Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: A multivariate meta-analysis

Tzu-Lin Yeh; Ming-Chieh Tsai; Wen-Hsuan Tsai; Yu-Kang Tu; Kuo-Liong Chien

doi:10.1371/journal.pone.0278685

. 2023 Jan 25;18(1):e0278685. doi: 10.1371/journal.pone.0278685

Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: A multivariate meta-analysis

Tzu-Lin Yeh ^1,², Ming-Chieh Tsai ^2,^3,⁴, Wen-Hsuan Tsai ⁴, Yu-Kang Tu ², Kuo-Liong Chien ^2,^5,^*

Editor: Ming-Chang Chiang⁶

PMCID: PMC9876280 PMID: 36696429

Abstract

Aims

To explore the effect of glucagon-like peptide-1 receptor agonist (GLP-1 RAs) on glycemic control and weight reduction in adults.

Methods

Databases were searched from August 2021 to March 2022. Data were analyzed using mean difference (MD) values with 95% confidence intervals (CIs). Both random-and fixed-effect models were employed. Heterogeneity was explored using pre-specified subgroup analyses and meta-regression. Structural equation modeling fitting was used for the multivariate meta-analysis.

Results

A total of 31 double-blind randomized controlled trials with 22,948 participants were included in the meta-analysis. The MD and 95% CI of the pooled GLP1-RA-induced change in the glycated hemoglobin level was -0.78% (-0.97%, -0.60%) in the random-effects model and -0.45% (-0.47%, -0.44%) in the fixed-effect model, with a high heterogeneity (I² = 97%). The pooled body weight reduction was -4.05 kg (-5.02 kg, -3.09 kg) in the random-effects model and -2.04 kg (-2.16 kg, -1.92 kg) in the fixed-effect model (I² = 98%). The standardized pooled correlation coefficient between HbA1c levels and body weight was -0.42. A negative correlation between glycemic control and weight reduction was obtained.

Conclusion

Long-acting GLP-1 RAs significantly reduced the glycated hemoglobin level and body weight in adults.

Introduction

Glucagon-like peptide 1, an incretin secreted from the gut, exerts metabolic effects through glucose-dependent stimulation of insulin secretion, delayed gastric emptying, inhibition of appetite, and increased natriuresis [1]. Glucagon-like peptide receptor agonists (GLP-1 RAs) have been used to treat patients with diabetes since 2007 [2]. and have been approved as anti-obesity drugs since 2014 [3]. However, long-acting GLP-1 RAs have attracted increasing interest due to their better efficacy in diabetes and obesity treatment [4]. Long-acting GLP-1 RA treatment was shown to be associated with a pooled glycated hemoglobin (HbA1c) reduction of 0.99% and a pooled body weight reduction of 2.69 kg (heterogeneity, approximately 90%) [5]. The high heterogeneity can be partially explained by differences in the underlying conditions of participants [6] and the GLP-1 RA interventions [7]. Moreover, participant age and the baseline glycemic level may interact with the results in children [6], indicating the existence of potential effect modifiers. However, further analysis to explore the high heterogeneity and potential effect modifiers in adults is lacking [8, 9].

Glycemic control is intertwined with the weight reduction caused by long-acting GLP-1 RAs through insulin resistance and metabolic changes [10]. Thus, these two outcomes of interest should not be independently estimated. However, previous randomized controlled trials (RCTs) rarely reported the correlation coefficients at the within-study level [11], and to the best of our knowledge, no correlation coefficient was reported in between-study-level meta-analysis [12, 13].

Thus, to explore the high heterogeneity and possible effect modifiers associated with these findings, we performed further univariate meta-analyses of the glycemic control and weight reduction caused by long-acting GLP-1 RAs in adults. Considering the correlation between these outcomes, our study used the structural equation modeling approach for multivariate meta-analysis to jointly estimate the effect sizes for glycemic control and weight reduction in one model and to investigate the associations between these two outcomes of long-acting GLP-1 RA treatment.

Materials & methods

Search strategy and selection criteria

We searched the Medline, Ovid EMBASE, Cochrane Library and ClinicalTrials.gov databases for relevant studies from August 2021 to March 2022 by using the following keywords: “Glucagon-Like Peptide 1” OR “GLP-1” OR “Placebo” OR “Body Weights” OR “Glucose” OR “Glycosylated Hemoglobin A” OR “Trials, Randomized Clinical.” The PRISMA checklist and detailed search strategies are shown in Supplement and S1 Table. To enable a comprehensive search, we did not include limiting parameters for language, article type, year of publication, animal or human subjects, and age of participants.

We included all eligible publications that met the following inclusion criteria: (1) adult participants older than 18 years, either from the general population or including patients with a specific disease; (2) intervention with U.S. Food and Drug Administration approved long-acting GLP-1 RAs, including liraglutide, once-weekly exenatide, dulaglutide, albiglutide, and semaglutide, which were administered orally or subcutaneously, either in same or different doses; (3) comparison with a placebo; (4) glycemic or anthropometric changes as either primary or secondary outcome measures; (5) phase 3 or phase 4 randomized, double-blind, placebo-controlled trials without cross-over or open-label in any study period. We excluded articles that met the following criteria: (1) were duplicated publications or used duplicated populations, such as a post-hoc analysis of an included trial; (2) included participants with other conditions that interfered with outcome assessment, such as pregnancy or weight reduction surgery; (3) assessed other active components in addition to GLP-1 RAs in the treatment arm; (4) performed active comparisons rather than comparisons with placebo; (4) used outcome measures that were not of our interest; (6) reported conference abstracts, review articles, or phase 1 or 2 RCTs. All included trials were assessed for bias using the Cochrane risk-of-bias tool 2.0 [14]. The details of the data extraction in our study were described in supplement (S1 File).

Data were analyzed using the mean difference (MD) with 95% confidence intervals (CIs) for continuous outcomes. For the univariate meta-analysis, we used the statistical software R, version 4.0.3, and the meta package. Both random- and fixed-effect models were employed using DerSimonian and Laird’s method [15]. The results of the meta-analysis are presented in forest plots. Heterogeneity was quantified using the Cochran Q test and I² statistics [16]. Heterogeneity was explored in pre-specified subgroup analyses by participants’ disease and intervention drugs. Potential effect modifiers were determined in meta-regression analysis. Publication bias was inspected using the symmetry of the funnel plot and Egger’s test [17]. Contour-enhanced funnel plots to enhance the recognition of the causes of asymmetry and trim-and-fill analysis to estimate the effect size were performed if a bias existed. To ensure robustness, a further meta-analysis restricted to articles with a low risk of bias was performed. Since the correlation was not reported in each original study, we set the correlation coefficient between HbA1c level and body weight changes as 0.2, based on a reasonable assumption and previous literature [11]. We used the metaSEM package to fit the structural equation modeling using the maximum likelihood estimation in one step. Effect sizes and effect size variances were the essential arguments to be specified. The results of the multivariate meta-analysis model were visualized by plotting. To explore the direction of the pooled correlation coefficient, we further restricted the multivariate meta-analysis according to participant characteristics. Sensitivity analyses were performed by setting other correlation coefficients and restricting to studies with a low risk of bias.

