Cardiometabolic and Renal Outcomes in Semaglutide Users with Type 2 Diabetes Achieving Glycemic and Weight Goals: An Observational Cohort Study

Abstract

Introduction

Within the cardiovascular-kidney-metabolic syndrome (CKM) framework, semaglutide has demonstrated benefits beyond glycemic control and weight loss in clinical trials. However, most real-world studies in type 2 diabetes (T2D) have limited assessment of broader cardiometabolic and renal outcomes. We evaluated CKM-relevant outcomes among individuals with T2D who achieved substantial hemoglobin A1c (HbA1c) and weight improvements after initiating semaglutide in real-world settings.

Methods

This observational pre-post study used Optum’s de-identified Market Clarity Data from January 1, 2007, to June 30, 2024. The primary cohort comprised individuals with T2D who achieved glycemic control (HbA1c < 7%) and weight loss (≥ 5%) goals after semaglutide initiation. We compared baseline (1 year before initiation) with 1st-year and 2nd-year follow-up for cardiometabolic endpoints (3-point and 5-point major adverse cardiovascular events [MACE]), cardiometabolic risk factors, and renal outcomes. Sensitivity analysis was performed in an exploratory cohort of patients in the top tertile of Hb1Ac reduction and weight loss.

Results

We identified 413 patients in the primary cohort (mean age 59.6 years and balanced sex distribution). Significant reductions were observed in low-density lipoprotein cholesterol (LDL-C), very-low-density lipoprotein cholesterol (VLDL-C), total cholesterol, triglycerides, systolic blood pressure, and diastolic blood pressure and high-density lipoprotein cholesterol (HDL-C) increased at both 1 and 2 years after semaglutide initiation (all p < 0.001). Fewer than 1% of patients experienced a ≥ 40% decline in estimated glomerular filtration rate (eGFR) during follow-up. Mean change in urine albumin-to-creatinine ratio (UACR) were − 20.13 mg/g in the 1st year (p < 0.001) and − 54.03 mg/g in the 2nd year (p < 0.001). The event rate of 3-point MACE decreased from 26.82 per 1000 person-years (PY) during baseline to 22.31 per 1000 PY in the 2nd year. The sensitivity analysis showed consistent results.

Conclusion

In this real-world study, semaglutide users who achieved glycemic and weight goals exhibited marked improvements in cardiometabolic and renal outcomes over 2 years.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-026-03610-7.

Key Summary Points

Why carry out this study?

Most real‑world studies of semaglutide in type 2 diabetes (T2D) focus on hemoglobin A1c (HbA1c) and weight, with limited assessment of broader cardiometabolic and renal outcomes relevant to the cardiovascular-kidney-metabolic (CKM) framework.

We asked whether adults with T2D who achieved glycemic control and weight‑loss goals after initiating semaglutide show concurrent improvements in cardiometabolic risk factors, renal measures, and major adverse cardiovascular events (MACE) over two years in real-world settings.

What was learned from the study?

Significant reductions were observed in low-density lipoprotein cholesterol (LDL-C), very-low-density lipoportein cholesterol (VLDL-C), total cholesterol, triglycerides, systolic and diastolic blood pressure at 1 and 2 years (all p < 0.001); urine albumin-to-creatinine ratio (UACR) decreased by −20.13 mg/g (year 1) and −54.03 mg/g (year 2), fewer than 1% experienced a ≥ 40% estimated glomerular filtration rate (eGFR) decline, and 3-point MACE fell from 26.82 to 22.31 per 1000 person-years from baseline to year 2.

Findings were consistent in the exploratory cohort using the top-tertile responder definition, indicating robustness of the observed associations across CKM-relevant domains in routine practice.

These results complement trial evidence and support a CKM-oriented approach to care with glucagon like peptide 1 receptor agonist (GLP-1 RA) therapy.

Introduction

Type 2 diabetes (T2D), cardiovascular disease (CVD), and chronic kidney disease (CKD) frequently coexist with a strong interconnection [1]. A recent concept of combined disease conditions is the Cardiovascular-Kidney-Metabolic Syndrome (CKM) introduced by the American Heart Association [2]. CKM results in multiorgan dysfunction and premature morbidity and mortality. For example, CVD mortality accounts for 43.6% of all deaths among patients with end-stage kidney disease (ESKD) [3]. The literature has established multiple mechanisms involved in CKM, including the interplay among hyperglycemia, insulin resistance, vascular stiffening, toxic lipid metabolites, chronic inflammation, endothelial dysfunction, and hemodynamic changes [1, 4]. The interrelated pathophysiological mechanisms of CKM often originate from excess or dysfunctional adipose tissue, which elevates inflammation, promotes oxidative stress, and contributes to insulin resistance, culminating in multiorgan system damage [5, 6]. These mechanisms and their link to obesity provide a solid foundation for the prevention and management of adverse outcomes associated with CKM. However, there are gaps in understanding the optimal therapeutic approach for the prevention and management of CKM, likely due to the multiple mechanisms behind CKM.

Semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1 RA), acts on the GLP-1 receptor through pathways similar to native GLP-1. In addition to improving glycemic control, GLP-1 RAs exert diverse physiological effects on cardiovascular and renal health by increasing insulin sensitivity in peripheral tissues, improving endothelial function, and reducing inflammation [7–9]. Consistent with these findings, clinical trials have shown that semaglutide provides benefits beyond glycemic control and weight loss, including reductions in major adverse cardiovascular events (MACE) and favorable effects in obesity-related heart failure with preserved ejection fraction, peripheral arterial disease, liver disease, and kidney outcomes [10–15]. The trials suggest that semaglutide may have beneficial effects through multiple mechanisms in CKM. A recent study using clinical trial data on proteomic changes also finds that the effects of semaglutide on lipid metabolism and inflammatory pathways extend beyond weight loss and glucose lowering [16]. Further understanding of GLP-1 RAs, such as semaglutide, on broader cardiometabolic and renal effects would be important, especially in real-world settings. However, evidence for the broader effects of semaglutide is still limited.

To better understand semaglutide’s role in CKM-oriented care in clinical practice, this study aimed to describe changes in cardiometabolic and renal outcomes after semaglutide initiation beyond hemoglobin A1c (HbA1c) and weight in real-world settings. In the context of the interplay of mechanisms of CKM, we explored whether the additional beneficial effects of semaglutide are also observed in cardiometabolic and renal outcomes, even when there are already beneficial effects on glycemic and weight control.

Methods

Study Design

This was an observational cohort study analyzing Optum’s de-identified Market Clarity Data (Optum^® Market Clarity) from January 1, 2007, to June 30, 2024. A pre- and post-index study design was employed (shown in Supplementary Fig. 1). The index date (Day 0) was defined as the new initiation date of once-weekly semaglutide (Ozempic^®, Novo Nordisk A/S, Bagsvaerd, Denmark; hereafter called semaglutide) and was selected between January 1, 2018, and July 1, 2023. The baseline period, encompassing the year prior to the index date (Days [− 365, − 1]), was used to evaluate the pre-index values of outcomes as well as patient characteristics. The follow-up period, during which post-index values were assessed, was defined as the interval between the index date and end of follow-up. Outcomes were assessed at the 1st- and 2nd-year follow-up periods. The end of follow-up was defined as the end of the study, lapse of continuous enrollment, or death, whichever occurred first. Eligible patients were required to have at least a 1-year follow-up period (≥ 365 days).

Data Source

Optum^® Market Clarity is an integrated, multi-source dataset of medical claims, pharmacy claims, and electronic health records. It links electronic health record data, including laboratory results, vital signs and measurements, diagnoses, procedures, and information derived from unstructured clinical notes using natural language processing, with historical, linked administrative claim data, including pharmacy claims, physician claims, clinical information facility claims, and medications prescribed and administered. It is statistically de-identified under the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule’s Expert Determination method and managed in accordance with Optum^® customer data use agreements.

Study Sample

Eligible patients were required to: (1) have a confirmed T2D diagnosis, defined as ≥ 2 claims on distinct days at least 30 days apart in the study period, with ≥ 1 T2D diagnosis at baseline or the index date (Days [– 365, 0]); (2) have ≥ 2 prescriptions of semaglutide, with the index date (Day 0) defined as the first prescription and selected between January 1, 2018, and July 1, 2023; (3) be aged ≥ 18 years on the index date; and (4) have continuous enrollment during the baseline period (Days [− 365, − 1]) and the 1-year follow-up period (Days [0, 364]).

Exclusion criteria were: (1) ≥ 1 prescription for any other GLP-1 RA (except index semaglutide) before or on the index date, (2) any diagnosis of type 1 diabetes during the study period, (3) evidence of pregnancy (including gestational diabetes) during the study period, (4) bariatric surgery or use of anti-obesity medications during the study period, (5) missing age or sex, (6) initiation of another new glucose-lowering therapy (GLT; including fixed-dose combinations) on the index date, and (7) CKD stage 5 including ESKD at baseline.

The primary cohort was defined as those who reached HbA1c and weight goals. Additional inclusion criteria for this cohort were: (1) baseline HbA1c ≥ 9%, defined as the closest value to the index date within Days [− 120, − 1]; (2) HbA1c < 7% during the 1st-year follow-up (Days [0, 364]); and (3) ≥ 5% weight loss before and after the index date, with baseline weight measured within Days [− 120, − 1] (closest to the index date) and follow-up weight as the latest value within Days [0, 119].

