Comparative efficacy and safety of three fixed‐ratio combination products in type 2 diabetes: A network meta‐analysis

Xiaomei Wang; Jiali Qin; Yang Liu; Xianying Wang

doi:10.1111/jdi.70293

. 2026 Mar 28;17(6):979–988. doi: 10.1111/jdi.70293

Comparative efficacy and safety of three fixed‐ratio combination products in type 2 diabetes: A network meta‐analysis

Xiaomei Wang ^1,², Jiali Qin ^1,², Yang Liu ¹, Xianying Wang ^1,^✉

PMCID: PMC13238613 PMID: 41902544

Abstract

Objective

To systematically evaluate and compare the efficacy and safety of three fixed‐ratio combination products—insulin degludec/liraglutide (IDegLira), insulin glargine/lixisenatide (iGlarLixi), and insulin degludec/insulin aspart (IDegAsp)—in patients with type 2 diabetes.

Methods

We systematically searched PubMed, Embase, Cochrane Library, CNKI, Wanfang, and VIP up to July 2025 for randomized controlled trials (RCTs) comparing the three combinations of primary interest (IDegLira, iGlarLixi, IDegAsp) and their individual components (insulin degludec, insulin glargine, liraglutide, and lixisenatide). Inclusion of the individual components enabled indirect comparisons. Data extraction, risk‐of‐bias assessment, and GRADE evaluation were performed. Network meta‐analysis was conducted using Stata 14.0, with treatments ranked by the surface under the cumulative ranking curve (SUCRA).

Results

Twenty‐one RCTs involving 12,815 patients were included. Both IDegLira (OR = 1.69, 95% CI: 1.08–2.65) and iGlarLixi (OR = 1.67, 95% CI: 1.17–2.37) had a higher incidence of treatment‐emergent adverse events (TEAEs) than IDegAsp; no other significant pairwise differences were observed. Based on SUCRA values, which provide a probabilistic ranking (indicating the likelihood of being the best rather than direct statistical superiority), IDegLira had the highest probability of being optimal for reducing HbA1c (89.4%), fasting plasma glucose (81.8%), and incidence of hypoglycemic events (57.6%), while IDegAsp ranked highest regarding the incidence of TEAEs (97.9%). Inconsistency in the hypoglycemia network, likely due to varied definitions, warrants cautious interpretation.

Conclusions

Among the three fixed‐ratio combination products, IDegLira appears most effective for glycemic control (in terms of HbA1c and FPG reduction), whereas IDegAsp demonstrates the best safety profile regarding incidence of TEAEs.

Keywords: Insulin degludec/insulin aspart, Insulin degludec/liraglutide, Insulin glargine/lixisenatide

Diabetes mellitus is a multifactorial chronic disease with rapidly increasing global prevalence. Projections indicate 783.2 million affected individuals by 2045, with type 2 diabetes comprising 90–95% of cases ¹ , ² . Standard type 2 diabetes mellitus management typically includes insulin and/or oral hypoglycemic agents ³ . Although basal insulin effectively controls fasting plasma glucose (FPG), it frequently causes weight gain and nocturnal hypoglycemia ⁴ . When glycemic targets remain unmet, guidelines recommend intensifying therapy with mealtime insulin or glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) ⁵ .

Basal insulin provides prolonged release for stable daily levels ⁶ , while rapid‐acting insulin counters postprandial excursions ⁷ . Insulin degludec/insulin aspart (IDegAsp) combines basal insulin degludec (IDeg) and rapid‐acting insulin aspart (IAsp) in a co‐formulation. IDeg's pharmacology enables basal glucose control with mealtime management support ⁸ . Administered once/twice daily with main meals without resuspension, IDegAsp reduces improper mixing risks and hypoglycemia while improving adherence ⁹ .

GLP‐1RAs effectively lower blood glucose (especially postprandial glucose) and promote weight loss ¹⁰ , ¹¹ . Combining basal insulin with a GLP‐1RA in a single regimen enhances glycemic control compared with basal insulin alone, mitigates the associated weight gain without increasing hypoglycemia risk. However, this approach may introduce gastrointestinal side effects, notably nausea and vomiting ¹² . Currently approved fixed‐ratio combination products include insulin degludec/liraglutide (IDegLira) and insulin glargine/lixisenatide (iGlarLixi). Both allow for once‐daily injection, thereby improving treatment adherence ¹³ .

