & Metabolic Syndrome volume 16, Article number: 264 (2024) Cite this article

Abstract

Background

Considering the increasing prevalence of obesity/overweight, its treatment or prevention with new interventions can greatly help health and reduce its adverse effects in people. One of these new interventions is investigating the effect of Survodutide as a dual agonist of glucagon and GLP-1 receptors, which seems to be able to influence weight loss processes in different ways. In this study, we investigated the effect of injectable Survodutide on weight loss.

Methods

In order to identify all randomized controlled trials that investigated the effects of Survodutide on factores related to obesity, a systematic search was conducted in the original databases using predefined keywords until August 2024. The pooled weighted mean difference and 95% confidence intervals were computed using the random-effects model.

Results

The Findings from 18 treatment arms with 1029 participants indicated significant reductions in weight (WMD: -8.33 kg; 95% CI: -10.80, -5.86; I2 = 99.6%), body mass index (BMI) (WMD:-4.03 kg/m2; 95% CI: -4.86, -3.20; I2 = 72.7%), and waist circumferences (WC) (WMD: -6.33 cm; 95% CI: -8.85 to -3.81; I2 = 99.5%) following the Survodutide injection compared to the control group. Subgroup analysis reveals that longer interventions (more than 16 weeks) and higher doses (more than 2 mg/week) of Survodutide are associated with more significant reductions in weight and WC. These results were also observed in the meta-regression analysis.

Conclusions

The results of this meta-analysis show that Survodutide is effective in reducing weight, BMI and waist circumference, especially with longer interventions and higher doses.

Introduction

Obesity is an imperative public health problem and a complex multifactorial disease that has reached pandemic dimensions. According to estimates made by the WHO, by 2025 there will be more than 700 million obese adults [1,2,3]. The prevalence of obesity in the world is predicted to increase from 14% in 2020 to 24% in 2035 [4]. Obesity has been mentioned as a significant risk factor for non-communicable chronic diseases (NCDs), mental health changes, and consequently impacts on the functional capacity of individuals and their quality of life [5].

Indeed, obesity is classified as a chronic disease, necessitating a comprehensive and sustained approach to its treatment. The primary goals of obesity management include long-term weight control and the management of any associated conditions and individual health needs [6]. This approach typically involves a combination of lifestyle changes (such as diet and physical activity), behavioral therapies, pharmacotherapy, and, in some cases, surgical interventions [7]. Weight regain is a is an effect observed when adherence to treatment fails, regardless of the treatment offered, which makes us think of the importance of individualizing treatment [8, 9]. To address multicausality, obesity treatments may involve, in addition to lifestyle changes in combination surgical interventions as bariatric surgery for individuals with BMI of 35 kg/m2 or greater, or a BMI of 30 kg/m2 or greater and diabetes mellitus. Other treatment coadjutant is pharmacological therapies recommended in individuals with a BMI of 27 kg/m2 or greater in the presence of one or more concurrent conditions [7,8,9,10].

Several candidate therapies that target the complex disease pathophysiology of obesity are currently being investigated, yet there is a great unmet need to provide a safe and effective weight-reducing pharmacotherapy that reduces the overall disease burden in people living with obesity [10]. GLP-1 receptor agonists in homoeostasis in favour of body weight loss, by reducing food intake and delaying gastric emptying, and improves glucose tolerance by stimulating insulin secretion [11]. Survodutide (BI 456906) is a dual agonist of glucagon receptor and GLP-1 receptor that is derived from glucagon and administered once weekly approved treatments for Type 2 diabetes mellitus, with liraglutide and semaglutide also approved for the obesity treatment [12]. Preclinical investigations of survodutide demonstrated that its administration led to a more significant reduction in body weight in murine models compared to the most effective semaglutide, due to concurrent activation of the glucagon receptor and GLP-1 receptor [13]. The enhanced efficacy of survodutide was partially ascribed to elevated energy expenditure, stemming from glucagon receptor agonism in the liver and adipose tissue, which stimulated gluconeogenesis, glycogenolysis, and lipolysis, alongside decreases in gastric emptying and energy intake [13,14,15].