We also conducted a sensitivity analysis in an exploratory cohort that was constructed from patients in the top tertiles of both HbA1c reduction and weight loss. Please note that the differences in sample sizes between the main and exploratory cohorts should not be interpreted as evidence of semaglutide's effectiveness in glycemic or weight control. Missing HbA1c and weight data reduce sample sizes in both cohorts, but the impact is greater in the main cohort because it requires complete baseline and follow-up measurements and attainment of specific HbA1c and weight targets, leading to differential exclusion.

Outcomes

Cardiometabolic risk factors included low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), very-low-density lipoprotein cholesterol (VLDL-C), total cholesterol, triglycerides, systolic blood pressure, and diastolic blood pressure. The pre- and post-index changes of these outcomes as continuous variables were assessed. Renal outcomes included changes in estimated glomerular filtration rate (eGFR): continuous and categorical (≥ 40% decline, < 40% decline, increase) [17–23] and changes in urine albumin-to-creatinine ratio (UACR), continuous and categorical (< 30, 30–300, > 300). The valid ranges of clinical measurements are provided in Supplementary Table 1. These outcomes were assessed as the changes in 1st- and 2nd-year follow-up from baseline. If there were multiple baseline values, the one closest to the index date was chosen. For follow-up values, the furthest from the index date and closest to the end of the follow-up period was chosen. During the follow-up periods, a biologically plausible period of 90 days after the index date was used to allow the drug to take effect before recording changes in these outcomes; therefore, only data for these outcomes measured during the follow-up period between Day 89 and the end of the 1st- or 2nd-year follow-up periods were used.

Cardiometabolic endpoint outcomes included the event rates of MACE, which were assessed during baseline, and 1st- and 2nd-year follow-up. MACE included ischemic stroke, myocardial infarction (MI), 3-point MACE (ischemic stroke, MI, or all-cause death), and 5-point MACE (ischemic stroke, MI, all-cause death, hospitalization for heart failure, or hospitalization for unstable angina).

Covariates

Baseline covariates included age, sex, race, ethnicity, geographic region, index year, T2D history, payer type, prescriber’s specialty, Charlson Comorbidity Index (CCI) [24, 25], diabetes complication severity index (DCSI) [26, 27], body mass index (BMI), and number of all distinct prescription drugs. Baseline comorbidities included distinct diagnosis of any of the following (yes, no): hypertension, hyperlipidemia, atrial fibrillation and flutter, deep vein thrombosis or pulmonary embolism, chronic heart failure, dementia, CKD stage, depression, anxiety, smoking, neuropathic pain, atherosclerotic cardiovascular disease (ASCVD), and additional weight or obesity-related conditions. Baseline GLT measures included types of GLT drug classes, number of GLT drug classes, and number of GLTs (by generic names). Baseline non-GLT medication use included antihypertensive agents, antiplatelets, antihyperlipidemic agents, anticoagulants, antidepressants, additional antianginal agents, additional HF drugs, medications associated with weight gain, and medications associated with weight loss. Baseline cardiovascular procedures included percutaneous coronary intervention, coronary artery bypass grafting, percutaneous intervention—carotid, percutaneous intervention—peripheral arteries, and major amputations. In addition to baseline characteristics, semaglutide utilization was measured during follow-up, including the highest dose reached, the proportion of days patients were on their highest dose, adherence, and persistence.

Statistical Analysis

Descriptive analyses were conducted for outcomes and covariates. Counts and frequencies were used for categorical variables; means and standard deviations (SDs) and medians and interquartile ranges (IQRs) were for continuous variables. Comparisons of within-subject changes between baseline and follow-up were evaluated with unadjusted paired t-tests and Wilcoxon signed-rank test for continuous outcomes, and McNemar’s test for categorical outcomes. The main analysis was conducted in the primary cohort, and the exploratory cohort was used for sensitivity analysis.

To assess the potential influence of concomitant medication changes on the observed cardiometabolic and renal outcomes, we assessed key drug class changes during follow-up and conducted a restricted sensitivity analysis with stable background cardiometabolic pharmacotherapy during follow-up. Stable therapy was defined as no initiation or discontinuation of medication classes for lipid-lowering agents, antihypertensive agents, sodium–glucose cotransporter-2 inhibitors (SGLT2is), insulin, or any new GLT during the 1-year follow-up. R (versions 4.3.0 and 4.4.1) was used for the analysis.

Ethics

This study was conducted in accordance with the Declaration of Helsinki. This retrospective analysis used Optum® Market Clarity, a fully de-identified, HIPAA-compliant dataset; under US federal regulations (45 CFR 46), analyses of de-identified data do not constitute human subjects research and do not require review by an Institutional Review Board. No identifiable private information was accessed.

This study analyzed secondary data from the de-identified Optum® Market Clarity without direct subject contact or intervention; per 45 CFR 46, analyses of secondary, de-identified data are not human subjects research and do not require consent.