In current clinical practice, IDegLira, iGlarLixi, and IDegAsp represent the principal fixed‐ratio combination products for patients with type 2 diabetes mellitus inadequately controlled on oral antihyperglycemic drugs. Although they differ in pharmacological composition—IDegLira and iGlarLixi are insulin–GLP‐1RA combinations, whereas IDegAsp is a co‐formulation of two insulin analogues—all three are developed to simplify treatment regimens, improve glycemic control through synergistic mechanisms, and potentially reduce injection frequency and side effects. Clinicians frequently face the dilemma of choosing among these advanced therapies, yet, direct comparative evidence is scarce. Therefore, this study employed a network meta‐analysis, incorporating trials involving their individual components (basal insulins and GLP‐1RAs), to indirectly compare the efficacy (including glycated hemoglobin, FPG, 2‐h postprandial glucose, and body weight) and safety (incidence of hypoglycemic events and incidence of treatment‐emergent adverse events) profiles of these three fixed‐ratio combination products. Our aim is to provide an evidence‐based hierarchy to aid personalized clinical decision‐making among these important therapeutic classes.

INFORMATION AND METHODOLOGY

Inclusion and exclusion criteria

Inclusion criteria:

Study type: Randomized controlled trials (RCTs) published in either Chinese or English were included.
Study subjects: Participants were patients with type 2 diabetes mellitus who met the diagnostic criteria of either the World Health Organization or the American Diabetes Association.
Interventions: The intervention group received one of the following treatment regimens: IDegLira, iGlarLixi, IDegAsp, IDeg, iGlar, liraglutide, or lixisenatide. The control group received any of the other regimens mentioned above. There were no restrictions on dosage, frequency, or mode of administration.
Outcome measures: The primary efficacy outcome was glycated hemoglobin (HbA1c). Secondary outcomes included: efficacy—fasting plasma glucose (FPG), 2‐h postprandial glucose (2 hPG), body weight; safety—incidence of hypoglycemic events and incidence of treatment‐emergent adverse events (TEAEs).

Exclusion criteria:

Studies involving patients with severe comorbidities such as hepatic or renal impairment, or cardiovascular disease.
Duplicate publications.
Studies without accessible full text or critical data.
Studies that did not report the primary efficacy outcome.
Treatment duration of less than 18 weeks.
Non‐research literature, such as conference abstracts, case reports, or expert opinions.

Literature search and study selection

A systematic literature search was conducted in PubMed, Embase, the Cochrane Library, CNKI, Wanfang Data, and VIP databases. The following search terms were used: “insulin degludec/liraglutide,” “insulin glargine/lixisenatide,” “insulin degludec/insulin aspart,” “insulin degludec,” “insulin glargine,” “insulin aspart,” “IDegLira,” “iGlarLixi,” “IDegAsp,” “IDeg,” “iGlar,” “IAsp,” “liraglutide,” “lixisenatide,” “diabetes mellitus type 2,” “type 2 diabetes,” and “T2DM.” The final search was conducted on July 2025, covering all publications up to that date.

Two independent reviewers used EndNote 21.3 software to remove duplicates and perform the screening. Any disagreements were resolved through discussion. If consensus could not be reached, a third reviewer was consulted. The following information was extracted from the included studies: first author, publication year, number of participants, treatment regimen, treatment duration, and outcome indicators.

Risk of bias assessment

The risk of bias of the included RCTs was independently assessed by two reviewers using the Cochrane Collaboration Risk of Bias Tool (version 5.4.1) ¹⁴ , covering the following seven domains: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other sources of bias. Each domain was rated as having low, unclear, or high risk of bias. Discrepancies were resolved by discussion or adjudicated by a third reviewer.

GRADE evidence quality assessment

The quality of evidence for each outcome was evaluated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. The GRADE system classifies evidence into four levels: high, medium, low, and very low. The evaluation was based on five domains for downgrading: risk of bias, inconsistency, indirectness, imprecision, and publication bias ¹⁵ .

Statistical analysis

Network meta‐analysis was conducted using Stata 14.0 software. Network plots were generated to illustrate the relationships between interventions. Global inconsistency was assessed: if P > 0.05, consistency was considered acceptable. Loop inconsistency within closed loops was assessed by calculating the inconsistency factor (IF) and its 95% confidence interval (CI). When P > 0.05 and the lower limit of the 95% CI of the IF value was equal to 0, the results of the direct and indirect comparisons were considered consistent; otherwise, it was considered that there is a significant inconsistency in the closed loop. Local inconsistency tests were performed by node splitting to assess absolute differences between direct and indirect evidence.

