암부담 분석 및 예측(2026-2035년)

Cancer remains one of the most significant global health challenges, affecting millions of individuals annually and imposing a considerable burden on healthcare systems, economies, and societies worldwide. According to the latest global estimates, approximately 20 million new cancer cases and 9.7 million cancer-related deaths occurred in 2022. Furthermore, global cancer incidence is projected to increase to more than 35 million new cases annually by 2050, representing a 77% increase compared to 2022 levels. This growth is largely attributed to population aging, population growth, urbanization, and increasing exposure to cancer risk factors.

Cancer burden analysis encompasses the systematic evaluation of incidence, prevalence, mortality, survival, disability-adjusted life years (DALYs), economic burden, healthcare utilization, and patient population trends across different cancer types, demographic groups, and geographic regions. These analyses play a critical role in healthcare policy development, pharmaceutical market assessment, clinical trial planning, public health interventions, and long-term healthcare resource planning.

Market Drivers

Rising Global Cancer Incidence

One of the primary drivers of market growth is the continuous increase in cancer incidence worldwide. Global estimates indicate that nearly one in five people will develop cancer during their lifetime, making cancer one of the leading causes of morbidity and mortality globally. The growing number of cancer diagnoses is increasing demand for epidemiological intelligence, disease burden assessments, and healthcare forecasting solutions.

Population Aging and Demographic Shifts

Cancer risk increases substantially with age due to cumulative exposure to environmental and lifestyle risk factors and age-related biological changes. As global populations continue to age, particularly in developed and emerging economies, the number of cancer patients is expected to increase significantly. The World Health Organization identifies population aging as one of the major contributors to the future cancer burden.

Increasing Prevalence of Modifiable Risk Factors

The growing prevalence of tobacco use, obesity, unhealthy diets, alcohol consumption, physical inactivity, environmental pollution, and chronic infections continues to contribute to rising cancer incidence worldwide. Public health organizations increasingly rely on cancer burden analysis to identify high-risk populations and evaluate prevention strategies.

Expansion of Healthcare Data Infrastructure

The increasing availability of cancer registries, electronic health records, insurance claims databases, genomic repositories, mortality databases, and population health platforms is improving the quality and accessibility of cancer-related data.

These resources enable more accurate disease burden assessments, survival analyses, patient population forecasting, and healthcare planning activities.

Market Restraints

Variability in Cancer Registration and Reporting

Significant differences exist in cancer registry coverage, diagnostic infrastructure, healthcare accessibility, and disease reporting standards across countries.

These disparities can create inconsistencies in epidemiological datasets and affect the accuracy of global disease burden estimates.

Underdiagnosis and Underreporting

Many low- and middle-income countries continue to experience limitations in cancer screening, pathology services, and healthcare infrastructure. Consequently, cancer incidence and mortality may be underreported in certain regions.

This can complicate disease burden analyses and long-term forecasting efforts.

Complexity of Global Disease Patterns

Cancer encompasses hundreds of disease subtypes with varying biological characteristics, risk factors, treatment pathways, and outcomes. Understanding the interaction among demographic, environmental, genetic, and behavioral factors remains a complex analytical challenge.

Technology and Segment Insights

The global cancer burden analysis market can be segmented by cancer type, burden metric, data source, application, end user, and geography.

By cancer type, the market includes lung cancer, breast cancer, colorectal cancer, prostate cancer, liver cancer, stomach cancer, pancreatic cancer, cervical cancer, ovarian cancer, hematologic malignancies, pediatric cancers, and other cancer types. Lung cancer remains the most frequently diagnosed cancer globally, accounting for approximately 2.5 million new cases in 2022 and remaining the leading cause of cancer-related mortality worldwide. Breast cancer represents the most commonly diagnosed cancer among women globally.

By burden metric, the market includes incidence analysis, prevalence analysis, mortality assessment, survival analysis, disability-adjusted life years (DALYs), quality-adjusted life years (QALYs), economic burden evaluation, healthcare utilization analysis, and patient population forecasting. Incidence and mortality analyses represent major segments due to their importance in healthcare planning and policy development.