Results

Description of studies and quality assessment

Thirty-one double-blind RCTs [18–47] were included in our meta-analysis (Fig 1). Seven of these were phase 4 trials [24, 25, 29, 35, 38, 42, 43]. The eligible participants ranged from non-diabetic overweight/obese general individuals to patients with schizophrenia [31], obstructive sleep apnea [20], or polycystic ovary syndrome [25]; patients with type 1 diabetes mellitus (DM) [24, 28, 33]; various groups of type 2 DM patients, including drug-naïve patients [19, 41], those treated with insulin [18, 26, 40, 46], those with chronic kidney disease [22, 36], and those with cardiovascular disease [27, 30, 34]. Liraglutide was the most commonly used GLP-1 RA, followed by subcutaneous semaglutide [21, 34, 40, 41, 44, 47], oral semaglutide [19, 30, 36, 46] and dulaglutide [27], once-weekly exenatide [31], and albiglutide [37]. A total of 23,061 participants (mean age, 54.1 years; 54.1% women; baseline body mass index (BMI), 33.7 kg/m²; baseline HbA1c, 7.8%; mean disease duration, 8.2 years; mean study period, 38.1 weeks) were included in the univariate meta-analysis. The baseline characteristics of the included studies are presented in S2 Table. In the GLP-1 RA arm, a total of 12,319 participants (mean age, 54.1 years; 54.4% women, mean baseline BMI, 33.9 kg/m²; mean baseline HbA1c level, 7.7%; mean follow-up duration, 38.1 weeks; mean duration of diabetes, 8.0 years) were included in the multivariate meta-analysis. Most of the included RCTs were assessed as showing high quality with a low risk of bias; only five trials [28, 31, 32, 35, 38] did not use the intention-to-treat analysis and were thus assessed as showing some concerns (S3 Table).

Results of the univariate meta-analysis

The MD (95% CI) for the pooled HbA1c change caused by GLP-1 RAs was -0.78% (-0.97%, -0.60%) in the random-effect model and -0.45% (-0.47%, -0.44%) in the fixed-effect model, with a high heterogeneity (I² = 97%). Forest plots are shown in S1 Fig. Subgroup analysis based on participant characteristics showed that the MD (95% CI) for the pooled HbA1c change was -0.99% ([-1.17%, -0.82%], I² = 94%) in type 2 DM patients, -0.27% ([-0.31%, -0.24%], I² = 39%) in participants with overweight/obesity, and -0.18% ([-0.35%, -0.01%], I² = 0%) in type 1 DM patients (S2 Fig). The MD (95% CI) for the pooled HbA1c change was -1.06% ([-1.50%, -0.62%], I² = 99%) with subcutaneous semaglutide, -0.54% ([-0.76%, -0.33%], I² = 93%) with liraglutide, -0.94% ([-1.18%, -0.70%], I² = 89%) with oral semaglutide, and -0.82% ([-1.23%, -0.41%], I² = 80%) with dulaglutide/exenatide/albiglutide (S3 Fig). Meta-regression (Table 1) showed that the pooled HbA1c reduction significantly interacted with participants’ baseline age (p = 0.032), proportion of female participants (p = 0.017), the baseline HbA1c level (p = 0.018), and gastrointestinal side effect (p = 0.002) but did not interact with baseline body weight or BMI level, duration of diabetes, follow-up period or insulin use. A one-year increase in the participants’ age significantly decreased the pooled HbA1c change by 0.026%; a 1% increase in the proportion of female participants significantly increased the pooled HbA1c change by 0.015%; a 1% increase in the baseline HbA1c level significantly reduced the pooled HbA1c level by 0.262%; and 1% increase in gastrointestinal side effect significantly increase the pooled HbA1c level by 0.017%. The funnel plot (S4 Fig) showed asymmetry, and publication bias was confirmed by Egger’s test (p = 0.004). To ensure that the bias did not contribute to the underlying differences between studies, we further omitted outliers [31], participants without diabetes [31, 44], and participants without type 2 diabetes [24, 28, 33], and the Egger’s test still showed significant bias (S5 Fig). In the assessment of the reasons for this asymmetry, the contour-enhanced funnel plot indicated that studies with a positive MD with any p value were not found (Fig 2). Therefore, we conducted a trim-and-fill analysis to examine the influence of publication bias. The trim-and-fill analysis showed 10 unpublished studies. Considering these unpublished studies, the MD (95% CI) for the pooled HbA1c change was -0.45% (-0.58%, -0.31%), which was also similar to the results of the fixed-effect model. Further analysis by restricting articles with low bias showed robust results (-0.78% [-0.97%, -0.59%], I² = 98%) (S6 Fig).

Table 1. Univariate meta-regression of the effects of glucagon-like peptide-1 receptor agonists on glycated hemoglobin levels and weight reduction.

	Glycated hemoglobin			Body weight
	MD (95% CI)	p	R²(%)	MD (95% CI)	p	R²(%)
Age (years)	-0.026 (-0.049, -0.002)	0.032	17.2	0.093 (-0.016, 0.202)	0.091	6.0
Proportion of women (%)	0.015 (0.003, 0.027)	0.017	17.3	-0.065 (-0.117, -0.013)	0.016	18.0
Baseline glycated hemoglobin (%)	-0.262 (-0.473, -0.050)	0.018	25.1	1.130 (-0.132, 2.393)	0.077	9.6
Baseline body mass index (kg/m²)	0.021 (-0.045, 0.087)	0.514	0	-0.217 (-0.553, 0.120)	0.197	3.5
Baseline body weight (kg)	0.010 (-0.013, 0.033)	0.374	1.8	-0.045 (-0.157, 0.068)	0.424	0
Duration of diabetes (years)	-0.004 (-0.035, 0.027)	0.788	0	0.105 (-0.060, 0.269)	0.203	3.7
Study duration (weeks)	0.002 (-0.007, 0.011)	0.660	0	-0.052 (-0.094, -0.010)	0.018	16.2
Gastrointestinal side effect (%)	0.017 (0.007, 0.027)	0.002	35.1	-0.059 (-0.110, -0.008)	0.025	15.1
Insulin use (%)	0.000 (-0.005, 0.005)	0.863	0	0.015 (-0.011, 0.040)	0.249	2.2

