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  string(1277) "Background: SGLT2 inhibitors produce modest weight loss in people with type 2 diabetes mellitus (T2DM), but inter-individual response varies substantially. Whether baseline adiposity modifies the randomized weight-lowering effect remains uncertain.

Objective: To determine whether baseline body mass index (BMI) modifies the effect of SGLT2 inhibition on body weight.

Study Design: Secondary individual participant data (IPD) meta-analysis of completed randomized controlled trials.

Participants: Adults with T2DM randomized to an SGLT2 inhibitor or placebo/control.

Primary and Secondary Outcome Measure(s): The primary outcome is body weight at approximately 24–26 weeks. Secondary outcomes include absolute and percentage weight change, BMI change, waist circumference, clinically meaningful weight reduction, and longitudinal weight trajectories where available.

Statistical Analysis: A one-stage IPD meta-analysis will estimate treatment-by-baseline BMI interaction effects while preserving trial-specific randomized comparisons and accounting for clustering within trials. Nonlinearity will be assessed using restricted cubic splines. Secondary effect modifiers and two-stage random-effects sensitivity analyses will also be examined."
  ["project_brief_bg"]=>
  string(1658) "SGLT2 inhibitors are established therapies for T2DM and have important cardiovascular and kidney benefits. In addition to their glycemic effects, SGLT2 inhibitors consistently produce modest reductions in body weight. However, considerable heterogeneity exists in individual weight response, and it remains uncertain whether baseline adiposity systematically modifies the magnitude of weight loss attributable to treatment.



Trial-level aggregate analyses cannot adequately address participant-level treatment-effect heterogeneity because relationships observed between study-level characteristics and treatment effects may not reflect within-trial individual-level associations. Access to anonymized IPD from randomized trials provides an opportunity to determine whether baseline BMI modifies the randomized effect of SGLT2 inhibition while preserving within-trial treatment comparisons.



This study will combine eligible canagliflozin trials obtained through the YODA Project with eligible SGLT2 inhibitor trials requested through Vivli as part of a broader IPD meta-analysis. The primary objective is to characterize the relationship between baseline BMI and treatment-associated weight reduction, including potential nonlinear relationships. Secondary analyses will evaluate other clinically relevant participant characteristics and weight-related outcomes.



The findings may improve understanding of heterogeneity in weight response to SGLT2 inhibitors, provide more individualized estimates of expected weight reduction, and inform future research examining treatment response according to baseline adiposity."
  ["project_specific_aims"]=>
  string(1528) "This study is a secondary analysis of previously completed randomized clinical trials using existing anonymized participant-level data; no new participant recruitment or data collection will be undertaken.



Primary objective: To determine whether baseline body mass index (BMI) modifies the randomized treatment effect of SGLT2 inhibition on body weight among adults with type 2 diabetes mellitus.



Primary hypothesis: The magnitude of placebo-adjusted weight reduction with SGLT2 inhibition differs across the continuous distribution of baseline BMI.



Secondary objectives: (1) quantify the overall effect of SGLT2 inhibition on body weight; (2) characterize the relationship between baseline BMI and treatment-associated weight change, including potential nonlinear relationships; (3) determine whether baseline body weight, age, sex, HbA1c, and eGFR modify the effect of SGLT2 inhibition on body weight; (4) assess whether weight-lowering effects differ among empagliflozin, dapagliflozin, and canagliflozin; and (5) evaluate secondary anthropometric outcomes including percentage body-weight change, BMI change, and waist circumference where available.



The analysis will preserve within-trial randomization. Baseline BMI will be analyzed as a continuous effect modifier using a treatment-by-BMI interaction, with nonlinear treatment-effect modification explored using restricted cubic splines. Other treatment-effect modifiers will be prespecified secondary analyses."
  ["project_study_design"]=>
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    ["label"]=>
    string(52) "Meta-analysis (analysis of multiple trials together)"
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  ["project_purposes"]=>
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      ["value"]=>
      string(56) "new_research_question_to_examine_treatment_effectiveness"
      ["label"]=>
      string(114) "New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations"
    }
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      ["value"]=>
      string(22) "participant_level_data"
      ["label"]=>
      string(36) "Participant-level data meta-analysis"
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      ["value"]=>
      string(56) "participant_level_data_meta_analysis_from_yoda_and_other"
      ["label"]=>
      string(69) "Meta-analysis using data from the YODA Project and other data sources"
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  ["project_research_methods"]=>
  string(1220) "This study will include anonymized IPD from completed randomized controlled trials of canagliflozin made available through the YODA Project. Eligible participants will be adults with T2DM randomized to canagliflozin or placebo/control with baseline body weight and baseline BMI available. For the primary analysis, participants must also have body-weight assessment at approximately 24–26 weeks; where an exact assessment is unavailable, the closest assessment within 20–30 weeks will be used. Participants without the data required for a specific analysis will not contribute to that analysis.



