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EpiCast Report:慢性淋巴性白血病的流行病學預測

EpiCast Report: Chronic Lymphocytic Leukemia - Epidemiology Forecast to 2025

出版商 GlobalData 商品編碼 301138
出版日期 內容資訊 英文 47 Pages
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EpiCast Report:慢性淋巴性白血病的流行病學預測 EpiCast Report: Chronic Lymphocytic Leukemia - Epidemiology Forecast to 2025
出版日期: 2017年11月01日 內容資訊: 英文 47 Pages
簡介

所謂慢性淋巴性白血病(CLL),是白血球(淋巴球)癌症的一種,帶給特定的淋巴球(B細胞)--主要骨髓、血液內集積,對抗感染疾病的細胞--不良影響。CLL在西歐各國是一般白血病形態,年度平均發病率為每10萬人口有5.0件(不論年齡)。基本上是老年人發病的疾病,40歲以下的患者比例為10%以下。全球主要6個國家的發病數量,從2013年的37,795件,預計到2023年增加到45,683,其年複合成長率(CAGR)推算為2.09%。還有治療完畢的患病人數,從2013年的150,800人,到2023年增加到183,165(年複合成長率(CAGR)是2.15%)。

本報告提供全球主要6個國家(美國、法國、德國、義大利、西班牙、英國)的慢性淋巴性白血病(CLL)的發病情形和今後預測相關分析、疾病的特徵(風險要素和主要的共生病症等等)全球各國的趨勢、目前患病者的發病情形、今後10年的發病、患病數量的預測值等調查評估,並將其結果依為您概述為以下內容。

第1章 目錄

第2章 簡介

  • 概要
  • 近日出版的相關調查

第3章 流行病學

  • 疾病的背景
  • 風險要素和共生病症
  • 全世界的趨勢
    • 發病數量
    • 存活率:美國、歐洲5個國家的情況
  • 預測手法
    • 利用之資訊來源
    • 未利用之資訊來源
    • 預測的前提條件與手法:確診的發病數量
    • 預測的前提條件與手法:確診的患病人數(今後5年份)
    • 預測的前提條件與手法:診斷時的Rai分類
  • 慢性淋巴性白血病(CLL)的流行病學預測(今後11年份)
    • 確診的發病數量
    • 確診的發病數量(各年齡)
    • 確診的發病數量(性別)
    • 確診的發病數量(已調整年齡)
    • 確診的發病數量(診斷時的各Rai分類)
    • 確診的患病人數:今後5年的預測
  • 議論
    • 流行病學性的預測相關結論
    • 分析的限制
    • 分析的優勢

第4章 附錄

圖表一覽

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目錄
Product Code: GDHCER164-17

Chronic lymphocytic leukemia (CLL), 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. In CLL, the DNA of a B cell is damaged so that it cannot fight infection, but instead, it grows out of control and affects the healthy blood cells that can fight infection (NCI, 2016). CLL is closely related to small lymphocytic lymphoma (SLL), a type of non-Hodgkin's lymphoma that presents primarily in the lymph nodes.

In the 7MM, epidemiologists forecast an increase in the diagnosed incident cases of CLL from 40,631 diagnosed incident cases in 2015 to 49,643 diagnosed incident cases in 2025, with an annual growth rate (AGR) of 2.22% during the forecast period. The US will have the highest number of diagnosed incident cases of CLL among the 7MM throughout the forecast period, while Spain will have the lowest.

The report "EpiCast Report: Chronic Lymphocytic Leukemia - Epidemiology Forecast to 2025" provides an overview of the risk factors, comorbidities, and the global and historical trends for 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. Additionally, the CLL diagnosed incident cases are segmented by Rai and Binet stage at diagnosis, symptom status (symptomatic vs. asymptomatic), and immunoglobulin heavy chain variable (IGHV) region gene mutation status (mutated vs. unmutated) for the 7MM.

Scope

  • The Chronic lymphocytic leukemia (CLL) EpiCast Report provides an overview of the risk factors and global trends of CLLin the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan).
  • The report includes a 10-year epidemiological forecast for the diagnosed incident cases of CLL and five-year diagnosed prevalent cases of CLL. Incident cases are segmented by age, sex, Rai and Binet stage at diagnosis, symptom status (symptomatic vs. asymptomatic), and immunoglobulin heavy chain variable (IGHV) region gene mutation status (mutated vs. unmutated) for the 7MM. The diagnosed incident cases of CLL with the mutations 17p deletion, 11q deletion, and TP53 are also provided in the report.
  • The CLL epidemiology report is written and developed by Masters- and PhD-level epidemiologists.
  • The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.

Reasons to buy

The CLL EpiCast report 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 population by two staging systems.

