EpiCast Report: Heart Failure – Epidemiology Forecast to 2025

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Published: May 01, 2016 Report Code: GDHCER117-16-ST

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Heart Failure (HF), also referred to as congestive cardiac failure, is a heterogeneous condition in which the heart is unable to pump out sufficient blood to meet the metabolic needs of the body. Eventually, without the heart's pumping action to deliver oxygen and nutrient-rich blood to the cells, fatigue, shortness of breath, and coughing results. HF commonly occurs in people above 50 years of age, and severity increases progressively with age. Symptoms can develop quickly, such as in acute HF, at which time the patient needs to be hospitalized. However, in chronic HF, the symptoms develop gradually. Due to the chronic nature of cardiovascular diseases, many of the risk factors for HF, such as chronic obstructive pulmonary disease (COPD) and anemia, are also comorbid conditions.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of HF will increase from 1,094,344 cases in 2015 to 1,400,377 cases in 2025 at an Annual Growth Rate (AGR) of 2.80%. In the 7MM, GlobalData epidemiologists forecast that the diagnosed prevalent cases of chronic HF will increase from 13,756,453 cases in 2015 to 16,105,489 cases in 2025 at an AGR of 1.71%. The US will have the highest number of diagnosed incident cases of HF and diagnosed prevalent cases of chronic HF among the 7MM throughout the forecast period with 1,052,831 diagnosed incident cases of HF and 6,170,142 diagnosed prevalent cases of chronic HF in 2025. In the 7MM in 2015, 37.59% of the diagnosed prevalent cases of chronic HF are in NYHA Class I, 39.54% in NYHA Class II, 19.11% in NYHA Class III, and 3.75% in NYHA Class IV.

GlobalData epidemiologists utilized comprehensive, country-specific data from national HF registers and peer-reviewed journal articles to arrive at a meaningful, in-depth analysis and forecast for the diagnosed incident cases of HF, as well as the diagnosed prevalent cases of chronic HF. In this analysis, GlobalData epidemiologists provide detailed, clinically relevant segmentations for diagnosed incident and diagnosed prevalent cases of HF. Finally, the same forecast methodology was used across the 7MM, thereby allowing for meaningful global comparisons of the diagnosed incident and diagnosed prevalent cases of HF across these markets.

Scope

The Heart Failure (HF) EpiCast Report and EpiCast Model provide an overview of the risk factors and global trends of HF in the 7MM (US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiology forecast of HF diagnosed incident and diagnosed prevalent cases segmented by age and sex. Diagnosed incident cases are further segmented by ejection fraction, ventricular dysfunction, acute HF hospitalizations (by worsening HF, advanced HF, de novo HF), re-admissions (within 3 months) post-discharge after acute HF hospitalization, and hospital length of stay for acute HF hospitalization in these seven markets. Diagnosed prevalent cases are further segmented by chronic HF (by ejection fraction), and also classified according to the New York Heart Association (NYHA) functional classes I–IV, and American College of Cardiology Foundation/American Heart Association (ACCF/AHA) stages B, C and D in these seven markets.

The HF epidemiology report and model were 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.

The EpiCast 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.

Table of Contents

1Table of Contents

1.1List of Tables

1.2List of Figures

2Epidemiology

2.1Disease Background

2.2Risk Factors and Comorbidities

2.3Global Trends

2.3.1US

2.3.25EU

2.3.3Japan

2.4Forecast Methodology.

2.4.1Sources Used Tables

2.4.2Forecast Assumptions and Methods

2.4.3Sources Not Used

2.5Epidemiological Forecast for HF (2015–2025)

2.5.1Diagnosed Incident Cases

2.5.2Diagnosed Prevalent Cases

2.6Discussion

2.6.1Epidemiological Forecast Insight

2.6.2Limitations of the Analysis

2.6.3Strengths of the Analysis

3Appendix

3.1Bibliography

3.2About the Authors

3.2.1Epidemiologists

3.2.2Reviewers

3.2.3Global Director of Therapy Analysis and Epidemiology

3.2.4Global Head of Healthcare

3.3About GlobalData

3.4About EpiCast

3.5Disclaimer

Table

Table 1: Risk Factors and Comorbidities for HF

Table 2: NYHA Functional Classes I–IV

Table 3: ACCF/AHA Stages A, B, C, and D

Table 4: 7MM, Sources of Epidemiological Data Used for the Forecast of HF Diagnosed Incident Cases