The broader IPD meta-analysis will additionally include eligible randomized trials of empagliflozin and dapagliflozin requested through Vivli (Vivli request 00017742). Heart failure and type 1 diabetes populations will not be combined with the primary T2DM population.



Participant-level data will remain within their respective secure data-sharing environments. Harmonized trial-specific estimates will be combined across data sources where direct participant-level pooling across platforms is not permitted. Trial membership and randomized treatment allocation will be preserved throughout."
  ["project_main_outcome_measure"]=>
  string(1229) "Primary outcome: Body weight at approximately 24–26 weeks after randomization, expressed in kilograms and analyzed with adjustment for baseline body weight. Where body weight is not available at exactly 24 or 26 weeks, the measurement closest to 24 weeks within a prespecified 20–30-week window will be used. The primary treatment effect will be expressed as the adjusted mean difference in body weight between participants randomized to SGLT2 inhibition and placebo/control.



Secondary outcomes: Absolute change in body weight (kg), percentage change in body weight from baseline, change in BMI (kg/m²), and change in waist circumference (cm) where available. Achievement of ≥3% and ≥5% body-weight reduction will also be evaluated where these outcomes can be derived from baseline and follow-up measurements. Body weight at all available study visits will be requested to permit secondary longitudinal analyses of weight trajectories.



Continuous anthropometric outcomes will primarily be analyzed continuously rather than categorized. Clinically interpretable categories may be used for descriptive presentation but will not replace continuous-variable analyses for the primary hypothesis."
  ["project_main_predictor_indep"]=>
  string(1062) "Primary independent variable: Randomized treatment allocation, defined as assignment to an eligible SGLT2 inhibitor (empagliflozin, dapagliflozin, or canagliflozin) versus the corresponding placebo/control group. Randomized treatment will be analyzed according to original treatment assignment wherever possible.



Primary prespecified effect modifier: Baseline BMI (kg/m²). BMI will be analyzed as a continuous variable to avoid loss of information associated with arbitrary categorization. The primary treatment-effect-modification analysis will evaluate the interaction between randomized treatment allocation and continuous baseline BMI. Potential nonlinearity in treatment-effect modification across the BMI distribution will be explored using restricted cubic splines.



Baseline body weight, age, sex, HbA1c, eGFR, and individual SGLT2 inhibitor will be evaluated as prespecified secondary effect modifiers. Continuous variables will preferentially remain continuous, while sex and SGLT2 inhibitor will be modeled categorically."
  ["project_other_variables_interest"]=>
  string(1157) "Additional variables of interest will include age, sex, race/ethnicity, baseline body weight, height, HbA1c, fasting plasma glucose, renal function, duration of diabetes, background glucose-lowering therapy, SGLT2 inhibitor molecule and dose, treatment exposure/discontinuation, and study visit/time from randomization.



Age, baseline body weight, HbA1c, fasting glucose, eGFR, and diabetes duration will preferentially be analyzed as continuous variables. Sex will be analyzed according to the categories available within the source trials. Race/ethnicity will be harmonized across trials into clinically interpretable categories only where source definitions permit reliable mapping; otherwise original trial-specific categories will be retained. Background glucose-lowering therapies will be harmonized by medication class, including metformin, sulfonylureas, insulin, thiazolidinediones, DPP-4 inhibitors, and other relevant therapies.



These variables will primarily be used for cohort characterization and prespecified secondary treatment-effect-modification analyses. Baseline BMI remains the sole primary effect modifier."
  ["project_stat_analysis_plan"]=>
  string(4502) "This study is a secondary analysis of previously completed randomized controlled trials using existing anonymized individual participant data (IPD); no new participant recruitment or data collection will be undertaken. IPD from eligible trials will be harmonized using common definitions and units. The IPD will not be analyzed as a single pooled cohort. Trial membership and the randomized structure of each individual trial will be explicitly preserved throughout the analysis, and analyses will follow the intention-to-treat principle where possible.



The primary outcome will be body weight at approximately 24–26 weeks after randomization. Where an assessment is not available at exactly 24 or 26 weeks, the measurement closest to 24 weeks within a prespecified 20–30-week window will be used. This secondary analysis will use an analysis-of-covariance (ANCOVA) framework, modeling follow-up body weight with adjustment for baseline body weight. Trials without an eligible body-weight assessment within the 20–30-week window will not contribute to this analysis but may contribute to prespecified secondary analyses of earlier weight response and longitudinal weight trajectories.



