Editor's Note: This article was updated for minor editorial additions and formatting changes, per request of the authors.
Abstract: In order to identify drivers of chronic kidney disease (CKD) stage progression and health care costs associated with progression, we conducted a retrospective, longitudinal observational study querying the Humedica electronic medical records database for adult patients in the United States with new, sustained, or progressive CKD (stage 2, 3a, 3b, or 4/5) with ≥ 1 year pre-index and ≥ 3 years post-index data. Data was analyzed for 212,920 CKD stages among 189,799 patients (52,280 age ≥ 65 years; 137,519 age ≥ 65 years). On Poisson regression, diabetes, heart failure, cardiovascular disease, and pre-index hyperkalemia predicted CKD progression. CKD progression rates were highest among patients with stage 3a or 3b disease (38%-43% at 3 years). Progressing patients averaged 12 to 16 months in their index stage. Incremental cost increased with each successive stage (all P < .001, except stage 3a vs 2 in Medicare patients) and was higher in Commercial patients vs Medicare. Hyperkalemia and the well-known comorbidities were associated with CKD progression. Incremental costs with CKD progression are substantial, especially in younger patients.
Acknowledgments: Writing and editorial support were provided by Impact Communication Partners Inc., and funded by Relypsa, Inc., a Vifor Pharma Group Company.
Chronic kidney disease (CKD) affects 13.6% of the US adult population, with a projected increase to 16.7% by 2030.1,2 Risk factors for progression of CKD include diabetes, albuminuria, and various cardiovascular comorbidities, which provide the targets for current CKD management.3-6 With CKD progression adverse cardiovascular events and mortality increase.7-11 Importantly, the associations between decreased estimated glomerular filtration rate (eGFR) and risk of major cardiovascular events and death appear independent of concomitant chronic diseases (eg, cardiovascular disease or heart failure).7
Prevalence estimates of CKD, based on cross-sectional analyses,12,13 provide a snapshot with little information about CKD progression over time. Most information on effects of CKD progression on health care costs was also derived from cross-sectional studies. Notwithstanding these limitations, a direct association between progression and cost was demonstrated. In Australia, annual health care costs increased from $1829 for individuals without CKD to $14,545 for those with stage 4/5 CKD.14 In a Japanese cohort, medical expenditures increased with CKD stage.15,16 In our previous study of CKD patients with a prescription history of renin-angiotensin-aldosterone system inhibitor (RAASi) therapy, all-cause costs per patient were exponentially higher at each successive CKD stage.17 We hypothesized that other factors, such as hyperkalemia, may also contribute to cost independently through increased provider-driven hospitalization.
Longitudinal analyses of real-world clinical practice are needed to evaluate the rate of CKD stage progression, explore risk factors driving progression, and assess how CKD progression affects health care costs. Importantly, identifying cost drivers of CKD progression may help uncover cost-reducing strategies. We report a retrospective longitudinal study of a large electronic US medical database evaluating the rates and risk factors for progression by CKD stage over 3 years and impact on health care costs.
Methods
Study Population and Cohorts
Demographic and clinical characteristics were evaluated at the onset of each CKD stage using prior data. Patients were assigned by age at first inclusion to Medicare (age ≥ 65 years) or Commercial (age ≥ 65 years) cohorts for modeling insurance coverage. Comorbidities were identified by single occurrence of any indicator in pre-stage data using diagnosis codes, laboratory values, or antihyperglycemic medications (Supplementary Table 2). Prescriptions for RAASi were classified by dose level at the beginning of each CKD stage as “maximum” (recommended labeled dose, Supplementary Table 3), “submaximum” (any lesser amount), or “discontinued” ( ≥ 390 days elapsed since most recent prescription). Outpatient diuretic therapy during the 12-month pre-index period was categorized hierarchically as loop diuretic, other diuretic, or none. Visit frequency was characterized as infrequent (0-1 visit) or frequent (≥ 2 visits) based on the number of office/clinic visits in the 12 months preceding the end of the outcome period or CKD progression.
Classification of Services and Medications
Health care services were classified as inpatient, emergency department visits, or by type of outpatient service. Prescriptions were identified by generic name of the primary ingredient, irrespective of dose, brand, or formulation.
Cost of Services and Medications
Average health plan-allowed cost was obtained from 2013 Commercial insurance and Medicare claims data (OptumInsight, Minneapolis, MN) per inpatient day for surgical and non-surgical admissions (with and without comorbidities), per visit for outpatient and physician care and services, and per filled prescription (along with percent refills) for common medications (all forms and doses, by generic name of primary ingredient). Average allowed cost per service in Commercial or Medicare insurance claims was applied to each service event for the Commercial and Medicare groups, respectively. Outpatient dialysis services in patients without evidence of kidney transplant were excluded from ESRD costs due to significant underrepresentation in the source data. For high-frequency medications, average cost per filled prescription plus refills at observed rates was assessed in claims data. Average cost per written prescription (fill + refills) was applied to each evaluated medication; average cost per prescription of these drugs, weighted at actual usage in the data set, was applied to prescriptions of drugs for which specific cost data was not acquired. Costs were normalized to 2016 US dollars at 3% per annum.