Phase II and III clinical trials have been carried out to report the results of trials with this drug in obese people. However, so far, a comprehensive study has not been conducted to investigate the effects of this new drug on different dimensions of weight loss in the form of a meta-analysis study. In this context, this study aimed to investigate the effect of Survodutide (BI 456906) in obesity management, using as outcomes anthropometric indices and indicators such as weight, BMI, and waist circumference (WC).

Methods

Search strategy

This systematic review and meta-analysis was performed without regard to time or language limitations in accordance with the Preferred Reporting Criteria for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16]. The general search principles of the articles included in this study also considering the medical subject headings (MeSH) and Emtree (Embase subject title) in accordance with the following search guidelines for a comprehensive search in all major databases including PubMed/MEDLINE, Web of Science, Cochrane CENTRAL, SCOPUS, and Embase was completed by August 2024: (survodutide OR “BI 456906” OR “Dual GLP-1/Glucagon Agonist” [ A) AND (“Body Weight” OR “Body Weight Changes” OR “Body Mass Index” OR “Weight Loss” OR “Obesity” OR “Waist Circumference” OR “Adipose Tissue” OR “Waist Circumference” OR “Quetelet Index” OR “BMI” OR “Weight Reduction” OR “Abdominal Obesity” OR “Central Obesity” OR “Visceral Obesity”) AND (“Clinical Trials as Topic” OR “Cross-Over” OR “Double-Blind” OR “Single-Blind " OR “Random Allocation” OR “Clinical Trial”). In addition, in order to avoid ignoring or losing articles related to the present study, we manually reviewed and searched the lists of all general articles obtained from databases as well as meta-analysis and review articles related to the purpose of the study.

Eligibility criteria

In order to check the eligibility criteria of the articles, two authors independently, after removing the duplicate articles based on the comprehensive review of the article (including the title, abstract and the entire text of the article), the publications based on the Population, Intervention, Comparison, Outcomes, and Study design (PICOS) criteria. The following designs were identified, evaluated and classified. PICOS criteria include: (1) The study population includes all healthy or unhealthy individuals with an age greater than or equal to 18 years; (2) The investigated intervention was also limited to the prescription of Survodutide; (3) The individulas who used a lifstyle intervention or a placebo were also considered as the control group; (4) Weight, body mass index (BMI) and waist circumference (WC) variables were evaluated as outcomes of this study; (5) Finally, the included studies were designed as a randomized, controlled clinical trial.

In addition to the above criteria, studies were eligible that had an intervention duration of more than or equal to 2 weeks and also reported baseline and end-of-study data on weight, BMI, and WC variables. If the publications had several follow-up periods after the intervention, the data related to the last follow-up period were reviewed and evaluated. Publications conducted on animals, articles with repeated data or without control group, as well as systematic review and meta-analysis studies were excluded from the evaluation and analysis of our study.

Data extraction

In order to systematically review and analyze the data, two authors independently provided the details of the eligible studies including the name of the first author along with the year of publication, the sample size for both the intervention and control groups, mean age and body mass index of the participants in the studies, the study population, the details of the intervention in both groups, and finally the mean and standard deviation (S.D.s) of the investigated outcomes at the baseline and last follow-up levels (or changes between baseline and post-intervention) were extracted.

Quality assessment

Using the most recent version of the Cochrane risk-of-bias tool for randomized trials (RoB 2), the trial’s methodological quality was evaluated [17]. A number of possible causes of bias were investigated and ranked by the study’s authors: insufficient outcome data, biased reporting, blinding of participants and staff, blinding of allocation concealment, blinding of volunteers and researchers, and random sequence formation. Each research was evaluated by two authors who separately determined the level of bias and labeled it as low, high, or uncertain. In order to reach a consensus, a third author was brought in to carefully address any disagreements.

Furthermore, we used the NutriGrade (Grading of Recommendations Assessment, Development, and Evaluation) grading system [18] to check how well this analytical study (assessing the overall quality of the evidence provided by the present systematic review and meta-analysis) held up. An all-encompassing 10-point grading method that evaluates several factors impacting study quality is the NutriGrade checklist. There are a total of seven distinct parts to the scale, and they are as follows: (1) bias risk; (2) precision; (3) heterogeneity; (4) directness; (5) publication bias; (6) funding bias; and (7) research design.