Table of Contents

1 Table of Contents

1 Table of Contents 2

  • 1.1 List of Tables 4
  • 1.2 List of Figures 4

2 Executive Summary 5

  • 2.1 Related Reports 8
  • 2.2 Upcoming Reports 8

3 Epidemiology 9

  • 3.1 Disease Background 9
  • 3.2 Risk Factors and Comorbidities 10
  • 3.3 Global and Historical Trends 11
  • 3.4 Forecast Methodology 13
    • 3.4.1 Sources 14
    • 3.4.2 Forecast Assumptions and Methods 21
    • 3.4.3 Diagnosed Incident Cases 22
    • 3.4.4 Diagnosed Incident Cases by Stage at Diagnosis (Rai Staging) 24
    • 3.4.5 Diagnosed Incident Cases by Stage at Diagnosis (Binet Staging) 24
    • 3.4.6 Diagnosed Incident Cases by Disease Symptom Status 25
    • 3.4.7 Mutations (17p deletion, 11q Deletion, and TP53) Among the Diagnosed Incident Cases of CLL 25
    • 3.4.8 IGHV Mutation Among Diagnosed Incident Cases of CLL 27
    • 3.4.9 Five-Year Diagnosed Prevalent Cases of CLL 28
  • 3.5 Epidemiological Forecast for CLL (2015-2025) 29
    • 3.5.1 Diagnosed Incident Cases of CLL 29
    • 3.5.2 Age-Specific Diagnosed Incident Cases of CLL 30
    • 3.5.3 Sex-Specific Diagnosed Incident Cases of CLL 31
    • 3.5.4 Diagnosed Incident Cases of CLL by Stage at Diagnosis (Rai Staging) 32
    • 3.5.5 Diagnosed Incident Cases of CLL by Stage at Diagnosis (Binet Staging) 33
    • 3.5.6 Diagnosed Incident Cases of CLL by Disease Symptom Status 34
    • 3.5.7 Diagnosed Incident Cases of CLL with 17p Deletion 35
    • 3.5.8 Diagnosed Incident Cases of CLL with 11q Deletion 36
    • 3.5.9 Diagnosed Incident Cases of CLL with TP53 Mutation 37
    • 3.5.10 Diagnosed Incident Cases of CLL by IGHV Mutation Status 38
    • 3.5.11 Five-Year Diagnosed Prevalent Cases of CLL 38
  • 3.6 Discussion 39
    • 3.6.1 Epidemiological Forecast Insight 39
    • 3.6.2 Limitations of Analysis 40
    • 3.6.3 Strengths of Analysis 40

4 Appendix 42

  • 4.1 Bibliography 42
  • 4.2 About the Authors 45
    • 4.2.1 Epidemiologist 45
    • 4.2.2 Reviewers 45
    • 4.2.3 Global Director of Therapy Analysis and Epidemiology 46
    • 4.2.4 Global Head and EVP of Healthcare Operations and Strategy 46
  • 4.3 About GlobalData 47
  • 4.4 Contact Us 47
  • 4.5 Disclaimer 47

List of Tables

1.1 List of Tables

  • Table 1: CLL Clinical Stages 10
  • Table 2: Risk Factors and Comorbidities for CLL 11
  • Table 3: 7MM, Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, Selected Years 2015-2025. 29
  • Table 4: 7MM, Five-Year Diagnosed Prevalent Cases of CLL, Both Sexes, Ages ≥18 Years, Selected Years 2015-2025 39

List of Figures

1.2 List of Figures

  • Figure 1: 7MM, Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, 2015 and 2025 6
  • Figure 2: 7MM, Five-Year Diagnosed Prevalent Cases of CLL, Both Sexes, Ages ≥18 Years , 2015 and 2025 7
  • Figure 3: 7MM, CLL Age-Standardized Diagnosed Incidence (Cases per 100,000 Population), Men, Ages ≥18 Years, 2005 to 2025 12
  • Figure 4: 7MM, CLL Age-Standardized Diagnosed Incidence (Cases per 100,000 Population), Women, Ages ≥18 Years, 2005 to 2025 13
  • Figure 5: 7MM, Sources Used, Diagnosed Incident Cases of CLL 14
  • Figure 6: 7MM, Sources Used, Diagnosed Incident Cases of CLL by Stage at Diagnosis (Rai Staging) 15
  • Figure 7: 7MM, Sources Used, Diagnosed Incident Cases of CLL by Stage at Diagnosis (Binet Staging) 16
  • Figure 8: 7MM, Sources Used, 17p Deletion Among the Diagnosed Incident Cases of CLL 17
  • Figure 9: 7MM, Sources Used, 11q Deletion Among the Diagnosed Incident Cases of CLL 18
  • Figure 10: 7MM, Sources Used, TP53 Mutation Among the Diagnosed Incident Cases of CLL 19
  • Figure 11: 7MM, Sources Used, Diagnosed Incident Cases of CLL by IGHV Mutation Status 20
  • Figure 12: 7MM, Sources Used and Not Used, Five-Year Diagnosed Prevalent Cases of CLL 21
  • Figure 13: 7MM, Age-Specific Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, 2015 30
  • Figure 14: 7MM, Sex-Specific Diagnosed Incident Cases of CLL, Both Sexes, Ages ≥18 Years, 2015 31
  • Figure 15: 7MM, Diagnosed Incident Cases of CLL by Stage at Diagnosis (Rai Staging), Both Sexes, Ages ≥18 Years, 2015 32
  • Figure 16: 7MM, Diagnosed Incident Cases of CLL by Stage at Diagnosis (Binet Staging), Both Sexes, Ages ≥18 Years, 2015 33
  • Figure 17: 7MM, Diagnosed Incident Cases of CLL by Disease Symptom Status, Both Sexes, Ages ≥18 Years, 2015 34
  • Figure 18: 7MM, Diagnosed Incident Cases of CLL with 17p Deletion, Both Sexes, Ages ≥18 Years, 2015 35
  • Figure 19: 7MM, Diagnosed Incident Cases of CLL with 11q Deletion, Both Sexes, Ages ≥18 Years, 2015 36
  • Figure 20: 7MM, Diagnosed Incident Cases of CLL with TP53 Mutation, Both Sexes, Ages ≥18 Years, 2015 37
  • Figure 21: 7MM, Diagnosed Incident Cases of CLL by IGHV Mutational Status, Both Sexes, Ages ≥18 Years, 2015 38
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