Results

Primary Cohort

After applying the inclusion and exclusion criteria, we identified 413 patients in the main cohort who achieved HbA1c < 7% within 1 year of semaglutide initiation and ≥ 5% weight loss within 4 months of initiation (shown in Supplementary Fig. 2). The mean age was 56.9 years, and the sex distribution was approximately balanced. Three quarters of patients were white. Patients had a mean T2D duration of 3.42 years. Approximately 88.1% of semaglutide prescriptions were written by primary care providers or endocrinologists. The most common comorbidities were hypertension (74.3%) and hyperlipidemia (74.8%). The vast majority of patients (97.6%) were people living with overweight or obesity. Almost two-thirds (65.3%) of patients reached a ≥ 1 mg dose of semaglutide during follow-up. About 55.4% of semaglutide users were adherent and 41.2% were persistent during follow-up. Key baseline characteristics are presented in Table 1, and the full set of baseline characteristics and semaglutide utilization is reported in Supplementary Table 2.

Table 1.

Key patient baseline characteristics of the primary cohort (N = 413)

	Mean ± SD/N (%)
Demographics
Age at index date (years)
Mean ± SD	56.87 ± 12.08
Age at index date, n (%)
18–44	60 (14.5%)
45–64	247 (59.8%)
65–79	93 (22.5%)
≥ 80	13 (3.1%)
Sex, n (%)
Male	209 (50.6%)
Female	204 (49.4%)
Race, n (%)
Black	53 (12.8%)
Asian	10 (2.4%)
White	312 (75.5%)
Other/unknown	38 (9.2%)
Ethnicity, n (%)
Hispanic	26 (6.3%)
Not Hispanic	318 (77.0%)
Unknown	69 (16.7%)
Geographic region, n (%)
Northeast	89 (21.5%)
South	131 (31.7%)
Midwest	144 (34.9%)
West	34 (8.2%)
Other/unknown	15 (3.6%)
T2D history (years) from the earliest data available
Mean ± SD	3.42 ± 2.55
Payer type, n (%)
Commercial	261 (63.2%)
Medicaid	31 (7.5%)
Medicare	120 (29.1%)
Other/unknown	< 5
Baseline comorbidities, n (%)
CCI adjusted without diabetes
Mean ± SD	0.96 ± 1.42
DCSI
Mean ± SD	1.42 ± 1.77
Baseline medications
GLT during the baseline period
Baseline GLT drug class, n (%)
Insulin	139 (33.7%)
Biguanides (metformin)	330 (79.9%)
SU	116 (28.1%)
Meglitinides	< 5
TZD	15 (3.6%)
Alpha-glucosidase inhibitors	< 5
SGLT2is	69 (16.7%)
DPP-4i	59 (14.3%)
Baseline laboratory values
BMI, n (%)
< 25 or unknown	10 (2.4%)
25–< 30	74 (17.9%)
30–< 35	112 (27.1%)
35–< 40	105 (25.4%)
≥ 40	112 (27.1%)
Semaglutide utilization measured during follow-up
Dosing
Highest dose, n (%)
< 1 mg	143 (34.6%)
1 m	186 (45.0%)
2 mg	84 (20.3%)
Persistence, n (%)
Persistence	170 (41.2%)

BMI body mass index, CCI Charlson Comorbidity Index, DCSI Diabetes Compliations Severity Index, DPP4i dipeptidyl peptidase-4 inhibitors, ER emergency room, GLP1-RA glucagon-like peptide 1 receptor agonists, GLT glucose lowering therapy, SD standard deviation, SGLT2i sodium-glucose co-transporter-2 inhibitors, SU sulfonylureas, T2D type 2 diabetes, TZD thiazolidinediones

For cardiometabolic risk factors, we observed significant reductions in LDL-C, VLDL-C, total cholesterol, triglycerides, systolic blood pressure, and diastolic blood pressure after both 1 and 2 years following semaglutide initiation (all p < 0.001; Table 2). In the 1st year, mean reductions were 16.62 mg/dl for LDL-C, 11.99 mg/dl for VLDL-C, 27.51 mg/dl for total cholesterol, and 94.03 mg/dl for triglycerides. Systolic and diastolic blood pressure decreased by 2.44 mmHg and 5.62 mmHg, respectively, in the 1st year. All these 1st-year changes persisted in the 2nd year (Table 2). In addition, HDL-C increased by 3.47 mg/dl and 5.09 mg/dl in the 1st and 2nd years, respectively (both p < 0.001).

Table 2.

