DRG Epidemiology's coverage of malignant melanoma comprises epidemiological estimates of key patient populations across 45 countries worldwide. We report both the incidence and prevalence of malignant melanoma for each country, as well as annualized case counts projected to the national population.
Most patient populations are forecast over a period of 20 years for the major mature pharmaceutical markets and 10 years for the other countries covered in this report. In addition to forecasting incident and prevalent patient populations, the number of drug-treatment opportunities at specific lines of therapy are also forecast across the major mature pharmaceutical markets.
DRG Epidemiology's malignant melanoma forecast will answer the following questions:
- How will improvements in survival change the number of people diagnosed with malignant melanoma per year?
- How will decreasing recurrence risk change the number of people living with malignant melanoma?
- Of all people diagnosed with malignant melanoma, how many in each country across the major mature pharmaceutical markets are drug-treated?
- How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of malignant melanoma over the forecast period?
All forecast data are available on the DRG Insights Platform in tabular format, with options to download to MS Excel. All populations are accompanied by a comprehensive description of the methods and data sources used, with hyperlinks to external sources. A summary evidence table generated as part of our systematic review of the epidemiological literature is also provided for full transparency into research and methods. In addition, we provide a graphical depiction of the patient flow between or within different disease states for the countries considered in this report. These patient flow diagrams are provided at the regional level, but may be requested for any specific country or forecast year.
DRG Epidemiology provides at least ten years of forecast data for the following malignant melanoma patient populations:
- Diagnosed incident cases by stage.
- Diagnosed prevalent cases by resectability status.
- First recurrence by site.
- First regional recurrence by resectability status.
- Second recurrence by site.
- Second regional recurrence by resectability status.
- First-line nonresectable BRAF+ve and BRAF-ve DTP subpopulation(s).
- Adjuvant drug-treatable population.
- Other lines of treatment.
… and many more (details available on request).
Note: Coverage may vary by country and region.
- Mature Markets Data
- Key Findings
- Diagnosed Incidence of Malignant Melanoma per 100,000 Among People of All Ages in 2017 and 2037
- The Patient Flow Diagram for Malignant Melanoma in 2017
- Epidemiology Data
- Diagnosed Incident Cases
- Stage Distribution
- Recurrent Incident Cases
- Brain Metastases Status
- Diagnosed Prevalent Cases
- Drug-treatable and Drug-Treated Populations
- Reference Materials
- Literature Review
- Risk/Protective Factors
- Risk/Protective Factors
Author(s): Oliver Blandy; Nishant Kumar, MPH
Oliver Blandy, BSc PGCE MSc, joined Decision Resources Group (DRG) as an Associate Epidemiologist in 2017. He focuses on the epidemiology of cancer. Oliver holds an MSc from the University of Bristol where he specialized in Nutrition, Physical Activity and Public Health. He also holds a BSc in Chemistry and has a Post Graduate Certificate in Education (PGCE), both from the University of Bristol and taught general science and Advanced Chemistry in high school for two years. Before joining the team at DRG, Oliver worked as a Research Assistant for Imperial College London where he was the lead for several studies within an NIRH funded research group that investigated healthcare associated infections and antimicrobial resistance.
Nishant is a senior epidemiologist and head of oncology within the epidemiology team at Decision Resources Group. He also covers some CNS diseases, including Alzheimer’s disease and dementia. His key interests are developing interactive patient flows, and modelling disease progression to forecast commercially relevant drug-treatable incident and prevalent populations. Nishant also spends a lot of time collaborating with clients to help answer more specific questions through custom work and consulting projects. His qualifications include an MSc in Public Health with specialization in epidemiology and statistics from King’s College London, and a BSc in Medical Studies from the University of Birmingham.