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Chronic Kidney Disease-Anemia – Epidemiology Forecast to 2029

The diagnosed prevalent cases of chronic kidney disease-anemia (CKD-anemia) in the eight major markets (*8MM) are projected to increase from four million cases in 2019 to 4.5 million cases in 2029, equating to an annual growth rate (AGR) of 1.13%. This report reveals that in 2029, China will have the highest number of diagnosed prevalent cases of CKD-anemia in the 8MM at two million, whereas the UK with nearly 74,000 cases will have the lowest number of these cases. The number of diagnosed prevalent cases of CKD-anemia was higher in women than in men in the 8MM combined, though there are variations in the predominant sex by market. This is driven by differences in the diagnosed prevalent cases of CKD by sex, as well as underlying demographic differences in these markets.

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Shilpa Shaji, MPH, Epidemiologist at GlobalData, comments: “Anemia may begin to develop in the early stages of CKD and it tends to worsen as CKD progresses.

“Even though CKD-anemia has been associated with substantial morbidity and mortality, with appropriate treatment modalities such as iron therapy and erythropoiesis-stimulating agents, anemia can be effectively treated and thus the patients’ quality of life can be improved.”

*8MM: The US, 5EU (France, Germany, Italy, Spain, UK), Japan and China

Scope

The CKD-Anemia Epidemiology Report and Model provide an overview of the risk factors and global trends of chronic kidney disease-anemia (CKD-anemia) in the eight major markets (8MM: US, France, Germany, Italy, Spain, UK, Japan, and China).

The report includes a 10-year epidemiology forecast for the diagnosed prevalent cases of CKD-anemia. The diagnosed prevalent cases of CKD-anemia are segmented by age (≥18 years), sex, stage, as well as by cause of anemia (kidney-related causes and other causes), and by dialysis dependency (dialysis-dependent and non-dialysis-dependent) in the 8MM. The model additionally provides diagnosed and total prevalent cases of CKD segmented by age (≥18 years), sex, and stage.

The CKD-anemia epidemiology report and model were 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 8MM.

The Epidemiology Model is easy to navigate, interactive with dashboards, and epidemiology-based with transparent and consistent methodologies. Moreover, the model supports data presented in the report and showcases disease trends over a 10-year forecast period using reputable sources.

Reasons to Buy

The CKD-Anemia Epidemiology series will allow you to:

  • Develop business strategies by understanding the trends shaping and driving the global CKD-anemia markets.
  • Quantify patient populations in the global CKD-anemia markets to improve product design, pricing, and launch plans.
  • Organize sales and marketing efforts by identifying the age groups and sex that present the best opportunities for CKD-anemia therapeutics in each of the markets covered.
  • Understand magnitude of CKD-anemia population by its severity.

Table of Contents

1 Table of Contents

1.1 List of Tables

1.2 List of Figures

2 Chronic Kidney Disease-Anemia: Executive Summary

2.1 Related Reports

2.2 Upcoming Reports

3 Epidemiology

3.1 Disease Background

3.2 Risk Factors and Comorbidities

3.3 Global and Historical Trends

3.4 Forecast Methodology

3.4.1 Sources

3.4.2 Forecast Assumptions and Methods

3.4.3 Diagnosed Prevalent Cases of CKD-Anemia and Diagnosed Prevalent Cases of CKD-Anemia by Stage

3.4.4 Diagnosed Prevalent Cases of CKD-Anemia Based on Dialysis Dependency

3.4.5 Diagnosed Prevalent Cases of CKD-Anemia Based on Cause of Anemia

3.5 Epidemiological Forecast for CKD-Anemia (2019–2029)

3.5.1 Diagnosed Prevalent Cases of CKD-Anemia

3.5.2 Age-Specific Diagnosed Prevalent Cases of CKD-Anemia

3.5.3 Sex-Specific Diagnosed Prevalent Cases of CKD-Anemia

3.5.4 Diagnosed Prevalent Cases of CKD-Anemia by Stage

3.5.5 Diagnosed Prevalent Cases of CKD-Anemia Based on Dialysis Dependency

3.5.6 Diagnosed Prevalent Cases of CKD-Anemia Based on Cause of Anemia

3.6 Discussion

3.6.1 Epidemiological Forecast Insight

3.6.2 Coronavirus Disease 2019 Impact

3.6.3 Limitations of the Analysis

3.6.4 Strengths of the Analysis

4 Appendix

4.1 Bibliography

4.2 Primary Research – Prescriber Survey

4.3 About the Authors

4.3.1 Epidemiologist

4.3.2 Reviewers

4.3.3 Global Director of Therapy Analysis and Epidemiology

4.3.4 Global Head and EVP of Healthcare Operations and Strategy

4.4 About GlobalData

4.5 Contact Us

4.6 Disclaimer

List of Tables

Table 1: Risk Factors and Comorbidities for CKD-Anemia

Table 2: High-Prescribing Physicians (non-KOLs) Surveyed, By Country

List of Figures

Figure 1: 8MM, Diagnosed Prevalent Cases of CKD-Anemia, Both Sexes, N, Ages ≥18 Years, 2019 and 2029

Figure 2: 8MM, Diagnosed Prevalence of CKD-Anemia, Men and Women, %, Ages ≥18 Years, 2019

Figure 3: 8MM, Sources Used and Not Used to Forecast the Diagnosed Prevalent Cases of CKD-Anemia, Diagnosed Prevalent Cases of CKD-Anemia by Stage, and Diagnosed Prevalent Cases of CKD-Anemia Based on Dialysis Dependence

Figure 4: 8MM, Sources Used to Forecast the Diagnosed Prevalent Cases of CKD-Anemia Based on Cause of Anemia

Figure 5: 8MM, Diagnosed Prevalent Cases of CKD-Anemia, N, Both Sexes, Ages ≥18 Years, 2019

Figure 6: 8MM, Diagnosed Prevalent Cases of CKD-Anemia by Age, N, Both Sexes, 2019

Figure 7: 8MM, Diagnosed Prevalent Cases of CKD-Anemia by Sex, N, Ages ≥18 Years, 2019

Figure 8: 8MM, Diagnosed Prevalent Cases of CKD-Anemia by Stage, N, Both Sexes, Ages ≥18 Years, 2019

Figure 9: 8MM, Diagnosed Prevalent Cases of CKD-Anemia Based on Dialysis Dependence, N, Both Sexes, Ages ≥18 Years, 2019

Figure 10: 8MM, Diagnosed Prevalent Cases of CKD-Anemia Based on Cause of Anemia, N, Both Sexes, Ages ≥18 Years, 2019

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