Cardiometabolic risk factor changes after semaglutide initiation among individuals with type 2 diabetes who achieved glycemic and weight goals

Cardiovascular risk factors	Baseline	Changes between baseline and 1st-year follow-up period	Baseline	Changes between baseline and 2nd-year follow-up period
Low-density lipoprotein cholesterol (LDL-C)
n (%)		269 (64.8%)		190 (45.8%)
Mean ± SD	94.37 (36.89)	− 16.62 (35.8)	91.04 (35.48)	− 14.08 (38.6)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	90.0 (49.0)	− 12.0 (37.0)	86.5 (48.3)	− 13.0 (43.8)
High density lipoprotein cholesterol (HDL-C)
n (%)		272 (65.5%)		192 (46.3%)
Mean ± SD	41.87 (10.8)	3.47 (9.3)	41.11 (10.61)	5.09 (9.8)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	40.0 (12.0)	3.0 (11.0)	39.0 (12.0)	4.0 (9.0)
Very-low-density lipoprotein cholesterol (VLDL-C)
n (%)		79 (19.0%)		57 (13.7%)
Mean ± SD	36.9 (17.34)	− 11.99 (17.6)	35.95 (18.71)	− 11.28 (17.3)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	32.0 (19.5)	− 9.0 (19.0)	30.0 (21.0)	− 8.00 (− 15.0)
Total cholesterol
n (%)		272 (65.5%)		191 (46.0%)
Mean ± SD	176.82 (48.13)	− 27.51 (45.4)	173.99 (48.08)	− 23.21 (47.9)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	171.0 (58.3)	− 19.50 (50.0)	168.0 (51.5)	− 19.0 (47.0)
Triglycerides
n (%)		273 (65.8%)		189 (45.5%)
Mean ± SD	229.48 (220.48)	− 94.03 (210.5)	230.44 (191.64)	− 91.09 (163.5)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	172.0 (132.0)	− 48.0 (115.0)	183.0 (143.0)	− 56.0 (119.0)
Systolic blood pressure
n (%)		410 (98.8%)		306 (73.7%)
Mean ± SD	130.66 (15.33)	− 2.44 (11.4)	130.33 (14.87)	-4.51 (18.0)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	130.0 (20.0)	− 2.0 (14.4)	130.0 (20.0)	− 4.0 (22.9)
Diastolic blood pressure
n (%)		410 (98.8%)		306 (73.7%)
Mean ± SD	78.79 (10.2)	− 5.62 (17.9)	78.46 (10.16)	− 2.33 (11.2)
P valuea	–	< 0.001	–	< 0.001
Median (IQR)	80.0 (14.8)	− 5.0 (21.8)	79.0 (14.0)	− 2.0 (13.0)

SD standard deviation, IQR interquartile range

^aP-values were assessed using paired Wilcoxon signed-rank tests

For renal outcomes, mean changes in eGFR were 0.17 ml/min/1.73 m² in the 1st year (p = 0.87) and − 0.55 ml/min/1.73 m² in the 2nd year (p = 0.35) (Table 3; Supplementary Fig. 3a). Fewer than 1% of patients experienced a ≥ 40% decline in eGFR in both year 1 and year 2 of follow-up (Fig. 1a). Mean changes in UACR were − 20.13 mg/g in the 1st year (p < 0.001) and − 54.03 mg/g in the 2nd year (p < 0.001) (Table 3; Supplementary Fig. 3b). The proportion of patients with UACR < 30 mg/g increased from 54.6% at baseline to 63.3% in the 1st year and 67.3% in the 2nd year (Fig. 1b).

Table 3.

Renal outcome changes after semaglutide initiation among individuals with type 2 diabetes who achieved glycemic and weight goals

Renal outcomes	Baseline	1st year	Baseline	2nd year
Estimated glomerular filtration rate (eGFR)		Changes from baseline		Changes from baseline
N (%)	331 (80.1)	331 (80.1)	331 (80.1)	240 (58.1)
Mean ± SD	76.19 (20.02)	0.17 (14.58)	76.19 (20.02)	− 0.55 (15.78)
P-valuea	–	0.9	–	0.4
Median (IQR)	76.0 (30)	0.0 (12.7)	76.0 (30.0)	0.0 [16.9]
Urine albumin-to-creatinine ratio (UACR)		Changes from baseline		Changes from baseline
N (%)	112 (27.1)	112 (27.1)	95 (23.0)	95 (23.0)
Mean ± SD	99.24 (343.32)	− 20.13 (218.76)	168.62 (578.11)	− 54.03 (531.96)
P-valuea	–	< 0.001	–	< 0.001
Median (IQR)	21.0 (74.0)	− 9.0 (33.9)	22.0 (57.6)	− 5.1 (48.2)

SD standard deviation, IQR interquartile range

^aP-values were assessed using paired Wilcoxon signed-rank test

Fig. 1.

Renal outcome changes after semaglutide initiation among individuals with type 2 diabetes who achieved gylcemic and weight goals. eGFR estimated glomerular filtration rate, UACR urine albumin-to-creatinine ratio, SD standard deviation

All MACE event rates assessed were lower in the 2nd year after semaglutide initiation than during the baseline period prior to initiation (Table 4). For example, the event rate of ischemic stroke decreased from 12.15 per 1000 person-years (PY) during baseline to 3.17 per 1000 PY in the 2nd year. The event rate of 3-point MACE decreased from 26.82 per 1000 PY during baseline to 22.31 per 1000 PY in the 2nd year.