By data source, the market includes cancer registries, electronic health records, hospital databases, insurance claims databases, mortality databases, genomic databases, population health surveys, and public health surveillance systems. Cancer registries remain among the most important sources of oncology intelligence due to their comprehensive disease tracking capabilities.

By application, the market includes healthcare planning, public health policy development, clinical research support, pharmaceutical market assessment, clinical trial planning, resource allocation, prevention strategy development, and healthcare investment analysis. Patient population forecasting and healthcare planning represent significant application areas due to increasing oncology service demands.

By end user, the market serves pharmaceutical companies, biotechnology firms, healthcare providers, academic institutions, government agencies, public health organizations, contract research organizations, and healthcare consulting firms. Government agencies and public health organizations account for a significant share of demand due to their responsibilities for cancer surveillance and healthcare planning.

Technological advancements are transforming cancer burden analysis through artificial intelligence, machine learning, predictive analytics, population health modeling, natural language processing, and real-world evidence platforms. These technologies enable more accurate disease forecasting, identification of emerging trends, patient stratification, and healthcare resource optimization.

The integration of genomic information, molecular profiling data, environmental exposure metrics, lifestyle factors, and healthcare utilization records is creating increasingly sophisticated analytical models that support precision public health and personalized oncology initiatives.

Global Burden Insights

Cancer burden varies significantly across regions and socioeconomic groups. High-income countries generally report higher cancer incidence rates due to more extensive screening and diagnostic capabilities, while lower-income countries often experience higher mortality rates because of delayed diagnosis and limited access to treatment. The International Agency for Research on Cancer projects that low- and medium-human-development countries will experience the largest proportional increases in cancer incidence and mortality by 2050.

Global analyses indicate that lung cancer remains the most commonly diagnosed cancer and the leading cause of cancer death worldwide. Colorectal, breast, prostate, liver, and stomach cancers also contribute substantially to the global disease burden. Additionally, approximately 53.5 million individuals worldwide were living within five years of a cancer diagnosis in 2022, highlighting the growing importance of survivorship and long-term disease management.

Competitive and Strategic Outlook

The competitive landscape includes epidemiology research organizations, healthcare analytics providers, academic research institutions, cancer research centers, public health agencies, contract research organizations, and healthcare intelligence companies. Market participants are increasingly investing in advanced analytics technologies, artificial intelligence platforms, real-world evidence solutions, and integrated oncology intelligence systems.

Strategic collaborations among pharmaceutical companies, healthcare providers, academic institutions, government agencies, and technology firms are becoming increasingly common as stakeholders seek to improve cancer surveillance, patient population forecasting, and healthcare planning capabilities.

Organizations are also expanding investments in precision medicine, genomic analytics, and digital health technologies to improve understanding of disease burden and support evidence-based healthcare decision-making.

Conclusion

The global cancer burden analysis market is poised for robust growth through 2031, supported by rising cancer incidence, aging populations, expanding healthcare data infrastructure, and increasing demand for evidence-based oncology intelligence. With approximately 20 million new cancer cases and 9.7 million deaths recorded globally in 2022 and annual cases projected to exceed 35 million by 2050, the importance of comprehensive cancer burden analysis continues to increase. Advances in artificial intelligence, real-world evidence generation, predictive analytics, and population health technologies are expected to significantly enhance disease surveillance and forecasting capabilities. As healthcare systems worldwide seek to improve cancer prevention, diagnosis, treatment, and survivorship outcomes, cancer burden analysis will remain a critical component of healthcare planning, policy development, and oncology market evaluation.

Key Benefits of this Report

• Insightful Analysis: Comprehensive evaluation of global cancer incidence, prevalence, mortality, survival, and disease burden trends.
• Competitive Landscape: Understand emerging epidemiological trends, research developments, and oncology market dynamics.
• Market Drivers and Future Trends: Assess key factors influencing cancer burden growth and healthcare demand.
• Actionable Recommendations: Support healthcare planning, policy development, investment decisions, and oncology strategy formulation.
• Caters to a Wide Audience: Suitable for pharmaceutical companies, healthcare providers, academic institutions, public health agencies, consultants, and investors.