Primary Outcomes: CKD Progression Rates and Cost of Progression
Rates of CKD progression (defined as progression from one stage to any higher stage, including progression from stage 3a to 3b) were calculated at 1, 2, and 3 years by payer group. Average time in each CKD stage (months over the 3-year period) was also calculated. Incremental cost of CKD progression at 1 year was evaluated longitudinally by comparing mean change in cost (12 months post- vs pre-index) per patient for all patients who did vs did not progress to any higher stage within 1 year. Progression rates and incremental cost results were further stratified by single-stage progression vs progression of > 1 stage.
Statistical Analyses
Within the Medicare and Commercial cohorts, Poisson regression models were used to evaluate the role of a priori-defined independent variables in predicting progression from each CKD stage within 1 year. Independent variables (age [continuous] sex, region, all defined comorbidities [heart failure, diabetes, hypertension, cardiovascular disease, and hyperkalemia], RAASi dose level, visit frequency [frequent/infrequent], and diuretics [loop/other/none]) were evaluated using a stepwise selection procedure (α = 0.05). Interaction terms (selected a priori for clinical significance) included heart failure with hyperkalemia and RAASi therapy with specified comorbidities (diabetes, cardiovascular disease, hypertension, and hyperkalemia).
The significance of the difference in mean cost increase between patients who progressed and those who did not was evaluated by t-test. Differences in mean change in cost for patients with single-stage vs multi-stage progression among patients who progressed within 1 year were compared using ANOVA. Multivariate linear regression models were developed for predictors of cost of CKD progression, and logistic regression models were developed for predictors of single-stage vs multi-stage progression during 1 year. The cost of progression for Medicare vs Commercial patients within each CKD stage was compared using a repeated measures ANOVA. Cox proportional hazards analyses were conducted to assess factors associated with time in each stage over the 3-year outcome period in the Commercial and Medicare groups. As this was a longitudinal analysis, each patient served as his/her own pre-index cost basis.
All statistical analyses were performed using SAS/STAT® software, version 9.4 (SAS Institute, Cary, NC). P-values > .05 were considered significant.
Results
Study Population
The study population (N = 189,799) consisted of 52,280 patients aged > 65 years (Commercial insurance) and 137,519 patients aged ≥ 65 years (Medicare). The mean ages of these groups were 55.4 and 75.2 years, respectively; the Medicare cohort had more females (67% vs 51%) and fewer African Americans (8% vs 20%) than the Commercial cohort (Table 1; Supplementary Table 4).
Rate of CKD Progression
The rate of CKD progression within the first year was highest in patients with stage 3a/3b disease (19%-22%) in both the Commercial and Medicare groups vs approximately 10% of stage 2 patients (Figure 1). CKD progression was seen in 16%-17% of stage 2 patients vs 30% to 33% of stage 3a/3b patients by 2 years, and in 23% of stage 2 patients vs 38%-43% of stage 3a/3b patients by 3 years. Rates of progression by > 1 stage increased over time, and progression by > 1 stage was generally more common among Commercial patients than among Medicare patients. The rate of progression from stage 4/5 to ESRD was also higher in Commercial vs Medicare patients. Progression from CKD stages 3a/3b to ESRD occurred at lower, but still meaningful, rates during the 3-year post-index observation period.
Predictors of CKD Progression at 1 Year
Regression analysis by payer group for each CKD stage showed that independent predictors identified for the Commercial and Medicare groups differed; however, several factors were consistently identified across models (Table 2). Among comorbidities, diabetes was the most consistent predictor of CKD progression. Compared to patients without diabetes, patients with diabetes had a higher risk of progression from stage 2, stage 3a, and stage 3b, for both insurance groups. Diabetes was also predictive of progression from stage 4/5 to ESRD in the Commercial group but not in the Medicare group. Heart failure, cardiovascular disease, and pre-index hyperkalemia were also consistent predictors of CKD progression, whereas hypertension was generally associated with lower rates of progression in Medicare patients but had no effect on progression in Commercial patients. Prescriptions for loop diuretics were consistently associated with higher risk of CKD progression. Frequent health care visits (≥ 2/year) were generally associated with lower risk of progression. Demographic factors did not consistently predict CKD progression, although age, sex, and region were retained in the final Poisson regression models at some stages.
