Graphical abstract
Keywords: Chronic Renal insufficiency, Chronic kidney disease, Diabetes Mellitus Type 2, Drug utilization, Non-steroidal mineralocorticoid receptor antagonist, FOUNTAIN
Highlights
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Finerenone was mostly used as a complementary therapy in patients with CKD and T2D.
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Most patients had moderate kidney impairment and multiple cardiovascular conditions.
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Over half of patients remained on finerenone one year after starting treatment.
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Real-world use aligned with clinical guidelines and regulatory labelling.
Abstract
Background
Finerenone, a nonsteroidal mineralocorticoid receptor antagonist, improves renal and cardiovascular outcomes in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D). However, evidence on its use in clinical practice remains limited. Within the FOUNTAIN platform (NCT05526157; EUPAS48148), this study aimed to characterize the profiles and treatment patterns of patients initiating finerenone in the United States following its regulatory approval in 2021.
Methods
This observational study used Optum’s de-identified Clinformatics® Data Mart Database to identify adults with T2D and CKD who initiated finerenone between July 2021 and September 2023. Baseline demographic and clinical characteristics (e.g., estimated glomerular filtration rate, urine albumin-to-creatine ratio [uACR]) were assessed, and treatment utilization patterns were described.
Results
Among 3,591 new finerenone users, mean age was 72.2 years and 47.5% were female. Most (62.4%) had stage 3 CKD, and of those with recorded uACR, 86.5% had moderate/severe albuminuria (≥30 mg/g). Renin-angiotensin-aldosterone system inhibitors (RAASi; 80.0%), sodium-glucose cotransporter 2 inhibitors (SGLT2i; 41.4%), and glucagon-like peptide-1 receptor agonists (GLP-1 RA; 30.2%) usage was common in the 90 days preceding finerenone initiation. Finerenone was typically initiated as an add-on to RAASi (58.5%), SGLT2i (28.0%), or GLP-1 RA (21.1%); monotherapy usage was infrequent (8.5%). Among those with ≥ 12 months’ follow-up, 56.0% remained on finerenone at 12 months and 16.7% had titrated from 10 mg to 20 mg.
Conclusions
Finerenone was primarily prescribed as a pillar of therapy that is used in combination with complementary medications in patients with T2D and CKD, aligning with clinical guidelines and regulatory labeling.
Introduction
Chronic kidney disease (CKD) is a progressive complication of type 2 diabetes (T2D) and a growing global health burden. [1] The worldwide prevalence of T2D is projected to reach 1.27 billion by 2050, [2] and ∼ 30% to 40% of people with T2D are expected to develop CKD. [3], [4] Individuals with both T2D and CKD face substantially increased morbidity, mortality, and cardiovascular risk. Although diabetes-attributed CKD accounts for up to 50% of kidney failure cases in developed countries, [5], [6] most patients die from cardiovascular complications before reaching end-stage renal disease. [7] CKD management in T2D focuses on slowing progression of kidney dysfunction and reducing cardiovascular risk through control of glycemia, dyslipidemia, and blood pressure. [8], [9] Although renin-angiotensin-aldosterone system inhibitors (RAASi; i.e., angiotensin-converting enzyme inhibitor(s) [ACEi], angiotensin receptor blockers [ARB]) are established cardiorenal protective medications for CKD and T2D, residual risk of disease progression and cardiovascular events is high even in optimally managed patients [10].
