Chronic Lymphocytic Leukemia: Epidemiology Forecast to 2027

Chronic lymphocytic leukemia (CLL) (International Statistical Classification of Diseases and Related Health Problems, 10th Revision [ICD-10] code = C91.1), also known as chronic lymphoid leukemia, is a type of cancer of the white blood cells (lymphocytes). CLL affects a particular lymphocyte, the B cell, which accumulates mainly in the bone marrow and blood, and normally fights infection.

GlobalData epidemiologists utilized national databases and robust peer-reviewed journal articles to build the CLL diagnosed incident and diagnosed prevalent cases forecast for the 7MM. The disease definition for CLL was consistent with the ICD-10 code C91.1. Whenever available, country-specific sources were utilized. In cases of data scarcity, appropriate proxies were used to fill the data gaps.

The diagnosed incident cases of CLL in the 7MM will increase from 41,974 cases in 2017 to 50,474 cases in 2027, at an Annual Growth Rate (AGR) of 2.03% over the forecast period. For the majority of the forecast period, the US will have the highest number of diagnosed incident cases of CLL. GlobalData epidemiologists attribute the growth in the diagnosed incident cases of CLL in the 7MM to the moderately rising trend in incidence in the 7MM, combined with the changing population demographics in the respective markets.

Scope

The Chronic Lymphocytic Leukemia (CLL) Epidemiology Report and Model provide an overview of the risk factors and global trends of CLL in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Canada).

The report includes a 10-year epidemiological forecast for the diagnosed incident cases of CLL segmented by age (for ages 18 years and older) and sex. The CLL diagnosed incident cases are segmented by Rai stage, modified Rai stage, and Binet stage at diagnosis, as well as high-risk cytogenetics for the 7MM. Additionally, GlobalData epidemiologists provide a forecast for the diagnosed prevalent cases of CLL in the 7MM. To forecast the diagnosed incident and diagnosed prevalent cases of CLL in the 7MM, GlobalData epidemiologists used data from nationally representative, population-based studies for the 7MM.

The CLL 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 7MM.

 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 CLL Epidemiology series will allow you to:

Develop business strategies by understanding the trends shaping and driving the global CLL market.

Quantify patient populations in the global CLL market 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 CLL therapeutics in each of the markets covered.

Understand magnitude of CLL patient population by stage.

Table of Contents

1 Table of Contents

1.1 List of Tables

1.2 List of Figures

2 Chronic Lymphocytic Leukemia: Executive Summary

2.1 Related Reports

2 ...

1 Table of Contents

1.1 List of Tables

1.2 List of Figures

2 Chronic Lymphocytic Leukemia: 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 Used

3.4.2 Forecast Assumptions and Methods – Population

3.4.3 Forecast Assumptions and Methods – Diagnosed Incident Cases of CLL

3.4.4 Diagnosed Incident Cases by Stage at Diagnosis (Rai Staging and Modified Rai Staging)

3.4.5 Diagnosed Incident Cases by Stage at Diagnosis (Binet Staging)

3.4.6 High-Risk Cytogenetics (11q Deletion, 13q Deletion, 17p Deletion, p53 mutation, CD38, ZAP70 and IGHV [Unmutated]) Among the Diagnosed Incident Cases of CLL

