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Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells
Published on: June 7, 2019
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Conditional Melanoma Cancer Survival in the United States
Ray M Merrill1, Simone Bateman2
1Department of Health Science, Brigham Young University, Provo, UT 84602, USA. Ray_Merrill@byu.edu.
Cancers
|February 6, 2016
Summary
Conditional relative survival offers valuable melanoma prognosis, improving with each year survived. Survival rates vary by age, sex, race, and diagnosis stage.
Area of Science:
- Oncology
- Biostatistics
- Epidemiology
Background:
- Relative survival is a key metric for cancer prognosis.
- Conditional relative survival provides personalized prognostic information based on time survived.
- Melanoma survival statistics are crucial for patient management and public health.
Purpose of the Study:
- To present conditional relative survival estimates for melanoma patients in the United States.
- To analyze factors influencing conditional relative survival, including age, sex, race, and disease stage.
- To offer detailed prognostic insights for melanoma patients at different survival milestones.
Main Methods:
- Utilized population-based cancer registry data from the Surveillance, Epidemiology, and End Results (SEER) Program.
- Included 62,803 male and 50,261 female melanoma cases diagnosed between 2000-2008.
- Calculated five-year conditional relative survival probabilities for patients surviving 1-5 years post-diagnosis, with follow-up through 2012.
Main Results:
- Five- and ten-year relative survival decreased with increasing age, later stage at diagnosis, and was lower in males, Blacks, and Hispanics.
- Five-year conditional relative survival consistently improved with each additional year survived post-diagnosis.
- Factors like older age, male sex, Black and Hispanic race, and later stage at diagnosis showed greater potential for conditional survival improvement.
Conclusions:
- Conditional relative survival is a valuable tool for refining melanoma prognosis.
- Survival outcomes are significantly influenced by demographic and clinical factors.
- Personalized survival estimates can empower patients and guide clinical decision-making.
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