The 2022 Kidney Disease: Improving Global Outcomes (KDIGO) guidelines recommend using newer drug classes, such as sodium-glucose cotransporter 2 inhibitors (SGLT2i), glucagon-like peptide-1 receptor antagonists (GLP-1 RA), and nonsteroidal mineralocorticoid receptor antagonists (ns-MRAs), alongside RAASi to improve outcomes in patients with CKD and T2D. [8] Finerenone, the most extensively studied ns-MRA, has shown efficacy in preventing kidney function deterioration and adverse cardiovascular events in patients with CKD and T2D. [11], [12], [13] Approved by the United States (US) Food and Drug Administration in 2021, [14] finerenone is recommended as add-on therapy under 2024 KDIGO guidelines for patients with T2D, an estimated glomerular filtration rate [eGFR] ≥ 25 mL/min/1.73 m2, normal serum potassium concentration, and persistent albuminuria despite maximally tolerated RAASi therapy. [15] However, real-world data assessing how finerenone is prescribed in clinical practice and whether such use aligns with current guidelines and regulatory labeling remain limited [16], [17], [18].
In the rapidly evolving CKD and T2D treatment landscape, it is important to better understand patient characteristics and utilization patterns of cardioprotective and renoprotective medications. Performed as part of the FOUNTAIN (FinerenOne mUlti-database NeTwork for evidence generAtIoN) platform, [19] this study aimed to describe baseline characteristics, comorbidities, and comedications in adults with CKD and T2D who initiated finerenone and to characterize early treatment utilization patterns following approval in the US.
Methods
Study design
This observational study used data from Optum’s de-identified Clinformatics® Data Mart Database (Optum® CDM), an administrative health claims database for members of large commercial and Medicare Advantage health plans, to describe the clinical profiles and treatment utilization patterns of patients initiating finerenone after US approval (9 July 2021 through 30 September 2023).
Study population
Eligible patients were adults (aged ≥ 18 years) with CKD and T2D and ≥ 12 months of continuous enrollment in Optum® CDM prior to index date, defined as the earliest recorded finerenone prescription. For the primary analysis cohort, patients were excluded if they had type 1 diabetes, kidney cancer, or kidney failure (eGFR < 15 mL/min/1.73 m2 at 2 measurements 90–540 days apart, CKD stage 5, maintenance dialysis, and/or kidney transplant) on or before the index date. Patients were followed from the day after index until the first occurrence of study end, database disenrollment, or development of kidney failure/cancer, or death (Fig. S1). A “wide finerenone cohort” that included all patients prescribed finerenone (i.e., a diagnosis of CKD or T2D was not required, exclusion criteria were not applied, inclusion criteria were relaxed, and the development of kidney failure or kidney cancer was not considered a censoring criterion) was additionally assessed in a sensitivity analysis.
Variables
Demographic and clinical characteristics
Available demographic and lifestyle information at index included age, sex, race, obesity status, and smoking status. Baseline clinical characteristics included markers of T2D severity (hemoglobin A1c [HbA1c], Diabetes Complications Severity Index), kidney function (diagnosis codes, eGFR), use of medications other than glucose-lowering drugs (GLDs), and comorbidities. CKD was defined by ≥ 1 diagnostic code (stages 2–4 or unspecified) or 2 measurements of eGFR 15–60 mL/min/1.73 m2 or urine albumin-to-creatinine ratio (uACR) ≥ 30 mg/g measured 90–540 days apart. In the absence of eGFR, uACR, and stage-specific or stage unspecified diagnosis codes, patients were classified as CKD stage unspecified. Hyperkalemia was defined by an inpatient diagnostic code or serum potassium level > 5.5 mmol/L within 365 days before or on index. Type 1 diabetes was defined by ≥ 2 diagnostic codes; T2D required ≥ 1.
Exposures
Exposures to finerenone and other relevant medication classes (i.e., other medications of interest [ACEi, ARB, SGLT2i, GLP-1 RA, or steroidal MRA]) were determined from prescription claims, identified by National Drug Codes. Indication data were unavailable. Current use was defined as the day after the index to the end of presumed supply for consecutive prescriptions plus a 30-day grace period. Discontinuation was defined as the day after current use ended. Treatment initiation categories were monotherapy (only finerenone), combination therapy (simultaneous initiation of finerenone with another drug of interest), add-on therapy (finerenone added to another drug of interest), and switched-to therapy (existing drug of interest replaced by finerenone). Treatment utilization outcomes, including discontinuations, treatment switches, or add-ons, were assessed at 90 days, 180 days, 270 days, and 1 year post-index.
