Pairwise meta-analysis

Body weight change in kilograms (diabetes)

Type 2 diabetes (adults); background therapy: one or more non insulin glucose lowering drugs

weeks 36 to 64 (target week 52)Not stated by the trialsEach dose separatelyMean differenceSeparate part 2 of a disconnected network

Randomized trials

Treatments

560

Participants

Trial arms

In plain language

Across 2 trials with 560 participants, 0 of 1 treatment had a clearly better result than exenatide 10 ug subcutaneous twice daily on body weight change in kilograms (diabetes), 1 a clearly worse one. The most favorable estimate was for Premixed insulin: mean difference 4.79 kg (95% credible interval 1.24 to 7.65).

Lower values favor the treatment. "Clearly" means the 95% credible interval excludes no difference. These are averages across trials; they do not say how any one person will respond. Not medical advice.

Network of trials

Each circle is a treatment; each line joins treatments that were randomized against each other in at least one trial.

Node area shows participants; line width shows trials comparing two treatments directly. Blue: GLP-1 receptor agonist containing treatments; grey: comparators. Hover over or tab to a node or line for details.

Effects compared with Exenatide 10 ug subcutaneous twice daily

Mean difference in kg. Lower values favor the treatment.

Versus Exenatide 10 ug subcutaneous twice daily. Blue: Bayesian random effects posterior median with 95% credible interval (thick) and 95% prediction interval (dashed). Amber diamond: frequentist estimate with 95% confidence interval. Hover over or tab to a row for its values.

Effects of each treatment versus Exenatide 10 ug subcutaneous twice daily
Treatment	Bayesian MD (95% CrI)	95% prediction interval	Frequentist MD (95% CI)	Verdict
Premixed insulin INS_PREMIX	4.79 (1.24 to 7.65)	-0.97 to 9.88	4.78 (3.24 to 6.33)	Worse

Ranking

How likely each treatment is to be among the best. Rankings ignore the size of differences and their certainty, so read them with the effects above.

Heterogeneity, fit and convergence

Bayesian random effects (primary)

Heterogeneity (tau): 1.400 (95% CrI 0.099 to 4.700)
Residual deviance: 4.2 for 4 data points
DIC: 8.2 (pD 4.0)
Largest R-hat: 1.002
Smallest ESS: bulk 1,766, tail 1,786
Divergent transitions: 0
Convergence: All criteria met
Priors: PR01 N(0, 25^2); PR03 N(0, 12.5^2); PR07 half normal(0, 2.5^2) on tau

Frequentist check (netmeta)

Method: inverse variance, REML, MD
Tau: 0.958
I squared: 70%
Q (total): 3.32 on 1 df, P = 0.068

Inconsistency

Do trials comparing two treatments directly agree with the indirect evidence through other treatments?

No comparison here has both direct and indirect evidence, so inconsistency cannot be checked by node splitting.

Small study effects

A comparison adjusted funnel plot: each point is one trial comparison, centered on its own network estimate. Asymmetry can signal that small trials with unfavorable results are missing.

Fewer than ten trial comparisons, too few to judge funnel plot asymmetry.

Baseline characteristics of the trials

The baseline value of each effect modifier or prognostic factor that applies here, per trial: mean or percent over arms, weighted by the number randomized. A note under a value names a stand in (a median for a mean, 100 minus the male share, Asian subgroup rows, an all Asian site list); "not reported" means no source of the trial prints it.

Baseline effect modifiers and prognostic factors per trial
Trial	Baseline BMI or body weight (kg/m2) effect modifier, prognostic factor; 2 of 2	Sex (percent female) effect modifier, prognostic factor; 2 of 2	Background glucose lowering therapy (stratum S0 to S4) effect modifier, prognostic factor; 2 of 2	Asian ancestry or region (percent Asian) effect modifier, prognostic factor; 1 of 2	Kidney function (eGFR) (mL/min/1.73 m2) prognostic factor, effect modifier; 0 of 2	Treatment duration (weeks) effect modifier; 2 of 2	Lifestyle co-intervention intensity (none standard intensive) effect modifier, prognostic factor; 2 of 2
NCT00082407 S000441	30.4	48.98	S1	not reported	not reported	52	not_reported
S003030 S003030	24	39.39	S1	100 region: all sites in Asia	not reported	52	standard

Comparability of the trials

Checked across designs (the set of treatments each trial compares) for eligibility, outcome definition and assessment, and the baseline factors above. Flags point to possible intransitivity; notes describe variation that is not tied to design.

FlagBaseline, Asian ancestry or region: not reported by 1 of 2 trials
FlagBaseline, Kidney function (eGFR): not reported by 2 of 2 trials
NoteOutcome assessment, analysis set: mixed: full_analysis 1, modified_itt 1
NoteOutcome assessment, definition: mixed: mean HbA1c change baseline to week 52 1, not stated 1

Comparability items per trial
Trial	time weeks	analysis set	definition	instrument	adjudicated	proportion method	intercurrent events (discontinuation)	intercurrent events (rescue)	blinding	funding	start year	Eligibility
NCT00082407	52	modified_itt	not stated	not stated	not stated	not stated	not stated	not stated	open_label	industry	2003	Age 30 to 75; HbA1c 7.0 to 11.0 on metformin plus sulfonylurea; BMI 25 to 40
S003030	52	full_analysis	mean HbA1c change baseline to week 52	not stated	not stated	not stated	not stated	not stated	open_label	industry	2015	age 20 to 75; HbA1c 7.5 to 11 percent; two or more oral agents for 3 months

Trial data

What each trial contributes. Arm rows give the arm value with its standard error, or events over participants; contrast rows give the mean difference on the analysis scale against the trial's first row. Flags mark converted, combined or approximated inputs.

Trial data entering this analysis
Trial	Arm	Treatment	Week	Data	Value	SE	Events / N	Source
NCT00082407	A1	EXEN_SC_10UG_BID	52	arm, change	-2.500	0.200	253	R0025791:Table 2
NCT00082407	A2	INS_PREMIX	52	arm, change	2.900	0.200	248	R0025791:Table 2
S003030	A1	EXEN_SC_10UG_BID	52	arm, change	-2.210	0.660	27	R0018574:Table 2
S003030	A2	INS_PREMIX	52	arm, change	1.570	0.523	32	R0018574:Table 2

Rerun this analysis yourself

Remove treatments or trials and refit the frequentist and Bayesian models in your browser, with the same methods as the published analysis.

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