Progressive chronic kidney disease in primary care: modifiable risk factors and predictive model

Real-world evidence for steroidal mineralocorticoid receptor antagonists in patients with chronic kidney disease

Background

Mineralocorticoid receptor antagonists (MRAs) were shown to delay chronic kidney disease (CKD) progression in patients with hypertension and/or heart failure (HF) and proteinuria.

Objective

We conducted a systematic literature review on real-world evidence to identify the literature gaps related to the efficacy and safety outcomes of MRAs administered to CKD patients.

Results

A total of 751 records were identified of which, 23 studies (26 publications) were analyzed. Studies included heterogeneous populations, including the overall CKD, CKD and diabetes, CKD and HF, and CKD and a history of cardiovascular disease. Most of the studies were small and non-rigorous, resulting in a notable lack of evidence in these populations. In the overall CKD population, steroidal MRAs resulted in a significant or sustained eGFR reduction but no efficacy in delaying progression to end-stage kidney disease. No cardiovascular protection was found. Results for all-cause mortality and hospitalization for HF were inconsistent; however, the longest follow-up studies indicate similar or lower incidence for spironolactone non-users. Most results consistently reported a higher incidence of hyperkalemia among patients on steroidal MRAs in all CKD stages, and side effects led to high discontinuation rates in the real-world setting.

Conclusions

Despite the limited availability of evidence on the effectiveness and safety of steroidal MRAs in CKD patients and subgroups with diabetes, HF or history of cardiovascular disease, MRAs were shown to have a limited effect on renal and cardiovascular outcomes. Gaps in the evidence regarding the efficacy and safety of MRAs are particularly relevant in diabetic CKD patients; therefore, further research is warranted.

Comorbidity, life-style factors and healthcare utilization in incident chronic kidney disease: sex-specific analyses of claims data

BACKGROUND

Chronic kidney disease (CKD) is common in aging men and women. In contrast to other European countries, Germany lacks CKD registries. The aim of this study was to determine the incidence of CKD stages 2-5 in men and women in Germany. Furthermore, differences between the sexes in terms of comorbidities, potentially inappropriate medications (PIM), and healthcare utilization were examined.

METHODS

In this retrospective observational study, claims data from members of a statutory health insurance fund aged 18 years or older with incident CKD between 2011 and 2018 were analyzed. Incident CKD was defined as having two confirmed diagnoses of CKD stages 2-5 from outpatient care or one primary or secondary diagnosis from inpatient care.

RESULTS

The age- and sex-standardized incidence of all CKD stages was 945/100 000 persons between 2011 and 2018. Incident CKD, especially stages 3 and 4, occurred more frequently in women, while the incidence of stages 2 and 5 was higher in men. While women visited their GP more frequently and were prescribed PIMs more often, men were more likely to visit a nephrologist and were more often hospitalized after the incident CKD diagnosis.

CONCLUSION

More awareness needs to be raised towards the early detection of CKD and the use of PIMs, especially in women. Improved care coordination is needed to avoid an overprovision of patients with uncomplicated incident stages and ensure that patients with advanced CKD stages get timely access to specialist care.

A systematic review of statistical methodology used to evaluate progression of chronic kidney disease using electronic healthcare records

Background

Electronic healthcare records (EHRs) are a useful resource to study chronic kidney disease (CKD) progression prior to starting dialysis, but pose methodological challenges as kidney function tests are not done on everybody, nor are tests evenly spaced. We sought to review previous research of CKD progression using renal function tests in EHRs, investigating methodology used and investigators’ recognition of data quality issues.

Methods and findings

We searched for studies investigating CKD progression using EHRs in 4 databases (Medline, Embase, Global Health and Web of Science) available as of August 2021. Of 80 articles eligible for review, 59 (74%) were published in the last 5.5 years, mostly using EHRs from the UK, USA and East Asian countries. 33 articles (41%) studied rates of change in eGFR, 23 (29%) studied changes in eGFR from baseline and 15 (19%) studied progression to binary eGFR thresholds. Sample completeness data was available in 44 studies (55%) with analysis populations including less than 75% of the target population in 26 studies (33%). Losses to follow-up went unreported in 62 studies (78%) and 11 studies (14%) defined their cohort based on complete data during follow up. Methods capable of handling data quality issues and other methodological challenges were used in a minority of studies.