Statistical analysis
Analyses were descriptive and programmed in SAS v9.4 or higher (SAS Institute, Inc.). Categorical variables were summarized using counts and proportions; continuous variables were reported using means, standard deviations (SDs), medians, 25th/75th percentiles, and 1st/99th percentiles, as appropriate. Patient treatment status was assessed at 90 days, 180 days, 270 days, and 1 year post-index and classified as: (1) treated with finerenone; (2) untreated with finerenone; (3) death; and (4) lost to follow-up, study end, or censored. Therapy persistence was defined as continuous use of finerenone without a treatment gap > 90 days. Dose titration was assessed over the 1 year follow-up and included up-titration (increase from initial dose) and down-titration (reduction from initial dose), based on prescription records.
Results
After applying inclusion and exclusion criteria (Table S1), the final analysis included 3,591 new finerenone users with T2D and CKD in the primary analysis cohort and 5,201 in the wide finerenone sensitivity analysis cohort (Table S2). As demographic and clinical characteristics were similar between cohorts, results hereafter describe the primary cohort (full details provided in Supplementary Material).
Demographic and clinical characteristics
There was a steady increase in new users of finerenone from 2021 to 2023, with most patients entering in 2023 (55.7%), despite only 9 months of available data due to study end (Table 1). At baseline, the study population had a mean age of 72.2 years (SD, 8.7) and was 47.5% female and 46.4% White; 49.0% had obesity and 19.5% were current smokers. The most observed cardiovascular comorbidities included hypertension (96.7%) and hypercholesterolemia (91.1%); other commonly observed macrovascular and cardiovascular comorbidities or risk factors included coronary heart disease (37.0%), peripheral vascular disease (34.7%), congestive heart failure (25.3%), chronic obstructive pulmonary disease (18.5%), and cerebrovascular disease (15.2%). Excluding GLDs, the most frequently prescribed medications in the 180 days before and including index were statins (84.5%), RAASi (ARB, 69.7%; ACEi, 28.9%), and beta-blockers (59.6%). Other commonly prescribed agents included calcium channel blockers (47.9%), thiazide-like diuretics (28.5%), loop diuretics (27.6%), and lipid-lowering drugs other than statins (23.3%).
Table 1.
Selected Baseline Characteristics of New Finerenone Users.
| Characteristic | Primary analysis cohort (n = 3,591) |
|---|---|
| Demographic and lifestyle characteristics | |
| Age at index date, years | |
| Mean (SD) | 72.2 (8.7) |
| Female sex, n (%) | 1,706 (47.5) |
| Race, n (%) | |
| Asian | 258 (7.2) |
| Black | 784 (21.8) |
| Hispanic | 597 (16.6) |
| White | 1,667 (46.4) |
| Other/unknown | 285 (7.9) |
| Calendar year of index date, n (%) | |
| 2021a | 101 (2.8) |
| 2022 | 1,489 (41.5) |
| 2023b | 2,001 (55.7) |
| Obesity, yes (by diagnosis), n (%) | 1,759 (49.0) |
| Current smoker, yes, n (%) | 700 (19.5) |
| Comorbidities | |
| Time from first recorded CKD code at index date, years | |
| Mean (SD) | 5.0 (3.6) |