The primary hypothesis is that baseline body mass index (BMI) modifies the randomized effect of SGLT2 inhibition on body weight. A one-stage IPD meta-analysis will be performed, with trial-specific effects and appropriate modelling of clustering of participants within trials to account for differences among studies and preserve the independence of individual trials. Treatment effects will therefore be estimated from within-trial randomized comparisons rather than by treating participants from different trials as a single cohort. The model will include randomized treatment allocation, baseline body weight, baseline BMI, and a treatment-by-baseline BMI interaction. The treatment-by-BMI interaction will constitute the primary statistical test of treatment-effect modification. Appropriate within-trial centering will distinguish participant-level treatment-effect modification from between-trial associations.



Baseline BMI will primarily be modelled continuously. Potential nonlinear treatment-effect modification will be investigated using restricted cubic splines, with placebo-adjusted treatment effects and 95% confidence intervals estimated across the observed BMI distribution.



Prespecified secondary treatment-effect modifiers will include baseline body weight, age, sex, HbA1c, eGFR, and SGLT2 inhibitor molecule. Secondary outcomes will include absolute and percentage body-weight change, BMI change, waist circumference, and ≥3% and ≥5% body-weight reduction where derivable. Weight measurements from all available study visits will be used, where appropriate, in secondary analyses examining earlier treatment effects and longitudinal weight trajectories.



A two-stage IPD meta-analysis will be performed as a sensitivity analysis. Treatment effects and treatment-by-covariate interactions will be estimated separately within individual trials and subsequently pooled using random-effects meta-analysis. Between-trial heterogeneity will be quantified using τ² and I² where appropriate.



Missingness will be described by trial and variable. The main analysis will include randomized participants with available baseline body weight and an eligible follow-up body-weight measurement. Multiple imputation may be considered for missing participant-level baseline covariates used in secondary multivariable analyses where appropriate, with complete-case analyses performed as sensitivity analyses. Variables not collected within an entire trial will be distinguished from participant-level missingness.



Prespecified sensitivity analyses will include restriction to trials with a 24–26-week assessment, restriction to Phase III trials, exclusion of insulin-treated populations, exclusion of participants with advanced renal impairment, analyses according to individual SGLT2 inhibitor, alternative modelling of baseline BMI, and comparison of one-stage and two-stage IPD approaches. Effect estimates will be presented with 95% confidence intervals. The treatment-by-BMI interaction will constitute the single prespecified treatment-effect-modification hypothesis; all other interaction analyses will be considered secondary and interpreted with appropriate consideration of multiplicity."
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      ["label"]=>
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  ["project_timeline"]=>
  string(314) "Anticipated project start: March 2027

Data harmonization and primary analyses: March–August 2027

Analysis completion: September 2027

Manuscript drafting: September–November 2027

First manuscript submission: December 2027

Results reported to the YODA Project: By February 2028"
  ["project_dissemination_plan"]=>
  string(896) "Results will be submitted for publication in a peer-reviewed cardiovascular, diabetes, or metabolic journal. Potential journals include Diabetes Care, Diabetologia, The Lancet Diabetes & Endocrinology, and JAMA Cardiology, depending on the scope and findings of the completed analysis. Findings may also be presented at major scientific meetings, including the American Diabetes Association Scientific Sessions, European Association for the Study of Diabetes Annual Meeting, and European Society of Cardiology Congress.



The target audience includes clinicians, researchers, trialists, and guideline stakeholders involved in diabetes, obesity, cardiovascular disease, and pharmacotherapy. Results will be reported irrespective of the direction or statistical significance of findings and in accordance with applicable IPD meta-analysis reporting standards, including PRISMA-IPD."
  ["project_bibliography"]=>
  string(2204) "

Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373:2117-2128.
Neal B, Perkovic V, Mahaffey KW, et al. Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med. 2017;377:644-657.
Wiviott SD, Raz I, Bonaca MP, et al. Dapagliflozin and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2019;380:347-357.
Storgaard H, Gluud LL, Bennett C, et al. Benefits and harms of sodium-glucose co-transporter 2 inhibitors in patients with type 2 diabetes: a systematic review and meta-analysis. PLoS One. 2016;11:e0166125.
Vasilakou D, Karagiannis T, Athanasiadou E, et al. Sodium-glucose cotransporter 2 inhibitors for type 2 diabetes: a systematic review and meta-analysis. Ann Intern Med. 2013;159:262-274.
Riley RD, Lambert PC, Abo-Zaid G. Meta-analysis of individual participant data: rationale, conduct, and reporting. BMJ. 2010;340:c221.
Stewart LA, Clarke M, Rovers M, et al. Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement. JAMA. 2015;313:1657-1665.
Khanna S, Kalman E, Thungathurthi K, et al. SGLT2 inhibitors reduce epicardial adipose tissue volume and thickness: a systematic review and meta-analysis. Int J Obes (Lond). 2026.

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