Conclusions

Studies based on renal function tests in EHRs may have overstated reliability of findings in the presence of informative missingness. Future renal research requires more explicit statements of data completeness and consideration of i) selection bias and representativeness of sample to the intended target population, ii) ascertainment bias where follow-up depends on risk, and iii) the impact of competing mortality. We recommend that renal progression studies should use statistical methods that take into account variability in renal function, informative censoring and population heterogeneity as appropriate to the study question.

Diabetes, Hypertension, and Incidence of Chronic Kidney Disease: Is There any Multiplicative or Additive Interaction?

BACKGROUND

The burden of chronic kidney disease (CKD) is on the rise worldwide; diabetes and hypertension are mentioned as the main contributors.

OBJECTIVES

The current study aimed to investigate the multiplicative and additive interaction of diabetes and hypertension in the incidence of CKD.

METHODS

In this population-based cohort study, 7342 subjects aged 20 years or above (46.8% male) were divided into four groups: no diabetes and hypertension; diabetes and no hypertension; hypertension and no diabetes; and both diabetes and hypertension. The multivariable Cox regression was used to determine the effect of diabetes, hypertension, and their multiplicative interaction on CKD. The following indices were used to determine the additive interaction of diabetes and hypertension: the relative excess risk of interaction, the attributable proportion due to interaction, and the synergism index.

RESULTS

Diabetes and hypertension had no significant multiplicative interaction in men (hazard ratio of 0.93, P value: 0.764) and women (hazard ratio of 0.79, P value: 0.198); furthermore, no additive interaction was found in men (relative excess risk due to interaction of 0.79, P value: 0.199; attributable proportion due to interaction of 0.22, P value: 0.130; synergy index of 1.44, P value: 0.183) and women (relative excess risk due to interaction of -0.26, P value: 0.233, attributable proportion due to interaction of -0.21, P value: 0.266; synergy index of 0.48, P value: 0.254).

CONCLUSIONS

This study demonstrated no synergic effect between diabetes and hypertension on the incidence of CKD.

Development of risk models for major adverse chronic renal outcomes among patients with type 2 diabetes mellitus using insurance claims: a retrospective observational study

Objective: To develop and validate models allowing the prediction of major adverse chronic renal outcomes (MACRO) in patients with type 2 diabetes mellitus (T2DM) using insurance claims data.Methods: The Optum Integrated Real World Evidence Electronic Health Records and Claims de-identified database (10/01/2006-09/30/2016) was used to identify T2DM patients ≥50 years old. Risk factors were assessed over a 12-month baseline period, and MACRO were subsequently assessed until the end of data availability, continuous enrollment, or death. Separate models were built for moderate-to-severe diabetic kidney disease (DKD), end-stage renal disease (ESRD), and renal death. A random split-sample approach was employed, where 70% of the sample served for model development (training set) and the remaining 30% served for validation (testing set). C-statistics were used to assess model performance.Results: A total of 160,031 patients were included. Risk factors associated with MACRO for all models included adapted diabetes complications severity index, heart failure, anemia, diabetic nephropathy, and CKD. C-statistics ranged between 0.70 (moderate-to-severe DKD) and 0.84 (renal death) in the testing set. A substantial proportion (e.g. 88.7% for moderate-to-severe DKD) of patients predicted to be at high-risk of MACRO did not have diabetic nephropathy, proteinuria, or CKD at baseline.Conclusions: The models developed using insurance claims data could reliably predict the risk of MACRO in patients with T2DM and enabled patients at higher-risk of DKD to be identified in the absence of baseline diabetic nephropathy, CKD, or proteinuria. These models could help establish strategies to reduce the risk of MACRO in T2DM patients.

Comparison and development of machine learning tools in the prediction of chronic kidney disease progression

BACKGROUND

Urinary protein quantification is critical for assessing the severity of chronic kidney disease (CKD). However, the current procedure for determining the severity of CKD is completed through evaluating 24-h urinary protein, which is inconvenient during follow-up.

OBJECTIVE

To quickly predict the severity of CKD using more easily available demographic and blood biochemical features during follow-up, we developed and compared several predictive models using statistical, machine learning and neural network approaches.