What Businesses Use Our Reports For

Patient population forecasting, disease burden assessment, healthcare resource planning, oncology market evaluation, clinical trial strategy development, public health policy formulation, investment analysis, epidemiological intelligence, and competitive benchmarking.

Report Coverage

• Historical data from 2021 to 2024, Base year 2025, and Forecast years from 2026 to 2031
• Global, regional, and country-level incidence, prevalence, mortality, survival, and patient population analysis
• Cancer type-specific burden assessment, risk factor analysis, and disease burden forecasting
• Healthcare utilization, economic burden evaluation, and oncology planning insights
• Competitive intelligence, research developments, and future market opportunity assessment.

TABLE OF CONTENTS

1. Executive Summary

• 1.1 Global Cancer Burden Overview
  • 1.1.1 Definition of Cancer Burden Analysis
  • 1.1.2 Scope of DALYs, QALYs & Disease Trend Assessment
  • 1.1.3 Key Findings and Strategic Insights
  • 1.1.4 Global Burden Distribution by Cancer Type
  • 1.1.5 Mortality and Disability Trends
  • 1.1.6 Healthcare System Impact Assessment
  • 1.1.7 Economic Burden and Productivity Loss
  • 1.1.8 Emerging Trends in Oncology Outcomes Measurement
• 1.2 Executive Snapshot by Cancer Category
  • 1.2.1 Solid Tumors
  • 1.2.2 Hematologic Malignancies
  • 1.2.3 Rare and Orphan Cancers
  • 1.2.4 Pediatric Oncology Burden
• 1.3 Key Epidemiological Metrics
  • 1.3.1 Disability-Adjusted Life Years (DALYs)
  • 1.3.2 Quality-Adjusted Life Years (QALYs)
  • 1.3.3 Years of Life Lost (YLLs)
  • 1.3.4 Years Lived with Disability (YLDs)
  • 1.3.5 Survival and Quality-of-Life Metrics

2. Disease & Epidemiology Analysis

• 2.1 Introduction to Global Cancer Epidemiology
  • 2.1.1 Definition and Classification of Cancer
  • 2.1.2 Pathophysiology and Disease Progression
  • 2.1.3 Global Oncology Disease Burden
• 2.2 Global Incidence and Prevalence Analysis
  • 2.2.1 Overall Cancer Incidence
  • 2.2.2 Prevalence by Cancer Type
  • 2.2.3 Mortality Trends
  • 2.2.4 Five-Year Survival Trends
  • 2.2.5 Recurrence and Relapse Trends
• 2.3 Burden Analysis by Cancer Type
  • 2.3.1 Breast Cancer
  • 2.3.2 Lung Cancer
  • 2.3.3 Colorectal Cancer
  • 2.3.4 Prostate Cancer
  • 2.3.5 Liver Cancer
  • 2.3.6 Gastric Cancer
  • 2.3.7 Cervical Cancer
  • 2.3.8 Ovarian Cancer
  • 2.3.9 Pancreatic Cancer
  • 2.3.10 Leukemia
  • 2.3.11 Lymphoma
  • 2.3.12 Multiple Myeloma
  • 2.3.13 Melanoma
  • 2.3.14 Brain and CNS Tumors
  • 2.3.15 Pediatric Cancers
• 2.4 DALYs Analysis
  • 2.4.1 DALYs by Cancer Type
  • 2.4.2 DALYs by Age Group
  • 2.4.3 DALYs by Gender
  • 2.4.4 DALYs by Socioeconomic Status
  • 2.4.5 Trends in Years of Life Lost (YLLs)
  • 2.4.6 Trends in Years Lived with Disability (YLDs)
• 2.5 QALYs Analysis
  • 2.5.1 QALY Assessment Framework
  • 2.5.2 Treatment Impact on QALYs
  • 2.5.3 Quality-of-Life Outcomes by Therapy Type
  • 2.5.4 Comparative QALY Assessment Across Cancer Types
  • 2.5.5 Utility Scores and Patient-Reported Outcomes
• 2.6 Demographic and Risk Factor Analysis
  • 2.6.1 Age-Based Epidemiology
  • 2.6.2 Gender-Based Trends
  • 2.6.3 Lifestyle Risk Factors
  • 2.6.4 Tobacco and Alcohol Impact
  • 2.6.5 Obesity and Metabolic Factors
  • 2.6.6 Occupational and Environmental Exposure
  • 2.6.7 Genetic and Hereditary Factors
  • 2.6.8 Infectious Disease-Associated Cancers
• 2.7 Screening and Early Detection Trends
  • 2.7.1 Mammography Screening
  • 2.7.2 Colonoscopy and FIT Testing
  • 2.7.3 Low-Dose CT Screening
  • 2.7.4 HPV Screening Programs
  • 2.7.5 Biomarker and Liquid Biopsy Adoption