Table 4.

Changes in event rates of major adverse cardiovascular events (MACEs) after semaglutide initiation among individuals with type 2 diabetes who achieved glycemic and weight goals (N = 413)

MACE (per 1000 PY)	Baseline	1st-year follow-up period	2nd-year follow-up period
Ischemic stroke	12.2	0.0	3.2
Myocardial infarction (MI)	14.6	12.2	6.4
3-point MACE: ischemic stroke MI or all-cause death	26.8	12.2	22.3
5-point MACE: ischemic stroke, MI, all-cause death, hospitalization for heart failure, or hospitalization for unstable angina	41.8	24.6	28.7

By design, the MACE events during baseline and the 1st-year follow-up period did not include death, but the 2nd-year follow-up period did include death

A sensitivity analysis restricted to semaglutide users in the primary cohort who received stable treatment with cardiometabolic therapies during follow-up (1st year: n = 234; 2nd year: n = 130) demonstrated a similar association between semaglutide and improvements in cardiometabolic and renal outcomes over 2 years (Supplementary Tables 3–6). The results were largely consistent with the primary analysis, with the exception of a numerical increase in 3-point MACE and a lack of changes in systolic and diastolic blood pressure at the 2-year follow-up among people who received stable treatment with cardiometabolic therapies and had already achieved glycemic and weight loss goals.

Exploratory Cohort

For the exploratory cohort, we identified 1177 patients who were in the top tertiles for both HbA1c reduction and weight loss after semaglutide initiation (shown in Supplementary Fig. 2). Overall, baseline characteristics were similar to the main cohort (shown in Supplementary Table 7). The mean age was 57.7 years. Most patients were women (54.1%) and white (76.6%). The mean detectable T2D duration was 3.80 years. At baseline, there were higher percentages of patients using antihypertensive agents, antihyperlipidemic agents, and SGLT2is than in the main cohort.

Cardiometabolic risk factor changes in the exploratory cohort mirrored those in the main cohort. Significant reductions were observed in LDL-C, VLDL-C, total cholesterol, triglycerides, systolic blood pressure, and diastolic blood pressure after both the 1st- and 2nd-year follow-ups after semaglutide initiation, while HDL-C increased significantly (all p < 0.001; Supplementary Table 8).

For renal outcomes in the exploratory cohort, mean change in eGFR was – 0.98 ml/min/1.73 m² in the 1st year (p = 0.010) and − 1.16 ml/min/1.73 m² in the 2nd year (p = 0.008; Supplementary Table 9). Fewer than 2% of patients experienced a ≥ 40% decline in eGFR in both year 1 and year 2 of follow-up (Supplementary Fig. 4). The proportion of patients with UACR < 30 mg/g increased from 53.6% at baseline to 63.5% in the 1st year and 64.8% in the 2nd year (shown in Supplementary Fig. 4), while the proportion with UACR > 300 mg/g decreased from 6.5% at baseline to 4.1% in the 1st year and 5.5% in the 2nd year (shown in Supplementary Fig. 4).

We observed consistent trends in all the MACE event rates assessed as in the primary cohort. The MACE event rates were lower in the 2nd year after semaglutide initiation than during baseline (Supplementary Table 10).

Discussion

Among semaglutide users with T2D who achieved HbA1c and weight loss goals, this real-world analysis observed an association between semaglutide use and subsequent improvements across multiple CKM domains, including significant reductions in atherogenic lipids and blood pressure, meaningful decreases in UACR with largely stable eGFR, and lower MACE rates. More importantly, the results may suggest that there may be bundled, continued, and broader cardiometabolic and renal benefits of semaglutide among those who have already achieved glycemic and weight goals.

Bundled benefits in cardiometabolic and renal conditions have important implications for the question of optimal therapy for CKM. The multiple mechanisms of CKM and their interplay suggest that a therapy only targeting a single mechanism would not be ideal. Nevertheless, a therapy that may have broad effects across multiple mechanisms could be optimal for the management of CKM and the prevention of its adverse outcomes. Clinical trials have separately demonstrated semaglutide’s benefits across the spectrum of CKM. The findings from many trials are largely consistent with those observed in this study.

