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)

September 16, 2025 updated by: Daniel Walker, Ohio State University

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

Active, not recruiting

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

Observational

Enrollment (Estimated)

23280000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Ohio
      • Columbus, Ohio, United States, 43202
        • Ohio State University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

The data for this study comes from claims and electronic health records data sources. MarketScan and All of Us are nationally representative databases, and therefore contain patients from all over the US. LifeScale is a local database from The Ohio State University Wexner Medical Center (OSUWMC) and contains patients who seek care at OSUWMC inpatient and outpatient facilities. Adult patients included in the study have evidence of CKMS stage 1 or 2, ≥1 prescription for a GLP-1RA, SGLT2i, DPP4i, or obesity medication, and at least 180 days of continuous database enrollment prior to the first prescription for any medication of interest. Patients will be excluded if they have evidence of stage 3 or 4 CKMS, cancer, renal replacement therapy, end stage renal disease, or solid organ transplant during the baseline period (180 days prior to index date), any history of type I diabetes, or missing sex information. These study criteria will be applied to each of the sources of secondary data to co

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

This section provides details of the study plan, including how the study is designed and what the study is measuring.

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:

  • Nonfatal myocardial infarction
  • Nonfatal stroke
  • Death within 14 days of myocardial infarction, ischemic stroke, heart failure, acute coronary syndrome, coronary artery bypass grafting, or percutaneous coronary intervention
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

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 15, 2025

Primary Completion (Estimated)

June 30, 2029

Study Completion (Estimated)

June 30, 2029

Study Registration Dates

First Submitted

September 16, 2025

First Submitted That Met QC Criteria

September 16, 2025

First Posted (Estimated)

September 23, 2025

Study Record Updates

Last Update Posted (Estimated)

September 23, 2025

Last Update Submitted That Met QC Criteria

September 16, 2025

Last Verified

September 1, 2025

More Information

Terms related to this study

Other Study ID Numbers

  • STUDY20250372

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

Yes

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

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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