3. Market Dynamics

• 3.1 Market Drivers
  • 3.1.1 Rising Global Cancer Incidence
  • 3.1.2 Increasing Aging Population
  • 3.1.3 Advancements in Precision Oncology
  • 3.1.4 Growing Adoption of Value-Based Healthcare
  • 3.1.5 Expansion of Cancer Screening Programs
• 3.2 Market Restraints
  • 3.2.1 High Cost of Oncology Therapies
  • 3.2.2 Limited Access in Low- and Middle-Income Regions
  • 3.2.3 Variability in Reimbursement Policies
  • 3.2.4 Regulatory Challenges
  • 3.2.5 Data Standardization Limitations
• 3.3 Market Opportunities
  • 3.3.1 Expansion of Immuno-Oncology
  • 3.3.2 Integration of AI in Oncology Analytics
  • 3.3.3 Personalized Medicine and Biomarker Testing
  • 3.3.4 Digital Health and Remote Monitoring
  • 3.3.5 Expansion of Preventive Oncology
• 3.4 Market Challenges
  • 3.4.1 Clinical Trial Recruitment Complexity
  • 3.4.2 Healthcare Infrastructure Gaps
  • 3.4.3 Drug Affordability Concerns
  • 3.4.4 Inequities in Cancer Care Access

4. Commercial & Market Access

• 4.1 Oncology Market Access Overview
  • 4.1.1 Pricing and Reimbursement Models
  • 4.1.2 Health Technology Assessment (HTA) Frameworks
  • 4.1.3 Cost-Effectiveness Thresholds
  • 4.1.4 Role of QALYs in Reimbursement Decisions
• 4.2 Payer Landscape
  • 4.2.1 Public Payers
  • 4.2.2 Private Insurance Providers
  • 4.2.3 Value-Based Contracting
  • 4.2.4 Outcomes-Based Agreements
• 4.3 Access to Cancer Therapies
  • 4.3.1 Access to Targeted Therapies
  • 4.3.2 Access to Immunotherapies
  • 4.3.3 Access to Cell and Gene Therapies
  • 4.3.4 Access Disparities by Region