The surface under the cumulative ranking curve (SUCRA) was calculated for each treatment to rank efficacy and safety. Continuous outcomes were expressed as mean difference (MD) with 95% CI, while dichotomous outcomes were presented as odds ratio (OR) with 95% CI. SUCRA rankings were interpreted based on the assumption that lower outcome values represented better treatment effects.

Publication bias was evaluated using funnel plots and Egger's test. A P‐value <0.05 was considered indicative of publication bias.

RESULTS

Literature screening and basic characteristics of included studies

A total of 12,810 records were retrieved from the database search. After removing 978 duplicates, 11,631 articles were excluded based on titles and abstracts as they clearly did not meet the inclusion criteria. Following full‐text review, 180 articles were excluded due to discrepancies in interventions, study types, or outcome measures. Ultimately, 21 RCTs involving 12,815 patients were included in the analysis. Seven treatment regimens were investigated in the included studies: IDegLira, iGlarLixi, IDegAsp, IDeg, iGlar, Liraglutide, and Lixisenatide. The basic characteristics of the included studies are presented in Table 1.

Table 1.

Basic characteristics of included studies

First author and year of publication	Number of patients/case			Treatment regimen			Treatment duration/week	Outcome measure
First author and year of publication	I	C	C	I	C	C	Treatment duration/week	Outcome measure
Yuan (2022) ¹⁶	212	214		iGlarLixi	iGlar		30	①②③④⑤⑥
Terauchi (2020) ¹⁷	260	261		iGlarLixi	iGlar		26	①②③④⑤⑥
Riddle (2013) ¹⁸	223	223		iGlarLixi	iGlar		24	①②③④⑤⑥
Kaneto (2020) ¹⁹	255	257		iGlarLixi	iGlar		26	①②③④⑤⑥
Aroda (2016) ²⁰	367	369		iGlarLixi	iGlar		30	①②③④⑤⑥
Yang (2022) ²¹	351	350	177	iGlarLixi	iGlar	Lixisenatide	24	①②③④⑤⑥
Rosenstock (2016) ²²	469	467	234	iGlarLixi	iGlar	Lixisenatide	30	①②③④⑤⑥
Watada (2020) ²³	161	160		iGlarLixi	Lixisenatide		26	①②④⑤⑥
Liu (2024) ²⁴	291	291		iGlarLixi	IDegAsp		24	①⑤⑥
Onishi (2013) ²⁵	147	149		IDegAsp	iGlar		26	①②⑤⑥
Kawaguchi (2024) ²⁶	18	18		IDegLira	iGlarLixi		18	①②
Gough (2014) ²⁷	833	413	414	IDegLira	IDeg	Liraglutide	26	①②⑤⑥
Lingvay (2016) ²⁸	278	279		IDegLira	iGlar		26	①②④⑤⑥
Mu (2017) ²⁹	373	187		IDeg	iGlar		26	①②④⑤⑥
Rosenstock (2018) ³⁰	463	466		IDeg	iGlar		24	①②④⑤⑥
Pan (2016) ³¹	555	278		IDeg	iGlar		26	①②⑤⑥
Aso (2017) ³²	32	12		IDeg	iGlar		24	①②
Rodbard (2013) ³³	773	257		IDeg	iGlar		104	①②⑤⑥
Guo (2020) ³⁴	30	31		iGlar	Liraglutide		26	①②④⑤⑥
Pasquel (2021) ³⁵	137	136		iGlar	Liraglutide		26	①②⑤⑥
D'Alessio (2015) ³⁶	474	470		iGlar	Liraglutide		24	①②⑤⑥

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①: HbA1c; ②: FPG; ③: 2 hPG; ④: Body weight; ⑤: Incidence of hypoglycemic events; ⑥: Incidence of TEAEs.

Risk of bias and publication bias

In the domains of allocation concealment and blinding of participants and investigators, 23 studies were deemed at unclear risk of bias due to insufficient information. Four studies were rated as high risk: one because allocation was not concealed, and three due to a lack of blinding that could introduce performance bias. Regarding the blinding of outcome assessment, 15 studies were judged as unclear risk owing to inadequate reporting, and one study was at high risk because the absence of blinding could have influenced the results. The risk of bias in the remaining domains was generally low, with detailed results provided in Figures S1 and S2.