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CI, confidence interval; MD, mean difference; R² (%), percentage of heterogeneity explained

Fig 2 — (upper left) Contour-enhanced funnel plot of the pooled glycated hemoglobin level after treatment with a glucagon-like peptide-1 receptor agonist. (lower left) Filled funnel plot of the pooled glycated hemoglobin level after treatment with a glucagon-like peptide-1 receptor agonist. (upper right) Contour-enhanced funnel plot of the pooled body weight after treatment with a glucagon-like peptide-1 receptor agonist. (lower right) Filled funnel plot of the pooled body weight after treatment with a glucagon-like peptide-1 receptor agonist.

The pooled body weight reduction caused by GLP1-RA was -4.05 kg (-5.02 kg, -3.09 kg) in the random-effects model and -2.04 kg (-2.16 kg, -1.92 kg) in the fixed-effect model (I² = 98%). Forest plots are shown in S1 Fig. Subgroup analysis by participants’ characteristics (S2 Fig) showed that the MD (95% CI) for the pooled body weight change was -3.14% ([-3.84%, -2.44%], I² = 97%) in type 2 DM patients, -5.77% ([-8.35%, -3.20%], I² = 99%) in participants with overweight/obesity, and -4.15% ([-5.04%, -3.25%], I² = 0%) in type 1 DM patients. The MD (95% CI) for the pooled body weight change was -6.58% ([-9.24%, -3.92%], I² = 98%) with subcutaneous semaglutide, -3.87% ([-4.57%, -3.17%], I² = 73%) with liraglutide, -2.91% ([-3.48%, -2.34%], I² = 67%) with oral semaglutide, and -0.47 ([-1.50%, 0.56%], I² = 98%) with dulaglutide/exenatide/albiglutide (S3 Fig). Meta-regression (Table 1) showed that the pooled body weight reduction significantly interacted with the proportion of female participants (p = 0.016), the follow-up period (p = 0.018) and gastrointestinal side effect (p = 0.025), and had a borderline interaction with participants’ baseline age (p = 0.091) and the participants’ baseline HbA1c level (p = 0.077), but did not interact with baseline BMI level or body weight, insulin use, or the duration of diabetes. A 1% increase in the proportion of female participants significantly decreased the pooled body weight reduction by 0.065 kg; a one-week increase in the treatment duration significantly decreased the pooled body weight reduction by 0.052 kg; a 1% increase in gastrointestinal side effect significantly decreased the pooled body weight reduction by 0.059 kg. Publication bias was present, and the funnel plot and Egger’s test results (p value < 0.001) are shown in S4 Fig. After omitting outliers [45] and restricting the study to participants with diabetes or type 2 diabetes, Egger’s test still showed significant bias (S5 Fig). The contour-enhanced funnel plot also showed the absence of studies with a positive MD, and publication bias existed (Fig 2). The trim-and-fill analysis revealed 15 unpublished studies (Fig 2). Considering these unpublished studies, the MD (95% CI) of the pooled body weight reduction was -1.76 kg (-2.63 kg, -0.88 kg), which was almost half of the current results and similar to the results obtained with the fixed-effect mode. Further analysis by restricting articles with low bias showed similar results: -4.29% ([-5.37%, -3.22%], I² = 98%) (S6 Fig).

Results of the structural equation modeling multivariate meta-analysis

Maximum likelihood estimation worked well in the analysis. Table 2 shows that the pooled HbA1c change induced by GLP1-RAs was -0.85% (95% CI [-1.03%, -0.66%], I² = 99%), and the pooled body weight change was -4.03 kg (95% CI [-5.11 kg, -2.95 kg], I² = 99%), which were similar to the results of the univariate meta-analysis. However, overall, the pooled between-study level correlation coefficient between HbA1c and body weight changes from baseline was -0.42, which was the opposite of the within-study level. To explore the negative correlation, we further restricted the multivariate analysis to participants with or without diabetes. The pooled HbA1c change by GLP1-RA was -0.96% (95% CI [-1.14%, -0.79%], I² = 96%), the pooled body weight change was -3.23 kg (95% CI [-3.86 kg, -2.59 kg], I² = 95%); the amount of between-study heterogeneity of body weight decreased from 7.36 to 1.77 and the 95% CI became narrower. The pooled correlation coefficient turned to a positive estimate of 0.32. There were only five studies focused on participants without diabetes. The pooled HbA1c change by GLP1-RA was -0.27% (95% CI [-0.31%, -0.23%], I² = 13%), the pooled body weight change was -6.76 kg (95% CI [-10.81 kg, -2.72 kg], I² = 99%); the amount of between-study heterogeneity of body weight was much increased to 20.84 with a wide 95% CI due to the limited included articles. However, the pooled correlation coefficient was positive of 0.81. The pooled results for all participants and the results restricted to patients with diabetes are shown in Fig 3. Sensitivity analyses of all participants and patients with diabetes by setting the correlation coefficient to 0.1 and 0.3 and restricting the study selection to studies with a low risk of bias yielded robust results (S4 Table). Further sensitivity analyses of participants without diabetes were not performed due to the limited included articles.

Table 2. The pooled results for glycated hemoglobin level and weight reduction on comparison of glucagon-like peptide-1 receptor agonist and placebo by using the structural equation modeling multivariate meta-analysis according to participant characteristics.