In the SUSTAIN-6 clinical trial, once-weekly semaglutide at 0.5 mg and 1 mg was shown to reduce the risk of a composite of cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke by 26% (hazard risk 0.74, 95% CI 0.58–0.95, p < 0.001) among patients with T2D and CVD, CKD, or both in 104 weeks while significantly reducing weight and HbA1c [11]. Our study showed MACE outcomes consistent with those in the SUSTAIN-6 trial. The mean systolic blood pressure was reduced by 3.4 mmHg at a dose of 0.5 mg and 5.4 mmHg at 1 mg in SUSTAIN-6. The systolic blood pressure reduction observed in this study was largely consistent, ranging between – 2.4 mmHg and – 4.6 mmHg in 1 to 2 years of follow-up. The SOUL trial also demonstrated that oral semaglutide reduced the risk of adverse cardiovascular events among patients with T2D, ASCVD, and/or CKD over a mean of 47.5 months of follow-up [15]. In the SOUL study, significant improvements in HbA1c, systolic blood pressure, weight, and high-sensitivity C-reactive protein were also found. The SELECT clinical trial reported that semaglutide also significantly reduced the CVD outcomes among patients with preexisting CVD and those with obesity and no T2D [10].

The FLOW trial showed that semaglutide reduced the risk of onset of kidney failure, ≥ 50% eGFR reduction, and CKD- or CVD-related mortality with a median follow-up of 3.4 years among individuals with T2D and CKD [7]. In the FLOW trial, semaglutide was found to reduce the risk of major adverse kidney events and ≥ 50% reduction in eGFR by 24% and 27%, respectively [28]. Our study found that semaglutide significantly improved UACR, and < 1% of patients had eGFR decline ≥ 40% among individuals with T2D without CKD stage 5. The absence of a significant eGFR change in our cohort likely reflects lower baseline kidney risk and the shorter observation period: baseline eGFR was ~ 76 ml/min/1.73 m² versus ~ 47 ml/min/1.73 m² in FLOW, and our follow-up was 1 or 2 years versus a median 3.4 years in FLOW, which may be insufficient to detect meaningful eGFR differences in earlier-stage T2D. Nonetheless, we observed consistent reductions in UACR, while eGFR remained largely stable over time.

Beyond effects demonstrated in type 2 diabetes populations, semaglutide has shown clinically relevant benefits across other CKM domains (for example, in obesity-related cardiovascular and liver trials), supporting the CKM conceptual framework and the possibility of multiorgan effects. In the pooled analysis of the STEP-HFpEF and STEP-HFpEF DM trials, semaglutide was found to significantly improve heart-failure-related symptoms over 52 weeks [13]. Improvement in systolic blood pressure (– 4.6 mmHg) and C-reactive protein was also shown. The STRIDE trial also showed that semaglutide led to a greater estimated median ratio to baseline in maximum walking distance at week 52 than the placebo among people with symptomatic peripheral artery disease and T2D [14]. The recent ESSENCE trial showed the benefit of semaglutide in liver fibrosis and metabolic dysfunction-associated steatohepatitis [29].

Nonetheless, most clinical trials of semaglutide have examined separate CKM mechanisms across different patient populations. While the cumulated evidence from these trials suggests semaglutide is associated with diverse, interrelated improvements in cardiometabolic and renal outcomes, further research is needed to directly establish a causal link between semaglutide and long-term, bundled CKM-related health benefits. The unique strength of the current study is the observation of improvements in cardiovascular and renal outcomes among semaglutide users after already achieving significant improvements in glycemic and weight control, which may suggest a bundled benefit of semaglutide across CKM-relevant domains. These findings align with literature proposing multiple pathways through which semaglutide may act, mitigating vascular stiffening, adverse lipid profiles, inflammation, and endothelial dysfunction, alongside effects on glycemic control, insulin resistance, and weight loss [1, 4]. Furthermore, these bundled benefits were observed in real-world settings and are relevant to clinical practice. A recent large US electronic health record study similarly reported reductions in LDL, total cholesterol, triglycerides, and systolic blood pressure with concurrent improvements in HbA1c and body weight among individuals with T2D and ASCVD [30]. Together, these results help address an evidence gap in CKM-oriented care by characterizing multiorgan effects in real-world semaglutide users and supporting the clinical relevance of GLP-1 RA-centered strategies for integrated CKM risk reduction.

We also evaluated alternative definitions by replicating the same analyses in a cohort comprising patients in the top tertiles of both HbA1c reduction and weight loss after semaglutide initiation. Results were largely consistent between the primary cohort (goal-based: HbA1c < 7% and ≥ 5% weight loss) and the exploratory cohort (top tertiles for both HbA1c reduction and weight loss), despite the exploratory cohort having more comorbidities and higher baseline risk. These concordant findings support the robustness of associations across cardiovascular and renal outcomes among semaglutide responders. Emerging data suggest that semaglutide’s benefits regarding cardiometabolic and renal outcomes may be independent of—or only minimally mediated by—glycemic control and weight loss; however, further research is warranted [31–34]. In this study, the observed benefits were seen among semaglutide users who achieved HbA1c and weight-loss goals, suggesting continued CKM benefit even among those who meet initial T2D treatment targets.

