Anais brasileiros de dermatologia · 2013
A melanoma risk score in a Brazilian population.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Bakos Lucio, Mastroeni Simeona, Bonamigo Renan Rangel, Melchi Franco, Pasquini Paolo, Fortes Cristina
Аннотация
BACKGROUND: Important risk factors for cutaneous melanoma (CM) are recognized, but standardized scores for individual assessment must still be developed.
OBJECTIVES: The objective of this study was to develop a risk score of CM for a Brazilian sample.
METHODS: To verify the estimates of the main risk factors for melanoma, derived from a meta-analysis (Italian-based study), and externally validate them in a population in southern Brazil by means of a case-control study. A total of 117 individuals were evaluated. Different models were constructed combining the summary coefficients of different risk factors, derived from the meta-analysis, multiplied by the corresponding category of each variable for each participant according to a mathematical expression.
RESULTS: the variable that best predicted the risk of CM in the studied population was hair color (AUC: 0.71; 95% CI: 0.62-0.79). Other important factors were freckles, sunburn episodes, and skin and eye color. Consideration of other variables such as common nevi, elastosis, family history, and premalignant lesions did not improve the predictive ability of the models.
CONCLUSION: The discriminating capacity of the proposed model proved to be superior or comparable to that of previous risk models proposed for CM.
OBJECTIVES: The objective of this study was to develop a risk score of CM for a Brazilian sample.
METHODS: To verify the estimates of the main risk factors for melanoma, derived from a meta-analysis (Italian-based study), and externally validate them in a population in southern Brazil by means of a case-control study. A total of 117 individuals were evaluated. Different models were constructed combining the summary coefficients of different risk factors, derived from the meta-analysis, multiplied by the corresponding category of each variable for each participant according to a mathematical expression.
RESULTS: the variable that best predicted the risk of CM in the studied population was hair color (AUC: 0.71; 95% CI: 0.62-0.79). Other important factors were freckles, sunburn episodes, and skin and eye color. Consideration of other variables such as common nevi, elastosis, family history, and premalignant lesions did not improve the predictive ability of the models.
CONCLUSION: The discriminating capacity of the proposed model proved to be superior or comparable to that of previous risk models proposed for CM.