FormalPara Key Summary Points

Why carry out this study?

Chronic kidney disease (CKD) is highly prevalent but remains under-diagnosed, leading to missed opportunities to slow disease progression with guideline-directed interventions.

This analysis of patients with estimated glomerular filtration rate (eGFR) measurements indicative of stage 3 CKD aimed to investigate changes in CKD management and monitoring practices, eGFR decline and clinical outcomes following a recorded diagnosis of CKD.

What was learned from the study?

In patients with stage 3 CKD, presence of a CKD diagnosis code was followed by an improvement in CKD management and monitoring practices and an attenuation in eGFR decline.

Conversely, delayed diagnosis was associated with an elevated risk of adverse cardiorenal outcomes, including kidney failure, CKD progression and the composite of myocardial infarction, stroke and hospitalization for heart failure.

These findings suggest that a recorded diagnosis of stage 3 CKD is an important first step to reduce the risk of disease progression and associated complications.

Digital Features

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Introduction

Chronic kidney disease (CKD) is an established public health concern, affecting an estimated 11% of the global population [1]. The prevalence of CKD is rising, owing in part to increasing prevalence of risk factors for CKD, such as type 2 diabetes (T2D) and hypertension [2, 3]. However, the disease is often under-recognized by patients and healthcare practitioners [4]. This is particularly the case for stage 1–3 CKD, which is primarily asymptomatic and is usually identified through laboratory measurements of kidney function such as estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) [5].

Increased emphasis is being placed on early intervention in CKD. For example, recent guidance from the Kidney Disease: Improving Global Outcomes (KDIGO) workgroup stressed the importance of early intervention and appropriate management of CKD to delay disease progression and minimize associated complications [5, 6]. CKD is managed using a multifaceted approach that includes lifestyle changes, blood pressure control [7], lipid management [8], glycaemic control in patients with T2D [9, 10] and, more recently, use of new drugs with cardiovascular and renal benefits, such as sodium–glucose co-transporter-2 (SGLT-2) inhibitors [11, 12]. Despite efforts to improve healthcare practitioner awareness of CKD, as well as clear guidelines advocating for early intervention and the approval of new drugs shown to improve outcomes in patients with the disease, diagnosis rates of stage 1–3 CKD remain low [13,14,15,16,17,18,19]. These low diagnosis rates are driven in part by low rates of UACR testing in routine clinical practice [2, 20, 21] as well as a lack of clinical recognition of reduced eGFR values [22].

A recorded diagnosis represents the formal basis for the treatment a patient receives and is crucial for informing other members of the multidisciplinary teams often involved in the management of patients with CKD. Timely and accurate diagnosis allows healthcare practitioners to tailor decision-making to individual patients [23]. Furthermore, a diagnosis provides an opportunity to improve the health literacy of patients [24], supporting lifestyle changes that are often the foundation of disease management in early stage CKD [5, 25]. Recorded diagnoses can also inform healthcare policy, resource allocation and research priorities [26, 27].

Despite the high prevalence of CKD and the risk of complications and mortality associated with the disease, there has been little research on associations between a recorded CKD diagnosis and patient management or clinical outcomes. The REVEAL-CKD study programme (NCT04847531) is a multinational, observational study designed to investigate the prevalence and consequences of undiagnosed stage 3 CKD in large populations across several countries. Here, we investigate associations between a recorded diagnosis of CKD and the medical management of, and clinical outcomes in, adult patients in the USA with eGFR measurements indicative of stage 3 CKD.

Methods

The study design for REVEAL-CKD has been reported in detail elsewhere [28] and is briefly summarized below.

Data for this analysis were extracted from TriNetX [29], a database of integrated electronic medical records and insurance claims data from 35 healthcare organizations in the USA. TriNetX provides clinical patient data and prescription information from both inpatient and outpatient encounters. REVEAL-CKD used de-identified data from existing databases and did not require data collection beyond that of routine clinical care. No identifiable information was collected or examined as part of the study. All externally conducted analyses were completed in line with local ethics regulations/legislation. De-identified, internally licensed databases were shared with AstraZeneca by the licensee; therefore, ethics review and approval were not required for the use of these databases for this study.

