Network meta-analysis

Diarrhea

Type 1 diabetes

longest follow-upRecorded harmsEach dose separatelyHazard ratio (from event counts)

Randomized trials

Treatments

2,233

Participants

279

Events

In plain language

Across 2 trials with 2,233 participants, 0 of 3 treatments had a clearly better result than placebo on diarrhea, 1 a clearly worse one, and for 2 the evidence could not tell them apart from placebo. The most favorable estimate was for Liraglutide 0.6 mg subcutaneous once daily: hazard ratio (from event counts) 0.96 (95% credible interval 0.54 to 1.67).

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

Hazard ratio (from event counts). Lower values favor the treatment.

Versus Placebo, log scale. 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 HR (95% CrI)	95% prediction interval	Frequentist HR (95% CI)	Verdict
Liraglutide 0.6 mg subcutaneous once daily LIRA_SC_0p6MG_QD	0.96 (0.54 to 1.67)	0.42 to 2.19	0.99 (0.67 to 1.47)	Unclear
Liraglutide 1.2 mg subcutaneous once daily LIRA_SC_1p2MG_QD	1.38 (0.81 to 2.40)	0.60 to 3.09	1.41 (0.98 to 2.04)	Unclear
Liraglutide 1.8 mg subcutaneous once daily LIRA_SC_1p8MG_QD	1.78 (1.05 to 3.10)	0.80 to 4.08	1.85 (1.30 to 2.65)	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.

League table

Every treatment against every other: hazard ratio (from event counts) of the row treatment versus the column treatment, posterior median and 95% credible interval. Green: row clearly better; red: row clearly worse.

Every treatment in a row compared with every treatment in a column
Row versus column	PLACEBO	LIRA_SC_0p6MG_QD	LIRA_SC_1p2MG_QD	LIRA_SC_1p8MG_QD
PLACEBO	PLACEBO	1.04 0.60 to 1.84	0.72 0.42 to 1.23	0.56 0.32 to 0.95
LIRA_SC_0p6MG_QD	0.96 0.54 to 1.67	LIRA_SC_0p6MG_QD	0.70 0.39 to 1.19	0.54 0.31 to 0.93
LIRA_SC_1p2MG_QD	1.38 0.81 to 2.40	1.44 0.84 to 2.53	LIRA_SC_1p2MG_QD	0.78 0.46 to 1.33
LIRA_SC_1p8MG_QD	1.78 1.05 to 3.10	1.85 1.08 to 3.20	1.28 0.75 to 2.18	LIRA_SC_1p8MG_QD

Heterogeneity, fit and convergence

Bayesian random effects (primary)

Heterogeneity (tau): 0.219 (95% CrI 0.065 to 0.662), log scale
Residual deviance: 6.7 for 8 data points
DIC: 13.0 (pD 6.3)
Largest R-hat: 1.001
Smallest ESS: bulk 3,435, tail 3,887
Divergent transitions: 0
Convergence: All criteria met
Priors: PR02 N(0, 5^2); PR05 N(0, 2.5^2); PR09 log normal(-1.87, 1.52^2) on tau^2 (Adverse events, pharm vs placebo control)

Frequentist check (netmeta)

Method: inverse variance, REML, OR
Tau: 0.000
I squared: 0%
Q (total): 1.12 on 3 df, P = 0.773

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.

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.

NoteOutcome assessment, time point: selected time points span 27 to 52 weeks
NoteData handling, input conversions: nonserious_only 8

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
ADJUNCT TWO™	27	safety	not stated	not stated	not stated	not stated	not stated	not stated	double_blind	industry	2014	type 1 diabetes at least 12 months; BMI 20 or more; HbA1c 7.0 to 10 percent; basal bolus insulin
ADJUNCT ONE™	52	safety	not stated	not stated	not stated	not stated	not stated	not stated	double_blind	industry	2013	T1D at least 12 months; BMI 20 or higher; HbA1c 7.0 to 10 percent; CSII or basal bolus insulin

Trial data

What each trial contributes. Arm rows give the arm value with its standard error, or events over participants; contrast rows give the hazard ratio (from event counts) on the analysis scale (log) against the trial's first row. Flags mark converted, combined or approximated inputs.

Trial data entering this analysis
Trial	Arm	Treatment	Week	Data	Events / N	Flags	Source
ADJUNCT TWO™	A1	LIRA_SC_0p6MG_QD	27	arm, events	14 / 212	nonserious_only	registry:adverse_events
ADJUNCT TWO™	A2	LIRA_SC_1p2MG_QD	27	arm, events	25 / 209	nonserious_only	registry:adverse_events
ADJUNCT TWO™	A3	LIRA_SC_1p8MG_QD	27	arm, events	30 / 207	nonserious_only	registry:adverse_events
ADJUNCT TWO™	A4	PLACEBO	27	arm, events	17 / 207	nonserious_only	registry:adverse_events
ADJUNCT ONE™	A1	LIRA_SC_0p6MG_QD	52	arm, events	41 / 351	nonserious_only	registry:adverse_events
ADJUNCT ONE™	A2	LIRA_SC_1p2MG_QD	52	arm, events	50 / 350	nonserious_only	registry:adverse_events
ADJUNCT ONE™	A3	LIRA_SC_1p8MG_QD	52	arm, events	64 / 349	nonserious_only	registry:adverse_events
ADJUNCT ONE™	A4	PLACEBO	52	arm, events	38 / 348	nonserious_only	registry:adverse_events

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.

Open in the NMA lab