Data synthesis and statistical analysis

Statistical software STATA version 12.0 was used for the data analysis. Additionally, using Endnote software allowed for the efficient administration of eligible articles and the removal of duplicate articles. We calculated the means and standard deviations (S.D.s) of different data types by converting them using a preset procedure [19, 20]. In the absence of standard deviations, the following technique was used to determine the amount of the change: To find the formula for the change in standard deviation, we first take the square root of the difference between the sum of the squares of the baseline and final standard deviations, then subtract twice the product of the baseline and final standard deviation correlation coefficients, and finally, we add the absolute values of the standard deviations to get the final standard deviation. Applying this formula, we can get the standard deviation from the standard error of the mean (SEM): Multiplying SEM by the square root of the total number of participants (n) in each group yields S.D. Using a random-effects model, the study results were meta-analyzed. To give each piece of research its due, the study used the time-honored inverse variance approach. Utilizing data acquired from the temporal maximum, the technique enabled the integration of many exams into a single research cohort. Q Statistics and I-squared (I2) were used to evaluate the research’ heterogeneity. Various degrees of heterogeneity have been found and categorized as minor, low, moderate, and high in this study’s research. Levels were quantified using I2 values that ranged from 0 to 25%, 26–50%, 51–75%, and 76–100% [21]. The most likely contributing factors to heterogeneity were evaluated using subgroup analysis. In this research, the investigated factors for subgroup analysis included the dose and the duration of the intervention as well as mean age of participants. We ran a sensitivity analysis to find out how much each study contributed to the overall mean difference. We used Egger’s test, a well-known and statistically-established method, to determine whether publication bias exists [22].

Results

The flow diagram of the study including identification, screening, eligibility and final sample is shown in Fig. 1. After a complete search in the main databases stated in the work method, a total of 239 publications were entered into the Endnote software, of which 61 studies were removed due to duplication, and finally 178 studies were evaluated and screened. After the initial evaluation, including the review of the title and abstract and compliance with the inclusion and exclusion criteria, 167 were excluded and 11 studies were identified for the final evaluation and review through full text. Out of the 11 identified studies, 6 studies were excluded from our study due to various reasons described in Fig. 1, and finally 5 [14, 15, 23,24,25] articles with 18 treatment arms were included in the present meta-analysis for systematic review and data analysis.

Fig. 1
figure 1

Literature search and review flowchart for selection of studies

Full size image

Study characteristics

The characteristics of the aggregated articles are presented in Table 1. According to the findings presented in Table 1, three multicenter articles were conducted in different countries and continents, and two studies were conducted in Germany and Japan. In addition, all of the articles were done in parallel design. The publications included in this study were published between the time frame of 2022 to 2024, and the duration of the follow-up interventions varied from 16 to 48 weeks. At the baseline, the average age and proportion of male participants varied between 34.2 and 57.3 years and 32–100%, respectively. The mean BMI at the baseline level was between 25.2 and 37.1 in the studies included. The doses of injectable drugs used in the included studies also varied from 0.3 to 4.8 mg per week, and in all studies, placebo was used as the control group. According to our research, three studies have been conducted on participants with overweight/obese, and two publications have been done in people with type 2 diabetes and metabolic dysfunction–associated steatohepatitis (MASH).

Table 1 Characteristics of eligible studies
Full size table

Table 2 displays the results of the assessment conducted to evaluate the quality of the eligible studies. Moreover, the quality of the present meta-analysis was evaluated using the NutriGRADE score method, resulting in a grade of 9, indicating a very good level of quality.

Table 2 Risk of bias assessment according to the Cochrane’s risk of bias assessment tool
Full size table

Meta-analysis

A quantitative meta-analysis showed that survodutide has a significant lowering effect on weight (WMD: -8.33 kg with Pvalue < 0.001; 95% CI: -10.80, -5.86; p < 0.001; I2 = 99.6%), BMI (WMD:-4.03 kg/m2 with Pvalue < 0.001; 95% CI: -4.86, -3.20; p = 0.026; I2 = 72.7%), and WC (WMD: -6.33 cm with Pvalue < 0.001; 95% CI: -8.85 to -3.81; p < 0.001; I2 = 99.5%) (Figs. 2 and 3).