Time in CKD Stage
Patients who progressed within 3 years stayed in their index CKD stage for a mean of 12 to 16 months before progressing. On average, patients stayed slightly longer in stage 2 before progressing than in stages 3a or 3b, and patients in the Medicare group stayed slightly longer in each stage than those in the Commercial group (Supplementary Figure 2).
Predictors of Time in CKD Stage
Cox proportional hazards analyses evaluated factors associated with time in each stage over the 3-year outcome period in the Commercial and Medicare groups. Diabetes was a strong and significant predictor of faster progression (ie, shorter time in stage) at all CKD stages. In the Commercial group, diabetes increased the hazard for progression by 40.3% to 81.5% in stage 2 patients, depending on the RAASi level; by 42.1% in stage 3a; by 35.3% in stage 3b; and by 12.4% to 96.8% in stage 4/5 patients, again depending on RAASi dose level (Supplementary Table 5). In the Medicare group, diabetes increased the likelihood for progression by 34.6% in stage 2, 26.4% in stage 3a, 30.7% in stage 3b, and 26.2% in stage 4/5 (Supplementary Table 6).
Heart failure was predictive of faster progression in stage 2 patients without evidence of hyperkalemia and in stage 3a patients in the Commercial group, and in stage 3a patients and in stage 3b patients without evidence of hyperkalemia in the Medicare group. Cardiovascular disease was associated with a small increase in the hazard of CKD stage progression at stage 2 (also at stage 3a in the Medicare group), but with reduced likelihood for progression in stage 4/5.
A history of pre-index hyperkalemia was often associated with faster CKD stage progression. In the Commercial group, hyperkalemia increased the likelihood for progression by 14.9% in stage 2 patients without evidence of heart failure and by 10.8% in stage 3a patients (Supplementary Table 5). In the Medicare group, hyperkalemia was associated with increased likelihood for progression by 14.0% to 41.8% in stage 2 patients without evidence of heart failure, depending on the RAASi dose level; by 27.7% in stage 3a patients; and by 22.0% in stage 3b patients (Supplementary Table 6).
Prescriptions for loop diuretics were strongly associated with faster CKD stage progression, increasing the hazard by 71.1% in stage 2, 55.5% in stage 3a, 46.9% in stage 3b, and nonsignificantly by 11.0% in stage 4/5 in the Commercial group; and by 63.2% in stage 2, 32.3% in stage 3a, 24.5% in stage 3b, and 19.2% in stage 4/5 in the Medicare group. RAASi dose level was independently associated with progression in the Medicare group, but its impact varied, depending on disease stage, from increased likelihood of progression in stage 2 to decreased likelihood in stage 4/5.
Incremental Cost of CKD Progression at 1 Year
At each index CKD stage in both the Commercial and Medicare groups, patients who progressed within 1 year had greater increases in costs over the previous year compared with patients without disease progression, as shown in Figure 2; all differences P > .0001. The incremental cost of progression was significantly higher at each successive stage in both insurance groups, with the exception of progression from stage 3a compared with progression from stage 2 in Medicare patients (NS; all other differences P > .001). The cost increase with each stage of CKD progression was sharper in Commercial than in Medicare patients. The incremental annualized cost of progression ranged from $29,687 at stage 2 to $67,417 at stage 4-5 in Commercial patients compared with $14,451 at stage 2 to $33,273 at stage 4-5 in Medicare patients. The cost increases were greater for progression by > 1 stage compared with progression by 1 stage, and in turn, for no progression (Figure 3) (eg, for stage 3a, Commercial: $76,823, $27,385, and $7,228, respectively; Medicare: $37,403, $12,747, and $4,138). Patients who were not prescribed RAASi tended to have greater cost increases compared with those prescribed RAASi, which was evident at early disease stages regardless of CKD stage progression (including those with no progression from their index stage) (Supplementary Figure 3).
Discussion
This longitudinal observational study demonstrates that the rate of CKD progression is highest at stages 3a and 3b, where approximately 20% of patients had progressed by 1 year and ~40% had progressed by 3 years. Poisson regression analysis showed that comorbid diabetes, heart failure, cardiovascular disease, and—surprisingly—pre-index hyperkalemia were significantly associated with progression within the first year. Cox proportional hazards modeling of time in CKD stage identified diabetes, heart failure, and pre-index hyperkalemia among independent factors associated with shorter time spent in CKD stages, especially in the early stages. Rates of progression were higher in the Commercial group than in the Medicare group. Our findings underscore the need to focus on avoidable drivers of CKD progression and cost, especially in the context of efforts to optimize chronic diabetes, heart failure, and hypertension management. The identification of pre-index hyperkalemia as a potentially avoidable driver of cost (while its association is more difficult to interpret and may reflect confounding by severity) provides a straightforward mechanism by which the treatment of hyperkalemia can test causality in future studies.