Patients eligible for inclusion in REVEAL-CKD (aged ≥ 18 years) were identified by the presence of two consecutive eGFR measurements indicative of stage 3a/3b CKD (≥ 30 and < 60 ml/min/1.73 m2) recorded > 90 days apart (up to a maximum of 730 days), taken between 1 January 2015 and 31 December 2020 (Fig. 1). All patients had at least 12 months of continuous presence in the database before the first qualifying eGFR measurement. Patients with a solid organ transplant, renal replacement therapy or any evidence of advanced CKD (stages 4, 5 and end-stage renal disease) recorded before the second qualifying eGFR measurement were excluded. eGFR was calculated from serum creatinine, sex and age using the CKD Epidemiology Collaboration (CKD-EPI) equation [30]. In line with expert recommendations, race was not included in the calculation of eGFR [31]. Diagnoses of CKD were identified by the presence of an International Classification of Diseases (ICD)-9/10 code for CKD (any stage). The full list of ICD-9/10 codes used to determine diagnoses can be found in Supplementary Materials Table 1.

Fig. 1
figure 1

Study timeline. aeGFR was calculated using the CKD Epidemiology Collaboration equation from serum creatinine, sex and age values. bTwo consecutive eGFR measurements ≥ 30 and < 60 ml/min/1.73 m² recorded 91–730 days apart from 2015 to 2020. cEligible patients required ≥ 12 months of continuous database presence before the first qualifying eGFR measurement. dIncluded patients lacked a CKD diagnosis before and up to 6 months after the second qualifying eGFR measurement and were diagnosed with CKD 6 months or more after their second qualifying eGFR measurement. eCKD diagnosis status was determined by the presence of an International Classification of Diseases-9/10 code for CKD (any stage). CKD chronic kidney disease, eGFR estimated glomerular filtration rate

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Patients eligible for REVEAL-CKD were included in this analysis if they did not have a CKD diagnosis any time before, and up to 6 months after the date of their second qualifying eGFR measurement, and subsequently received a CKD diagnosis (i.e. there was a period of ≥ 6 months between their second qualifying eGFR measurement and the first recorded CKD diagnosis; Fig. 1). The index date for this analysis was defined as the date of the CKD diagnosis. Patients were classified into CKD stage according to the most recent eGFR measurement available on, or within 12 months before, the index date.

Statistical Analysis

Demographic and clinical characteristics of patients at index are presented descriptively. The incidence of CKD management practices and treatment patterns (identified using pharmacy claims) is presented as events per person-year with exact Poisson confidence intervals (CIs) and compared between the 180 days pre-and post-diagnosis using a Poisson regression model.

Estimated eGFR trajectories as a function of time to (and from) CKD diagnosis were estimated by applying a generalized additive model [32].

The annual eGFR decline before and after a CKD diagnosis was estimated by fitting individual linear regression models with time to diagnosis as the only independent variable for the 2-year period before, and up to 2-year period after, a CKD diagnosis. Estimated annual eGFR decline was summarized using medians and compared before and after CKD diagnosis using the Wilcoxon rank sum test. To minimize the observed effect of regression to the mean, calculation of eGFR slopes excluding eGFR measurements taken within 0.5 years before or after the date of CKD diagnosis was also performed.

The incidence of clinical outcomes was estimated as the number of events per 100 person-years and presented with 95% exact Poisson CIs.

Associations between diagnostic delay and post-diagnosis event rates were assessed using a Cox regression model. Diagnostic delay was defined as the time from 6 months after the second qualifying eGFR measurement to CKD diagnosis. This Cox regression model was adjusted for sex, age, history of diabetes (type 1 and type 2), number of pre-index visits, eGFR change rate (difference between eGFR at second qualifying measurement and eGFR at or within 12 months before CKD diagnosis divided by the time between those measurements) and eGFR at second qualifying eGFR measurement. Hazard ratios from this model estimated the relative increase in risk for each year of diagnostic delay; a hazard ratio > 1 indicates that greater diagnostic delay increased the risk of an event.

All hypothesis tests were performed at the 5% significance level. Missing data were not imputed. All statistical analyses were performed in R version 4.0.2.