METHODS

The clinical and blood biochemical results from 551 patients with proteinuria were collected. Thirteen blood-derived tests and 5 demographic features were used as non-urinary clinical variables to predict the 24-h urinary protein outcome response. Nine predictive models were established and compared, including logistic regression, Elastic Net, lasso regression, ridge regression, support vector machine, random forest, XGBoost, neural network and k-nearest neighbor. The AU-ROC, sensitivity (recall), specificity, accuracy, log-loss and precision of each of the models were evaluated. The effect sizes of each variable were analysed and ranked.

RESULTS

The linear models including Elastic Net, lasso regression, ridge regression and logistic regression showed the highest overall predictive power, with an average AUC and a precision above 0.87 and 0.8, respectively. Logistic regression ranked first, reaching an AUC of 0.873, with a sensitivity and specificity of 0.83 and 0.82, respectively. The model with the highest sensitivity was Elastic Net (0.85), while XGBoost showed the highest specificity (0.83). In the effect size analyses, we identified that ALB, Scr, TG, LDL and EGFR had important impacts on the predictability of the models, while other predictors such as CRP, HDL and SNA were less important.

CONCLUSIONS

Blood-derived tests could be applied as non-urinary predictors during outpatient follow-up. Features in routine blood tests, including ALB, Scr, TG, LDL and EGFR levels, showed predictive ability for CKD severity. The developed online tool can facilitate the prediction of proteinuria progress during follow-up in clinical practice.

Fast GFR decline and progression to CKD among primary care patients with preserved GFR

BACKGROUND

Fast glomerular filtration rate (GFR) decline is associated with adverse outcomes, but the associated risk factors among patients without chronic kidney disease (CKD) are not well defined.

METHODS

From a primary care registry of 37,796, we identified 2219 (6%) adults with at least three estimated (e)GFR values and a baseline eGFR between 60 and 119 ml/min/1.73 m² during an observation period of 8 years. We defined fast GFR decline as > 5 ml/min/1.73 m² per year. The outcome measure was incident CKD (eGFR < 60 ml/min/1.73 m²). Clinical and demographic characteristics were compared using Chi-square and independent-samples t tests.

RESULTS

Older age, African-American race, unmarried status, hypertension and type 2 diabetes were more common in both fast decliners and those who developed incident CKD (p < 0.0001 to < 0.05). Lower neighborhood socioeconomic status, current smoking and baseline eGFR 90-119 ml/min/1.73 m² were associated with fast decline (p < 0.01), while baseline eGFR 60-74 ml/min/1.73 m² with incident CKD (p < 0.05). In multivariate regression models, among fast decliners with mildly reduced baseline eGFR (60-89 ml/min/1.73 m²), older age was significantly associated with incident CKD [odds ratio (OR) 1.04; 95% CI 1.01-1.08], and among those with normal baseline eGFR (≥ 90-119 ml/min/1.73 m²), type 2 diabetes was significantly associated with incident CKD (OR 3.83; 95% CI 1.35-10.89).

CONCLUSIONS

Among primary care patients without CKD, GFR is checked infrequently. We have identified patients at high risk of progressive CKD, in whom we suggest a closer monitoring of renal function.

CE: Improving Outcomes for Patients with Chronic Kidney Disease: Part 1

: The burden of chronic kidney disease (CKD) is rising both in this country and worldwide. An estimated 10% to 15% of U.S. adults are currently living with CKD. Reducing the CKD burden requires a systematic, interdisciplinary approach to care. The greatest opportunities to reduce the impact of CKD arise early, when most patients are being followed in primary care; yet many clinicians are inadequately educated on this disease. Nurses are well positioned to facilitate the implementation of collaborative care. This two-part article aims to provide nurses with the basic information necessary to assess and manage patients with CKD. Part 1 offers an overview of the disease, describes identification and etiology, and discusses ways to slow disease progression. Part 2, which will appear next month, addresses disease complications and treatment of kidney failure.

Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study

Background

Chronic kidney disease (CKD) is a growing public health challenges worldwide. Various studies have investigated risk factors of incident CKD; however, a very few studies examined interaction between these risk factors. In an attempt to clarify the potential interactions between risk factors of CKD, we performed survival tree analysis.