Additionally, therapeutic inertia has been identified for GLP-1 RA among patients with T2D and high risk in clinical practice [30, 35]. In developing the CKM management framework, it is also important to identify and develop strategies to address therapeutic inertia for the use of evidence-based therapies for optimal care. No therapy is optimal if it is not used. Significant mortality, morbidities, and burden of CKM with multiorgan involvement have been shown to be very costly in terms of human life and healthcare [36, 37]. Patient access to therapy, even after meeting T2D treatment goals for glycemic control and weight loss, remains imperative to ensure continued treatment of other CKM outcomes.

This study has several limitations. First, due to the nature of the observational, single-arm, pre- and post-index study design, we are unable to reach any conclusions around causality, including but not limited to limitations on temporal relationships and confounding bias. Future research using time-varying causal methods (for example, marginal structural models or inverse-probability weighting), together with more complete, temporally resolved covariate data and/or an active-comparator design, is warranted. Second, as this is an exploratory analysis, we do not have a sufficiently large sample size for some of the outcomes, limiting our ability to detect significant differences. Third, while the primary cohort had a well-balanced sex distribution, investigating the potential impact of sex on broader CKM-related benefits of semaglutide treatment may be a promising avenue for future research. Fourth, the generalizability of these findings may be limited to the health plans covered in the database analyzed. Additionally, several landmark trials used different populations and higher semaglutide doses (e.g., 2.4 mg in STEP). Our study reports real-world outcomes in a responder-defined T2D cohort treated at variable doses including lower doses; therefore, cross-population or cross-dose extrapolation should be made cautiously, and our results do not establish or imply efficacy in non-diabetic populations or at other doses. Fifth, some inclusion criteria may introduce selection and survivor bias; this may result in preferential inclusion of individuals who may be healthier or more adherent, or who can better manage their health or receive better care, for example, due to requiring both baseline and follow-up HbA1c and weight measurements, as well as requiring continuous enrollment and at least 1 year of follow-up. Sixth, some outcomes and variables may have measurement errors, such as misclassification of billing codes or underreporting by using codes. Seventh, the low number of ≥ 40% eGFR-decline events in our study likely reflects the cohort’s relatively preserved baseline eGFR and the relatively short follow-up. Therefore, this binary outcome, although recommended by guidelines and regulatory bodies [17–19], should be interpreted cautiously and considered alongside our primary renal outcomes of continuous eGFR and UACR changes, which better capture subtle shifts in renal risk over the examined follow-up period. Lastly, it is important to exercise caution when directly comparing detailed results between the main and exploratory cohorts, as well as between the 1st- and 2nd-year follow-up periods, because sample sizes differed due to varying inclusion/exclusion criteria and data availability.

Conclusions

In this real-world study, we observed an association between semaglutide and marked improvements in cardiometabolic and renal outcomes over 2 years among semaglutide users who had already achieved their glycemic and weight loss goals. These findings are consistent with results observed with semaglutide across randomized controlled trials, and the real-world evidence presented here further complements and reinforces that body of evidence.

Supplementary Information

Below is the link to the electronic supplementary material.

Author Contributions

Conceptualization: Xi Tan, Yuanjie Liang, Caroline Swift, Chalak Muhammad, Adam de Havenon; Methodology: Xi Tan, Yuanjie Liang; Formal analysis and investigation: Wan-Lun Tsai, Xi Tan; Writing—original draft preparation: Xi Tan, Gang Fang; Writing—review and editing: All authors; Approval of final manuscript: All authors.

Funding

The study, Rapid Service and Open Access fees, and medical writing assistance were funded by Novo Nordisk Inc, Plainsboro, NJ, USA.

Data Availability

The datasets generated during and/or analyzed during the current study are not publicly available because the database is commercially available and restrictions apply to the availability of these data, which were used under license for this study. Access to Optum^® Market Clarity can be requested directly from the data vendor (Optum). No additional data are available from the authors.

Declarations

Conflict of Interest

Xi Tan, Yuanjie Liang, Caroline Swift, Gang Fang, and Chalak Muhammad are employees of Novo Nordisk Inc. Wan-Lun Tsai was a contractor for Novo Nordisk Inc. at the time of the study. Adam de Havenon reports research funding from NIH/NINDS and the AAN, consulting for Novo Nordisk Inc., royalites from UptoDate, and equity in TitinKM and Certus.

Ethical Approval

This study was conducted in accordance with the Declaration of Helsinki. This retrospective analysis used Optum^® Market Clarity, a fully de-identified, HIPAA-compliant dataset; under US federal regulations (45 CFR 46), analyses of de-identified data do not constitute human subjects research and do not require review by an Institutional Review Board. No identifiable private information was accessed. This study analyzed secondary data from the de-identified Optum® Market Clarity without direct subject contact or intervention; per 45 CFR 46, analyses of secondary, de-identified data are not human subjects research and do not require consent.