Results

In total, 26,851 patients were included in the analysis (Supplementary Materials Fig. 1), with a median (interquartile range) follow-up time after CKD diagnosis of 1.01 (0.39–1.89) years. Demographic and clinical characteristics of patients at study index, overall and by CKD stage 3a/3b at study index (time of CKD diagnosis), are shown in Table 1. Overall, the mean age was 71.3 years, and 57.4% of patients were female. The mean (standard deviation) diagnostic delay (time from second qualifying eGFR measurement to CKD diagnosis) was 1.58 (0.90) years. When grouping patients by CKD stage based on their most recent eGFR measurement at or within 12 months before diagnosis, 10.0% of patients had stage 1/2 CKD and 10.1% of patients had stage 4/5 CKD; the remaining patients had stage 3a/b CKD. The proportions of patients with comorbidities such as hypertension, T2D, heart failure or a history of stroke or myocardial infarction tended to be higher in patients with stage 3b CKD at diagnosis than in those with stage 3a CKD.

Table 1 Demographic and clinical characteristics of patients, overall and by CKD stage (3a/3b) at study index (time of CKD diagnosis)
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CKD Management and Monitoring Practices

CKD management and monitoring practices, including select care quality indicators and prescribing of recommended medications in the 180 days before and after CKD diagnosis, were significantly improved following a CKD diagnosis (Fig. 2 and Supplementary Materials Table 2). The rate of blood pressure and creatinine monitoring doubled after a CKD diagnosis; more modest improvements in UACR testing and glycated haemoglobin (HbA1c) monitoring were also observed. Of note, while the rate of UACR testing did increase after a CKD diagnosis, it remained extremely low (0.05 measurements per person-year or 5 measurements per 100 person-years).

Fig. 2
figure 2

Rate ratios for CKD management and monitoring care quality indicators and prescription fills of guideline-recommended medications in the 180 days before and after a CKD diagnosis. Error bars indicate 95% CIs. ap values comparing rates of prescriptions per person-year for the 180 days before, and up to 180 days after, a CKD diagnosis are calculated using a Poisson regression model. ACE angiotensin-converting enzyme, ARB angiotensin II receptor blocker, CI confidence interval, CKD chronic kidney disease, DPP-4 dipeptidyl peptidase-4, GLP-1 glucagon-like peptide 1, HbA1c glycated haemoglobin, MRA mineralocorticoid receptor antagonist, SGLT-2 sodium-glucose cotransporter-2, T2D type 2 diabetes, UACR urinary albumin-to-creatinine ratio

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CKD diagnosis was associated with significant increases in the prescribing rates of guideline-recommended medications such as angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), mineralocorticoid receptor antagonists and SGLT-2 inhibitors. Similar trends were observed for glucose-lowering drugs in the subgroup of patients with T2D at study index (Fig. 2 and Supplementary Materials Table 2).

eGFR Decline Before and After a CKD Diagnosis

Models of annual eGFR decline before and after CKD diagnosis (excluding eGFR measurements taken within 0.5 years before or after a CKD diagnosis) showed a significant attenuation of annual eGFR decline following a CKD diagnosis, from 3.20 ml/min/1.73 m2 before diagnosis to 0.74 ml/min/1.73 m2 after diagnosis. In the subgroup of patients with T2D, the estimated annual eGFR decline decreased from 3.60 ml/min/1.73 m2 before diagnosis to 1.42 ml/min/1.73 m2 after diagnosis (Table 2). Furthermore, the overall proportion of patients who showed a rapid decline in eGFR (≥ 4 ml/min/1.73 m2 per year) was higher before a diagnosis (47.1% of patients) than after a diagnosis (39.2%; Table 2). Individual linear regression models that did not exclude values from within 0.5 years before or after a CKD diagnosis showed that the annual decline in eGFR decreased from 4.12 ml/min/1.73 m2 before diagnosis to 0.30 ml/min/1.73 m2 after diagnosis in the overall cohort and from 4.49 ml/min/1.73 m2 before diagnosis to 0.76 ml/min/1.73 m2 after diagnosis in the subgroup of patients with T2D (Supplementary Materials Table 3). The generalized additive model estimating eGFR trajectories also demonstrated this attenuation of eGFR decline after a CKD diagnosis (Fig. 3).