Methods

A total of 8238 participants (46.1% men) aged > 20 years without CKD at baseline [(1999–2001) and (2002–2005)], were followed until 2014. The first occurrence of CKD, defined as the estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m², was set as the main outcome. Multivariable Cox proportional hazard (Cox PH) regression was used to identify significant independent predictors of CKD; moreover, survival tree analysis was performed to gain further insight into the potential interactions between predictors.

Results

The crude incidence rates of CKD were 20.2 and 35.2 per 1000 person-years in men and women, respectively. The Cox PH identified the main effect of significant predictors of CKD incidence in men and women. In addition, using a limited number of predictors, survival trees identified 12 and 10 subgroups among men and women, respectively, with different survival probability. Accordingly, a group of men with eGFR > 74 ml/min/1.73 m², age ≤ 46 years, low level of physical activity, waist circumference ≤ 100 cm and FPG ≤ 4.7 mmol/l had the lowest risk of CKD incidence; while men with eGFR ≤ 63.4 ml/min/1.73 m², age > 50 years had the highest risk for CKD compared to men in the lowest risk group [hazard ratio (HR), 70.68 (34.57–144.52)]. Also, a group of women aged ≤ 45 years and eGFR > 83.5 ml/min/1.73 m² had the lowest risk; while women with age > 48 years and eGFR ≤ 69 ml/min/1.73 m² had the highest risk compared to low risk group [HR 27.25 (19.88–37.34)].

Conclusion

In this post hoc analysis, we found the independent predictors of CKD using Cox PH; furthermore, by applying survival tree analysis we identified several numbers of homogeneous subgroups with different risk for incidence of CKD. Our study suggests that two methods can be used simultaneously to provide new insights for intervention programs and improve clinical decision making.

The Tubulointerstitial Pathophysiology of Progressive Kidney Disease

Accumulating evidence suggests that the central locus for the progression of CKD is the renal proximal tubule. As injured tubular epithelial cells dedifferentiate in attempted repair, they stimulate inflammation and recruit myofibroblasts. At the same time, tissue loss stimulates remnant nephron hypertrophy. Increased tubular transport workload eventually exceeds the energy-generating capacity of the hypertrophied nephrons, leading to anerobic metabolism, acidosis, hypoxia, endoplasmic reticulum stress, and the induction of additional inflammatory and fibrogenic responses. The result is a vicious cycle of injury, misdirected repair, maladaptive responses, and more nephron loss. Therapy that might be advantageous at one phase of this progression pathway could be deleterious during other phases. Thus, interrupting this downward spiral requires narrowly targeted approaches that promote healing and adequate function without generating further entry into the progression cycle.

Social Determinants of Racial Disparities in CKD

Significant disparities in CKD rates and outcomes exist between black and white Americans. Health disparities are defined as health differences that adversely affect disadvantaged populations, on the basis of one or more health outcomes. CKD is the complex result of genetic and environmental factors, reflecting the balance of nature and nurture. Social determinants of health have an important role as environmental components, especially for black populations, who are disproportionately disadvantaged. Understanding the social determinants of health and appreciating the underlying differences associated with meaningful clinical outcomes may help nephrologists treat all their patients with CKD in an optimal manner. Altering the social determinants of health, although difficult, may embody important policy and research efforts, with the ultimate goal of improving outcomes for patients with kidney diseases, and minimizing the disparities between groups.

Primacy of lowered baseline glomerular filtration rate as a risk for incident chronic kidney disease: A longitudinal study in Japanese subjects

AIM

Risk profile for incident chronic kidney disease (CKD) in Japanese subjects has not been established. Our aim was to identify risk factors for CKD in Japanese.

METHODS

Consecutive 171 536 health examinees (median age 49 years and estimated glomerular filtration rate (eGFR) 78.2 mL/min per 1.73 m² ) without CKD were re-examined after a median period of 6.2 years. Results of Cox proportional hazards models in randomly assigned two thirds (Derivation cohort) were verified in the rest (Validation cohort). CKD was defined as eGFR <60 mL/min per 1.73 m² or positive dipstick proteinuria.

