- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07188545
- Original Trial
Using Secondary Data to Evaluate Sex-based Heterogeneity of GLP-1 Agonists and SGLT2 Inhibitors on Cardiovascular-Kidney-Metabolic Health (CKMH) Outcomes in Real-world Settings (DASH-CKMH) (DASH-CKMH)
Complex pathophysiological interactions among obesity, metabolic risk factors, chronic kidney disease (CKD), and the cardiovascular system lead to poor cardiovascular-kidney-metabolic health (CKMH), which is a major determinant of premature morbidity and mortality. Poor CKMH may lead to cardiovascular-kidney-metabolic syndrome (CKMS) - the five-stage framework introduced by The American Heart Association (AHA) which accounts for the critical overlap between cardiorenal syndrome and cardiometabolic disease.
Evidence from randomized controlled trials shows glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose co-transporter-2 inhibitors (SGLT2is) may improve CKMH in individuals with Type 2 Diabetes (T2D) and/ or obesity. However, there is modest evidence suggesting differential effectiveness of GLP-1RA and SGLT2i drugs between males and females. The extent of these sex-based differences is currently unknown. In part, this may be due to underrepresentation of females in clinical trials. Exploring sex-based differences in GLP-1RA and SGLT2i treatment on CKMH outcomes is important to inform CKMS treatment and equity in CKMH.
Robust secondary data sources present the opportunity to elucidate sex heterogeneity in GLP-1RA and SGLT2i treatment on CKMH outcomes. Using a target-trial emulation design, this study aims to observe differences in long-term CKMH outcomes between patients treated by GLP-1RA and SGLT2i medications versus those treated with active comparator medications, and whether there is an observed interaction between sex and treatment.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
A target-trial design will be conducted in three sources of secondary data: 1)Merative Marketscan (claims-based data derived from commercial insurers), 2) All of Us (public database of Electronic Health Record [EHR] and survey data), and 3) LifeScale (EHR- derived from The Ohio State University Wexner Medical Center).
To construct a clinically similar comparator group, we opted for patients treated with active comparator medications with similar indications to the GLP-1RA and SGLT2i intervention medications. The intervention group is defined as patients with any exposure to the intervention medications, and the comparator group is defined as exposure to the comparator medications with no exposure to the intervention medications in the 30 days following index.
To balance baseline characteristics between intervention and comparator groups, for each cohort established in the three secondary data sources we will apply propensity score matching. Matching variables will include the following confounders: index age, U.S. region, race/ethnicity (where available), rurality, insurance type, Charlson comorbidity index score, index year, Medicaid expansion status in state of residence. Match quality will be assessed by examining standardized mean differences (SMDs) of matching variables by treatment and control, with SMD ≤ 10% indicating a well-balanced cohort after matching.
The primary outcome of interest is 3-P MACE (three-point major adverse cardiovascular event), defined as any of the following: nonfatal myocardial infarction, nonfatal stroke, or cardiac-related death. Secondary outcomes include: all-cause mortality, advancing CKMS stage, stroke, myocardial infarction, incident coronary heart disease diagnosis, incident peripheral artery disease diagnosis, atrial fibrillation diagnosis, renal failure, kidney transplant, and kidney dialysis.
Primary and secondary outcomes are time-to-event variables; thus, differences in risk of outcomes between intervention and comparator groups will be tested using survival analysis methods. Kaplan-Meier survival curves will be used to visualize the risk of the outcomes between intervention and comparator up to five years, and Cox modelling will be used to adjust for residual confounding and examine whether differences in risk are significant between intervention and comparator groups. The Cox models will include a variable for treatment (intervention versus comparator), sex, and a sex-treatment interaction term. The analyses will be conducted separately for each of the three secondary data sources. To evaluate our secondary hypothesis of whether the target trial emulation studies in the three data sources are aligned, we will compute 3 binary metrics for each outcome of interest: 1) full statistical significance agreement: treatment effect estimates and 95% confidence intervals (CIs) on the same side of the null, 2) estimate agreement: treatment effect estimates fell within the 95% CI of one another; and 3) standardized difference agreement: standardized differences between treatment effect estimates.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
-
-
Ohio
-
Columbus, Ohio, United States, 43202
- Ohio State University
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Stage 1 or 2 CKMS at baseline
- At least one prescription for an intervention or comparator medication after CKMS diagnosis
- At least 180 days of continuous enrollment prior to the first prescription for any medication of interest (index date)
- Age 18+ at index date
Exclusion Criteria:
- Stage 3 or 4 CKMS at baseline
- Medications of interest during baseline period
- Any history of type I diabetes
- Cancer at baseline
- Renal replacement therapy at baseline
- End stage renal disease at baseline
- Solid organ transplant at baseline
- Missing sex
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Marketscan Cohort
Merative MarketScan Commercial Claims and Encounters and Medicare Supplemental Databases are nationally representative U.S. claims databases of commercially insured patients.
The databases include deidentified inpatient, outpatient, prescription drug, procedure, and enrollment records of beneficiaries, dependents, and retirees covered under a variety of fee-for-service and managed care health plans.
This database includes >250 million privately insured individuals and older individuals enrolled in Medicare with an employer sponsored Medigap plan.