| CKD stage based on eGFR or diagnosis codec, n (%) | |
| Stage 1 | 105 (2.9) |
| Stage 2 | 472 (13.1) |
| Stage 3 | 2,242 (62.4) |
| Stage 3a | 823 (22.9) |
| Stage 3b | 927 (25.8) |
| Stage 3 without specification of substage | 492 (13.7) |
| Stage 4 | 401 (11.2) |
| Stage 5 | 7 (0.2) |
| Unspecified stage | 244 (6.8) |
| Missing stage | 120 (3.3) |
| CKD stage based on uACR, n (%) | |
| A1 | 155 (4.3) |
| A2 | 455 (12.7) |
| A3 | 544 (15.1) |
| Missing stage | 2,437 (67.9) |
| Hospitalizations for acute kidney injury in the previous year | |
| Patients, n (%) | 42 (1.2) |
| Mean (SD) | 1.0 (0.2) |
| Median (1st, 99th percentiles) | 1 (1, 2) |
| Time from first recorded T2D code at index date, years | |
| Mean (SD) | 6.1 (4.2) |
| HbA1c, n (%) | |
| HbA1c ≤ 53 mmol/mol or ≤ 7% | 1,094 (30.5) |
| HbA1c > 53 mmol/mol to ≤ 63.9 mmol/mol or > 7% to ≤ 8% | 494 (13.8) |
| HbA1c > 63.9 mmol/mol to ≤ 74.9 mmol/mol or > 8% to ≤ 9% | 212 (5.9) |
| HbA1c > 74.9 mmol/mol or > 9% | 180 (5.0) |
| HbA1c missing | 1,611 (44.9) |
| Diabetes Complications Severity Index score | |
| Mean (SD) | 3.4 (2.2) |
| Insulin use, n (%)d | 1,472 (41.0) |
| Coronary heart disease, n (%) | 1,330 (37.0) |
| Cerebrovascular disease, n (%) | 546 (15.2) |
| Peripheral vascular disease, n (%) | 1,246 (34.7) |
| Hypertension, n (%) | 3,473 (96.7) |
| Hypercholesterolemia, n (%) | 3,272 (91.1) |
| Congestive heart failure, n (%) | 907 (25.3) |
| Severe liver disease, n (%) | 19 (0.5) |
| Chronic obstructive pulmonary disease, n (%) | 666 (18.5) |
| Malignancy (other than kidney cancer and nonmelanoma skin cancers), n (%) | 521 (14.5) |
| Retinopathy, n (%) | 1,169 (32.6) |
| Nephropathy, n (%) | 2,095 (58.3) |
| Neuropathy, n (%) | 1,567 (43.6) |
| Cardiovascular disease, n (%) | 2,026 (56.4) |
| Peripheral vascular disease, n (%) | 1,244 (34.6) |
| Metabolic complications, n (%) | 197 (5.5) |
| Hyperkalemia, n (%) | 336 (9.4) |
| Amputation, n (%) | 68 (1.9) |
| Gout or hyperuricemia, n (%) | 623 (17.3) |
| Comedications of interestd,e | |
| GLP-1 RA and fixed-dose combinations | 1,207 (33.6) |
| SGLT2i and fixed-dose combinations | 1,660 (46.2) |
| ACEi | 1,039 (28.9) |
| ARB | 2,504 (69.7) |
ACEi = angiotensin-converting enzyme inhibitors; ARB = angiotensin receptor blockers; CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; GLP-1 RA = glucagon-like peptide-1 receptor agonists; HbA1c = hemoglobin A1c (glycated hemoglobin); SD = standard deviation; SGLT2i = sodium-glucose cotransporter 2 inhibitors; T2D = type 2 diabetes; uACR = urine albumin-to-creatinine ratio.
Note: Lifestyle variables are defined using the most recent evaluation recorded on or before the index date.
Only 6 months of data were available due to the study start date.
Only 9 months of data were available due to the study end date.
Lookback period for these variables is the year before or on the index date (study days [−365,0]).
Prescribed from 180 days before and including index date.
Comedications of interest were defined as drugs with approved renal protective indications; however, data on the actual indication for use were unavailable.
