Discussion
In this large real-world cohort study of patients with CKD and type 2 diabetes with elevated UACR, we found that an increasing UACR was associated with a higher risk of kidney disease progression (including kidney failure), CV events, and all-cause mortality. Conversely, achieving a >30% decrease in UACR was associated with reduced risks of these outcomes. These results further demonstrated the potential benefits of UACR monitoring and management in patients with CKD and type 2 diabetes. Furthermore, the findings provide real-world evidence that supports the recommendation of American Diabetes Association (ADA) clinical guidelines12 to target a ≥30% decrease in urinary albumin for those with UACR levels ≥300 mg/g.
The association between elevated UACR and CV events has been extensively described,9 19–21 and an improvement in CV outcomes is a known effect of UACR-lowering pharmacotherapies.22 Less is known, however, about the change in the UACR over time, and its effect on CV outcomes. Our study results address this gap and further improve the chain of evidence, showing a strong and consistent association between change in UACR and a composite CV outcome along with its individual components, as well as all-cause mortality. Our results are consistent with those reported in a post-hoc analysis of the LEADER trial, in which a >30% UACR decrease was shown to be associated with a lower risk of major CV events.23
Change in UACR has been proposed as a surrogate endpoint for predicting kidney outcomes in patients with diabetes and kidney diseases.24 25 The value of such surrogacy is that it can shorten study duration and allow assessment of clinically important events (eg, CKD progression, for which ESKD is a frequently used endpoint) at earlier stages of disease.25 Recent large-scale meta-analyses evaluating the association between UACR change and kidney outcomes found that a 30% decrease in UACR was associated with a 27% lower risk of CKD progression and 22% lower risk of ESKD, with stronger associations observed in patients with higher baseline UACR (>30 or ≥300 mg/g).13 14 Retrospective studies of patients with type 2 diabetes in Japan also found that a ≥30% increase in UACR was associated with an increased risk of kidney disease progression.26 27 Although we used slightly different definitions, our results are broadly consistent with these earlier reports: a >30% UACR decrease was associated with a 16% lower risk of kidney disease progression and 19% lower risk of kidney failure.
The present study showed that both reducing albuminuria and maintaining a stable UACR level are associated with lower risk of adverse clinical outcomes compared with having a UACR increase. This is in line with the clinical guidelines targeting UACR for CKD management,8 12 highlighting the relevance of UACR control as a meaningful objective measure for clinicians. A recent post-hoc mediation analysis of data from two phase III clinical trials on finerenone, a drug recommended for UACR control and CV/CKD risk reduction, concluded that 84% of finerenone-associated improvement in renal outcomes and 37% of its improvement in CV outcomes were mediated by finerenone’s effect on decreasing UACR.28 While achieving reduction in UACR would lead to greater clinical benefits, maintaining a stable UACR level may be a suboptimal treatment target; it can nonetheless confer clinical benefits when a sustained reduction is not feasible.
It is important to note that the current study characterized UACR change patterns in real-world practice before the implementation of the most recent (2022) KDIGO guidelines,8 which emphasized UACR control and recommended CKD treatments with UACR reduction effects (ie, SGLT2i and finerenone).29–31 Nonetheless, over half of patients had a >30% UACR decrease 2 years after the initial test, which could be at least partially attributable to the widespread use of renin–angiotensin–aldosterone system (RAAS) inhibitors, which may have been initiated or increased in response to the elevated UACR observed during the initial testing.32
Despite a large proportion of patients with decreased or stable UACR, there were still more than 20% of patients who experienced an over 30% increase in UACR, indicating inadequate disease control. In addition, and more importantly, we also found that 47% of patients with elevated UACR did not have a valid subsequent UACR test within 0.5–2 years after the initial test. These results suggest an unmet need of UACR monitoring and management in this patient population, which may in turn lead to worsened clinical outcomes.
A strength of this study was the use of a large EHR database as the data source, which allowed the selection of a representative sample of patients with incident CKD and prior type 2 diabetes across all age groups and geographic regions in the USA. In addition, the use of real-world data helps capture the variability in patient characteristics and disease management strategies that are typically not reflected in the randomized clinical trials. Another strength was that unlike many other real-world studies which relied on diagnosis codes alone (which can result in underdetection of disease and delayed identification of incident disease onset), the current study used eGFR and UACR laboratory measures in addition to CKD diagnosis codes to identify patients with CKD and characterize disease stage. In addition, our use of the EMERGE algorithm,17 which required at least two separate modalities to identify a patient with type 2 diabetes, resulted in greater specificity in identifying patients with type 2 diabetes than studies that rely on diagnosis codes alone. By identifying patients with both CKD and type 2 diabetes, rather than relying exclusively on diagnosis codes for diabetic kidney disease, the study captured a broader and more representative patient population, which is also consistent with the target patient population for whom the ADA guidelines recommend treatments for the management of kidney disease and CV risk, such as SGLT2is, GLP-1 RAs, and non-steroidal mineralocorticoid receptor antagonists.12 Moreover, the study population includes a large proportion of patients with early-stage CKD who had elevated UACR, which is a critical subpopulation for patients with CKD and type 2 diabetes. Additionally, UACR change was carefully defined to minimize potential selection bias and reflect clinically meaningful categorization to inform clinical practice. Lastly, this study had a long duration of follow-up (median of 3.4 years) allowing the evaluation of long-term clinical outcomes.
There were also some limitations to the study that warrant mention. First, UACR measurements were less frequently recorded in the dataset, which has led to the use of a single UACR test to define albuminuria and UACR change and a relatively long interval to identify the follow-up UACR test (ie, 0.5–2 years after the initial UACR). Therefore, the UACR change reflects relative change measured at different timepoints compared with the initial UACR measurement. Second, as UACR measurements are highly variable, there may have been misclassification of UACR category and change status. However, this was partially mitigated by our requirement of observing large changes in UACR (ie, >30%) to be classified as having either an increase or decrease in UACR, which would reduce misclassification errors introduced by the fluctuation in UACR levels. Finally, to ensure that the selection of a study population with a follow-up UACR was independent of the duration of continuous eligibility, patients were required to have at least 2 years of continuous eligibility after the initial UACR test. Consequently, patients with rapid disease progression after the initial UACR test that led to early death were excluded.
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