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市場調查報告書

EpiCast Report:血友病的流行病學預測 (2024年)

EpiCast Report: Hemophilia - Epidemiology Forecast to 2024

出版商 GlobalData 商品編碼 344637
出版日期 內容資訊 英文 46 Pages
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EpiCast Report:血友病的流行病學預測 (2024年) EpiCast Report: Hemophilia - Epidemiology Forecast to 2024
出版日期: 2015年10月06日 內容資訊: 英文 46 Pages
簡介

所謂血友病是指X連鎖性·遺傳性的出血障礙,特徵是凝血因子中VII因子(A型血友病的情況) 或是IX因子 (B型血友病的情況)的生產、機能障礙的結果所造成凝血障礙。血友病患者(雖然也要看嚴重度)的關節、肌肉、軟組織、黏膜內部會自然發生出血,或是伴隨內傷或外傷的大量出血。全球9個國家確診的A、B型血友病患者數在2014年為60,671人(其中美國約佔28%),預測到2024年前將達到61,954人。由於血友病是遺傳性疾病,需要一輩子接受治療,但近年來由於高齡化及高血壓患者的增加,預測今後將需要血友病患者高血壓的對策。

本報告提供全球主要9個國家 (美國,德國,法國,義大利,西班牙,英國,日本,阿根廷,中國) 的A、B型血友病的發病情形與今後預測相關分析,提供您疾病的特徵,及目前患病者的發病情形,今後10年的患病數量的預測值等調查評估。

第1章 目錄

第2章 簡介

  • 疾病的概要
  • 相關分析
  • 出版預定的相關分析

第3章 流行病學的預測

  • 疾病的背景情況
  • 風險要素和共生病症
  • 全世界的趨勢
  • 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
  • A型血友病的流行病學的預測 (今後11年份)
    • 確診的患病人數
    • 確診的患病人數:各年齡
    • 確診的患病人數:男女
    • 確診的患病人數 (年齡已調整)
  • B型血友病的流行病學的預測 (今後11年份)
    • 確診的患病人數
    • 確診的患病人數:各年齡
    • 確診的患病人數:男女
    • 確診的患病人數 (年齡已調整)
  • A、B型血友病的流行病學的預測 (今後11年份)
    • 確診的患病人數
    • 確診的患病人數:男女
  • 議論
    • 流行病學的預測相關考察
    • 分析的限制
    • 分析的優勢

第4章 附錄

圖表一覽

目錄
Product Code: GDHCER091-15

Hemophilia is an X-linked hereditary bleeding disorder, characterized by impaired blood coagulation as a result of deficiencies in the production or function of coagulation factor VIII (hemophilia A) or factor IX (hemophilia B). Because of the deficiency of coagulation factor, hemophilia patients have a tendency for bleeding in joints, muscles, soft tissues, and within mucous membranes, which can be either spontaneous or due to internal or external trauma, depending on the severity of the disease.

In 2014, the 9MM had 60,671 diagnosed prevalent cases of hemophilia A and hemophilia B, around 28% of which occurred in the US. The diagnosed prevalent cases of hemophilia in the 9MM are expected to increase slightly to 61,954 cases by 2024. The US will have the largest proportion of diagnosed prevalent cases of hemophilia A and hemophilia B in the 9MM in 2024 at 29.05%. Because hemophilia is an inherited condition, it requires lifelong treatment. Given the increase in the prevalence of hypertension, with advancing age and increasing life expectancy in hemophiliacs due to advances in treatment, the challenges faced by hemophiliacs and the need for more supportive treatments and care will increase in the near future.

GlobalData epidemiologists forecast the epidemiological trend for hemophilia using data from the WFH Annual Global Survey Report, which is considered the gold standard for hemophilia data. The World Health Organization (WHO) authenticates the WFH data for hemophilia and other bleeding disorders and provides the most accurate data possible for hemophilia globally. The WFH Global Survey Report uses uniform data collection methods for each national member organization (NMO), allowing for a meaningful comparison of the diagnosed prevalent cases across the markets. A major strength of this analysis lays in the use of country-specific data and a uniform methodology across the markets to forecast the prevalent cases of hemophilia.

Scope

  • The Hemophilia EpiCast Report provides an overview of the risk factors and global trends of hemophilia in the 9MM (US, France, Germany, Italy, Spain, UK, Japan, Argentina, and China). In addition, the report includes a 10-year epidemiological forecast of the diagnosed prevalent cases of hemophilia, segmented by type (A and B), sex, and age (starting at ages 0 years) in these markets.
  • The hemophilia 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 9MM.

Reasons to buy

The Hemophilia EpiCast report will allow you to -

  • Develop business strategies by understanding the trends shaping and driving the global hemophilia market.
  • Quantify patient populations in the global hemophilia 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 hemophilia therapeutics in each of the markets covered.
  • Identify the hemophilia type that is most important to your marketing plans.