Markers of T2D severity
The median time from first recorded T2D diagnosis code to index was 5.3 years (1st-99th percentile: 1,16 years). HbA1c data were missing in 44.9%; among patients with data, 24.7% had HbA1c > 53 mmol/mol (>7%), and 5.0% >74.9 mmol/mol (>9%) (Fig. 1). Insulin use in the 180 days pre-index was reported for 41.0%; 16.2% had no GLD use other than insulin. Over half of patients were prescribed either 1 or 2 medications for T2D in the 180 days preceding index, with SGLT2i (46.2%), metformin (37.3%), GLP-1 RA (33.6%), and sulfonylureas (21.7%) being the most common (Table S3). The median Diabetes Complications Severity Index score was 3.0 (1st-99th percentile: 0,9).
Fig. 1.
CKD Stage and uACR Category of New Finerenone Users at Index Date. CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; uACR = urine albumin-to-creatinine ratio. Note: All patients met the inclusion eligibility criteria for CKD, which was assessed through diagnosis codes, eGFR test results, or uACR test results. CKD stage percentages were calculated among patients who have information available from eGFR measurements or diagnosis codes; albuminuria percentages were calculated from patients with available uACR values in the year before the index date.
Markers of kidney dysfunction severity
Based on the presence of at least 1 of a diagnosis code, eGFR, or uACR, the median time from the first recorded CKD diagnosis to index was 4.2 (1st-99th percentile: 0,15) years. Most patients lacked multiple kidney dysfunction markers: 12.9% had no CKD diagnosis code, 27.7% lacked eGFR, and 67.9% were missing uACR measurements within 1-year pre-index date (Table 1, Table S2). Among patients with available eGFR or diagnosis codes, stage 3 CKD was most prevalent (62.4%), and 6.8% stage unspecified (Fig. 1A). Albuminuria was common among the 32.1% with uACR data: 39.4% were A2 (30–300 mg/g) and 47.1% were A3 (>300 mg/g), respectively (Fig. 1B). Hyperkalemia was reported in 9.4%. Most patients had prior exposure to medications of interest before initiating finerenone: 92.2%, 87.7%, and 80.0% had historical (>365 days), previous (365–91 days), or recent (<90 days) use of RAASi, respectively (Table S4). Prior use of steroidal MRAs was observed in < 12.0%. Hospitalizations for acute kidney injury in the previous year were recorded in 1.2% of patients.
Characteristics of finerenone use at baseline and during follow-up
As most patients entered the cohort near the end of the defined analysis period (in 2023), “end of study” was the primary reason for ending finerenone exposure (86.3%; Table S5). The median duration of initial exposure was 3.5 months, with median follow-up of 7.1 months. Patients filled a median of 3 prescriptions over follow-up. Monotherapy use was infrequent (8.5%), with finerenone primarily prescribed as an add-on to other medications of interest (59.4%) (Fig. 2), most frequently to RAASi (58.5%), SGLT2i (28.0%), or GLP-1 RA (21.1%). Treatment switches occurred in 5.2%; mostly from RAASi (6.4%) or SGLT2i (4.8%). Most had 1 distinct current-use period of finerenone (80.8%), with interruptions lasting > 90 days reported in 6.2% of patients. SGLT2i was the most commonly started medication class during follow-up (7%).
Fig. 2.
Classification of Finerenone at Index Date. Notes: Monotherapy = finerenone initiated as the only medication of interest; combination therapy = simultaneous initiation of finerenone together with another medications of interest; add-on therapy = addition of finerenone to an existing medication of interest; switch only = an existing medication of interest is replaced by finerenone; add-on and switch = both add-on and switched-to finerenone at the same time.
Titration of initial finerenone dose
Most patients (n = 2,948; 82.1%) initiated 10-mg finerenone. Among 10-mg finerenone initiators with ≥ 12 months of follow-up (n = 701), 16.7% (n = 117) had up-titrated to 20 mg at 12 months (Table 2). At treatment initiation, 17.9% of patients (n = 643) received the 20-mg dose and, among those with ≥ 12 months of follow-up (n = 151), 8.6% (n = 13) were down-titrated to a 10-mg dose at 12 months. Although the baseline proportion of 20-mg finerenone initiators appears comparable with the percentage with an eGFR of ≥ 60 mL/min/1.73 m2 (16.0%), we did not explicitly evaluate the relationship between eGFR and the initially prescribed dose.