Fig. 2
figure 2

A. Forest plots from the meta-analysis of clinical trials investigating the effects of Survodutide on weight (kg). B. Forest plots from the meta‐analysis of clinical trials investigating the effects of Survodutide on body mass index (BMI)(kg/m2)

Full size image
Fig. 3
figure 3

Forest plots from the meta-analysis of clinical trials investigating the effects of Survodutide on waist circumference (WC) (cm)

Full size image

Quality assessment results

Table 2 displays the results of the assessment conducted to evaluate the quality of the eligible studies. Moreover, the quality of the present meta-analysis was evaluated using the NutriGRADE score method, resulting in a grade of 9, indicating a very good level of quality (Table 3).

Table 3 Nutrigrade assessment results
Full size table

Subgroup analysis

The stratified analysis based on the mean age, dose, and duration of intervention showed a greater effect of the Survodutide on the reduction of weight and WC during the intervention of > 16 weeks and with a dose > 2 mg/week. In addition, changes in weight and WC in people ≤ 50 years of age under Survodutide intervention were more than in people > 50 years of age (Table 4).

Table 4 The effect of Survodutide on pooled findings from the random-effects model and several subgroups (parameters related to weight loss)
Full size table

Meta-regression

Meta-regression between the Survodutide and absolute mean differences in weight and WC based on baseline levels of BMI, mean age, dose, and duration of intervention was performed. Meta-regression analysis showed a significant linear relationship between dose and duration of intervention with changes in weight (Coef = -0.167027, P = 0.008 for duration of intervention; Coef = -1.491788, P = 0.008 for dose of intervention) and WC (Coef = -0.1675654, P = 0.007 for duration of intervention; Coef = -1.85466, P = 0.001 for dose of intervention). But for other factors, no significant linear relationship was reported (Figs. 4 and 5).

Fig. 4
figure 4

Meta-regression analysis encompassing changes in weight according to A) Duration of intervention (weeks), B) Dose of intervention (mg/week), C) Mean age (years), and D) Mean baseline of BMI (kg/m2)

Full size image
Fig. 5
figure 5

Meta-regression analysis encompassing changes in waist circumference (WC) according to A) Duration of intervention (weeks), B) Dose of intervention (mg/week), C) Mean age (years), and D) Mean baseline of BMI (kg/m2)

Full size image

Sensitivity analysis

The leave-one-out method was applied to assess the influence of each individual study on the pooled effect size. The findings remained robust after sequential elimination of studies (Supplemental Fig. 1).

Publication bias

The visual inspection of funnel plot revealed no evidence of publication bias regarding the impacts of Survodutide on outcome measures. Additionally, the results of Egger’s regression test supported the absence of significant publication bias for weight (P = 0.362), BMI (P = 0.117), amd WC (P = 0.921) (Supplemental Fig. 2). Meta trim-and-fill analysis did not find the article.

Discussion

The results show that Survodutide is effective in reducing weight; BMI and WC which can bring significant health benefits to obese people. The weight reduction observed with the use of Survodutide is clinically significant. The narrow confidence interval (-10.80 to -5.86 kg) and extremely low P-value indicate high confidence in the drug’s efficacy. However, the high I² value (99.6%) suggests substantial heterogeneity between the included studies, which may be due to differences in Survodutide dosage, characteristics of the study population or measurement methods [26,27,28].

Subgroup analysis reveals that longer interventions (more than 16 weeks) and higher doses (more than 2 mg/week) of Survodutide are associated with more significant reductions in weight and WC. These findings are consistent with the literature, which suggests that both dose and duration of treatment are critical factors in the effectiveness of weight loss interventions [29, 30]. Longer interventions allow the physiological effects of the drug to accumulate, while higher doses can provide a more robust therapeutic response [31]. These results are important for the formulation of clinical guidelines and recommendations for treatment.

The subgroup analysis also indicated that individuals under 50 experienced more significant reductions in weight and WC compared to those over 50. This result can be explained by several factors. Younger individuals tend to have a higher basal metabolism and may respond better to weight loss interventions [32]. In addition, with increasing age, there may be greater resistance to weight loss due to hormonal changes, decreased muscle mass and other comorbidities that can affect the effectiveness of treatment [33, 34]. These results were also observed in the meta-regression analysis, which showed a significant linear relationship between the dose and duration of the intervention with changes in weight and waist circumference.

