Antihyperglycemic Treatment Patterns for Chronic Kidney Disease and Type 2 Diabetes

ABSTRACT

Objective: Patients with type 2 diabetes (T2D) are at high risk for developing chronic kidney disease (CKD). The onset of incident CKD may complicate glycemic control among these patients. This study aimed to characterize antihyperglycemic medication use after incident CKD onset among patients with T2D to inform disease management.

Study Design: Retrospective cohort study.

Methods: Patients with incident CKD and prior T2D were identified from the Optum electronic health records database between March 2013 and September 2021. Patterns of antihyperglycemic use were assessed during the 1-year baseline period and after incident CKD diagnosis and described by baseline hemoglobin A_1C (HbA_1C) level (controlled [< 7%] vs elevated [≥ 7%]) and CKD severity.

Results: The study consisted of 262,395 patients, of whom 51% had elevated HbA_1C. After CKD onset, 23.9% of patients initiated new antihyperglycemics within 1 year. Patients with elevated HbA_1C had shorter time to new treatment initiation compared with those with controlled HbA_1C (median, 28.7 vs 83.7 months). Patients with elevated urine albumin-to-creatinine ratio (uACR) had shorter median time to new treatment initiation (39.9-42.4 months) than those with normal uACR (59.8 months). Less than 7% of patients with stage 3 CKD and even smaller percentages of patients with higher stages of CKD utilized glucagon-like peptide 1 receptor agonists and sodium-glucose cotransporter 2 inhibitors.

Conclusions: Treatment of T2D was considerably heterogenous by HbA_1C level and CKD severity in patients with incident CKD. Current agents may not sufficiently fulfill the unmet need of T2D management in patients with CKD.

Am J Manag Care. 2024;30(9):In Press

Takeaway Points

This study examined the use of antihyperglycemic medications after chronic kidney disease (CKD) onset in patients with type 2 diabetes (T2D) in the US using electronic health records data.

• The management of diabetes was considerably heterogeneous and varied by disease severity; patients were likely to change antihyperglycemic medications after CKD onset, especially those with high hemoglobin A1C levels or a high urine albumin-to-creatinine ratio.
• Findings highlight the complexity of disease management in patients with T2D and CKD and suggest the necessity of more tailored approaches targeting glucose control and kidney protection.

Diabetes is the leading cause of chronic kidney disease (CKD).¹ The natural history of a patient with type 2 diabetes (T2D) and CKD involves glomerular hyperfiltration, progressing to albuminuria indicated by elevated urine albumin-to-creatinine ratio (uACR) and to declining kidney function characterized by descending estimated glomerular filtration rate (eGFR).^2,3

Glycemic control is crucial in disease management but can be challenging for patients with T2D and CKD. Undertreatment accelerates CKD progression,³ whereas overtreatment could lead to hypoglycemia and cause adverse outcomes.^4,5 The 2022 American Diabetes Association clinical guidelines suggest a hemoglobin A_1C (HbA_1C) target of less than 7% (or < 53 mmol/mol).⁶ The Kidney Disease: Improving Global Outcomes 2022 guidelines recommend more individualized targets (ranging from < 6.5% to < 8%) for patients with CKD and T2D to improve clinical outcomes while mitigating the risk for hypoglycemia.⁷ Additionally, newer antihyperglycemic treatments, such as glucagon-like peptide 1 receptor agonist (GLP-1 RA)^8-10 and sodium-glucose cotransporter 2 inhibitor (SGLT2i) agents,^11-13 offer alternative options with a reduced risk of hypoglycemia and proven cardiovascular and renal benefits.^14-17

Despite the importance of achieving target HbA_1C levels, insufficient glycemic control and poor treatment adherence are common in the population with T2D.^18,19 The coexistence of CKD further complicates treatment. Reduced kidney function may dampen treatment effectiveness, particularly in patients with lower eGFR levels.^20,21 Also, contraindications may limit medication options (eg, metformin is not recommended for stages 4 and 5 CKD).^20,22 Furthermore, treatment-related complications may trigger treatment interruptions, such as SGLT2i-associated urinary tract and genital infections, volume depletion, and diabetic ketoacidosis.²³ Consequently, treatment strategies often require adjustments following CKD onset.

This study characterized antihyperglycemic treatment patterns, especially treatment changes after CKD onset, among patients with T2D and incident CKD using an electronic health record (EHR) database in the US.

METHODS

Study Population and Design

This retrospective cohort study included adults (aged ≥ 18 years) with T2D and incident CKD diagnosis on or after March 29, 2013, using the Optum EHR database from January 1, 2007, through September 30, 2021. The data source was described in a previous study.²⁴ Because the data were deidentified, there were no requirements for institutional board review or informed consent.