RESULTS

In the Derivation cohort, CKD developed in 1002 (5.8%) subjects. Seven variables such as lower eGFR, male gender, higher uric acid concentration, lower red cell count and higher age and systolic blood pressure were identified as significant risks for CKD, with lowered eGFR being an overwhelmingly strong risk: adjusted hazard ratio for those with the baseline eGFR <70 mL/min per 1.73 m² was as high as 90.1. Performance of prediction of CKD by the probability on the basis of the seven risk factors combined was only marginally preferable to eGFR alone. The area under the receiver operating characteristic curve (95% CI) for the prediction was 0.846 (0.826-0.864) and 0.822 (0.802-0.840) (P < 0.01), the kappa statistic was 0.263 and 0.250 (n.s.), and the mean absolute difference between "predicted probability" and "observed" CKD was 1.4% and 1.9% (P = 0.14) by the combined model and eGFR alone, respectively.

CONCLUSION

Seven risk factors for incident CKD were identified in Japanese health examinees. However, lowered baseline eGFR outweighed other risks to the degree that eGFR alone was suffice for CKD prediction.

Progress in risk prediction for people with chronic kidney disease

PURPOSE OF REVIEW

Chronic kidney disease is common, but the associated risk of adverse outcomes is heterogeneous and methods for risk stratification are, therefore, required. We have reviewed recent progress in developing clinically applicable risk scores for people with chronic kidney disease.

RECENT FINDINGS

Large epidemiological studies have confirmed that lower glomerular filtration rate and albuminuria are the most important risk factors for adverse outcomes in all populations studied. Ongoing research has identified several potentially important novel risk factors, including genetic factors, metabolomic factors, fibroblast growth factor 23, novel cardiovascular risk factors [CXC motif, ligand 12 (CXCL12) and ceruloplasmin], skin autofluorescence and inflammatory markers (serum-free light chains and circulating receptors for tumour necrosis factor). Several risk scores have been developed and one in particular (by Tangri et al.) performs well, uses variables commonly assessed in clinical practice and has been externally validated. Further studies are required to assess its performance in populations outside of secondary care and its usefulness in guiding decision making in clinical practice.

SUMMARY

Although substantial progress has been made, the goal of achieving simple robust risk scores which are widely applicable and effective in guiding clinical decision making remains to be achieved.

Five-year incidence of chronic kidney disease (stage 3-5) and associated risk factors in a Spanish cohort: the MADIABETES Study

Objective

To evaluate the incidence rate of Chronic Kidney Disease (CKD) stage 3-5 (persistent decreased kidney function under 60 mL/min per 1.73 m²) among patients with type 2 diabetes over five years, to identify the risk factors associated with CKD, and develop a risk table to predict five-year CKD stage 3-5 risk stratification for clinical use.

Design

The MADIABETES Study is a prospective cohort study of 3,443 outpatients with type 2 diabetes mellitus, sampled from 56 primary health care centers (131 general practitioners) in Madrid (Spain).

Results

The cumulative incidence of CKD stage 3-5 at five-years was 10.23% (95% CI = 9.12–11.44) and the incidence density was 2.07 (95% CI = 1.83–2.33) cases per 1,000 patient-months or 2.48 (95% CI = 2.19–2.79) cases per 100 patient-years. The highest hazard ratio (HR) for developing CKD stage 3-5 was albuminuria ≥300 mg/g (HR = 4.57; 95% CI= 2.46-8.48). Furthermore, other variables with a high HR were age over 74 years (HR = 3.20; 95% CI = 2.13–4.81), a history of Hypertension (HR = 2.02; 95% CI = 1.42–2.89), Myocardial Infarction (HR= 1.72; 95% IC= 1.25–2.37), Dyslipidemia (HR = 1.68; 95% CI 1.30–2.17), duration of diabetes mellitus ≥ 10 years (HR = 1.46; 95% CI = 1.14-1.88) and Systolic Blood Pressure >149 mmHg (HR = 1.52; 95% CI = 1.02–2.24).

Conclusions

After a five-year follow-up, the cumulative incidence of CKD is concordant with rates described in Spain and other countries. Albuminuria ≥ 300 mg/g and age over 74 years were the risk factors more strongly associated with developing CKD (Stage 3-5). Blood Pressure, lipid and albuminuria control could reduce CKD incidence of CKD in patients with T2DM.