	All participants			Patients with diabetes			Patients without diabetes
Setting r = 0.2	Estimates (95% CI)	p	I ²	Estimates (95% CI)	p	I ²	Estimates (95% CI)	p	I ²
Glycated hemoglobin (%)	-0.85 (-1.03, -0.66)	<0.001	99%	-0.96 (-1.14, -0.79)	<0.001	96%	-0.27 (-0.31, -0.23)	<0.001	13%
Body weight (kg)	-4.03 (-5.11, -2.95)	<0.001	99%	-3.23 (-3.86, -2.59)	<0.001	95%	-6.76 (-10.81, -2.72)	0.001	99%
tao of glycated hemoglobin	0.18 (0.07, 0.30)	<0.001		0.13 (0.03, 0.23)	0.008		0	0.909
tao of body weight	7.36 (3.10, 11.63)	<0.001		1.77 (0.56, 2.99)	0.004		20.84 (-5.32, 47.00)	0.118
Covariance	-0.48 (-1.02, 0.05)	<0.001		0.15 (-0.12, 0.43)	0.281		0.04 (-0.14, 0.21)	0.682
Standardized correlation coefficient	-0.42			0.32			0.81

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CI, confidence interval; r, correlation coefficient between glycated hemoglobin and body weight changes within the study level; tao, the variance of effect measure

Fig 3 — (left) The pooled effect sizes and their confidence ellipse of the changes in the glycated hemoglobin level and body weight, in a comparison of glucagon-like peptide-1 receptor agonists and placebo in all participants. (middle) The pooled effect sizes and their confidence ellipse for changes in the glycated hemoglobin level and body weight, in a comparison of glucagon-like peptide-1 receptor agonists and placebo in patients with diabetes. (right) The pooled effect sizes and their confidence ellipse for changes in the glycated hemoglobin level and body weight, in a comparison of glucagon-like peptide-1 receptor agonists and placebo in patients without diabetes. x-axis: Effects of glucagon-like peptide-1 receptor agonists on glycated hemoglobin level; y-axis: effects of glucagon-like peptide-1 receptor agonists on body weight changes; black dots: individual studies; ellipses with dashed lines: 95% confidence interval; red diamond: pooled effect and 95% confidence interval; smaller gray ellipse: 95% confidence interval; larger red ellipse: 95% prediction interval.

Discussion

Our meta-analysis demonstrated that long-acting GLP-1 RAs significantly reduced HbA1c levels and body weight in adults. The high heterogeneity in our study might be attributed to the different GLP-1 RAs and the diverse populations ranging from non-diabetic overweight/obese participants to patients with diabetes complicated with end organ damage. The effects of GLP-1 RA were highly correlated with age, sex, baseline condition, treatment duration, and gastrointestinal side effect. For the correlation between glycemic control and weight reduction, the pooled effects were similar, since both effects were estimated independently. However, although the long-acting GLP-1 RA lowered the HbA1c more, it did not cause much decrease in the body weight in our included population. A positive association was found only in a specific condition.

Long-acting GLP-1 RAs showed better efficacy in weight reduction and glycemic control than short-acting GLP-1 RAs [5]. After the first wave of approvals for long-acting GLP-1 RAs from 2009 to 2014 [48–50], semaglutide was approved in 2017 [51], and the oral form of semaglutide was recently approved in 2020 [52]. Thus, meta-analyses published before 2015 [7, 12, 13, 53, 54] did not discuss all the currently available long-acting GLP-1 RAs, while more recent meta-analyses usually targeted semaglutide [8, 9] or focused on emerging outcomes such as cardiovascular or kidney disease [55, 56]. In contrast, our study aimed to investigate the glycemic control and weight reduction caused by long-acting GLP-1 RAs. Previous studies showed high heterogeneity (I² = 80%-90%) even for findings related to the same GLP-1 RAs [8, 9, 57]. All the potential effect modifiers in our study showed an opposite direction of interaction between glycemic control and weight reduction. Previous meta-analyses have rarely reported this topic and yielded inconsistent results [6, 57]; further studies are warranted to explore a potential effect modifier in the complex combinations between different interventions and target populations. Although unpublished studies (NCT01753362, NCT03480022, NCT02417142, NCT02473809, NCT04325581, NCT03048578, NCT01455441, NCT03466021, NCT04109547, NCT03811574, NCT03693430), withdrawn studies (NCT04057261, NCT02229240), terminated studies (NCT03279731, NCT01628445), studies with an unknown status (NCT01722240, NCT04046822, NCT01722240, NCT02016846, NCT04126603) or those on albiglutide, which was withdraw from the market, all possibly explained the publication bias, the pooled results for the significant HbA1c- and body weight-lowering effects remained robust.

According to a previous within-study-level study [11] and between-study-level network meta-analysis [58], GLP1 RAs showed a higher efficacy for glycemic control, and a compatible higher efficacy for weight reduction is expected. The ecological fallacy in our pooled negative associations between glycemic control and weight reduction may be partially explained by a publication bias, but was better explained by a higher coefficient of variation of GLP-1 RAs for reducing body weight than HbA1c levels and the underlying glucose level [4]. After removing these influential points, studies [20, 31, 44, 45] with prominent weight-reduction effects and modest effects on glycemic changes in non-diabetic participants yielded positive pooled results, supporting our explanation. The mechanism underlying the variable effects of GLP-1 RAs on body weight is not well understood. GLP-1 RAs decreased appetite through direct effects on the hypothalamus, neuronal activation in brain areas, reduced caloric intake, and interference of effective compensatory mechanisms counteracting weight loss [59–61].

Our study provided evidence that the actual effects of GLP-1 RAs on glycemic control and weight reduction were not as high as those reported in previous studies. Thus, a more conservative view of the current published results on GLP-1 RAs is recommended. Clinicians could expect positive associations between weight reduction and glycemic control in diabetes patients treated with GLP-1 RAs. However, marked weight loss in a non-diabetic patient in response to GLP-1 RA treatment did not indicate that clinicians could expect a corresponding glycemic improvement due to the results were interacted with the underlying glucose level.

To the best of our knowledge, our study is the first to consider the correlation between two dependent variables and estimate the relationship between the glycemic control and weight-reducing effects of GLP-1 RAs jointly with an unbiased methodology, a structural equation modeling approach for a multivariate meta-analysis. We comprehensively investigated heterogeneity, effect modifiers, and the reasons for and impact of publication bias. However, the study also had some limitations. First, confirmatory factor and mediation analyses were not performed. We contacted the original authors, but the lack of correlations among the observed variables in individual studies hindered further analysis. Second, our study focused on long-acting GLP1-RAs in comparison with placebo, and future studies should expand the scope to include short-acting GLP1-RAs and comparisons with active components or to sodium-glucose cotransporter-2 inhibitors. Third, the model could not estimate correlations between cardiovascular outcomes and glycemic control and/or weight reduction; the within-study correlation coefficients were not available for categorical variables.

In conclusion, long-acting GLP-1 RAs significantly lowered HbA1c levels and body weight in adults. However, the positive association between glycemic control and weight reduction was only observed in diabetic patients and in non-diabetic participants, but not in all participants with high heterogeneity treated with long-acting GLP-1 RAs.

Supporting information

S1 Checklist. PRISMA checklist 2020.

