Chronic Kidney Disease (CKD) induced Hyperparathyroidism (HPT), Hyperphosphatemia (HP), and Hyperkalemia (HK)

Chronic kidney disease (CKD), or chronic renal disease, is a condition characterized by a gradual loss of kidney function over time. In the early stages, CKD is a largely asymptomatic condition that damages the kidneys and leads to the loss of kidney function over time (Centers for Disease Control and Prevention, 2019). As the disease progresses, the symptoms worsen and eventually lead to kidney failure (Centers for Disease Control and Prevention, 2019). The glomerular filtration rate (GFR), a key measure of kidney function, is determined by the amount of creatinine in the blood, and the Kidney Disease Improving Global Outcomes (KDIGO) classification system is considered as the standard for GFR measurement and diagnosis of CKD (Levin et al., 2013).

In the 7MM, the diagnosed prevalent cases of CKD are expected to increase from 8,569,869 cases in 2020 to 9,440,881 cases in 2030, at an Annual Growth Rate (AGR) of 1.01%. In 2030, the US will have the highest number of diagnosed prevalent cases of CKD in the 7MM, with 4,253,149 diagnosed prevalent cases, whereas Italy will have the fewest diagnosed prevalent cases with 339,208 cases. In the 7MM, the total prevalent cases of CKD are expected to increase from 97,176,505 cases in 2020 to 107,283,608 cases in 2030, at an AGR of 1.04%. The publisher epidemiologists attribute the increase in the diagnosed prevalent cases and total prevalent cases of CKD to population dynamics in each market.

Scope

This report provides an overview of the risk factors, comorbidities, and the global and historical epidemiological trends for CKD in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan). The report includes a 10-year epidemiology forecast for the diagnosed and total prevalent cases of CKD. The diagnosed and total prevalent cases of CKD are segmented by age (18 years and older), sex, and stage. The diagnosed prevalent cases of CKD are segmented based on dialysis-dependent and non-dialysis-dependent cases
The dialysis dependent cases are further segmented by hemodialysis-dependent and peritoneal dialysis-dependent. Additionally, the diagnosed prevalent cases of CKD were further segmented by hyperparathyroidism, hyperphosphatemia, and hyperkalemia among dialysis-dependent and non-dialysis-dependent cases. This epidemiology forecast for CKD is supported by data obtained from peer-reviewed articles and population-based studies
The CKD epidemiology report is written and developed by Masters- and PhD-level epidemiologists
The Epidemiology Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM

Reasons to Buy this Report

The CKD Epidemiology series will allow you to:

Develop business strategies by understanding the trends shaping and driving the global CKD market
Quantify patient populations in the global CKD market to improve product design, pricing, and launch plans
Organize sales and marketing efforts by identifying the age groups that present the best opportunities for CKD therapeutics in each of the markets covered
Understand magnitude of CKD by stage, hemodialysis-dependent and peritoneal dialysis-dependent; hyperparathyroidism, hyperphosphatemia, and hyperkalemia among dialysis-dependent and non-dialysis-dependent cases of CKD.

1. CKD - Hyperparathyroidism, Hyperphosphatemia, and Hyperkalemia: Executive Summary

1.1 Catalyst
1.2 Related Reports
1.3 Upcoming Reports

2. Epidemiology

2.1 Disease Background
2.2 Risk Factors and Comorbidities
2.3 Global and Historical Trends
2.4 7MM Forecast Methodology
2.4.1 Sources
2.4.2 Forecast Assumptions and Methods
2.4.3 Forecast Assumptions and Methods: Diagnosed Prevalent Cases of CKD - 7MM
2.4.4 Forecast Assumptions and Methods: Total Prevalent Cases of CKD
2.4.5 Forecast Assumptions and Methods: Diagnosed and Total Prevalent Cases of CKD by Stage
2.4.6 Diagnosed Prevalent Cases of CKD Based on Dialysis Dependence
2.4.7 Diagnosed Prevalent Cases of CKD with Hyperparathyroidism Among Dialysis-Dependent and Non-Dialysis-Dependent CKD Cases
2.4.8 Diagnosed Prevalent Cases of CKD with Hyperphosphatemia Among Dialysis Dependent and Non-dialysis Dependent CKD Cases
2.4.9 Diagnosed Prevalent Cases of CKD with Diagnosed Prevalent Cases of CKD with Hyperkalemia Among Dialysis-Dependent and Non-Dialysis-Dependent CKD Cases
2.5 Epidemiological Forecast for Chronic Kidney Disease Hyperparathyroidism, Hyperphosphatemia and Hyperkalemia (2020-2030)
2.5.1 Diagnosed Prevalent Cases of CKD
2.5.2 Age-Specific Diagnosed Prevalent Cases of CKD
2.5.3 Sex-Specific Diagnosed Prevalent Cases of CKD
2.5.4 Diagnosed Prevalent Cases of CKD by Stage
2.5.5 Diagnosed Prevalent Cases of CKD Based on Dialysis Dependence
2.5.6 Diagnosed Prevalent Cases of CKD with Hyperparathyroidism Among Dialysis-Dependent and Non-dialysis-Dependent CKD Cases
2.5.7 Diagnosed Prevalent Cases of CKD with Hyperphosphatemia Among Dialysis-Dependent and Non-Dialysis-Dependent CKD Cases
2.5.8 Diagnosed Prevalent Cases of CKD With Hyperkalemia Among Dialysis-Dependent and Non-Dialysis-Dependent CKD Cases
2.5.9 Total Prevalent Cases of CKD
2.5.10 Age-Specific Total Prevalent Cases of CKD
2.5.11 Sex-Specific Total Prevalent Cases of CKD
2.5.12 Total Prevalent Cases of CKD by Stage
2.6 Discussion
2.6.1 Epidemiological Forecast Insight
2.6.2 COVID-19 Impact
2.6.3 Limitations of the Analysis
2.6.4 Strengths of the Analysis