Our data showed that CKD progression was more common and more rapid in the Commercial cohort. Younger populations tend to have intrinsic renal parenchymal disease or glomerular disease, whereas older populations usually have kidney disease due to underlying cardiac or vascular disease. However, the difference in CKD progression rates between the Commercial and Medicare groups may also reflect a selection bias, inasmuch as only patients with 3 years of post-index data were included in this study. Patients who died within the first 3 years were excluded, and the Medicare group may have been skewed by the deaths of older patients in later CKD stages.
The rate of CKD progression appears to accelerate from stage 2 to stage 4/5. The transition from stage 2 to stage 3a may lead to use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, if not already prescribed.18-21 Interestingly, RAASi dose level was associated with more rapid CKD progression at stage 2 in the present study, and was only associated with slower progression in stage 4/5 disease in the Medicare group. Angiotensin blockade is known to increase serum creatinine due to greater dilation of efferent than afferent glomerular arterioles that leads to reduced intraglomerular hydrostatic pressure; this effect is seen early in the course of treatment and normally stabilizes.22 Furthermore, patients with significant proteinuria may be more likely to receive RAASi but also more likely to progress.
For an observational study, the longitudinal design provides a unique approach for evaluating the cost of CKD progression in a real-world setting, allowing patients to serve as their own controls. The incremental cost for the 1-year post-index period compared with the previous year was higher at each successive stage for patients with progression compared with nonprogressed patients. Moreover, cost increases were greater for patients with > 1 stage progression compared with 1 stage progression. Notably, the cost increases associated with CKD progression were higher among Commercial patients than Medicare patients, likely reflecting differences in reimbursement rates and the types of kidney disease within a younger population. Costs are well recognized to be high for CKD patients with diabetes, heart failure, and previous cardiovascular events.23-27
Additional focus may need to be placed on hyperkalemia management. Interestingly, we observed that patients prescribed RAASi tended to have lower cost increases than those who were not prescribed RAASi, particularly at early CKD stages but also among patients with no stage progression. This observation suggests that use of RAASi in early CKD stages may be beneficial not only clinically but also economically. The use of RAASi at recommended doses is often limited by hyperkalemia,28-30 but recent data suggest that correcting hyperkalemia with potassium binder agents allows patients to continue receiving RAASi without lowering the dosage.31,32 Furthermore, hyperkalemia is common in patients with advanced CKD, reflecting reduced renal excretion of potassium, and has been found to be an independent predictor of all-cause mortality and cardiovascular events.33-35 Notably, in our study the models identified hyperkalemia as an independent predictor of CKD progression in stages 2, 3a, and 3b, but not in stage 4/5. This may be a function of the smaller sample size in the later stages. Furthermore, in the advanced CKD stages, patients are likely to have competing comorbidities, including uncontrolled blood pressure and cardiovascular disease; and accordingly, the effect of hyperkalemia may get excluded from the multivariate models.
Several limitations of our study should be noted. First, the study required an eGFR measurement or diagnosis code to qualify for CKD stage progression. Decreases in eGFR may be indicative of other processes besides progression, such as acute kidney injury or underlying subclinical disease. Acute kidney injury may have a variable effect on serum creatinine trajectories and eGFR measurement, and thereby influence apparent CKD stage.36 Moreover, CKD stage determined by eGFR is known to fluctuate over short time periods.37 However, the observations of increasing comorbidities, RAASi dose levels, and diuretic use are consistent with clinical expectations for CKD progression, and thus provide some reassurance that the eGFR paradigm used herein was largely detecting advancing CKD stage. Second, the calculation of eGFR varies at different sites; the individual methods used were not accessible within the Humedica database. Although this may contribute to variation in staging and progression, which is typical for a large database analysis, the longitudinal design allowed patients to serve as their own controls, such that eGFR calculation likely remained constant for each patient over time unless their provider system changed methods during the study. Third, race/ethnicity was not recorded for a large proportion of patients, and patients resided mostly in the South and Midwest regions, with limited numbers from the West. Therefore, the present data may not be fully representative of the entire US CKD population. Finally, as noted above, survival bias and selection bias may have influenced the results, as only patients with post-index data for 3 years were included, thus excluding patients who expired during that period.
Conclusion
In summary, we confirmed traditional risk factors for CKD progression but also identified hyperkalemia as an independent risk factor for progression. We showed that the rate and cost of CKD progression is potentially greater in younger patients. These findings underscore the importance of monitoring patients regularly, treating proteinuria and hyperkalemia, and potentially devising management protocols for younger patients in whom disease may be more rapidly progressive than in their older counterparts. More studies are needed to better delineate the drivers of progression in the younger population as compared to older populations, with specific attention paid to the pathophysiological differences between these 2 groups.
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