Funnel plots corrected and Egger's test indicated no publication bias (P > 0.05). The corrected HbA1c funnel plot is shown in Figure 1; others are in Figure S3.

Corrected funnel plot of each treatment regimen for HbA1c.

Evidence network and consistency assessment

Due to incomplete reporting of certain outcomes in some studies, not all outcome measures were included in every analysis. The network evidence map for HbA1c is presented in Figure 2, and the network evidence maps of the other outcomes are presented in Figure S4. In these plots, the edges represent the number of RCTs that directly compared two treatments, while the size of each node reflects the sample size for that regimen.

Network evidence map of each treatment regimen for HbA1c.

Closed loops were formed in the network for all outcomes, including HbA1c, FPG, 2 hPG, body weight, incidence of hypoglycemic events, and incidence of TEAEs. Global inconsistency tests indicated good agreement across all outcome networks (P > 0.05).

However, loop‐specific inconsistency testing revealed significant inconsistency in the IDegLira–iGlar–Liraglutide loop under the outcome measure of the incidence of hypoglycemic events (P < 0.05). Further node‐splitting analysis indicated statistically significant inconsistency between IDegLira and Liraglutide, and between iGlar and Liraglutide (P < 0.05). For all other outcome measures, no significant differences were found between direct and indirect comparisons (P > 0.05).

Results of network meta‐analysis

HbA1c

A total of 21 RCTs ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ , ²⁴ , ²⁵ , ²⁶ , ²⁷ , ²⁸ , ²⁹ , ³⁰ , ³¹ , ³² , ³³ , ³⁴ , ³⁵ , ³⁶ reported HbA1c outcomes across seven treatment regimens. The overall findings indicated that both combinations (IDegLira and iGlarLixi) demonstrated significantly greater HbA1c reduction compared with most individual agents (IDeg, iGlar, liraglutide, and lixisenatide). Additionally, IDegAsp, IDeg, iGlar, and liraglutide all demonstrated greater HbA1c reduction compared with lixisenatide. No other statistically significant differences were observed. All reported comparisons were statistically significant (P < 0.05). Detailed results are shown in Figure 3.

FPG

Twenty RCTs ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ , ²⁵ , ²⁶ , ²⁷ , ²⁸ , ²⁹ , ³⁰ , ³¹ , ³² , ³³ , ³⁴ , ³⁵ , ³⁶ reported FPG outcomes. The main results showed that in reducing FPG, both IDegLira and iGlarLixi were significantly superior to liraglutide and lixisenatide (P < 0.05). IDegAsp, IDeg, iGlar, and liraglutide were all significantly better than lixisenatide. Furthermore, IDeg was significantly more effective than iGlar and liraglutide, and iGlar outperformed liraglutide (all P < 0.05). No other pairwise comparisons showed statistically significant differences. Detailed results are shown in Figure 4.

Forest plot of pairwise comparisons for FPG.

2 hPG

Seven RCTs ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² reported two hPG levels across three treatment regimens. iGlarLixi demonstrated a significant reduction in two hPG compared with iGlar [MD = –3.04, 95% CI (−5.01, –1.07)] (P < 0.05). No significant differences were observed between other regimens (P > 0.05). Detailed results are shown in Figure S5.

Body weight

Twelve RCTs ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ , ²⁷ , ²⁸ , ²⁹ , ³⁰ reported changes in body weight. IDeg [MD = 2.51, 95% CI (0.30, 4.72)] and iGlar [MD = 1.80, 95% CI (0.27, 3.33)] were significantly inferior to Lixisenatide (P < 0.05). No other statistically significant differences were observed (P > 0.05). Detailed results are shown in Figure S5.

Incidence of hypoglycemic events

Nineteen RCTs ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ , ²⁴ , ²⁵ , ²⁷ , ²⁸ , ²⁹ , ³⁰ , ³¹ , ³³ , ³⁴ , ³⁵ , ³⁶ reported hypoglycemia incidence across seven treatment regimens. Compared with Liraglutide, the following regimens showed significantly higher odds of hypoglycemic events: IDegLira [OR = 3.03, 95% CI (1.35, 6.78)], iGlarLixi [OR = 5.25, 95% CI (2.56, 10.77)], IDegAsp [OR = 5.59, 95% CI (2.09, 14.94)], IDeg [OR = 4.07, 95% CI (2.04, 8.09)], iGlar [OR = 4.67, 95% CI (2.55, 8.56)]. Similarly, all regimens above were significantly inferior to Lixisenatide in reducing hypoglycemia incidence (P < 0.05 for all). No other pairwise comparisons were statistically significant. Detailed results are shown in Figure S5.

