Pairwise meta-analysis

Body weight change in kilograms (diabetes)

Type 2 diabetes (adults); background therapy: no glucose lowering drug (lifestyle only)

weeks 20 to 36 (target week 26)Treatment policyDoses of a drug pooledMean difference

Randomized trials

Treatments

703

Participants

Trial arms

In plain language

Across 2 trials with 703 participants, 0 of 1 treatment had a clearly better result than placebo on body weight change in kilograms (diabetes), and for 1 the evidence could not tell it apart from placebo. The most favorable estimate was for Semaglutide tablet: mean difference -0.73 kg (95% credible interval -3.80 to 2.30).

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 Placebo

Mean difference in kg. Lower values favor the treatment.

Versus Placebo. 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 Placebo
Treatment	Bayesian MD (95% CrI)	95% prediction interval	Frequentist MD (95% CI)	Verdict
Semaglutide tablet SEMA_PO	-0.73 (-3.80 to 2.30)	-5.94 to 4.48	-0.73 (-1.90 to 0.45)	Unclear

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): 1.324 (95% CrI 0.175 to 4.518)
Residual deviance: 3.2 for 3 data points
DIC: 6.3 (pD 3.1)
Largest R-hat: 1.002
Smallest ESS: bulk 1,409, tail 1,568
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: 0.766
I squared: 82%
Q (total): 5.41 on 1 df, P = 0.020

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; 1 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; 2 of 2	Kidney function (eGFR) (mL/min/1.73 m2) prognostic factor, effect modifier; 1 of 2	Treatment duration (weeks) effect modifier; 2 of 2	Lifestyle co-intervention intensity (none standard intensive) effect modifier, prognostic factor; 2 of 2
PIONEER 1 S001741	not reported	49.22	S0	17.21	not reported	26	not_reported
PIONEER 11 S001791	28.2	36.27	S0	74.85	102.5	26	not_reported

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, Baseline BMI or body weight: not reported by 1 of 2 trials
FlagBaseline, Kidney function (eGFR): not reported by 1 of 2 trials
NoteOutcome assessment, intercurrent events (discontinuation): mixed: hypothetical 1, treatment_policy 1
NoteOutcome assessment, intercurrent events (rescue): mixed: hypothetical 1, treatment_policy 1
NoteData handling, input conversions: arms_combined 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
PIONEER 1	26	full_analysis	not stated	not stated	not stated	not stated	hypothetical	hypothetical	double_blind	industry	2016	adults with type 2 diabetes on diet and exercise only; HbA1c 7.0 to 9.5 percent
PIONEER 11	26	full_analysis	not stated	not stated	not stated	not stated	treatment_policy	treatment_policy	double_blind	industry	2019	age 18 or older; HbA1c 7.0 to 10.0 percent at screening, 7.0 to 9.5 at randomization; no glucose lowering drugs; eGFR 60 or more

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	Flags	Source
PIONEER 1	A1+A2+A3	SEMA_PO	26	arm, change	-2.700	0.175	525	arms_combined	registry:outcomes
PIONEER 1	A4	PLACEBO	26	arm, change	-1.400	0.262	178		registry:outcomes
PIONEER 11	A1	SEMA_PO	26	contrast, md	-0.100	0.408			R0019663:Figure 4
PIONEER 11	A4	PLACEBO	26	contrast, md					R0019663:Figure 4

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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