Patients with incident CKD after T2D diagnosis were identified using diagnosis codes and laboratory measures (ie, eGFR and uACR) according to CKD clinical guidelines.²⁵ Specifically, CKD was defined as 2 outpatient diagnoses on different dates or 1 inpatient diagnosis and/or 2 reduced eGFR measurements (< 60 mL/min/1.73 m²) 90 to 548 days apart and/or 2 impaired uACR measurements (≥ 30 mg/g) 90 to 548 days apart after T2D diagnosis.²⁶ eGFR was calculated using serum creatinine laboratory measurements per the 2021 CKD Epidemiology Collaboration creatinine equation.²⁷ uACR measurements included direct uACR laboratory results and calculated values from urine albumin and urine creatinine measured on the same date if a direct uACR measurement was unavailable. T2D was identified based on a modified algorithm from previous EHR studies,²⁸ using International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases, Tenth Revision diagnosis codes, antihyperglycemic medication use, and abnormal glucose tests (ie, ≥ 7.0 mmol/L fasting glucose or ≥ 11.1 mmol/L random glucose) or HbA_1C (ie, ≥ 6.5%).

The study index date was defined as the earliest date that met the CKD criteria following T2D diagnosis and was on or after March 29, 2013, the approval date of the first SGLT2i in the US. The follow-up period spanned from the index date to the end of continuous eligibility, death, or the end of data availability, whichever occurred first. The baseline period encompassed the 1 year prior to the index date. Patients were required to have no records indicating CKD at baseline and were also required to have (1) continuous data activity during the baseline period and 1 month after the index date and (2) antihyperglycemic medication use at any time prior to the index date. Continuous data activity was defined as having consecutive medical records with intervals of less than 6 months between adjacent records. Patients were excluded if they (1) had other types of diabetes or (2) had end-stage kidney disease, dialysis, or kidney transplantation during baseline.

Outcomes of Antihyperglycemic Treatment Patterns

Baseline antihyperglycemic medication use. Antihyperglycemic medication use was assessed on the drug class level including metformin, sulfonylureas, thiazolidinediones, SGLT2i, dipeptidyl-peptidase-4 inhibitors (DPP-4i), GLP-1 RA, and insulin. Patients who had multiple drug classes during baseline were considered as having concurrent use of multiple treatments.

New antihyperglycemic medication initiation. Changes of antihyperglycemic treatment were defined as new treatment initiation (ie, having a prescription of a new medication class that was not prescribed at baseline). Due to the lack of treatment duration information, treatment discontinuation was not considered in treatment changes. Multiple medications prescribed within the assessment time window were considered as concomitant use, which may include medications prescribed on the same date or in sequence, as well as the use of a polypill.

Covariates

Patient demographics including age, gender, race, ethnicity, and insurance type were assessed at index. CKD stage was defined using diagnosis codes or 2 eGFR measurements indicating the same stage, categorized into 5 stages based on eGFR level: stage 1 (≥ 90 mL/min/1.73 m²), stage 2 (60 to < 90 mL/min/1.73 m²), stage 3 (30 to < 60 mL/min/1.73 m²), stage 4 (15 to < 30 mL/min/1.73 m²), and stage 5 (< 15 mL/min/1.73 m²). uACR was categorized into 3 categories using laboratory measurements: normal (A1, < 30 mg/g), moderately increased (A2, 30-300 mg/g), and severely increased (A3, > 300 mg/g). Diabetes management status was defined based on HbA_1C measurement closest to the index date (ie, controlled HbA_1C [< 7%] vs elevated HbA_1C [≥ 7%]).²⁹ Comorbidities were identified using diagnosis codes during baseline.

Statistical Analyses

Baseline patient characteristics and antihyperglycemic medication use. Patient characteristics during baseline were summarized for the overall sample and by diabetes management status. Antihyperglycemic medication use during baseline was summarized separately for monotherapy and concomitant use of multiple drugs.

Treatment change after CKD onset. Patterns of new treatment initiation after CKD onset were assessed for the overall sample and by baseline diabetes management status, CKD stage, and uACR category. Time to the first new antihyperglycemic treatment initiation (in months) and the proportions of patients who initiated new antihyperglycemic treatment at 1, 3, and 5 years after the index date were estimated using cumulative incidence functions. Patients without new treatment initiation were censored at end of follow-up. Additionally, the distribution of newly initiated treatments at 90, 180, and 365 days after CKD onset were depicted using Sankey diagrams. Patients who had initiated multiple treatments prior to the prespecified time points were classified as having concomitant use of multiple treatments. Loss to follow-up was treated as a separate category.

