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1026631

Cystic Fibrosis (CF) - Epidemiology Forecast to 2030

Published: | GlobalData | 41 Pages | Delivery time: 1-2 business days

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Cystic Fibrosis (CF) - Epidemiology Forecast to 2030
Published: August 31, 2021
GlobalData
Content info: 41 Pages
Delivery time: 1-2 business days
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  • Table of Contents
Description

Cystic fibrosis (CF) is a progressive, inherited disorder that primarily affects the respiratory and digestive systems. In people with CF, mucus, sweat, and other fluids produced in these systems are sticky and thick, and may obstruct the passageways in the lungs and pancreas (Mayo Clinic, 2021). Mucus build-up and airway blockages in the lungs cause symptoms such as persistent cough, wheezing, inflamed nasal passages, and recurrent lung infections. Impacts on the digestive system can lead to chronic constipation, intestinal blockages, and weight loss (Mayo Clinic, 2021).

GlobalData epidemiologists utilized comprehensive, country-specific data from national CF registries and peer-reviewed journal articles to arrive at a meaningful, in-depth analysis and forecast for the diagnosed prevalent cases of CF. For all the 7MM, CF cases were segmented by age, sex, mutation type, and MRSA infection. Finally, historical data were evaluated in all 7MM to strengthen the forecast by more accurately capturing changes in prevalence throughout the forecast period.

GlobalData epidemiologists forecast that the diagnosed prevalent cases of CF in the 7MM will grow by an annual growth rate (AGR) of 0.51% over the next 10 years, from 69,134 cases in 2020 to 72,659 cases in 2030. For CF mutation type in 2020, the F508del was the most prevalent gene mutation, representing 80.51% of diagnosed prevalent cases of CF in the 7MM. With the more widespread implementation of newborn screening programs, CF is now detected, and thus intervention can begin, earlier than ever. GlobalData epidemiologists expect that continued improvements in the treatment and care of CF patients may drive the number of diagnosed prevalent cases higher as people with CF live longer.

Scope

  • The Cystic Fibrosis Epidemiology Report provides an overview of the risk factors, comorbidities, and global trends of Cystic Fibrosis (CF) 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 prevalent cases of CF segmented by age (0-1, 2-5, 6-11, 12-17, 18-29 years, and by 10-year age groups up to 80 years and older) and sex. Diagnosed prevalent cases of CF are further segmented by specific mutation type and chronic methicillin-resistant Staphylococcus aureus (MRSA) infection.
  • The CF 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

The CF Epidemiology series will allow you to -

  • Develop business strategies by understanding the trends shaping and driving the global CF markets.
  • Quantify patient populations in the global CF 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 CF therapeutics in each of the markets covered.
  • Understand magnitude of the CF population by age, sex, mutation type, and MRSA infection.
Table of Contents
Product Code: GDHCER278-21

Table of Contents

Table of Contents

1 Cystic Fibrosis: 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
    • 2.3.1 Registry-Based Diagnosed Prevalence of CF
    • 2.3.2 Registry-Based Diagnosed Prevalent Cases Adjusted for Underestimation
  • 2.4 Forecast Methodology
    • 2.4.1 Sources
    • 2.4.2 Sources Not Used
    • 2.4.3 Forecast Assumptions and Methods
    • 2.4.4 Registry-Based Diagnosed Prevalent Cases of CF
    • 2.4.5 Registry-Based Diagnosed Prevalent Cases of CF by Specific Mutation
    • 2.4.6 Registry-Based Diagnosed Prevalent Cases of CF with Chronic MRSA Infection
    • 2.4.7 Registry-Based Diagnosed Prevalent Cases Adjusted for Underestimation
  • 2.5 Epidemiological Forecast for CF (2020-2030)
    • 2.5.1 Registry-Based Diagnosed Prevalent Cases of CF
    • 2.5.2 Age-Specific Registry-Based Diagnosed Prevalent Cases of CF
    • 2.5.3 Sex-Specific Registry-Based Diagnosed Prevalent Cases of CF
    • 2.5.4 Registry-Based Diagnosed Prevalent Cases of CF with Specific Mutations
    • 2.5.5 Registry-Based Diagnosed Prevalent Cases of CF with Chronic MRSA Infection
    • 2.5.6 Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation
    • 2.5.7 Age-Specific Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation
    • 2.5.8 Sex-Specific Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation
    • 2.5.9 Registry-Based Diagnosed Prevalent Cases of CF with Specific Mutations Adjusted for Underestimation
    • 2.5.10 Registry-Based Diagnosed Prevalent Cases of CF with Chronic MRSA Infection Adjusted for Underestimation
  • 2.6 Discussion
    • 2.6.1 Epidemiological Forecast Insight
    • 2.6.2 COVID-19 Impact
    • 2.6.3 Limitations of Analysis
    • 2.6.4 Strengths of 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 Us

List of Tables

List of Tables

  • Table 1: Summary of Updated Data Types, Registry-Based Forecast
  • Table 2: Summary of Updated Data Types, Registry-Based Forecast Adjusted for Underestimation
  • Table 3: Risk Factors and Comorbidities for CF

List of Figures

List of Figures

  • Figure 1: 7MM, Registry-Based Diagnosed Prevalent Cases of CF, Both Sexes, All Ages, 2020 and 2030
  • Figure 2: 7MM, Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation, Both Sexes, All Ages, 2020 and 2030
  • Figure 3: 7MM, Registry-Based Diagnosed Prevalence of CF, Men and Women, All Ages, 2010-2030 (%)
  • Figure 4: 7MM, Registry-Based Diagnosed Prevalence of CF Adjusted for Underestimation, Men and Women, All Ages, 2010-2030 (%)
  • Figure 5: Sources Used for Registry-Based Diagnosed Prevalent Cases of CF
  • Figure 6: Sources Used for Registry-Based Diagnosed Prevalent Cases of CF by Specific Mutation
  • Figure 7: Sources Used for Registry-Based Diagnosed Prevalent Cases of CF with Chronic MRSA Infection
  • Figure 8: Sources Used for Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation
  • Figure 9: Registry-Based Diagnosed Prevalent Cases of CF, 7MM, Men and Women, All Ages, 2020
  • Figure 10: 7MM, Age-Specific Registry-Based Diagnosed Prevalent Cases of CF, Men and Women, 2020 (N)
  • Figure 11: 7MM, Sex-Specific Registry-Based Diagnosed Prevalent Cases of CF, All Ages, 2020 (N)
  • Figure 12: 7MM, Registry-Based Diagnosed Prevalent Cases of CF with Specific Mutations, Men and Women, All Ages, 2020 (N)
  • Figure 13: 7MM, Registry-Based Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, Men and Women, All Ages, 2020 (N)
  • Figure 14: Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation, 7MM, Men and Women, All Ages, 2020
  • Figure 15: 7MM, Age-Specific Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation, Men and Women, 2020 (N)
  • Figure 16: 7MM, Sex-Specific Registry-Based Diagnosed Prevalent Cases of CF Adjusted for Underestimation, All Ages, 2020 (N)
  • Figure 17: 7MM, Registry-Based Diagnosed Prevalent Cases of CF with Mutations Adjusted for Underestimation, Men and Women, All Ages, 2020 (N)
  • Figure 18: 7MM, Registry-Based Diagnosed Prevalent Cases of CF with Chronic MRSA Infection Adjusted for Underestimation, Men and Women, All Ages, 2020 (N)