Table 2 Annual eGFR decline before and after a diagnosis of CKD, excluding eGFR values taken within 0.5 years before or after a CKD diagnosis
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Fig. 3
figure 3

General additive model estimating eGFR trajectories of patients before and after a diagnosis of CKD. Shaded area represents 95% confidence intervals. CKD chronic kidney disease, eGFR estimated glomerular filtration rate

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Associations Between CKD Diagnostic Delay and Clinical Outcomes

Adjusted HRs estimating the relative change in risk of selected clinical outcomes after CKD diagnosis for each year of diagnostic delay are shown in Fig. 4. Diagnostic delay was associated with a significant increase in the incidence of kidney failure (including kidney transplant and chronic dialysis), progression to CKD stage 4/5, major adverse cardiovascular events (MACE; a composite of myocardial infarction and stroke) and MACE + (a composite of myocardial infarction, stroke and hospitalization for heart failure). Similarly, Kaplan-Meier curves of cumulative event rates by CKD stage at time of diagnosis indicated that event rates were typically higher in patients who received a diagnosis for CKD at a higher CKD stage (Supplementary Materials Fig. 2).

Fig. 4
figure 4

Associations between delayed CKD diagnosis and risk of clinical outcomes per year of diagnostic delay, evaluated using Cox regression analysis. Error bars indicate 95% CIs. Diagnostic delay is defined as the length of time between a patient’s second qualifying eGFR measurement and the date of first recorded ICD-9/10 diagnosis code for CKD (any stage). Hazard ratios estimate the relative increase in risk for each year of diagnostic delay; a hazard ratio > 1 indicates that longer diagnostic delay increases the risk of an event. aHazard ratios calculated using Cox regression adjusting for sex, age, history of diabetes (type 1 and type 2), number of pre-index visits, eGFR change rate and eGFR at date of second qualifying eGFR measurement. bComposite of cardiorenal outcomes including chronic dialysis, kidney transplant, CKD progression to stage 4/5, myocardial infarction, stroke and hospitalization for heart failure. cIncludes patients who underwent kidney transplant or chronic dialysis during follow-up, identified using recorded procedure codes (CPT, HCPCS, ICD-9-PCS or ICD-10-PCS). dIncludes patients who have a recorded ICD-9/10 code for stage 4 or 5 CKD (< 30 ml/min/1.73 m2) during follow-up. eIncludes patients who experienced myocardial infarction and/or stroke during follow-up, identified using ICD-9/10 codes. fIncludes patients who experienced myocardial infarction, stroke and/or hospitalization for heart failure during follow-up, identified using ICD-9/10 codes. CI confidence interval, CKD chronic kidney disease, CPT current procedural terminology, eGFR estimated glomerular filtration rate, HCPCS Healthcare Common Procedure Coding System, HR hazard ratio, ICD International Classification of Diseases, ICD-9/10-PCS International Classification of Diseases 9/10 Procedure Coding System, MACE major adverse cardiovascular events

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Discussion

This analysis of a large US cohort of patients with eGFR measurements indicative of stage 3 CKD showed that a recorded CKD diagnosis was associated with improvements in CKD management and monitoring and prescribing of guideline-recommended medications. Furthermore, an attenuation of annual eGFR decline was observed following a diagnosis. Conversely, delayed diagnosis was associated with a greater incidence of CKD progression and adverse cardiovascular outcomes. Taken together, these findings suggest that recording of a diagnosis is an important first step in improving quality of care and outcomes for patients with stage 3 CKD.

Early disease detection is important to avoid delayed treatment of CKD and prevent progression to end-stage renal disease [33]. Previous studies have shown that CKD diagnosis is often delayed, especially for stage 1–3 CKD [13, 14, 18, 19, 34, 35]. Low rates of diagnosis may be driven by suboptimal monitoring of UACR, which is an important indicator of early kidney damage. For example, despite clinical guidelines recommending annual testing of UACR and eGFR in patients with T2D, a study of 24 healthcare organizations in the USA showed that UACR tests were frequently underused in routine clinical practice [20]. Furthermore, a study of patients in the USA at risk for CKD (diagnosed with hypertension, diabetes or both) showed that 80% did not receive guideline-appropriate assessment of kidney function during the study period [21]. In line with these studies, we observed very low rates of UACR testing even among patients with a recorded CKD diagnosis, highlighting shortcomings in the detection of mild to moderate kidney damage that must be addressed to improve patient care.