SAS 9.4 (SAS Institute) and R 3.6.3 (R Foundation for Statistical Computing) were used for statistical analyses. All statistical tests were 2-sided, and a P value less than .05 was considered significant.

RESULTS

Patient Demographics and Clinical Characteristics

A total of 262,395 patients with CKD and prior T2D were included in the analyses (eAppendix Figure 1 [eAppendix available at ajmc.com]). The study population had a mean (SD) age of 66.5 (11.7) years, and 51.1% were female (Table 1). The majority were White (79.5%), followed by African American (13.6%) (eAppendix Table 1). Baseline CKD stage and uACR measurements were recorded for 84% and 61% of patients, respectively, with the most patients (45.0%) in CKD stage 3, followed by stages 1 (19.7%) and 2 (17.7%), and only a small proportion in stages 4 (1.6%) and 5 (0.3%). For uACR, 18.9%, 35.1%, and 7.0% of patients were in the A1, A2, and A3 categories, respectively. The most common comorbidities during baseline were hypertension (86.6%) and hyperlipidemia (79.7%).

Approximately 90% of the patients had baseline HbA_1C measurements and approximately 51% among them had elevated HbA_1C (≥ 7%). Higher proportions of patients with elevated HbA_1C had elevated uACR (43.6% for A2 and 9.6% for A3) compared with those with controlled HbA_1C (33.6% for A2 and 5.6% for A3).

Baseline Antihyperglycemic Medication Use

Metformin (67.8%), sulfonylurea (32.2%), and insulin (26.0%) were the most used medication classes during baseline (eAppendix Table 2). Nearly half of patients (47%) used 2 or more antihyperglycemic treatments during baseline. The top 5 baseline treatments were metformin monotherapy (27.4%), metformin and sulfonylurea (11.2%), insulin monotherapy (7.0%), insulin and metformin (6.0%), and DPP-4i and metformin (3.1%) (Table 2). Patients with elevated HbA_1C used, on average, more antihyperglycemic medications than those with controlled HbA1C (mean number of medication classes, 2.1 vs 1.5, respectively).

Metformin use decreased with advanced CKD stages, with approximately 29% of patients with stage 4 or 5 CKD using metformin compared with 81.1% of patients with stage 1 CKD (eAppendix Table 2). SGLT2i and GLP-1 RA were less used in patients with advanced eGFR stages but were more frequently used in patients with elevated uACR (eAppendix Table 2 and eAppendix Table 3). In contrast, insulin use was higher in advanced CKD stages (40.7% for stage 4 and 43.4% for stage 5 CKD vs approximately 26% for stage 1-3 CKD) and patients with macroalbuminuria (37.5% use for uACR A3 vs 22.4% for A1 and 26.1% for A2) (eAppendix Table 2 and eAppendix Table 3).

New Antihyperglycemic Treatment Initiation After CKD Onset

The median time to new treatment initiation after CKD onset was 50.4 months (Figure 1) with 23.9% initiating new treatment within 1 year and 42.7% initiating within 3 years. Treatment pathways were complex and multiple classes of antihyperglycemic medication were initiated within 1 year after CKD onset (eAppendix Figure 2). Among patients who initiated new antihyperglycemic treatments, about 22% initiated 2 or more different classes of antihyperglycemics. Patients with elevated HbA_1C had shorter time to new treatment initiation (median, 28.7 months vs 83.6 months, respectively), with a higher proportion initiating a new antihyperglycemic medication within 1 year compared with those with controlled HbA_1C (32.9% vs 14.0%) (Figure 1). The proportion of patients initiating 2 or more treatments within 1 year after CKD onset was also higher for patients with elevated HbA_1C compared with those with controlled HbA_1C (22.7% vs 16.9%). Among patients who initiated a single agent of antihyperglycemic medication within 1 year, the proportion of SGLT2i use and GLP-1 RA use was higher for patients with elevated HbA_1C than those with controlled HbA_1C (10.2% vs 6.0% for SGLT2i and 11.5% vs 7.0% for GLP-1 RA) (Figure 2).

When looking at the patterns of new treatment initiation by CKD severity, the median time from CKD onset to new antihyperglycemic treatment initiation increased with CKD stages, from 33.8 months for patients with stage 1 CKD to 74.8 months for those with stage 4 or 5 disease. A higher proportion of patients with stage 1 CKD (29.1%) initiated new treatments within 1 year compared with patients in other CKD stages, ranging from 21.7% to 23.5% (Figure 3). Among patients who initiated new antihyperglycemic treatment after CKD onset, higher proportions of patients with advanced CKD stages initiated insulin (34.0% for stage 4/5 vs 12.5% and 17.6% for stages 1 and 2, respectively) and fewer patients initiated a SGLT2i (2.2% for stage 4/5 vs 12.9% and 9.2% for stages 1 and 2, respectively), compared with patients with a milder CKD stage (eAppendix Table 4).