Table 5: 7MM, Sources of Epidemiological Data Used for the Forecast of Chronic HF Diagnosed Prevalent Cases

Table 6: 7MM, Sources of Epidemiological Data Used for the Classification of Diagnosed Prevalent Cases of Chronic HF According to the NYHA Functional Classes I–IV

Table 7: 7MM, Sources of Epidemiological Data Used for Forecast of HF Diagnosed Incident Cases of Acute HF Hospitalizations

Table 8: 7MM, Sources Not Used in Epidemiological Analysis of HF

Table 9: 7MM, Diagnosed Incident Cases of HF, Ages =45 Years, Both Sexes, N, 2015–2025

Table 10: 7MM, Age-Specific Diagnosed Incident Cases of HF, Both Sexes, N (Row %), 2015

Table 11: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages =45 Years, N (Row %), 2015

Table 12: 7MM, Diagnosed Incident Cases of Acute HF Hospitalizations, Ages =45 Years, Both Sexes, N, 2015–2025

Table 13: 7MM, Readmissions (Within Three Months) Post-Discharge After Acute HF Hospitalization Among Diagnosed Incident Cases of Acute HF, Ages =45 Years, Both Sexes, N, 2015–2025

Table 14: 7MM, Diagnosed Prevalent Cases of Chronic HF, Ages =45 Years, Both Sexes, N, 2015–2025

Table 15: 7MM, Age-Specific Diagnosed Prevalent Cases of Chronic HF, Both Sexes, N (Row %), 2015

Table 16: 7MM, Sex-Specific Diagnosed Prevalent Cases of Chronic HF, Ages =45 Years, N (Row %), 2015

Figures

Figure 1: 7MM, Diagnosed Incident Cases of HF, Ages =45 Years, Both Sexes, N, 2015–2025

Figure 2: 7MM, Diagnosed Incident Cases of HF by Age Group, Both Sexes, N, 2015

Figure 3: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages =45 Years, N, 2015

Figure 4: 7MM, Age-Standardized Diagnosed Incidence of HF (Cases per 100,000 Population), Ages =45 Years, by Sex, 2015

Figure 5: 7MM, Diagnosed Incident Cases of HF Segmented by EF, Ages =45 Years, Both Sexes, N, 2015

Figure 6: 7MM, Diagnosed Incident Cases of HF Segmented by Ventricular Dysfunction, Ages =45 Years, Both Sexes, N, 2015

Figure 7: 7MM, Diagnosed Incident Cases of Acute HF Hospitalizations, Ages =45 Years, Both Sexes, N, 2015–2025

Figure 8: 7MM, Diagnosed Incident Cases of Acute HF Hospitalizations, Ages =45 Years, Both Sexes, N, 2015

Figure 9: 7MM, Readmissions (Within Three Months) Post-Discharge After Acute HF Hospitalization Among Diagnosed Incident Cases of Acute HF, Ages =45 Years, Both Sexes, N, 2015–2025

Figure 10: 7MM, Hospital Length Of Stay For Acute HF Hospitalization, Ages =45 Years, Both Sexes, Days, 2015

Figure 11: 7MM, Diagnosed Prevalent Cases of Chronic HF, Ages =45 Years, Both Sexes, N, 2015–2025

Figure 12: 7MM, Age-Specific Diagnosed Prevalent Cases of Chronic HF, Both Sexes, N, 2015

Figure 13: 7MM, Sex-Specific Diagnosed Prevalent Cases of Chronic HF, Ages =45 Years, N, 2015

Figure 14: 7MM, Age-Standardized Diagnosed Prevalence of Chronic HF (%), Ages =45 Years, by Sex, 2015

Figure 15: 7MM, Diagnosed Prevalent Cases of Chronic HF Segmented by EF, Ages =45 Years, Both Sexes, N, 2015

Figure 16: 7MM, Diagnosed Prevalent Cases of Chronic HF Segmented by NYHA Classes, Ages =45 Years, Both Sexes, N, 2015

Figure 17: 7MM, Diagnosed Prevalent Cases of Chronic HF Segmented by ACCF/AHA Stages, Ages =45 Years, Both Sexes, N, 2015

Figure 18: 7MM, Prevalent Cases of Comorbidities Among Diagnosed Prevalent Cases of Chronic HF, Both Sexes, Ages =45 Years, N, 2015

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