Incidence of TEAEs

Nineteen RCTs ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ , ²⁴ , ²⁵ , ²⁷ , ²⁸ , ²⁹ , ³⁰ , ³¹ , ³³ , ³⁴ , ³⁵ , ³⁶ reported data on incidence of TEAEs. IDegLira [OR = 1.69, 95% CI (1.08, 2.65)] and iGlarLixi [OR = 1.67, 95% CI (1.17, 2.37)] were associated with a significantly higher incidence of TEAEs compared with IDegAsp. iGlarLixi also showed a significantly higher rate than iGlar [OR = 1.25, 95% CI (1.08, 1.45)]. In contrast, IDegLira, iGlarLixi, IDegAsp, IDeg, and iGlar all had significantly lower incidence of TEAEs compared with Liraglutide (P < 0.05). Similarly, iGlarLixi, IDegAsp, IDeg, and iGlar were superior to Lixisenatide in reducing TEAEs (P < 0.05). No other differences were statistically significant. Detailed results are shown in Figure S5.

SUCRA ranking

The results showed that IDegLira had the highest likelihood of being the optimal treatment regimen in terms of HbA1c levels, with a SUCRA ranking of IDegLira (89.4%) > iGlarLixi (88.9%) > IDegAsp (65.2%) > Liraglutide (37.8%) > IDeg (36.8%) > iGlar (31.7%) > Lixisenatide (0.2%). In terms of FPG levels, IDeg had the highest likelihood of being the optimal treatment regimen, with a SUCRA ranking of IDeg (88.8%) > IDegLira (81.8%) > iGlarLixi (55.6%) > iGlar (52.7%) > IDegAsp (51.0%) > Liraglutide (20.2%) > Lixisenatide (0%). In terms of 2 hPG levels, iGlarLixi had the highest likelihood of being the optimal treatment regimen, with a SUCRA ranking of iGlarLixi (88.8%) > Lixisenatide (53.7%) > iGlar (7.5%). In terms of body weight level, Liraglutide had the greatest likelihood of being the optimal treatment regimen, with a SUCRA ranking of Liraglutide (78.7%) > IDegLira (74.4%) > Lixisenatide (72.9%) > iGlarLixi (42.3%) > iGlar (23.3%) > IDeg (8.4%). In terms of the incidence of hypoglycemic events, the SUCRA ranking was as follows: Lixisenatide (97.1%) > Liraglutide (86.1%) > IDegLira (57.6%) > IDeg (41.8%) > iGlar (29.7%) > iGlarLixi (18.8%) = IDegAsp (18.8%). However, this ranking should be interpreted with caution due to the identified loop inconsistency tests related to hypoglycemia. In terms of the incidence of TEAEs, IDegAsp had the highest likelihood of being the optimal treatment regimen, with a SUCRA ranking of IDegAsp (97.9%) > iGlar (78.0%) > IDeg (70.8%) > iGlarLixi (43.1%) > IDegLira (42.5%) > Lixisenatide (14.8%) > Liraglutide (2.8%). SUCRA plots for each outcome measure are provided in Figure S6.

GRADE quality of evidence evaluation

Downgrading of the overall quality of evidence evaluation will occur due to the fact that most of the literature does not have sufficient information to judge the risk of bias in terms of allocation concealment and blinding, high risk situations for partial blinding, heterogeneity of the results of the included studies, 95% CI of the effect sizes of the results of the studies crossing the line of nullity, and the susceptibility of SUCRA ranking to be altered due to a certain factor. Detailed results of HbA1c are given in Table 2, the quality of evidence ratings for the rest of the outcome measures are shown in Tables S1–S5.

Table 2.