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S1 File. Details of data extraction in the study.

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S1 Table. Search strategy.

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S2 Table. Characteristics of included randomized double-blind placebo-controlled studies.

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S3 Table. Summary of risk of bias assessment for included studies.

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S4 Table. Sensitivity analysis of the pooled results for glycated hemoglobin level and weight reduction on comparison of glucagon-like peptide-1 receptor agonist and placebo by using the structural equation modeling multivariate meta-analysis according to participant characteristics.

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S1 Fig. Forest plots of univariate meta-analysis.

CI, confidence interval; MD, mean difference; SE, standard error; TE, treatment effect.

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S2 Fig. Forest plots of univariate meta-analysis, subgroup by participants’ characteristics.

CI, confidence interval; DM, diabetes mellitus; MD, mean difference; SE, standard error; TE, treatment effect.

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S3 Fig. Forest plots of univariate meta-analysis, subgroup by different glucagon-like peptide-1 receptor agonists.

CI, confidence interval; GLP1 RA, Glucagon-like peptide-1 receptor agonist; MD, mean difference; sc, subcutaneous; SE, standard error; TE, treatment effect. GLP1 = Others referred to Dulaglutide, once-weekly Exenatide and Albiglutide.

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S4 Fig. Funnel plots and the Egger’s tests of the univariate meta-analysis.

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S5 Fig. Funnel plots and the Egger’s tests of the univariate meta-analysis in different conditions.

DM, diabetes mellitus; HbA1c, glycated hemoglobin.

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S6 Fig. Forest plot of pooled glycated hemoglobin level and body weight reduction, comparing Glucagon-like peptide-1 receptor agonist and placebo, by restricting articles with low bias.

CI, confidence interval; MD, mean difference; SE, standard error; TE, treatment effect.

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Acknowledgments

We would like to thank Editage for editing and proofreading this manuscript.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The authors received no specific funding for this work.

References

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PLoS One. doi: 10.1371/journal.pone.0278685.r001

Decision Letter 0

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21 Oct 2022

PONE-D-22-25301Association between glycemic control and weight reduction of glucagon-like peptide-1 receptor agonists: a multivariate meta-analysisPLOS ONE

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript is to evaluate effects of GLP1R agonists on HbA1c and body weight reductions in real world population by meta-analysis methodology. Authors found positive association between HbA1c and body weight reductions by GLP1R agonists treatment in a diabetes patient population.

I have a couple of critiques authors should address.

1. HbA1c reduction by GLP1R agonists treatment is interacted with the baseline HbA1c. Therefore, restricting population to DM patients skews associations between body weight and HbA1c effects to make another bias. Authors should touch on the issue.

2. Authors do not take adverse effects into account in the analyses. Nausea is well-known adverse effect for GLP1R agonists. Hence, the AE could reduce appetite to modify body weight in entire population. Is there any interaction between AE and body weight?

3. Line 296-321; Authors discuss about genetic polymorphisms as the potential reasons for different HbA1c responses. I do not understand the logic here. What kind of genetic polymorphisms is authors suggesting? The cited paper does not explain any polymorphisms for the GLP1R agonist responses. Is it a bit too haste to discuss about genetic differences for the different HbA1c effects?

4. Line 216-221; Numbers here do not match to the table 2. Please double check.

5. Reference #57 is irrelevant.

6. Table 1; Baseline BMI is not interacted with GLP1R agonists mediated body weight changes. How about to use baseline body weight?

7. Table 2 and S5 Table; What is a definition of tao?

Reviewer #2: With reference to the review of Manuscript number PONE-D-22-25301 “Association between glycemic control and weight reduction of glucagon-like peptide-1 receptor agonists: a multivariate meta-analysis”

Following views are there:

A useful study in a way that obese adults are prone to development of diabetes the study shows that glucagon-like peptide-1 receptor agonists improve glycaemia and decreases the body weight, both effects can protect obese adults from developing diabetes.

However many background con founders can effect the weight gain or loss therefore stratification is desired like patient with and without background Insulin treatment will have different effect on body weight reduction. Different duration of treatment can affect body weight differently. Kindly include non diabetic patients in Table 2 ,5. (All Participants, diabetic and non diabetic participants.)

Quality assessment of primary studies to evaluate the reliability of study results is an essential and mandatory part of meta-analyses. Which scale was used for present study to asses the quality ? Kindly provide score of the studies in table 3.

Adverse events, including nausea, diarrhea, headaches, dizziness and vomiting Associated with glucagon-like peptide-1 receptor agonists can be different in different subsets and will affect eating and weight loss differently. Were there unacceptable side effects in your study, which can outweigh the weight loss benefits in any subset?

Over all a nice study can be published with minor improvements.

Reviewer #3: 1. Title: Ambiguous- the authors need to modify the title. We suggest “Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: a multivariate meta-analysis”

2. Abstract

a) Aims: Requires modification to be in consonance with the new title

b) Methods: First sentence- The authors should state the exact time of commencement of the study and not just state “from study inception”.

c) Conclusion: The last sentence should be moved to the results section. However, the implication(s) of the result contained in the sentence can be included in the conclusion section as done in the conclusion section of the manuscript.

3. Introduction: Well written

4. Materials and Methods:

a) Line 61: There is the need for the authors to define the word “inception” and state categorically the date the study commenced OR did the authors mean since the inception of the databases? If yes, this should be expressly stated.

b) Lines 83 – 85: The last sentence in the methodology section should be moved to appropriate place as it described specific roles of some authors.

5. Data analysis: This section is too long. I would suggest that the authors revise lines 88 – 99 or move it to the supplementary section..

6. Results:

a) Table 1: The authors should unbold the results in bold format. The contents of the Table are already explained in lines 155 – 159 and the p-values are self-explanatory.

b) There is the need to ensure uniform decimal points for the p-values.

c) The authors should remove the sentence “bold indicates statistical significance” from the legend since the results will be unbolded.

d) Going through row 3 in Table 1, Age vs Body weight has p-value of 0.072 which is not significant but was bolded.

7. Discussion:

a) Line 263- Long-acting GLP-1 Ras “showed” and not “show”.

8. Conclusion: Sentence 2- Replace “could” with “might”

Other Comments

1. Inclusion of withdrawn, terminated and unknown status studies as stated in lines 278 – 280 is a source of concern as they could obscure the true findings and conclusion of this study. Is it possible for the authors to reanalyze the retrieved data without the aforementioned studies and find out if a similar outcome will still emerge?