3. Appendix

3.1 Bibliography
3.2 About the Authors
3.2.1 Epidemiologist
3.2.2 Reviewers
3.2.3 Global Director of Therapy Analysis and Epidemiology
3.2.4 Global Head and EVP of Healthcare Operations and Strategy

Contact

List of Tables

Table 1: Summary of Newly Added Data Types
Table 2: Summary of Updated Data Types
Table 3: KDIGO Classification of CKD
Table 4: Risk Factors and Comorbidities for CKD

List of Figures

Figure 1: 7MM, Diagnosed Prevalent Cases of CKD, Both Sexes, N, Ages =18 Years, 2020 and 2030
Figure 2: 7MM, Total Prevalent Cases of CKD, Both Sexes, N, Ages =18 Years, 2020 and 2030
Figure 3: 7MM, Diagnosed Prevalence of CKD, Men and Women, %, Ages =18 Years, 2020
Figure 4: 7MM, Total Prevalence of CKD, Men and Women, %, Ages =18 Years, 2020
Figure 5: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of CKD
Figure 6: 7MM, Sources Used to Forecast the Diagnosed and Total Prevalent Cases of CKD by Stage
Figure 7: 7MM, Sources Used and Not Used to Forecast the Diagnosed Prevalent Cases of CKD Based on Dialysis Dependence
Figure 8: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of CKD with Hyperparathyroidism, Hyperphosphatemia, and Hyperkalemia Among Dialysis-Dependent and Non-dialysis-Dependent CKD Cases
Figure 9: 7MM, Sources Used and Not Used to Forecast the Total Prevalent Cases of CKD
Figure 10: 7MM, Diagnosed Prevalent Cases of CKD, N, Both Sexes, Ages =18 Years, 2020
Figure 11: 7MM, Diagnosed Prevalent Cases of CKD by Age, N, Both Sexes, 2020
Figure 12: 7MM, Diagnosed Prevalent Cases of CKD by Sex, N, Ages =18 Years, 2020
Figure 13: 7MM, Diagnosed Prevalent Cases of CKD by Stage, N, Both Sexes, Ages =18 Years, 2020
Figure 14: 7MM, Diagnosed Prevalent Cases of CKD Based on Dialysis Dependence, N, Both Sexes, Ages =18 Years, 2020
Figure 15: 7MM, Diagnosed Prevalent Cases of CKD with Hyperparathyroidism, N, Both Sexes, Ages =18 Years, 2020
Figure 16: 7MM, Diagnosed Prevalent Cases of CKD With Hyperphosphatemia, N, Both Sexes, Ages =18 Years, 2020
Figure 17: 7MM, Diagnosed Prevalent Cases of CKD with Hyperkalemia, N, Both Sexes, =18 Years, 2020
Figure 18: 7MM, Total Prevalent Cases of CKD, N, Both Sexes, Ages =18 Years, 2020
Figure 19: 7MM, Diagnosed Total Cases of CKD by Age, N, Both Sexes, 2020
Figure 20: 7MM, Total Prevalent Cases of CKD by Sex, N, Ages =18 Years, 2020
Figure 21: 7MM, Total Prevalent Cases of CKD by Stage, N, Both Sexes, Ages =18 Years, 2020

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Chronic Kidney Disease (CKD) induced Hyperparathyroidism (HPT), Hyperphosphatemia (HP), and Hyperkalemia (HK) - Epidemiology Forecast to 2030

Table of Contents

Table of Contents

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