However, this relationship was not found when evaluating baseline BMI levels and the average age of the participants. This suggests that the relationship is not linear and may be influenced by other variables not captured in the meta-regression. The lack of a significant linear relationship with other factors suggests that the response to treatment may be influenced by multiple variables, requiring a personalized approach to the management of obesity and associated conditions. Jaison and collaborators (2024) described that the relationship between BMI and obesity-related health outcomes can be complex and influenced by multiple variables, not necessarily linear [35].

Individuals with obesity have a heightened risk of cardiovascular disease due to the presence of hypertension and hypercholesterolemia. In trials, survodutide medication significantly decreased systolic and diastolic blood pressure, along with other cardiovascular risk factors, in persons with a BMI of 27 kg/m² or above [14]. GLP-1 receptor agonists are recognized for their cardiovascular advantages, especially in individuals with type 2 diabetes [36]. Numerous cardiovascular outcome studies have been conducted for GLP-1 receptor agonists, revealing decreases in three-point major adverse cardiovascular events for survodutide and other GLP-1 receptor agonists, assessed in individuals with obesity and type 2 diabetes [14, 36, 37].

Several potential mechanisms have been proposed for the drug effects of Survodutide as a novel subcutaneous GLP-1R and glucagon receptor (GCGR) /GLP-1R dual agonist. In addition to the glucose-lowering effects associated with GLP-1R agonism, GLP-1R and GCGR agonism through liver receptors may lead to increased energy expenditure [38]. This effect can be observed at doses that do not activate the sympathetic nervous system, thereby avoiding potential harmful effects on the cardiovascular system [38]. GCGR signaling also leads to stimulation of hepatic glucose production (via glycogenolysis and gluconeogenesis), stimulation of lipolysis and amino acid breakdown, and suppression of hepatic lipid accumulation [39]. The efficacy of GCGR/GLP-1R dual agonism has been demonstrated by oxyntomodulin, an endogenous proglucagon derivative [40]. Oxyntomodulin has been shown to reduce bodyweight and food intake in rodents and humans [41] and to increase energy expenditure in people with obesity [42], via activity at both receptors.

Several clinical guidelines have endorsed the use of very-low-calorie diets (VLCDs) or meal replacements (MRs) as a part of medical nutrition therapy (MNT) for obesity, primarily based on evidence that shows an average weight reduction of ~ 7–8 kg or more with total diet replacement over at least 12 months in large, randomized controlled trials [43]. Furthermore, a study published in the New England Journal of Medicine in 2017 reported that five years after bariatric surgery, patients maintained an average weight loss of 25% of their initial body weight [44]. However, bariatric surgery showed superior efficacy, it also carried a higher risk of complications. In contrast, Survodutide presented a noninvasive alternative with significant weight reduction and lower incidences of adverse effects.

In most trials, the most frequently reported adverse effects of survodutide were GI disorders, namely nausea, vomiting, diarrhea, constipation and dyspepsia [45]. In the diabetes trial, GI disorders were reported by 55% and 22% of patients randomized to survodutide and placebo, respectively.

Strengths and limitations

The current study has several positive features: a rigorous methodology was used based on the PRISMA guidelines; a comprehensive literature search included independent databases; search, selection, and data extraction applied to the selected studies were performed separately, and in duplicate, by two researchers; and a third party was accessed to resolve disagreements. Furthermore, because the evaluation of this drug was recent, few studies were found and this is our main limitation [26]. Significant heterogeneities were seen both clinically and statistically. The variations in intervention-specific parameters (such as drug dosages, and protocol duration) and patient-specific factors (including genes, age, sex, ethnicity, disease history, and carbohydrate and fat intake) may account for these disparities. Also, the small number of studies conducted in this field due to the novel nature of the discussed drug was another limitation of our study. In addition, lack of registration of the current study in PROSPERO due to time limit was another limitation of this study.