Table 2.
Finerenone Dosing at Index Date and During Follow-Up.
| Primary analysis cohort (n = 3,591) | |
|---|---|
| Strength of index finerenone, n (%) | |
| 10 mg | 2,948 (82.1) |
| 20 mg | 643 (17.9) |
| Dose frequency of index finerenone, n (%) | |
| Once daily | 3,572 (99.5) |
| Other | 19 (0.5) |
| Proportion of patients who had a 10-mg daily dose at the index date and titrated up to 20 mg, n/N (%) | |
| at 1 montha | 49/2,808 (1.7) |
| at 6 monthsb | 195/1,797 (10.9) |
| at 12 monthsc | 117/701 (16.7) |
| Proportion of patients who had a 20-mg daily dose at the index date and titrated down to 10 mg, n/N (%) | |
| at 1 montha | 4/607 (0.7) |
| at 6 monthsb | 10/367 (2.7) |
| at 12 monthsc | 13/151 (8.6) |
n = numerator count; N = denominator count.
Denominator includes only those patients still being followed 1 month after the index date.
Denominator includes only those patients still being followed 6 months after the index date.
Denominator includes only those patients still being followed 12 months after the index date.
Temporal treatment changes during follow-up
The proportion of patients in each treatment state (current use, nonuse, or death) at the 4 prespecified timepoints of 90 days, 180 days, 270 days, and 1-year post-index are shown in Fig. 3. Among patients with ≥ 12 months follow-up, 56.0% were receiving finerenone at 1 year. The proportional increase in the no exposure treatment state (i.e., discontinuation) was 18% in the first 90 days and 14% between the 90- and 180-day timepoints. Beyond 180 days, the rate of discontinuation remained relatively stable. A small proportion of patients in the nonuser state resumed therapy later.
Fig. 3.
Treatment States at Specific Timepoints for New Finerenone Initiators. Notes: Sankey diagrams display the proportion of the population at each timepoint in each of the treatment states. The connecting bars between timepoints show the proportion of the population that moved from one state to a different state at the next timepoint. These figures display proportions of the population over time, and a patient may move between treatment states over time (e.g., begin as “treated,” move to “untreated” at the next timepoint, then move back to “treated” at the next). If death occurred, the patient was placed in a separate category and remained in that state for each subsequent checkpoint. The height of the bar at each timepoint displays the relative size of the cohort remaining under observation at each timepoint. Patients who were lost to follow-up are not included in the percentage calculations at each timepoint; thus, the percentages sum to 100% for each timepoint. The percentages describe the number of patients still under observation at that timepoint. The sum of the bars for each timepoint may not equal 100% due to rounding.
Discussion
Evaluating patient profiles and prescribing patterns for newly approved drugs is essential to understand early uptake in the target population and to identify gaps in guideline-concordant care that could impact patient outcomes. Using real-world data from Optum® CDM, this observational study characterized clinical profiles and treatment utilization patterns of patients with T2D and CKD initiating finerenone in the US following its regulatory approval in July 2021.
Patients who initiated finerenone were, on average, approximately 72 years of age; almost half had obesity (49.0%), and nearly all exhibited at least 1 cardiovascular comorbidity. Stage 3 CKD was most common (62.4%), and 86.5% of patients with laboratory uACR values exhibited moderate-to-severe albuminuria. T2D severity markers (e.g., Diabetes Complications Severity Index scores, HbA1c) indicated high disease burden, with many presenting with diabetic complications and, additionally, 41.0% using insulin. Notably, the demographic and clinical characteristics were highly comparable between the primary and wide finerenone analysis cohorts, indicating consistent patient profiles irrespective of CKD or T2D history in cohort definitions. At index, most patients were already receiving treatments of interest, most often RAASi (83.7%), SGLT2i (46.2%) or GLP-1 RA (33.6%), which was continued alongside finerenone for 59.4% of patients. Overall, findings suggest finerenone is primarily prescribed as a pillar of therapy used alongside complementary medications in patients with T2D and CKD, aligning with the 2024 KDIGO and 2025 American Diabetes Association guidelines [15], [20].
