Body weight change in kilograms (diabetes)
Type 2 diabetes (adults); background therapy: basal insulin with or without non insulin drugs
In plain language
Across 2 trials with 2,151 participants, 0 of 2 treatments had a clearly better result than semaglutide injection on body weight change in kilograms (diabetes), 2 a clearly worse one. The most favorable estimate was for Insulin aspart (prandial): mean difference 6.99 kg (95% credible interval 1.43 to 11.46).
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
Effects compared with Semaglutide injection
| Treatment | Bayesian MD (95% CrI) | 95% prediction interval | Frequentist MD (95% CI) | Verdict |
|---|---|---|---|---|
| Insulin aspart (prandial) INS_ASPART | 6.99 (1.43 to 11.46) | -0.63 to 13.92 | 7.10 (6.67 to 7.53) | Worse |
| Insulin glargine INS_GLARGINE | 8.26 (2.40 to 12.73) | 0.49 to 15.01 | 8.36 (7.55 to 9.17) | Worse |
Ranking
League table
| Row versus column | SEMA_SC | INS_ASPART | INS_GLARGINE |
|---|---|---|---|
| SEMA_SC | SEMA_SC | -6.99 -11.46 to -1.43 | -8.26 -12.73 to -2.40 |
| INS_ASPART | 6.99 1.43 to 11.46 | INS_ASPART | -1.27 -8.17 to 6.13 |
| INS_GLARGINE | 8.26 2.40 to 12.73 | 1.27 -6.13 to 8.17 | INS_GLARGINE |
Heterogeneity, fit and convergence
Bayesian random effects (primary)
Frequentist check (netmeta)
Inconsistency
No comparison here has both direct and indirect evidence, so inconsistency cannot be checked by node splitting; the between designs Q above is the global check.
Small study effects
Fewer than ten trial comparisons, too few to judge funnel plot asymmetry.
Baseline characteristics of the trials
| 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; 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 |
|---|---|---|---|---|---|---|---|
| SUSTAIN 11 S000363 | 31.55 | 48.86 | S2 | 19.55 | eGFR below 60: 0.1 percent | 52 | not_reported |
| NCT05514535 S001161 | 32.95 | 44.19 | S2 | 9.61 | 87.45 | 40 | not_reported |
Comparability of the trials
- FlagBaseline, Kidney function (eGFR): not reported by 1 of 2 trials
- NoteOutcome assessment, time point: selected time points span 40 to 52 weeks
| Trial | time weeks | analysis set | definition | instrument | adjudicated | proportion method | intercurrent events (discontinuation) | intercurrent events (rescue) | blinding | funding | start year | Eligibility |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SUSTAIN 11 | 52 | full_analysis | not stated | not stated | not stated | not stated | not stated | not stated | open_label | industry | 2018 | adults; HbA1c above 7.5 to 10.0 percent on insulin glargine plus metformin |
| NCT05514535 | 40 | full_analysis | not stated | not stated | not stated | not stated | not stated | not stated | open_label | industry | 2022 | adults with T2D, BMI 25 or more, HbA1c 7 to 10 percent, basal insulin up to 40 U/day plus metformin with or without SGLT2i |
Trial data
| Trial | Arm | Treatment | Week | Data | Value | SE | Events / N | Flags | Source |
|---|---|---|---|---|---|---|---|---|---|
| SUSTAIN 11 | A1 | SEMA_SC | 52 | arm, change | -4.200 | 0.163 | 801 | registry:outcomes | |
| SUSTAIN 11 | A2 | INS_ASPART | 52 | arm, change | 2.900 | 0.146 | 793 | registry:outcomes | |
| NCT05514535 | A1 | SEMA_SC | 40 | arm, change | -7.970 | 0.335 | 282 | registry:outcomes | |
| NCT05514535 | A2 | INS_GLARGINE | 40 | arm, change | 0.390 | 0.246 | 275 | registry:outcomes |
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.