Results of the quality of evidence evaluation under the outcome measure of HbA1c

Treatment regimen	Nature of evidence	Quality grade	Downgrading factor
IDegLira vs iGlarLixi	Mixed	Very low	Risk of bias¹; inaccuracy²; inconsistency³
IDegLira vs IDeg	Mixed	Low	Risk of bias¹; inconsistency³
IDegLira vs iGlar	Mixed	Low	Risk of bias¹; inconsistency³
IDegLira vs Liraglutide	Mixed	Low	Risk of bias¹; inconsistency³
iGlarLixi vs IDegAsp	Mixed	Low	Risk of bias¹; inaccuracy²
iGlarLixi vs iGlar	Mixed	Low	Risk of bias¹; inconsistency³
iGlarLixi vs Lixisenatide	Mixed	Low	Risk of bias¹; inconsistency³
IDegAsp vs iGlar	Mixed	Very low	Risk of bias¹; inaccuracy²; inconsistency³
IDeg vs iGlar	Mixed	Low	Risk of bias¹; inaccuracy²
IDeg vs Liraglutide	Mixed	Low	Risk of bias¹; inaccuracy²
iGlar vs Liraglutide	Mixed	Very low	Risk of bias¹; inaccuracy²; inconsistency³
iGlar vs Lixisenatide	Mixed	Low	Risk of bias¹; inconsistency³
IDegLira vs IDegAsp	Indirect	Low	Risk of bias¹; inaccuracy²
IDegLira vs Lixisenatide	Indirect	Medium	Risk of bias¹
iGlarLixi vs IDeg	Indirect	Very low	Risk of bias¹; inaccuracy²; inconsistency³
iGlarLixi vs Liraglutide	Indirect	Low	Risk of bias¹; inconsistency³
IDegAsp vs IDeg	Indirect	Low	Risk of bias¹; inaccuracy²
IDegAsp vs Liraglutide	Indirect	Low	Risk of bias¹; inaccuracy²
IDegAsp vs Lixisenatide	Indirect	Low	Risk of bias¹; inconsistency³
IDeg vs Lixisenatide	Indirect	Low	Risk of bias¹; inconsistency³
Liraglutide vs Lixisenatide	Indirect	Low	Risk of bias¹; inconsistency³
Ranking		Low	Risk of bias¹; inaccuracy⁴

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1: Unclear or high risk of bias; 2: 95% CI crossing the null line; 3: Heterogeneity of the results of the included studies; 4: SUCRA ranking is susceptible to change due to a factor.

DISCUSSION

Summary of Main findings

In this network, meta‐analysis of 21 RCTs involving 12,815 patients with type 2 diabetes, we directly compared three fixed‐ratio combination products: IDegLira, iGlarLixi, and IDegAsp. Our pairwise comparisons revealed that both IDegLira and iGlarLixi were associated with a higher incidence of TEAEs than IDegAsp, while no other significant differences were observed among the three combinations in terms of glycemic control or body weight. SUCRA‐based ranking indicated that IDegLira had the highest likelihood of being optimal for reducing HbA1c, FPG, and hypoglycemia risk, whereas IDegAsp ranked highest for safety in terms of incidence of TEAEs. However, inconsistency was identified within the hypoglycemia outcome network, warranting cautious interpretation of those findings.

Mechanistic interpretation of efficacy differences

The differential efficacy profiles of these combinations can be explained by their distinct pharmacological compositions. IDegLira combines the long‐acting GLP‐1RA liraglutide with insulin degludec. Long‐acting GLP‐1RAs exert sustained glucose‐lowering effects, primarily influencing FPG through enhanced insulin secretion and suppressed glucagon release ³⁷ . In contrast, iGlarLixi contains the short‐acting GLP‐1RA lixisenatide, which strongly delays gastric emptying, leading to more pronounced postprandial glucose control ³⁷ . IDegAsp, as a co‐formulation of basal and rapid‐acting insulin, primarily addresses both fasting and postprandial glucose excursions through direct insulin replacement ³⁸ . This mechanistic distinction aligns with our findings: IDegLira showed superior FPG reduction, whereas iGlarLixi demonstrated the best postprandial glucose control among the comparators. The three regimens compared here are pharmacologically distinct: IDegLira and iGlarLixi combine insulin with GLP‐1RA, whereas IDegAsp contains two insulin analogues. This difference explains their varied effects on fasting/postprandial glucose, body weight, and gastrointestinal tolerability. Our analysis does not treat them as identical therapies but addresses the practical clinical question of how these mechanistically different fixed‐ratio options compare. The ranking provided is based on the best available indirect evidence to guide individualized selection.