More than half of patients with at least 12 months of follow-up were currently using finerenone at 1 year (56.0%); only 6.2% experienced treatment interruptions lasting greater than 90 days. The proportion of patients on treatment with finerenone at the 12-month mark is broadly consistent with 12-month persistence rates observed for SGLT2i (50%) and GLP-1 RA therapies (52%) using Optum® CDM data. [21], [22] This finding suggests that persistence rates for finerenone in a clinically complex and multimorbid population are similar to those observed for SGLT2i and GLP-1 RA, both established medication classes. With respect to finerenone dosing, the percentage of patients with 20-mg at entry (17.9%) was comparable to those with baseline eGFR levels > 60 mL/min/1.73 m2 (16.0%), suggesting alignment with prescribing recommendations; however, we did not specifically evaluate whether the same patients with eGFR levels > 60 mL/min/1.73 m2 were also those initiating the 20-mg dose. Up-titration from 10-mg to 20-mg daily dose occurred in 16.7% of patients at month 12.
Relative to new users of finerenone in this study, initiators of SGLT2is and GLP-1 RAs in prior studies appear to be generally younger, with less severe kidney impairment and fewer cardiovascular comorbidities, and in receipt of less intensive T2D treatment. [21], [23], [24] The varied characteristics of these different medication cohorts may reflect the indications for GLP-1 RAs and SGLT2is beyond managing CKD progression risk, including hyperglycemia and weight management.
The patient profiles in this study are largely consistent with pivotal phase 3 trials [11], [12] where finerenone significantly reduced cardiorenal risks when added to existing cardioprotective medications in participants with moderate-to-severe CKD and T2D. Our findings also complement prior studies evaluating early postapproval use of finerenone in US clinical practice, [17], [18] which demonstrate prescription across diverse clinical and demographic groups in accordance with KDIGO guidelines. [15] Our results, derived from the Optum® CDM dataset, align broadly with the patient profiles of new finerenone users obtained from the OM1 Real-World Data CloudTM (OM1 RWDC), a multisource, US database of individually linked electronic health records and claims. [16] In both datasets, patients initiating finerenone were primarily in stage 3 CKD and with high prevalence of cardiovascular comorbidities. However, notable differences in prescribing patterns exist. Compared with patients in OM1 RWDC, patients in the present Optum® CDM dataset showed substantially higher baseline use of RAASi (83.7% vs. 49.4%), GLP-1 RAs (33.6% vs. 25.6%) and SGLT2is (46.2% vs. 38.0%), and less frequent initiation of finerenone as monotherapy (8.5% vs. 32.5%). Additionally, lower insulin use in the OM1 dataset may suggest better metabolic control in that population. The differences across studies using different data sources may be attributable to several factors, including formulary requirements, differences in clinical characteristics of underlying patient populations, or the nature of the data itself (i.e., electronic medical records vs. administrative claims).