5. Innovation & Pipeline Landscape

• 5.1 Overview of Oncology Innovation
  • 5.1.1 Evolution of Cancer Therapeutics
  • 5.1.2 Emerging Therapeutic Modalities
  • 5.1.3 Precision Oncology Innovations
• 5.2 Pipeline Analysis by Development Phase
  • 5.2.1 Phase I Pipeline Candidates
  • 5.2.2 Phase II Pipeline Candidates
  • 5.2.3 Phase III Pipeline Candidates
  • 5.2.4 Preclinical Oncology Programs
• 5.3 Pipeline Analysis by Modality
  • 5.3.1 Monoclonal Antibodies
  • 5.3.2 Immune Checkpoint Inhibitors
  • 5.3.3 CAR-T Cell Therapies
  • 5.3.4 Antibody-Drug Conjugates (ADCs)
  • 5.3.5 Cancer Vaccines
  • 5.3.6 Radiopharmaceuticals
  • 5.3.7 Gene Editing Therapies
  • 5.3.8 Small Molecule Targeted Therapies
• 5.4 Pipeline Analysis by Mechanism of Action
  • 5.4.1 PD-1/PD-L1 Inhibition
  • 5.4.2 CTLA-4 Inhibition
  • 5.4.3 HER2 Targeting
  • 5.4.4 EGFR Inhibition
  • 5.4.5 VEGF Inhibition
  • 5.4.6 PARP Inhibition
  • 5.4.7 KRAS Inhibition
  • 5.4.8 CD19/CD20 Targeting
• 5.5 Clinical Trial Landscape
  • 5.5.1 Trial Volume by Phase
  • 5.5.2 Trial Distribution by Cancer Type
  • 5.5.3 Endpoint Trends in Oncology Studies
  • 5.5.4 Biomarker-Driven Trial Design

6. Treatment Landscape

• 6.1 Standard of Care Overview
  • 6.1.1 Surgery
  • 6.1.2 Radiation Therapy
  • 6.1.3 Chemotherapy
  • 6.1.4 Immunotherapy
  • 6.1.5 Targeted Therapy
  • 6.1.6 Hormonal Therapy
  • 6.1.7 Cell and Gene Therapy
• 6.2 Approved Oncology Drug Landscape
  • 6.2.1 Immune Checkpoint Inhibitors
  • 6.2.2 Targeted Oncology Drugs
  • 6.2.3 Antibody-Drug Conjugates
  • 6.2.4 CAR-T Cell Therapies
  • 6.2.5 Radioligand Therapies
• 6.3 Treatment Algorithms by Cancer Type
  • 6.3.1 Breast Cancer Treatment Pathway
  • 6.3.2 Lung Cancer Treatment Pathway
  • 6.3.3 Colorectal Cancer Treatment Pathway
  • 6.3.4 Hematologic Cancer Treatment Pathway
• 6.4 Comparative Effectiveness Analysis
  • 6.4.1 Survival Outcomes Comparison
  • 6.4.2 QALY Gain Comparison
  • 6.4.3 Safety and Tolerability Comparison
  • 6.4.4 Real-World Evidence Analysis

7. Global Cancer Burden Analysis - DALYs, QALYs & Disease Trends Size & Forecast

• 7.1 Global Market Overview
  • 7.1.1 Historical Market Size Analysis
  • 7.1.2 Forecast Methodology
  • 7.1.3 Market Forecast by Value
  • 7.1.4 Market Forecast by Volume
• 7.2 Market Forecast by Cancer Type
  • 7.2.1 Solid Tumors
  • 7.2.2 Hematologic Malignancies
  • 7.2.3 Rare Cancers
• 7.3 Market Forecast by Therapy Type
  • 7.3.1 Chemotherapy
  • 7.3.2 Immunotherapy
  • 7.3.3 Targeted Therapy
  • 7.3.4 Cell Therapy
  • 7.3.5 Radiopharmaceuticals

8. Global Cancer Burden Analysis - DALYs, QALYs & Disease Trends Segmentation

• 8.1 By Cancer Type
  • 8.1.1 Breast Cancer
  • 8.1.2 Lung Cancer
  • 8.1.3 Colorectal Cancer
  • 8.1.4 Prostate Cancer
  • 8.1.5 Hematologic Malignancies
  • 8.1.6 Gynecologic Cancers
  • 8.1.7 Gastrointestinal Cancers
  • 8.1.8 Other Cancers
• 8.2 By Therapy Type
  • 8.2.1 Chemotherapy
  • 8.2.2 Immunotherapy
  • 8.2.3 Targeted Therapy
  • 8.2.4 Hormonal Therapy
  • 8.2.5 Cell and Gene Therapy
  • 8.2.6 Combination Therapy
• 8.3 By Drug Class
  • 8.3.1 PD-1/PD-L1 Inhibitors
  • 8.3.2 CTLA-4 Inhibitors
  • 8.3.3 Tyrosine Kinase Inhibitors
  • 8.3.4 PARP Inhibitors
  • 8.3.5 Monoclonal Antibodies
  • 8.3.6 Others
• 8.4 By Route of Administration
  • 8.4.1 Oral
  • 8.4.2 Intravenous
  • 8.4.3 Subcutaneous & Intratumoral
• 8.5 By End User
  • 8.5.1 Hospitals
  • 8.5.2 Cancer Specialty Centers
  • 8.5.3 Academic and Research Institutes
  • 8.5.4 Others
• 8.6 By Distribution Channel
  • 8.6.1 Hospital Pharmacies
  • 8.6.2 Retail & Specialty Pharmacies
  • 8.6.4 Online Pharmacies