Patients with elevated uACR had shorter median time to new treatment initiation (42.4 and 39.9 months for A2 and A3 categories, respectively) than those in the A1 category (59.8 months). Patients with higher levels of uACR were more likely to initiate new treatments within 1 year (A1: 20.6%; A2: 25.7%; A3: 27.5%) (eAppendix Figure 3). Among patients who initiated new antihyperglycemic treatment after CKD onset, higher proportions of patients with A2 or A3 uACR initiated SGLT2i (11.6% in A2 and 11.1% in A3) and GLP-1 RA (12.2% in A2 and 12.6% in A3) compared with patients with A1 uACR (7.8% for SGLT2i and 9.8% for GLP-1 RA) (eAppendix Table 5).

Patients using SGLT2i and DPP-4i monotherapies during baseline were more likely to initiate a new antihyperglycemic treatment (50.5% and 33.0% at year 1 for SGLT2i and DPP-4i, respectively) than the nonusers (23.5% and 23.2% at year 1 for nonusers of SGLT2i and DPP-4i, respectively) (eAppendix Figure 4). The median time to new treatment initiation after CKD onset was also short (11.6 months) for patients using SGLT2i monotherapy at the baseline.

DISCUSSION

In this contemporary study of a large, representative EHR database from the US, we observed diverse patterns of antihyperglycemic medication use before and after incident CKD onset among patients with T2D. The use of multiple antihyperglycemic treatments was common in patients with CKD and T2D, particularly those with elevated HbA1C. The antihyperglycemic treatment patterns varied by CKD stage and albuminuria severity, implying complexities in T2D management when developing CKD. Treatment change was more frequent for patients using SGLT2i. The study results also highlight an unmet need of T2D management in patients with T2D and incident CKD.

The study findings highlight significant heterogeneity and nonstandard approaches to antihyperglycemic treatment after CKD onset. In recent decades, the use of multiple antihyperglycemic treatments, including triple and quadruple combinations, was common in clinical practice, as monotherapy often failed after a period of treatment.³⁰ Consistently, we observed that patients with elevated HbA_1C tended to use multiple classes of antihyperglycemic medications. These patients were more likely to initiate new treatments after CKD onset. The frequent treatment changes may reflect the insufficiency of antihyperglycemic treatments and the challenges of managing T2D with CKD. On the other hand, patients with controlled diabetes tended to retain their original treatment for an extended period. For these patients, treatment options preserving glycemic control while reducing cardiovascular risk may be preferred after CKD onset.

New antihyperglycemic treatment initiation observed in this study included both treatment add-ons and switches. Both situations could partly be triggered by not being able to maintain therapeutic guideline targets. This is consistent with other studies that reported a high prevalence of hyperglycemia in patients with T2D and CKD in the US.³¹ Moreover, adverse events could lead to treatment switch. For example, metformin is known for its gastrointestinal adverse effects³² and the SGLT2i class is associated with an elevated risk of urinary tract and genital infections, volume depletion, diabetic ketoacidosis, and acute renal failure.^23,33-35 Patients who were unable to tolerate these treatments might change treatment strategy. Similar findings of frequent changes in treatment strategy were reported in literature. Fried et al reported 1-year discontinuation rates ranging from 56.9% to 75.7% for several antihyperglycemic medications (eg, SGLT2i, GLP-1 RA, insulin) in the population with T2D and CKD in the US.³⁶

Current clinical guidelines recommend using an SGLT2i in combination with metformin for first-line T2D treatment after CKD onset to mitigate cardiovascular events and renal risks.³⁷ GLP-1 RA agents are also recommended for patients with CKD not meeting glycemic targets using first-line treatment.⁷ Our study observed an increasing use of these agents in patients with moderate to severe CKD by 2021. Despite guideline recommendations, these agents may not sufficiently fulfill the unmet need in patients with CKD. In our study, patients using SGLT2i were more likely to initiate a new antihyperglycemic treatment after CKD onset than patients who used other medications. A recent study from Denmark by Malik et al showed that one-third of new SGLT2i users discontinued their treatments within 1 year.³⁸ Moreover, adding an SGLT2i to an existing diabetes regimen could disrupt stable glucose control, increasing the risk of hypoglycemia.³⁹