Table of Contents

1. Table of Contents

  • 1.1. List of Tables
  • 1.2. List of Figures

2. Introduction

  • 2.1. Catalyst
  • 2.2. Related Reports
  • 2.3. Upcoming Related Reports

3. Epidemiology

  • 3.1. Disease Background
  • 3.2. Risk Factors and Comorbidities
  • 3.3. Global Trends
  • 3.4. Forecast Methodology
    • 3.4.1. Sources Used
    • 3.4.2. Sources Not Used
    • 3.4.3. Forecast Assumptions and Methods
  • 3.5. Epidemiological Forecast for Hemophilia A (2014-2024)
    • 3.5.1. Diagnosed Prevalent Cases of Hemophilia A
    • 3.5.2. Diagnosed Prevalent Cases of Hemophilia A by Age
    • 3.5.3. Diagnosed Prevalent Cases of Hemophilia A by Sex
    • 3.5.4. Age-Standardized Diagnosed Prevalence of Hemophilia A
  • 3.6. Epidemiological Forecast for Hemophilia B (2014-2024)
    • 3.6.1. Diagnosed Prevalent Cases of Hemophilia B
    • 3.6.2. Diagnosed Prevalent Cases of Hemophilia B by Age
    • 3.6.3. Diagnosed Prevalent Cases of Hemophilia B by Sex
    • 3.6.4. Age-Standardized Diagnosed Prevalence of Hemophilia B
  • 3.7. Epidemiological Forecast for Hemophilia A and Hemophilia B (2014-2024)
    • 3.7.1. Diagnosed Prevalent Cases of Hemophilia A and Hemophilia B
    • 3.7.2. Diagnosed Prevalent Cases of Hemophilia A and Hemophilia B by Sex
  • 3.8. Discussion
    • 3.8.1. Conclusions on Epidemiological Trends
    • 3.8.2. Limitations of the Analysis
    • 3.8.3. Strengths of the Analysis

4. Appendix

  • 4.1. Bibliography
  • 4.2. About the Authors
    • 4.2.1. Epidemiologists
    • 4.2.2. Reviewers
    • 4.2.3. Global Director of Epidemiology and Health Policy
    • 4.2.4. Global Head of Healthcare
  • 4.3. About GlobalData
  • 4.4. About EpiCast
  • 4.5. Disclaimer

List of Tables

  • Table 1: Relationship of Bleeding Severity with Clotting Factor Level
  • Table 2: Hemophilia - Risk Factors and Comorbidities
  • Table 3: 9MM, Diagnosed Prevalence of Hemophilia A (per 100,000 Population), Both Sexes, All Ages, 2004-2013
  • Table 4: 9MM, Diagnosed Prevalence of Hemophilia B (per 100,000 Population), Both Sexes, All Ages, 2004-2013
  • Table 5: 9MM, Sources and Diagnosed Prevalence Data for Hemophilia A and B
  • Table 6: 9MM, Diagnosed Prevalent Cases of Hemophilia A, Both Sexes, All Ages, N, 2014-2024
  • Table 7: 9MM, Diagnosed Prevalent Cases of Hemophilia A, Both Sexes, by Age, N, Row (%), 2014
  • Table 8: 9MM, Diagnosed Prevalent Cases of Hemophilia A, by Sex, All Ages, N, Row (%), 2014
  • Table 9: 9MM, Diagnosed Prevalent Cases of Hemophilia B, Both Sexes, All Ages, N, 2014-2024
  • Table 10: 9MM, Diagnosed Prevalent Cases of Hemophilia B, Both Sexes, by Age, N, Row (%), 2014
  • Table 11: 9MM, Diagnosed Prevalent Cases of Hemophilia B, by Sex, All Ages, N, Row (%), 2014
  • Table 12: 9MM, Diagnosed Prevalent Cases of Hemophilia, Both Sexes, All Ages, N, 2014-2024
  • Table 13: 9MM, Diagnosed Prevalent Cases of Hemophilia A and Hemophilia B, by Sex, All Ages, N, Row (%), 2014

List of Figures

  • Figure 1: 9MM, Diagnosed Prevalent Cases of Hemophilia A, Both Sexes, All Ages, N, 2014-2024
  • Figure 2: 9MM, Diagnosed Prevalent Cases of Hemophilia A, Both Sexes, by Age, N, 2014
  • Figure 3: 9MM, Diagnosed Prevalent Cases of Hemophilia A, by Sex, All Ages, N, 2014
  • Figure 4: 9MM, Age-Standardized Diagnosed Prevalence of Hemophilia A (per 100,000 Population), by Sex, 2014
  • Figure 5: 9MM, Diagnosed Prevalent Cases of Hemophilia B, Both Sexes, All Ages, N, 2014-2024
  • Figure 6: 9MM, Diagnosed Prevalent Cases of Hemophilia B, Both Sexes, by Age, N, 2014
  • Figure 7: 9MM, Diagnosed Prevalent Cases of Hemophilia B, by Sex, All Ages, N, 2014
  • Figure 8: 9MM, Age-Standardized Prevalence of Diagnosed Hemophilia B (per 100,000 Population), by Sex, 2014
  • Figure 9: 9MM, Diagnosed Prevalent Cases of Hemophilia A and Hemophilia B, Both Sexes, All Ages, N, 2014-2024
  • Figure 10: 9MM, Diagnosed Prevalent Cases of Hemophilia A and Hemophilia B, by Sex, All Ages, N, 2014
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