Late diagnosis of end-stage renal disease has been associated with higher mortality risk [36], although little research has been done on the impact of diagnostic delay in early-stage CKD. In the present analysis, long delays in CKD diagnosis were common, and eGFR measurements indicated that some patients progressed to higher CKD stages before receiving a diagnosis. We found that both greater diagnostic delay and diagnosis at a later CKD stage at diagnosis were associated with significant increases in the risks of adverse cardiorenal outcomes, including CKD progression, kidney failure and MACE/MACE+. Given the progressive nature of CKD, it is important that healthcare practitioners act quickly to minimize deterioration of kidney function and delay the onset of complications.

Guideline-directed therapies to slow progression and improve outcomes are a core component of CKD management, and treatment is often modified depending on individual patient circumstances and comorbidities. For example, ACE inhibitor/ARB therapy has been shown to lower the risk of kidney failure and cardiovascular events significantly [37], glycaemic control in patients with T2D reduces the risk for microalbuminuria and macroalbuminuria [38], and treatment with SGLT-2 inhibitors is associated with a significant reduction in CKD progression in patients with or without T2D [39]. It is reassuring that we observed increases in the prescribing rates of all guideline-recommended treatments investigated following a CKD diagnosis. However, despite these improvements, Kaplan-Meier analysis of cumulative event rates after CKD diagnosis showed that many patients were still at risk of CKD progression and cardiovascular complications. Furthermore, previous findings from the REVEAL-CKD study have identified that many patients with stage 3 CKD do not receive appropriate treatment regardless of diagnosis status [13]. In the present study, the absolute rate of prescribing of guideline-directed therapies, in particular SGLT-2 inhibitors, remained low even after a diagnosis. This is likely explained by the small overlap between the period following US Food and Drug Administration (FDA) approval of SGLT-2 inhibitors for the prevention of kidney function decline and the data collection period for the present study. We identified patients using serum creatinine measurements taken between 2015 and 2020; the first FDA approval for the use of SGLT-2 inhibitors to limit kidney function decline in diabetic kidney disease was granted to canagliflozin in 2019 [40], whereas other SGLT-2 inhibitors such as dapagliflozin had yet to receive FDA approvals for use in CKD (with or without T2D) at this point in time. Results from clinical trials of these agents provide a clear rationale for prescribing these newer therapies to improve outcomes in patients with CKD [39]. There is a need for healthcare practitioners to accelerate the uptake of newer evidence-based therapies for CKD management to reduce the risk of CKD progression and complications.

eGFR decline has been implicated as a predictor for poor clinical outcomes [41]. An analysis of eGFR slopes in from multiple prospective cohorts, clinical trials and simulations showed that even a modest decrease in eGFR (0.75 ml/min/1.73 m2 over 2 years) had a meaningful effect on the likelihood of end-stage kidney disease and concluded that such a decline is a suitable surrogate endpoint for trials in CKD [42]. In the present study, the significant attenuation in eGFR decline observed following a CKD diagnosis exceeded this threshold, providing further evidence to support that recording of a CKD diagnosis is a key first step in the management of the disease. While the observed reduction in eGFR decline after diagnosis may be partially attributable to lifestyle changes, regression to the mean or other unidentified confounders, it is plausible that improvements in CKD monitoring practices and guideline-directed prescribing had a positive impact on slowing CKD progression.

A diagnosis presents opportunities for improved clinical transparency and multidisciplinary care. As an example, a diagnosis of CKD from a primary care practitioner is likely to influence the approach taken by an endocrinologist in the management of T2D or the approach taken by a cardiologist in the management of heart failure given that guideline-directed management of CKD in patients with such concomitant conditions often differs [9, 43]. Without a documented diagnosis, opportunities to manage CKD may be missed, putting patients at unnecessary risk of CKD progression and complications. Primary care practitioners may be hesitant to diagnose CKD because they are concerned about emotionally overwhelming patients by diagnosing them with a chronic condition with potentially severe consequences [22]. However, this should not be a reason to avoid diagnosing the condition; indeed, it has been shown that patients have a strong desire to be informed and educated about their CKD [44].