Conclusion

The results of this meta-analysis show that Survodutide is effective in reducing weight, BMI and waist circumference, especially with longer interventions and higher doses. Age is also an important factor, with younger individuals responding better to treatment. These findings provide a basis for optimizing clinical interventions and highlight the importance of considering individual factors when prescribing Survodutide for weight loss.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

References

  1. Murray CJ, Aravkin AY, Zheng P, Abbafati C, Abbas KM, Abbasi-Kangevari M, Abd-Allah F, Abdelalim A, Abdollahi M, Abdollahpour I. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of Disease Study 2019. Lancet. 2020;396(10258):1223–49.

    Article  Google Scholar 

  2. Ramage S, Farmer A, Apps Eccles K, McCargar L. Healthy strategies for successful weight loss and weight maintenance: a systematic review. Appl Physiol Nutr Metab. 2014;39(1):1–20.

    Article  CAS  PubMed  Google Scholar 

  3. Hruby A, Hu FB. The epidemiology of obesity: a big picture. PharmacoEconomics. 2015;33:673–89.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Chu P-Y, Yu Y-C, Pan Y-C, Dai Y-H, Yang J-C, Huang K-C, Wu Y-C. The efficacy of Lactobacillus delbrueckii ssp. bulgaricus supplementation in managing body weight and blood lipids of people with overweight: a Randomized Pilot Trial. Metabolites. 2024;14(2):129.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. McLachlan S, Collaboration NRF. Trends in adult body mass index in 200 countries since 1975: pooled analysis of 1,698 population-based measurement studies with 19.2 million participants. Lancet 2016, 387(10026).

  6. Li P, Huang Y, Wong A. Behavioural strategies to reduce obesity among lower socioeconomic adults living in high-income countries: a GRADE-assessed systematic review and meta-analysis of randomised controlled trials. Br J Nutr 2023:1–24.

  7. Wadden TA, Tronieri JS, Butryn ML. Lifestyle modification approaches for the treatment of obesity in adults. Am Psychol. 2020;75(2):235.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Machado AM, Guimarães NS, Bocardi VB, da Silva TPR, do, Carmo AS, de Menezes MC, Duarte CK. Understanding weight regain after a nutritional weight loss intervention: systematic review and meta-analysis. Clinical nutrition ESPEN 2022, 49:138–153.

  9. Reis MG, Moreira LFGG, de Andrade Carvalho LSV, de Castro CT, Vieira RAL, Guimarães NS. Weight regain after bariatric surgery: a systematic review and meta-analysis of observational studies. Obes Med 2023:100528.

  10. Chakhtoura M, Haber R, Ghezzawi M, Rhayem C, Tcheroyan R, Mantzoros CS. Pharmacotherapy of obesity: an update on the available medications and drugs under investigation. EClinicalMedicine. 2023;58:101882.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Nauck MA, Quast DR, Wefers J, Meier JJ. GLP-1 receptor agonists in the treatment of type 2 diabetes–state-of-the-art. Mol Metabolism. 2021;46:101102.

    Article  CAS  Google Scholar 

  12. Klein T, Augustin R, Hennige AM. Perspectives in weight control in diabetes–survodutide. Diabetes Res Clin Pract. 2024;207:110779.

    Article  CAS  PubMed  Google Scholar 

  13. Zimmermann T, Thomas L, Baader-Pagler T, Haebel P, Simon E, Reindl W, Bajrami B, Rist W, Uphues I, Drucker DJ. BI 456906: discovery and preclinical pharmacology of a novel GCGR/GLP-1R dual agonist with robust anti-obesity efficacy. Mol Metabolism. 2022;66:101633.

    Article  CAS  Google Scholar 

  14. le Roux CW, Steen O, Lucas KJ, Startseva E, Unseld A, Hennige AM. Glucagon and GLP-1 receptor dual agonist survodutide for obesity: a randomised, double-blind, placebo-controlled, dose-finding phase 2 trial. Lancet Diabetes Endocrinol. 2024;12(3):162–73.

    Article  PubMed  Google Scholar 

  15. Yazawa R, Ishida M, Balavarca Y, Hennige AM. A randomized phase I study of the safety, tolerability, pharmacokinetics and pharmacodynamics of BI 456906, a dual glucagon receptor/glucagon-like peptide‐1 receptor agonist, in healthy Japanese men with overweight/obesity. Diabetes Obes Metabolism. 2023;25(7):1973–84.