9. Geographical Analysis (Regional Level)

• 9.1 North America
  • 9.1.1 Regional Market Size and Forecast
  • 9.1.2 Cancer Burden and Epidemiology Trends
  • 9.1.3 Regional Regulatory Overview
  • 9.1.4 Reimbursement and Market Access
  • 9.1.5 Competitive Landscape
• 9.2 Europe
  • 9.2.1 Regional Market Size and Forecast
  • 9.2.2 Cancer Burden and Epidemiology Trends
  • 9.2.3 Regional Regulatory Overview
  • 9.2.4 Reimbursement and Market Access
  • 9.2.5 Competitive Landscape
• 9.3 Asia-Pacific
  • 9.3.1 Regional Market Size and Forecast
  • 9.3.2 Cancer Burden and Epidemiology Trends
  • 9.3.3 Regional Regulatory Overview
  • 9.3.4 Reimbursement and Market Access
  • 9.3.5 Competitive Landscape
• 9.4 Latin America
  • 9.4.1 Regional Market Size and Forecast
  • 9.4.2 Cancer Burden and Epidemiology Trends
  • 9.4.3 Regional Regulatory Overview
  • 9.4.4 Reimbursement and Market Access
  • 9.4.5 Competitive Landscape
• 9.5 Middle East & Africa
  • 9.5.1 Regional Market Size and Forecast
  • 9.5.2 Cancer Burden and Epidemiology Trends
  • 9.5.3 Regional Regulatory Overview
  • 9.5.4 Reimbursement and Market Access
  • 9.5.5 Competitive Landscape

10. Key Countries Analysis

• 10.1 United States
  • 10.1.1 Market Size
  • 10.1.2 Cancer Epidemiology
  • 10.1.3 FDA Regulatory Framework
  • 10.1.4 Reimbursement Landscape
  • 10.1.5 Key Companies and Product Presence
• 10.2 Canada
  • 10.2.1 Market Size
  • 10.2.2 Cancer Epidemiology
  • 10.2.3 Regulatory Framework
  • 10.2.4 Reimbursement Landscape
  • 10.2.5 Key Companies and Product Presence
• 10.3 Germany
• 10.4 United Kingdom
• 10.5 France
• 10.6 Italy
• 10.7 Spain
• 10.8 China
• 10.9 Japan
• 10.10 India
• 10.11 South Korea
• 10.12 Australia
• 10.13 Brazil
• 10.14 Mexico
• 10.15 Saudi Arabia
• 10.16 South Africa

11. Regulatory & Policy Landscape

• 11.1 United States Regulatory Framework
  • 11.1.1 FDA Oncology Drug Approval Pathways
  • 11.1.2 Accelerated Approval Programs
  • 11.1.3 Companion Diagnostic Regulations
• 11.2 Europe Regulatory Framework
  • 11.2.1 EMA Oncology Approval Process
  • 11.2.2 EU MDR Requirements
  • 11.2.3 HTA Harmonization Initiatives
• 11.3 Japan Regulatory Framework
  • 11.3.1 PMDA Oncology Review Process
  • 11.3.2 Sakigake Designation
• 11.4 India Regulatory Framework
  • 11.4.1 CDSCO Approval Requirements
  • 11.4.2 Pricing and Access Policies
• 11.5 China Regulatory Framework
  • 11.5.1 NMPA Oncology Approval Process
  • 11.5.2 Oncology Innovation Policies
• 11.6 Global Oncology Policy Trends
  • 11.6.1 Value-Based Oncology Care
  • 11.6.2 National Cancer Control Programs
  • 11.6.3 Real-World Evidence Integration
  • 11.6.4 Biosimilar and Generic Oncology Policies

