1. Melanoma-specific mortality and competing mortality in patients with non-metastatic malignant melanoma: a population-based analysis.
- Author
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Weidong Shen, Naoko Sakamoto, Limin Yang, Shen, Weidong, Sakamoto, Naoko, and Yang, Limin
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MELANOMA , *SKIN cancer , *MORTALITY , *POPULATION research , *EPIDEMIOLOGY , *DEMOGRAPHY , *REPORTING of diseases , *METASTASIS , *PROGNOSIS , *RISK assessment , *STATISTICAL models - Abstract
Background: The objectives of this study were to evaluate and model the probability of melanoma-specific death and competing causes of death for patients with melanoma by competing risk analysis, and to build competing risk nomograms to provide individualized and accurate predictive tools.Methods: Melanoma data were obtained from the Surveillance Epidemiology and End Results program. All patients diagnosed with primary non-metastatic melanoma during the years 2004-2007 were potentially eligible for inclusion. The cumulative incidence function (CIF) was used to describe the probability of melanoma mortality and competing risk mortality. We used Gray's test to compare differences in CIF between groups. The proportional subdistribution hazard approach by Fine and Gray was used to model CIF. We built competing risk nomograms based on the models that we developed.Results: The 5-year cumulative incidence of melanoma death was 7.1 %, and the cumulative incidence of other causes of death was 7.4 %. We identified that variables associated with an elevated probability of melanoma-specific mortality included older age, male sex, thick melanoma, ulcerated cancer, and positive lymph nodes. The nomograms were well calibrated. C-indexes were 0.85 and 0.83 for nomograms predicting the probability of melanoma mortality and competing risk mortality, which suggests good discriminative ability.Conclusions: This large study cohort enabled us to build a reliable competing risk model and nomogram for predicting melanoma prognosis. Model performance proved to be good. This individualized predictive tool can be used in clinical practice to help treatment-related decision making. [ABSTRACT FROM AUTHOR]- Published
- 2016
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