2. Did the authors exclude studies that included type 2 diabetics on insulin in the multivariate analysis as this could affect both the glycemic control and body weight?

3. The observed negative correlation between glycemic control and weight reduction in the univariate analysis is not unexpected because of the diverse population of the participants, different types of GLP-1 RAs and the publication bias.

Suggestion

This manuscript might benefit from a Biostatistician input(s) as I have limited knowledge on the statistical tools/methods used in the study.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes: Yuichiro Adachi

Reviewer #2: No

Reviewer #3: No

**********

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PLoS One. 2023 Jan 25;18(1):e0278685. doi: 10.1371/journal.pone.0278685.r002

Author response to Decision Letter 0

31 Oct 2022

Please see attached files "Response to Reviewers".

Response to reviewers:

PONE-D-22-25301

Association between glycemic control and weight reduction of glucagon-like peptide-1 receptor agonists: a multivariate meta-analysis

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

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Response: Thanks for your advice. We had changed the file names of the supplements.

2. Thank you for stating the following financial disclosure:

"The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

At this time, please address the following queries:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

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Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

Response: Thanks for your advice. We included our amended statements within the cover letter that “The authors received no specific funding for this work.”

Response: Thanks for your advice. We upload copies of the completed PRISMA checklist as Supporting Information with a file name “PRISMA checklist” and it was uploaded separately.

Reviewers' comments:

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: I Don't Know

3. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

5. Review Comments to the Author

Reviewer #1:

The manuscript is to evaluate effects of GLP1R agonists on HbA1c and body weight reductions in real world population by meta-analysis methodology. Authors found positive association between HbA1c and body weight reductions by GLP1R agonists treatment in a diabetes patient population. I have a couple of critiques authors should address.

Response: Thanks for your advice. We revised the discussion to touch on the issue: However, marked weight loss in a non-diabetic patient in response to GLP-1 RA treatment did not indicate that clinicians could expect a corresponding glycemic improvement due to the results were interacted with the underlying HbA1c level genetic polymorphisms.

Response: Thanks for your advice. Considering GI side effect could reduce appetite to modify body weight in entire population, we performed the interaction between AE and outcomes and the results were shown in Table 1.

Revised results: Meta-regression (Table 1) showed that the pooled HbA1c reduction significantly interacted with participants’ baseline age (p = 0.032), …, and gastrointestinal side effect (p = 0.002) but did not interact with ….. ; a 1% increase in the proportion of female participants significantly increased the pooled HbA1c change by 0.015%; …. and 1% increase in gastrointestinal side effect significantly increase the pooled HbA1c level by 0.017%.…………….

Meta-regression (Table 1) showed that the pooled body weight reduction significantly interacted with the proportion of female participants (p = 0.016),…and gastrointestinal side effect (p = 0.025), and ... A 1% increase in the proportion of female participants significantly decreased the pooled body weight reduction by 0.065 kg; …..; a 1% increase in gastrointestinal side effect significantly decreased the pooled body weight reduction by 0.059 kg.

Response: Thanks for your advice. We deleted the sentences. The revised discussion: The mechanism underlying the variable effects of GLP-1 RAs on body weight is not well understood. GLP-1 RAs decreased appetite through direct effects on the hypothalamus, neuronal activation in brain areas, reduced caloric intake, and interference of effective compensatory mechanisms counteracting weight loss.[60, 61].[1, 2] Genetic polymorphisms through signal transduction pathways from different hypothalamic effects in GLP-1 RA responders and non-responders[63] partially explained this difference.

….

Lin 304: However, marked weight loss in a non-diabetic patient in response to GLP-1 RA treatment did not indicate that clinicians could expect a corresponding glycemic improvement due to the results were interacted with the underlying HbA1c level genetic polymorphisms.

4. Line 216-221; Numbers here do not match to the table 2. Please double check.

Response: Thanks for your advice. We matched the numbers in the results with the table 2. The revised results:

Results of the structural equation modeling multivariate meta-analysis

Maximum likelihood estimation worked well in the analysis. Table 2 shows that the pooled HbA1c change induced by GLP1-RAs was -0.85% (95% CI [-1.03%, -0.66%], I2 = 99%), and the pooled body weight change was -4.03 kg (95% CI [-5.11 kg, -2.95 kg], I2 = 99%), which were similar to the results of the univariate meta-analysis. However, overall, the pooled between-study level correlation coefficient between HbA1c and body weight changes from baseline was -0.42, which was the opposite of the within-study level. To explore the negative correlation, we further restricted the multivariate analysis to participants with diabetes. The pooled HbA1c change by GLP1-RA was -0.96% (95% CI [-1.14%, -0.79%], I2 = 96%), the pooled body weight change was -3.23 kg (95% CI [-3.86 kg, -2.59 kg], I2 = 95%); the amount of between-study heterogeneity of body weight decreased from 7.36 to 1.77 and the 95% CI became narrower. The pooled correlation coefficient turned to a positive estimate of 0.32. And if we restricted the multivariate analysis to participants without diabetes of only five studies. The pooled HbA1c change by GLP1-RA was -0.27% (95% CI [-0.31%, -0.23%], I2 = 13%), the pooled body weight change was -6.76 kg (95% CI [-10.81 kg, -2.72 kg], I2 = 99%); the amount of between-study heterogeneity of body weight was much increased to 20.84 with a wide 95% CI due to the limited included articles. However, the pooled correlation coefficient was positive estimate of 0.81.

5. Reference #57 is irrelevant.

Response: Thanks for your advice. We deleted the reference #57

Thus, meta-analyses published before 2015….., while more recent meta-analyses usually targeted semaglutide[3-5] or focused on emerging outcomes such as cardiovascular or kidney disease.[6, 7] In contrast, our study aimed to investigate the glycemic control and weight reduction caused by long-acting GLP-1 RAs. Previous studies showed high heterogeneity (I2 = 80%-90%) even for findings related to the same GLP-1 RAs. [3-5] All the potential effect modifiers in our study showed an opposite direction of interaction between glycemic control and weight reduction. Previous meta-analyses have rarely reported this topic and yielded inconsistent results[3-5];

Reference 57. Li J, He K, Ge J, Li C, Jing Z. Efficacy and safety of the glucagon-like peptide-1 receptor agonist oral semaglutide in patients with type 2 diabetes mellitus: A systematic review and meta-analysis. Diabetes research and clinical practice. 2021;172:108656. Epub 2021/01/13. doi: 10.1016/j.diabres.2021.108656. PubMed PMID: 33434602.