    Article  CAS  Google Scholar 

  16. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Reviews. 2015;4(1):1.

    Article  Google Scholar 

  17. Higgins JP, Savović J, Page MJ, Elbers RG, Sterne JA. Assessing risk of bias in a randomized trial. Cochrane Handb Syst Reviews Interventions 2019:205–28.

  18. Schwingshackl L, Knüppel S, Schwedhelm C, Hoffmann G, Missbach B, Stelmach-Mardas M, Dietrich S, Eichelmann F, Kontopantelis E, Iqbal K, et al. Perspective: NutriGrade: a Scoring System to assess and judge the Meta-evidence of Randomized controlled trials and Cohort studies in Nutrition Research. Adv Nutr. 2016;7(6):994–1004.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Higgins J. Cochrane handbook for systematic reviews of interventions. Version 5.1. 0 [updated March 2011]. The Cochrane Collaboration. www cochrane-handbook org 2011.

  20. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol. 2005;5(1):13.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sanyal AJ, Bedossa P, Fraessdorf M, Neff GW, Lawitz E, Bugianesi E, Anstee QM, Hussain SA, Newsome PN, Ratziu V. A Phase 2 Randomized Trial of Survodutide in MASH and Fibrosis. The New England journal of medicine.

  24. Jungnik A, Arrubla Martinez J, Plum-Mörschel L, Kapitza C, Lamers D, Thamer C, Schölch C, Desch M, Hennige AM. Phase I studies of the safety, tolerability, pharmacokinetics and pharmacodynamics of the dual glucagon receptor/glucagon‐like peptide‐1 receptor agonist BI 456906. Diabetes Obes Metabolism. 2023;25(4):1011–23.

    Article  CAS  Google Scholar 

  25. Blüher M, Rosenstock J, Hoefler J, Manuel R, Hennige AM. And bodyweight reduction of survodutide, a dual glucagon/GLP–1 receptor agonist, compared with placebo and open–label semaglutide in people with type 2 diabetes: a randomised clinical trial. Diabetologia. 2023;67:470–82.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Borenstein M, Cooper H, Hedges L, Valentine J. Heterogeneity in meta-analysis. Handb Res Synthesis meta-analysis. 2019;3:453–70.

    Article  Google Scholar 

  27. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.

    Article  CAS  PubMed  Google Scholar 

  28. Poole C, Greenland S. Random-effects meta-analyses are not always conservative. Am J Epidemiol. 1999;150(5):469–75.

    Article  CAS  PubMed  Google Scholar 

  29. Williams R, Wood L, Collins C, Callister R. Effectiveness of weight loss interventions–is there a difference between men and women: a systematic review. Obes Rev. 2015;16(2):171–86.

    Article  CAS  PubMed  Google Scholar 

  30. Appel LJ, Clark JM, Yeh H-C, Wang N-Y, Coughlin JW, Daumit G, Miller ER III, Dalcin A, Jerome GJ, Geller S. Comparative effectiveness of weight-loss interventions in clinical practice. N Engl J Med. 2011;365(21):1959–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Coutinho W, Halpern B. Pharmacotherapy for obesity: moving towards efficacy improvement. Diabetol Metab Syndr. 2024;16(1):6.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Mäkinen V-P, Ala-Korpela M. Influence of age and sex on longitudinal metabolic profiles and body weight trajectories in the UK Biobank. Int J Epidemiol. 2024;53(3):dyae055.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Hornburg D, Wu S, Moqri M, Zhou X, Contrepois K, Bararpour N, Traber GM, Su B, Metwally AA, Avina M. Dynamic lipidome alterations associated with human health, disease and ageing. Nat Metabolism. 2023;5(9):1578–94.

    Article  CAS  Google Scholar 

  34. Panyard DJ, Yu B, Snyder MP. The metabolomics of human aging: advances, challenges, and opportunities. Sci Adv. 2022;8(42):eadd6155.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Asharaf H, Thimothy G, George S, Jose J, Paily R, Josey J, Sajna S, Radhakrishnan R. Psychological impact of obesity: a comprehensive analysis of health-related quality of life and weight-related symptoms. Obes Med. 2024;45:100530.