Data from 2012 to 2022 will be used in DASH-CKMS.
|
GLP-1RA and/or SGLT2i adult users with ≥1 prescription for the intervention GLP-1RA or SGLT2i medications (including combination drugs or mixed therapies with comparator medications). GLP-1RAs include: Exenatide, Liraglutide, Semaglutide, Dulaglutide, Lixisenatide, Albiglutide, Tirzepatide. SGLT2is include: Canagliflozin, Dapagliflozin, Bexagliflozin, Empagliflozin, Ertugliflozin, Sotagliflozin. DPP4i or Oral Obesity Agent adult users with ≥1 prescription for the comparator DPP4i or Oral Obesity Agent medications AND no intervention GLP-1RA or SGLT2i prescriptions in first 30 days of follow up. DPP4is include: Alogliptin, Saxagliptin, Linagliptin, Sitagliptin. Oral Obesity Agents include: Orlistat, Naltrexone-bupropion, Phentermine-topiramate, Phentermine, Diethylpropion, Bupropion (off-label), Topiramate (off-label) |
|
All of Us Cohort
All of Us is a unique de-identified dataset administered by the U.S. National Institutes of Health (NIH) containing data from surveys, genomic analyses, electronic health records (EHR), physical measurements, and wearables to study the full range of factors that influence health and disease.
All of Us is committed to recruiting a diverse participant pool that includes groups historically underrepresented in healthcare research.
To date, about 45% of All of Us participants are racial and ethnic minorities, and over 80% are underrepresented in biomedical research overall.
As of December 2024, there are more than 574,000 patient participants in All of Us who completed baseline surveys, provided physical measurements, and donated at least one biospecimen sample, and nearly 850,000 participants who have consented to join the program.
|
GLP-1RA and/or SGLT2i adult users with ≥1 prescription for the intervention GLP-1RA or SGLT2i medications (including combination drugs or mixed therapies with comparator medications). GLP-1RAs include: Exenatide, Liraglutide, Semaglutide, Dulaglutide, Lixisenatide, Albiglutide, Tirzepatide. SGLT2is include: Canagliflozin, Dapagliflozin, Bexagliflozin, Empagliflozin, Ertugliflozin, Sotagliflozin. DPP4i or Oral Obesity Agent adult users with ≥1 prescription for the comparator DPP4i or Oral Obesity Agent medications AND no intervention GLP-1RA or SGLT2i prescriptions in first 30 days of follow up. DPP4is include: Alogliptin, Saxagliptin, Linagliptin, Sitagliptin. Oral Obesity Agents include: Orlistat, Naltrexone-bupropion, Phentermine-topiramate, Phentermine, Diethylpropion, Bupropion (off-label), Topiramate (off-label) |
|
Lifescale Cohort
LifeScale data is an institution-scale clinical data warehouse from the Ohio State University Wexner Medical Center (OSUWMC) and Nationwide Children's Hospital (NCH).
The data is a limited de-identified copy of the OSU/NCH Caboodle clinical data warehouse mediated by an honest broker and governed under a comprehensive Institutional Review Board (IRB) protocol.
|
GLP-1RA and/or SGLT2i adult users with ≥1 prescription for the intervention GLP-1RA or SGLT2i medications (including combination drugs or mixed therapies with comparator medications). GLP-1RAs include: Exenatide, Liraglutide, Semaglutide, Dulaglutide, Lixisenatide, Albiglutide, Tirzepatide. SGLT2is include: Canagliflozin, Dapagliflozin, Bexagliflozin, Empagliflozin, Ertugliflozin, Sotagliflozin. DPP4i or Oral Obesity Agent adult users with ≥1 prescription for the comparator DPP4i or Oral Obesity Agent medications AND no intervention GLP-1RA or SGLT2i prescriptions in first 30 days of follow up. DPP4is include: Alogliptin, Saxagliptin, Linagliptin, Sitagliptin. Oral Obesity Agents include: Orlistat, Naltrexone-bupropion, Phentermine-topiramate, Phentermine, Diethylpropion, Bupropion (off-label), Topiramate (off-label) |
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
3-Point major adverse cardiovascular event (3P-MACE)
Time Frame: Up to 5 years
|
Any of the following events:
|
Up to 5 years
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
All-cause Mortality
Time Frame: Up to 5 years
|
evidence of death from any cause
|
Up to 5 years
|
|
Advancing CKMS stage
Time Frame: Up to 5 Years
|
advancing from the baseline CKMS stage
|
Up to 5 Years
|
|
stroke
Time Frame: up to 5 years
|
up to 5 years
|
|
|
Myocardial Infarction
Time Frame: up to 5 years
|
up to 5 years
|
|
|
Incident coronary heart disease diagnosis
Time Frame: up to 5 years
|
up to 5 years
|
|
|
Incident peripheral artery disease diagnosis
Time Frame: up to 5 years
|
up to 5 years
|
|
|
Atrial fibrillation diagnosis
Time Frame: up to 5 years
|
up to 5 years
|
|
|
renal failure
Time Frame: up to 5 years
|
up to 5 years
|
|
|
kidney transplant
Time Frame: up to 5 years
|
up to 5 years
|
|
|
kidney dialysis
Time Frame: up to 5 years
|
up to 5 years
|
|
|
heart failure
Time Frame: up to 5 years
|
up to 5 years
|
Collaborators and Investigators
Sponsor
Collaborators
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimated)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- STUDY20250372
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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