Strengths of this study include the use of a large, real-world dataset and the application of eligibility criteria that closely align with clinical prescribing guidelines. Exclusion criteria were minimized to better reflect real-world populations of patients with CKD and T2D initiating these medications. Additionally, the inclusion of the wide finerenone cohort with relaxed eligibility criteria enabled a broader characterization of patients receiving finerenone. The study had several limitations. As Optum® CDM is a claims database, estimates of CKD and T2D duration may vary according to when patients entered the database. Follow-up data were limited for patients who entered the study cohort in 2023, with a maximum of 9 months available due to the study-defined end of follow-up. Dosing and eGFR values were captured separately, preventing assessment of whether dose titration aligned with kidney function at the time of adjustment. Undercapture of medications is possible if patients paid out of pocket or sought care out of network. The lack of indication data, longitudinal observations (e.g., blood pressure, body weight), clinical rationale for discontinuation (e.g., due to hyperkalemia), or re-initiation of finerenone may also limit interpretation. Additionally, as data were generated for healthcare delivery, we observed relatively high rates of missing laboratory data for assessing T2D and CKD severity and—in addition to limited interpretability and variable-specific implications (e.g., missing uACR data may indicate suboptimal testing practices in the US setting)—potential variable misclassification was possible (e.g., potential KDIGO risk strata misclassification). Finally, generalizability may be limited; for example, patients with frequent healthcare utilization and continuous enrollment > 12 months, as specified under the eligibility criteria, may differ from those with less engagement or shorter enrollment histories. Additionally, the population in this study was older than typically enrolled in clinical trials and, therefore, may have a greater comorbidity burden. Future research is warranted to address these limitations as well as to better understand real-world nephroprotective treatment patterns and sequencing relative to finerenone initiation and within the context of clinical guidelines.
Conclusion
This study offers insights into the real-world use of finerenone among patients with T2D and CKD in the US. Our findings indicate that finerenone was rarely used as monotherapy and was most commonly initiated in combination with other therapies of interest, such as RAASi, SGLT2i, or GLP-1 RA. The clinical and demographic characteristics of patients initiating finerenone suggest that its use aligns with current treatment guidelines and approved labeling. As the therapeutic landscape of CKD and T2D continues to evolve, ongoing monitoring of real-world treatment patterns remains essential to optimize patient care with novel therapies like finerenone.
Funding statement
This study was funded by Bayer AG. Authors affiliated with Bayer were involved in the study design, analyses, and development of this publication.
Ethics Statement
This study was deemed not to involve human subjects under 45 Code of Federal Regulations 46.102(f) and was exempt from board oversight. RTI International’s institutional review board confirmed exemption from full review. This study was conducted in accordance with the Declaration of Helsinki 1964 and its later amendments.
CRediT authorship contribution statement
Csaba P. Kovesdy: Writing – review & editing. Craig I. Coleman: Writing – review & editing, Supervision, Project administration, Funding acquisition, Formal analysis, Data curation. Catherine B. Johannes: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Conceptualization. Anam M. Khan: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Conceptualization. Ryan Ziemiecki: Writing – review & editing, Validation, Supervision, Project administration, Methodology, Investigation, Conceptualization. J. Bradley Layton: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Conceptualization. David Vizcaya: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Conceptualization. Fangfang Liu: Writing – review & editing, Supervision, Project administration. Nikolaus G. Oberprieler: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: FL and NGO are employees of Bayer, which funded this study. DV was an employee of Bayer at the time the research was conducted and currently works at Alexion Pharmaceuticals SL. CBJ, AMK, RZ, and JBL are or were employees of RTI Health Solutions, a subsidiary of RTI International, a nonprofit organization that conducts work for government, public, and private organizations, including pharmaceutical companies. RTI Health Solutions received research funding for this study from Bayer. CIC has received grant funding and consulting fees from Bayer AG and AstraZeneca Pharmaceuticals. CPK received consulting fees from Abbott, Akebia, Ardelyx, Astra Zeneca, Bayer, Boehringer Ingelheim, Cara Therapeutics, CSL Behring, CSL Vifor, GSK, Pharmacosmos, ProKidney, Renibus and Takeda.
Acknowledgements
Gabrielle Dardis, PhD, and Matt Fitzpatrick, PhD, of RTI Health Solutions provided medical writing support with funding from Bayer AG.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jcte.2026.100435.
Appendix A. Supplementary data
The following are the Supplementary data to this article:
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