    Article  Google Scholar 

  36. Ussher JR, Drucker DJ. Glucagon-like peptide 1 receptor agonists: cardiovascular benefits and mechanisms of action. Nat Reviews Cardiol. 2023;20(7):463–74.

    Article  CAS  Google Scholar 

  37. Marso SP, Daniels GH, Brown-Frandsen K, Kristensen P, Mann JF, Nauck MA, Nissen SE, Pocock S, Poulter NR, Ravn LS. Liraglutide and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2016;375(4):311–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Salem V, Izzi-Engbeaya C, Coello C, Thomas D, Chambers E, Comninos A, Buckley A, Win Z, Al‐Nahhas A, Rabiner E. Glucagon increases energy expenditure independently of brown adipose tissue activation in humans. Diabetes Obes Metabolism. 2016;18(1):72–81.

    Article  CAS  Google Scholar 

  39. Hayashi Y. Glucagon regulates lipolysis and fatty acid oxidation through inositol triphosphate receptor 1 in the liver. J Diabetes Invest. 2021;12(1):32.

    Article  CAS  Google Scholar 

  40. Holst JJ, Albrechtsen NJW, Gabe MBN, Rosenkilde MM. Oxyntomodulin: actions and role in diabetes. Peptides. 2018;100:48–53.

    Article  CAS  PubMed  Google Scholar 

  41. Wynne K, Park AJ, Small CJ, Patterson M, Ellis SM, Murphy KG, Wren AM, Frost GS, Meeran K, Ghatei MA. Subcutaneous oxyntomodulin reduces body weight in overweight and obese subjects: a double-blind, randomized, controlled trial. Diabetes. 2005;54(8):2390–5.

    Article  CAS  PubMed  Google Scholar 

  42. Wynne K, Park A, Small C, Meeran K, Ghatei M, Frost G, Bloom S. Oxyntomodulin increases energy expenditure in addition to decreasing energy intake in overweight and obese humans: a randomised controlled trial. Int J Obes. 2006;30(12):1729–36.

    Article  CAS  Google Scholar 

  43. Edwards-Hampton SA, Ard J. The latest evidence and clinical guidelines for use of meal replacements in very-low-calorie diets or low-calorie diets for the treatment of obesity. Diabetes Obes Metab. 2024;26(Suppl 4):28–38.

    Article  PubMed  Google Scholar 

  44. Adams TD, Davidson LE, Litwin SE, Kim J, Kolotkin RL, Nanjee MN, Gutierrez JM, Frogley SJ, Ibele AR, Brinton EA. Weight and metabolic outcomes 12 years after gastric bypass. N Engl J Med. 2017;377(12):1143–55.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Abdelmoneim B, Ebtihal A, Mohamed F, Musaab F, Abdelmonem B. Survodutide, a new horizon in the treatment of obesity and type 2 diabetes mellitus: a narrative review. Yemen J Med. 2024;3(2):97–101.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study received financial support from the Postdoctoral Fund of Jinling Hospital (Nos.96492).

Author information

Authors and Affiliations

  1. Department of Gastroenterology and Hepatology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China

    Haijun Wan, Nuo Xu & Lijuan Wang

  2. Day Operation Management Center, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China

    Yaping Liu

  3. Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Somaye Fatahi

  4. Pediatric Gastroenterology and Hepatology Research Center, Pediatrics Centre of Excellence, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Hassan Sohouli

  5. Department of Nutrition, School of Nursing, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

    Nathalia Sernizon Guimarães

Authors
  1. Haijun Wan
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Nuo Xu
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Lijuan Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Yaping Liu
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Somaye Fatahi
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Mohammad Hassan Sohouli
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Nathalia Sernizon Guimarães
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

WH, XN, WL, LY, FS, SMH: conception, design, statistical analysis, data collection, writing-original draft, supervision. SMH, SN: data collection and writing-original draft. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Mohammad Hassan Sohouli.

Ethics declarations

Ethical approval

No applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

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/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wan, H., Xu, N., Wang, L. et al. Effect of survodutide, a glucagon and GLP-1 receptor dual agonist, on weight loss: a meta-analysis of randomized controlled trials. Diabetol Metab Syndr 16, 264 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01501-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01501-x

Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

Contact us