6. Table 1; Baseline BMI is not interacted with GLP1R agonists mediated body weight changes. How about to use baseline body weight?

Response: Thanks for your advice. We performed meta-regression with baseline body weight with the outcomes…

Revised results:

Meta-regression (Table 1) showed that the pooled HbA1c reduction significantly interacted with participants’ baseline age (p = 0.032), proportion of female participants (p = 0.017), the baseline HbA1c level (p = 0.018), and gastrointestinal side effect (p = 0.002) but did not interact with baseline body weight or BMI level, duration of diabetes, follow-up period or insulin use.

Meta-regression (Table 1) showed that the pooled body weight reduction significantly interacted with the proportion of female participants (p = 0.016), the follow-up period (p = 0.018) and gastrointestinal side effect (p = 0.025), and had a borderline interaction with participants’ baseline age (p = 0.091) and the participants’ baseline HbA1c level (p = 0.077), but did not interact with baseline BMI level or body weight, insulin use, or the duration of diabetes.

7. Table 2 and S5 Table; What is a definition of tao?

Response: Thanks for your advice. We revised the footnotes of the tables of table 2 and S5 table.

tao, the variance of effect measure

Reviewer #2:

With reference to the review of Manuscript number PONE-D-22-25301 “Association between glycemic control and weight reduction of glucagon-like peptide-1 receptor agonists: a multivariate meta-analysis”

Following views are there:

Response: Thanks for your advice, we performed further analyses to all participants, patients with diabetes and participants without diabetes.

Revised results: Table 2 shows that the pooled HbA1c change induced by GLP1-RAs was…. To explore the negative correlation, we further restricted the multivariate analysis to participants with diabetes. …. There were only five studies focused on participants without diabetes. The pooled HbA1c change by GLP1-RA was -0.27% (95% CI [-0.31%, -0.23%], I2 = 13%), the pooled body weight change was -6.76 kg (95% CI [-10.81 kg, -2.72 kg], I2 = 99%); the amount of between-study heterogeneity of body weight was much increased to 20.84 with a wide 95% CI due to the limited included articles. However, the pooled correlation coefficient was positive of 0.81. The pooled results for all participants and the results restricted to patients with diabetes are shown in Fig 3.

Response: Thanks for your advice. In line 83: All included trials were assessed for bias using the Cochrane risk-of-bias tool 2.0.[14]

Reference #14. Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ. Cochrane Handbook for Systematic Reviews of Interventions version 6.2: Cochrane; 2021.

We put the long table with 31 reference included articles in the S3 Table.

Reviewer #3:

1. Title: Ambiguous- the authors need to modify the title. We suggest “Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: a multivariate meta-analysis”

Response: Thanks for your advice. We modified the title to “Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: a multivariate meta-analysis”.

2. Abstract

a) Aims: Requires modification to be in consonance with the new title

Response: Thanks for your advice. We modified the aims of the abstract:

Previous aims of the abstract: To explore the effect of glucagon-like peptide-1 receptor agonist (GLP-1 Ras) on glycemic control and weight reduction in adults.

Revised aims of the abstract: To explore the effect of glucagon-like peptide-1 receptor agonist (GLP-1 Ras) on glycemic control and weight reduction in adults.

b) Methods: First sentence- The authors should state the exact time of commencement of the study and not just state “from study inception”.

Response: Thanks for your advice. We modified the methods of the abstract: Databases were searched from study inception August 2021 to March 2022.

Response: Thanks for your advice. The last sentence of the manuscript was moved to the results section.

Original abstract:

Results. ….The standardized pooled correlation coefficient between HbA1c levels and body weight was -0.40.

Conclusion. Long-acting GLP-1 RAs significantly reduced the glycated hemoglobin level and body weight in adults. However, a negative correlation between glycemic control and weight reduction was obtained.

Revised abstract:

Results. ….The standardized pooled correlation coefficient between HbA1c levels and body weight was -0.40. A negative correlation between glycemic control and weight reduction was obtained.

Original conclusion of the manuscript:

In conclusion, long-acting GLP-1 RAs significantly lowered HbA1c levels and body weight in adults. However, the positive association between glycemic control and weight reduction in diabetic patients could not be expected in non-diabetic patients treated with long-acting GLP-1 RAs.

Revised conclusion of the manuscript:

3. Introduction: Well written

4. Materials and Methods:

Response: Thanks for your advice. We revised the methos:

Original Search strategy and selection criteria

We searched the Medline, Ovid EMBASE, Cochrane Library and ClinicalTrials.gov databases for relevant studies from inception to March 2022 by using the following keywords:

Revised Search strategy and selection criteria

We searched the Medline, Ovid EMBASE, Cochrane Library and ClinicalTrials.gov databases for relevant studies from inception August 2021 to March 2022 by using the following keywords:

b) Lines 83 – 85: The last sentence in the methodology section should be moved to appropriate place as it described specific roles of some authors.

Response: Thanks for your advice. We deleted the last sentence in the methodology section: All included trials were assessed for bias using the Cochrane risk-of-bias tool 2.0.[14] The authors M. C. T. and W. H. T. conducted the searches and conducted quality assessments independently, and disagreements were resolved through consensus.

5. Data analysis: This section is too long. I would suggest that the authors revise lines 88 – 99 or move it to the supplementary section..

Response: Thanks for your advice. We move lines 88 – 99 to the supplementary section.

Revised methods:…All included trials were assessed for bias using the Cochrane risk-of-bias tool 2.0.[14]. The details of the data extraction in our study were described in supplement (S1 File).

S1 File. Details of data extraction in the study: The outcomes corresponding to glycemic changes were usually differences in HbA1c levels, changes in fasting plasma glucose levels, changes in self-monitored blood glucose levels from baseline, differences between groups, rate of achievement of an HbA1c target of 6.5% or 7.0%, or other measurements of insulin level or homeostatic model assessment scores among different studies. The outcomes of anthropometric changes were usually differences in body weight, body mass index (BMI), or waist circumference from baseline, differences between groups, or the rate of achievement of a 5%–10% reduction in body weight or BMI. To avoid unit-of-analysis errors,[15] we only extracted the most commonly reported, estimated treatment difference in HbA1c level and body weight from the baseline corresponding to a full dose of GLP-1 RAs in each RCT. The estimated treatment difference was determined using the Revman calculator with the numbers in each arm and the p-values.

6. Results:

a) Table 1: The authors should unbold the results in bold format. The contents of the Table are already explained in lines 155 – 159 and the p-values are self-explanatory.