12. Competitive Landscape

• 12.1 Market Share Analysis
• 12.2 Competitive Benchmarking
• 12.3 Strategic Collaborations and Partnerships
• 12.4 Mergers and Acquisitions
• 12.5 Licensing and Co-Development Agreements
• 12.6 R&D Investment Trends
• 12.7 Patent Landscape Analysis
• 12.8 Recent Product Approvals and Launches

13. Company Profiles

• 13.1 Merck & Co.
  • 13.1.1 Company Overview
  • 13.1.2 Approved Oncology Products
    • 13.1.2.1 Keytruda (pembrolizumab)
  • 13.1.3 Key Indications
  • 13.1.4 Pipeline Candidates and Clinical Stages
  • 13.1.5 Financial and Strategic Highlights
• 13.2 Bristol Myers Squibb
  • 13.2.1 Approved Oncology Products
    • 13.2.1.1 Opdivo (nivolumab)
    • 13.2.1.2 Yervoy (ipilimumab)
• 13.3 Roche Holding AG
  • 13.3.1 Approved Oncology Products
    • 13.3.1.1 Herceptin (trastuzumab)
    • 13.3.1.2 Avastin (bevacizumab)
    • 13.3.1.3 Tecentriq (atezolizumab)
• 13.4 AstraZeneca
  • 13.4.1 Approved Oncology Products
    • 13.4.1.1 Tagrisso (osimertinib)
    • 13.4.1.2 Imfinzi (durvalumab)
• 13.5 Novartis
  • 13.5.1 Approved Oncology Products
    • 13.5.1.1 Kisqali (ribociclib)
    • 13.5.1.2 Kymriah (tisagenlecleucel)
• 13.6 Pfizer
  • 13.6.1 Approved Oncology Products
    • 13.6.1.1 Ibrance (palbociclib)
    • 13.6.1.2 Adcetris (brentuximab vedotin)
• 13.7 Johnson & Johnson
  • 13.7.1 Approved Oncology Products
    • 13.7.1.1 Darzalex (daratumumab)
    • 13.7.1.2 Erleada (apalutamide)
• 13.8 Gilead Sciences
  • 13.8.1 Approved Oncology Products
    • 13.8.1.1 Trodelvy (sacituzumab govitecan)
    • 13.8.1.2 Yescarta (axicabtagene ciloleucel)
• 13.9 Eli Lilly and Company
  • 13.9.1 Approved Oncology Products
    • 13.9.1.1 Verzenio (abemaciclib)
    • 13.9.1.2 Retevmo (selpercatinib)
• 13.10 AbbVie
  • 13.10.1 Approved Oncology Products
    • 13.10.1.1 Venclexta (venetoclax)
  • 13.10.2 Pipeline Candidates and Clinical Development

14. Future Outlook

• 14.1 Future Burden of Cancer
• 14.2 Emerging Epidemiological Trends
• 14.3 Future Role of DALYs and QALYs in Oncology Decision-Making
• 14.4 AI and Predictive Analytics in Cancer Burden Assessment
• 14.5 Future of Precision Oncology
• 14.6 Preventive Oncology and Early Detection Outlook
• 14.7 Strategic Recommendations for Stakeholders

15. Methodology

• 15.1 Research Methodology Overview
• 15.2 Primary Research Methodology
• 15.3 Secondary Research Methodology
• 15.4 Epidemiology Modeling Approach
• 15.5 Forecasting Methodology
• 15.6 Data Validation and Triangulation
• 15.7 Assumptions and Limitations
• 15.8 Abbreviations and Definitions