3.4.7 Forecast Assumptions and Methods – Diagnosed Prevalent Cases of CLL

3.5 Epidemiological Forecast for CLL (2017–2027)

3.5.1 Diagnosed Incident Cases of CLL

3.5.2 Age-Specific Diagnosed Incident Cases of CLL

3.5.3 Sex-Specific Diagnosed Incident Cases of CLL

3.5.4 Diagnosed Incident Cases of CLL by Rai Stage at Diagnosis

3.5.5 Diagnosed Incident Cases of CLL by Modified Rai Stage at Diagnosis

3.5.6 Diagnosed Incident Cases of CLL by Binet Stage at Diagnosis

3.5.7 Diagnosed Incident Cases of CLL by High-Risk Cytogenetics

3.5.8 Diagnosed Prevalent Cases of CLL

3.6 Discussion

3.6.1 Epidemiological Forecast Insight

3.6.2 Limitations of the Analysis

3.6.3 Strengths of the Analysis

4 Appendix

4.1 Bibliography

4.2 About the Authors

4.2.1 Epidemiologist

4.2.2 Reviewers

4.2.3 Global Director of Therapy Analysis and Epidemiology

4.2.4 Global Head and EVP of Healthcare Operations and Strategy

4.3 About GlobalData

4.4 Contact Us

4.5 Disclaimer

List of Tables

Table 1: Risk Factors and Comorbid Conditions Associated with CLL

Table 2: 7MM, Diagnosed Incident Cases of CLL by High-Risk Cytogenetics, Both Sexes, Ages ≥18 ...

Table 1: Risk Factors and Comorbid Conditions Associated with CLL

Table 2: 7MM, Diagnosed Incident Cases of CLL by High-Risk Cytogenetics, Both Sexes, Ages ≥18 Years, N, 2017

List of Figures

Figure 1: 7MM, Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, N, 2017 and 2027

Figure 2: 7MM, Diagnosed Prevalent Cases of CLL ...

Figure 1: 7MM, Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, N, 2017 and 2027

Figure 2: 7MM, Diagnosed Prevalent Cases of CLL, Both Sexes, Ages ≥18 Years, N, 2017 and 2027

Figure 3: 7MM, Age-Standardized Diagnosed Incidence of CLL (Cases per 100,000 Population), Men, Ages ≥18 Years, 2017–2027

Figure 4: 7MM, Age-Standardized Diagnosed Incidence of CLL (Cases per 100,000 Population), Women, Ages ≥18 Years, 2017–2027

Figure 5: 7MM, Sources Used, Diagnosed Incident Cases of CLL

Figure 6: 7MM, Sources Used, Diagnosed Incident Cases of CLL by Stage at Diagnosis (Rai Staging and Modified Rai Staging)

Figure 7: 7MM, Sources Used, Diagnosed Incident Cases of CLL by Stage at Diagnosis (Binet Staging)

Figure 8: 7MM, Sources Used, 11q and 13q Deletion Among the Diagnosed Incident Cases of CLL

Figure 9: 7MM, Sources Used, 17p Deletion Among the Diagnosed Incident Cases of CLL

Figure 10: 7MM, Sources Used, TP53 Among the Diagnosed Incident Cases of CLL

Figure 11: 7MM, Sources Used, CD38 Among the Diagnosed Incident Cases of CLL

Figure 12: 7MM, Sources Used, ZAP70 Among the Diagnosed Incident Cases of CLL

Figure 13: 7MM, Sources Used, IGHV (Unmutated) Among the Diagnosed Incident Cases of CLL

Figure 14: 7MM, Sources Used, Diagnosed Prevalent Cases of CLL

Figure 15: 7MM, Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, N, 2017

Figure 16: 7MM, Age-Specific Diagnosed Incident Cases of CLL, Both Sexes, N, 2017

Figure 17: 7MM, Sex-Specific Diagnosed Incident Cases of CLL, Ages ≥18 Years, N, 2017

Figure 18: 7MM, Diagnosed Incident Cases of CLL by Rai Stage at Diagnosis, Both Sexes, Ages ≥18 Years, N, 2017

Figure 19: 7MM, Diagnosed Incident Cases of CLL by Modified Rai Stage at Diagnosis, Both Sexes, Ages ≥18 Years, N, 2017

Figure 20: 7MM, Diagnosed Incident Cases of CLL by Binet Stage at Diagnosis, Both Sexes, Ages ≥18 Years, N, 2017

Figure 21: 7MM, Diagnosed Prevalent Cases of CLL, Both Sexes, Ages ≥18 Years, N, 2017

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