Of note, our study population consisted mainly of elderly patients (mean age, 71.3 years). In these patients, healthcare practitioners may consider eGFR decline to be age-related [45], leading to underdiagnosis of CKD. However, our results demonstrate that in this elderly population, diagnosis may still have a positive impact. It is important that healthcare practitioners diagnose and treat CKD early in patients of all ages, even if the treatment of elderly patients may require adjustment to account for their age, frailty and comorbidities.

REVEAL-CKD uses a strict, consistent and internationally recognized definition of stage 3 CKD to ensure accurate identification of patients. Values for eGFR were calculated from serum creatinine according to the CKD-EPI equation, which is routinely used to calculate eGFR in real-world clinical practice. The present study examined a large cohort of patients from a wide range of healthcare organizations across the USA. Many of the patients in the present study were elderly, providing evidence of improvements following a CKD diagnosis in patients whose kidney function decline may be considered age-related rather than resulting from a disease state.

A limitation of the available data was short follow-up time after a CKD diagnosis. CKD is a chronic condition that tends to have a slow disease course, with deterioration in eGFR typically happening over the course of many years [46]. The short follow-up makes conclusions about the long-term impact of a diagnosis on eGFR and kidney function decline difficult to estimate. However, the observed improvements in CKD monitoring practices and prescribing of guideline-recommended medications were clear and immediate, and these were coupled with significant improvements in medium-term (2-year) eGFR decline. Although diagnosis of early-stage CKD (stage 1 and 2) typically requires confirmatory UACR testing [5], this analysis relied solely on eGFR values to identify patients with different CKD stages. REVEAL-CKD was designed specifically to evaluate stage 3 CKD, which is the earliest CKD stage identifiable by eGFR measurements alone [5]. This design choice was beneficial because very few patients had UACR data available at the time of CKD diagnosis (556 patients, 2.1%). However, because eGFR values were calculated from serum creatinine, individual readings may fluctuate slightly [47]. To minimize the impact of regression to the mean on annual eGFR decline before and after the diagnosis of CKD, eGFR values from the 0.5 years before and after CKD diagnosis were excluded from the regression models used to estimate eGFR slopes. However, regression to mean eGFR values may still account for some of the observed changes in eGFR decline. The individual linear regression models to estimate eGFR decline were adjusted for time to diagnosis only; other unidentified factors may have confounded these analyses.

Diagnoses of CKD made in environments that did not contribute to the database used will not have been captured. It was not possible to separate inpatient and outpatient encounters in this dataset; therefore, conclusions on potential differences in management and care quality between these two settings could not be drawn. Mortality data were not available in the dataset. This study does not capture lifestyle changes as a consequence of reduced eGFR or the presence of a CKD diagnosis, which would typically be the first step in the management of CKD. The findings from this study may not be generalizable to other countries which may have substantially different healthcare systems or CKD treatment policies. Finally, a high proportion of patients in the TriNetX dataset had commercial health insurance (including Medicare Advantage plans); therefore, this population may not be representative of the general population of the USA, in which a larger proportion may lack health insurance or be insured only through a basic Medicare plan.

Conclusions

The results of this analysis of patients from the USA with stage 3 CKD demonstrated that a recorded CKD diagnosis was associated with a significant improvement in measures of care quality and prescribing of guideline-recommended drugs. A recorded CKD diagnosis was also associated with a reduction in eGFR decline, whereas diagnostic delay was associated with an increased risk of adverse clinical outcomes. These findings provide compelling evidence indicating that diagnosis of stage 3 CKD is an important first step to reduce the risk of disease progression, thereby delaying adverse clinical outcomes. However, it should also be noted that diagnosis of stage 3 CKD can still be considered late identification of the disease: by this point a large portion of kidney function has already been lost. We observed very low rates of UACR testing, an important step in the diagnosis of stage 1/2 CKD, which should be addressed to improve early detection of CKD. Despite the improvements observed following a CKD diagnosis, it should be noted that many patients remain at risk of CKD progression and complications owing to diagnostic delay and under-prescribing of evidence-based therapies. Effective implementation of screening programmes, improved rates of UACR testing and recorded diagnosis and prescribing of newer therapies to treat patients with CKD are all important opportunities to lessen the clinical and economic burden of late-stage CKD on healthcare systems and improve patient outcomes.