The observed antihyperglycemic treatment patterns shortly before and after incident CKD also varied by CKD disease severity, which may be partially attributed to the challenges in T2D management imposed by the development of CKD. As expected, medications contraindicated for severe renal impairment (eg, metformin and SGLT2i) were used less in patients with stage 4/5 CKD, and medications with urine albumin–lowering effects (eg, SGLT2i and GLP-1 RA) were used more in patients with uACR greater than 30 mg/g. Similarly, Iyer et al reported similar variation in antihyperglycemic treatment use across CKD stages (eg, 66% of patients with stage 2 CKD received metformin and 9% received SGLT2i, compared with only 10% of patients with stage 4 CKD receiving metformin and 1% receiving SGLT2i).⁴⁰

Additionally, patients with albuminuria were more likely to have elevated HbA_1C and initiate new antihyperglycemic treatments. Albuminuria could further complicate glycemic control, potentially due to its connection with insulin resistance, which further deteriorates glucose control.^21,41 Enhancing awareness of albuminuria in disease management and promoting early and regular uACR testing in patients with T2D are warranted for early CKD detection and timely management. Additionally, for patients with well-controlled diabetes, medications that reduce urine albumin without altering glucose levels can be considered.

A notable strength of this study was the use of a large-scale EHR database, which permits the selection of a representative sample across all US geographic regions and age groups. Additionally, eGFR and uACR measures were used to identify and stage CKD in addition to diagnosis codes (use of CKD diagnosis codes alone may result in underdetection of CKD, delays in identifying incident CKD onset, and staging errors).⁴² Moreover, treatment patterns were comprehensively evaluated, covering baseline treatment use, time to new treatment initiation, and distribution of newly initiated treatments, and assessed across subgroups according to key clinical characteristics.

Limitations

Several limitations should be considered when interpreting the results. First, as with all EHR database analyses, diagnoses, laboratory tests, and medication prescriptions obtained outside the health care network were not captured. Second, the prescription information in our data indicates only that the medication was prescribed and does not guarantee that patients actually took the prescribed medication. In addition, data on prescription duration and dosing were incomplete in the EHR database, preventing assessment of treatment discontinuation and dose adjustment. However, new treatment initiation can serve as a surrogate for treatment changes. Third, the indication of SGLT2i was expanded and the treatment was recommended for CKD after the study period. Finally, this is a descriptive study with no hypothesis testing or statistical comparison. The results should not be used to imply any causal relationship.

CONCLUSIONS

In this population-based contemporary study of patients with T2D and incident CKD in US routine care, diabetes management was considerably heterogenous and challenging, with a high prevalence of insufficient glucose control. Patients with elevated HbA_1C used more antihyperglycemic medications (including SGLT2i and GLP-1 RA) and were more likely to change antihyperglycemic treatments after CKD onset. Antihyperglycemic treatment patterns also varied by CKD severity. The findings highlight the complexity and unmet need of T2D management in a patient population with incident CKD. More tailored approaches targeting glucose control and kidney protection are warranted.

Author Affiliations: Analysis Group, Inc (KAB, AW, XH, JC), Los Angeles, CA; Bayer AS (NGO), Oslo, Norway; Bayer PLC (GJ), Reading, United Kingdom; Bayer LLC (SB), Whippany, NJ; Bayer AG (AG), Berlin, Germany; Bayer Hispania (DV), Sant Joan Despi, Spain.

Source of Funding: This research was funded by Bayer AG.

Author Disclosures: Drs Betts, Wu, and He and Ms Chen are employed by Analysis Group, which received a consultancy fee from Bayer, a market authorization holder of medication with chronic kidney disease and type 2 diabetes indication. Drs Oberprieler, Beeman, and Vizcaya are employed by Bayer. Dr James is employed by Bayer and owns Bayer stock. Dr Gay was employed by Bayer at the time of completing this manuscript.

Authorship Information: Concept and design (KAB, NGO, AW, SB, AG, DV); acquisition of data (DV); analysis and interpretation of data (KAB, NGO, AW, GJ, SB, AG, XH, JC, DV); drafting of the manuscript (KAB, NGO, AW, GJ, SB, XH); critical revision of the manuscript for important intellectual content (KAB, NGO, AW, GJ, SB, AG, XH, DV); statistical analysis (KAB, AW, XH, JC); obtaining funding (DV); administrative, technical, or logistic support (KAB, AW, GJ, JC, DV); and supervision (KAB, AW, DV).

Address Correspondence to: David Vizcaya, PhD, MPH, Bayer Hispania, Avda Baix Llobregat 3-5, Sant Joan Despí 08970, Barcelona, Spain. Email: david.vizcaya@bayer.com.

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