Response: Thanks for your advice. We unbold the results in bold format.

b) There is the need to ensure uniform decimal points for the p-values.

Response: Thanks for your advice. We uniformed the decimal points for the p-values.

c) The authors should remove the sentence “bold indicates statistical significance” from the legend since the results will be unbolded.

Response: Thanks for your advice. We remove the sentence “bold indicates statistical significance” from the legend

d) Going through row 3 in Table 1, Age vs Body weight has p-value of 0.072 which is not significant but was bolded.

Response: Thanks for your advice. We unbold the results in Tables now.

7. Discussion:

a) Line 263- Long-acting GLP-1 Ras “showed” and not “show”.

Response: Thanks for your advice. We revised the sentence: Long-acting GLP-1 RAs showed better efficacy in weight reduction and glycemic control than short-acting GLP-1 RAs.[39]

8. Conclusion: Sentence 2- Replace “could” with “might”

Response: Thanks for your advice. We revised the discussion: Our meta-analysis demonstrated that long-acting GLP-1 RAs significantly reduced HbA1c levels and body weight in adults. The high heterogeneity in our study could might be attributed to the different GLP-1 RAs and the diverse populations ranging from non-diabetic overweight/obese participants to patients with diabetes complicated with end organ damage.

Other Comments

Response: Thanks for your advice. We did not analyze the articles in lines 278 – 280, the withdrawn, terminated and unknown status studies. We mentioned the above studies in the discussion due to these studies are potential unpublished studies, the possible source of the publication bias.

2. Did the authors exclude studies that included type 2 diabetics on insulin in the multivariate analysis as this could affect both the glycemic control and body weight?

Response: Thanks for your advice. We did not exclude studies that included type 2 diabetics on insulin in the multivariate analysis, thus insulin could affect both the glycemic control and body weight. We performed meta-regression with insulin with the outcomes:

The revised results:

Suggestion

This manuscript might benefit from a Biostatistician input(s) as I have limited knowledge on the statistical tools/methods used in the study.

Response: Thanks for your advice. The manuscript was supervised under a chief biostatistician professor in Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Yuichiro Adachi

Reviewer #2: No

Reviewer #3: No

Attachment

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PLoS One. doi: 10.1371/journal.pone.0278685.r003

Decision Letter 1

Ming-Chang Chiang

22 Nov 2022

Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: a multivariate meta-analysis

PONE-D-22-25301R1

Dear Dr. Yeh,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Ming-Chang Chiang

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: I congratulate authors to address all comments appropriately. Now, the manuscript is a good shape to publish.

I found a typo at line 225 (S5 Table). Please correct before publication.

Reviewer #2: May be accepted with current revisions. All comments were addressed. Quality has definitely improved. Will be a useful paper and guide further research.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Yuichiro Adachi

Reviewer #2: No

**********

PLoS One. doi: 10.1371/journal.pone.0278685.r004

Acceptance letter

Ming-Chang Chiang

24 Nov 2022

PONE-D-22-25301R1

Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: a multivariate meta-analysis

Dear Dr. Yeh:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ming-Chang Chiang

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. PRISMA checklist 2020.

(PDF)

Click here for additional data file.^{(166.8KB, pdf)}

S1 File. Details of data extraction in the study.

(DOCX)

Click here for additional data file.^{(15.1KB, docx)}

S1 Table. Search strategy.

(PDF)

Click here for additional data file.^{(94.3KB, pdf)}

S2 Table. Characteristics of included randomized double-blind placebo-controlled studies.

(PDF)

Click here for additional data file.^{(274.6KB, pdf)}

S3 Table. Summary of risk of bias assessment for included studies.

(PDF)

Click here for additional data file.^{(170.7KB, pdf)}

(PDF)

Click here for additional data file.^{(206.9KB, pdf)}

S1 Fig. Forest plots of univariate meta-analysis.

CI, confidence interval; MD, mean difference; SE, standard error; TE, treatment effect.

(JPG)

Click here for additional data file.^{(557KB, jpg)}

S2 Fig. Forest plots of univariate meta-analysis, subgroup by participants’ characteristics.

CI, confidence interval; DM, diabetes mellitus; MD, mean difference; SE, standard error; TE, treatment effect.

(TIF)

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S3 Fig. Forest plots of univariate meta-analysis, subgroup by different glucagon-like peptide-1 receptor agonists.

(TIF)

Click here for additional data file.^{(757.2KB, tif)}

S4 Fig. Funnel plots and the Egger’s tests of the univariate meta-analysis.

(TIF)

Click here for additional data file.^{(66.2KB, tif)}

S5 Fig. Funnel plots and the Egger’s tests of the univariate meta-analysis in different conditions.

DM, diabetes mellitus; HbA1c, glycated hemoglobin.

(TIF)

Click here for additional data file.^{(137.3KB, tif)}

S6 Fig. Forest plot of pooled glycated hemoglobin level and body weight reduction, comparing Glucagon-like peptide-1 receptor agonist and placebo, by restricting articles with low bias.

CI, confidence interval; MD, mean difference; SE, standard error; TE, treatment effect.

(JPG)

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Data Availability Statement

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PERMALINK

Effect of glucagon-like peptide-1 receptor agonists on glycemic control, and weight reduction in adults: A multivariate meta-analysis

Tzu-Lin Yeh

Ming-Chieh Tsai

Wen-Hsuan Tsai

Yu-Kang Tu

Kuo-Liong Chien

Roles

Abstract

Aims

Methods

Results

Conclusion

Introduction

Materials & methods

Search strategy and selection criteria

Results

Description of studies and quality assessment

Fig 1. Flowchart of the trial selection process.

Results of the univariate meta-analysis

Table 1. Univariate meta-regression of the effects of glucagon-like peptide-1 receptor agonists on glycated hemoglobin levels and weight reduction.

Fig 2. Contour-enhanced and filled funnel plots of glycated hemoglobin level and body weight.

Results of the structural equation modeling multivariate meta-analysis

Table 2. The pooled results for glycated hemoglobin level and weight reduction on comparison of glucagon-like peptide-1 receptor agonist and placebo by using the structural equation modeling multivariate meta-analysis according to participant characteristics.

Fig 3. The pooled effect sizes and their confidence ellipse for changes in glycated hemoglobin level and body weight in patients treated with a glucagon-like peptide-1 receptor agonist and placebo, in participants not restricted and restricted to diabetes.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Ming-Chang Chiang

Roles

Author response to Decision Letter 0

Decision Letter 1

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