Clinical implications and practical guidance

Our findings provide a clear, evidence‐based hierarchy to assist clinicians in selecting among these advanced therapies, a common dilemma in clinical practice. For patients whose primary therapeutic goal is overall glycemic control (HbA1c reduction), IDegLira appears to be the most effective option. For those with a high concern for TEAEs, particularly gastrointestinal tolerability, IDegAsp may be the preferred choice due to its favorable safety profile. iGlarLixi may be particularly suitable for individuals with prominent postprandial hyperglycemia. These insights are especially relevant in diverse clinical settings, including Asia, where patient phenotypes, dietary patterns, and tolerability considerations may further guide individualized therapy selection ¹ , ³ .

Safety considerations and inconsistency in hypoglycemia

The higher incidence of TEAEs with IDegLira and iGlarLixi is consistent with the known gastrointestinal side‐effect profile of GLP‐1RAs ¹² . The observed inconsistency in hypoglycemia outcomes within the IDegLira–iGlar–Liraglutide loop suggests that factors, such as trial design, patient characteristics, insulin titration protocols, or definition of hypoglycemia may influence this endpoint. For instance, the study by Pasquel et al. ³⁵ was identified as a contributor to local inconsistency. This underscores the need for standardized definitions and cautious interpretation of hypoglycemia data in future comparative studies. Our application of node‐splitting analysis transparently identified this inconsistency, enhancing the reliability of our interpretations for other, more consistent outcomes like HbA1c and TEAEs.

Limitations

Several limitations should be acknowledged. First, direct head‐to‐head trials among the three combinations are scarce, with only one trial each for iGlarLixi vs IDegLira and iGlarLixi vs IDegAsp, and none for IDegLira vs IDegAsp, which may affect the precision of indirect comparisons. Second, heterogeneity in outcome definitions (e.g., hypoglycemia) and variations in trial duration may introduce bias. Third, according to the GRADE framework, the certainty of evidence for several key comparisons was assessed as ‘Low’ or ‘Very Low’, primarily due to risk of bias in included studies (e.g., unclear allocation concealment) and imprecision. This underscores that our findings, while providing the best available comparative evidence to date, should be interpreted as hypothesis‐generating and highlight the need for future confirmatory trials. Finally, our analysis could not explore patient‐level effect modifiers such as diabetes duration, beta‐cell function, or body mass index due to limited reporting.

CONCLUSION

In conclusion, IDegLira appears most effective for glycemic control (in terms of HbA1c and FPG reduction), while IDegAsp offers the best safety profile regarding incidence of TEAEs. This study provides the first comparative evidence framework for three advanced fixed‐ratio combination products, offering crucial guidance for personalized treatment selection in type 2 diabetes mellitus. To solidify the evidence base, especially concerning hypoglycemia, and to validate these findings across different ethnicities, we advocate for well‐designed, head‐to‐head RCTs that include adequate representation of Asian populations.

FUNDING

This work was supported by Medical Science Research Project of Hebei (grant number 20240829).

DISCLOSURE

There are no conflicts of interest to declare.

Approval of the research protocol: N/A.

Informed consent: N/A.

Registry and the registration no. of the study/trial: N/A.

Animal studies: N/A.

Supporting information

Figure S1 Risk of bias bar plot.

Figure S2 Risk of bias plot.

Figure S3 Corrected funnel plots of each treatment regimen for different outcome measures.

Figure S4 Network evidence maps of each treatment regimen for different outcome measures.

Figure S5 Network meta‐analysis of each treatment regimen for different outcome measures.

Figure S6 SUCRA plots of each treatment regimen for different outcome measures.

Table S1 Results of the quality of evidence evaluation under the outcome measure of FPG.

Table S2 Results of the quality of evidence evaluation under the outcome measure of 2 hPG.

Table S3 Results of the quality of evidence evaluation under the outcome measure of body weight.

Table S4 Results of the quality of evidence evaluation under the outcome measure of the incidence of hypoglycemic events.

Table S5 Results of the quality of evidence evaluation under the outcome measure of the incidence of TEAEs. Search strategies.

JDI-17-979-s001.docx^{(183.3KB, docx)}

ACKNOWLEDGMENTS

This work was supported by Medical Science Research Project of Hebei (grant number 20240829).

Clinical Trial Registry

PROSPERO

CRD420251101623

DATA AVAILABILITY STATEMENT

See Figure S1 for available data.

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