BACKGROUND: A "clinically accessible," 4-variable (patient age, patient sex, tumor location, and tumour thickness) prognostic model has been published previously. This model evaluated variables that were commonly available to the clinician. Because models are heuristic, validity of a prognostic model should be evaluated in a population different from the original population. OBJECTIVE: To evaluate the external validity of this 4-variable melanoma prognostic model. DESIGN: To estimate the external validity of this model, we used a population-based cohort of individuals with melanoma. We also evaluated a 1-variable model (tumor thickness). Estimates of the external validity of these logistic regression models were made using the c statistic and the Brier score. SETTINGS AND PATIENTS: A total of 1261 patients with melanoma evaluated in a multispecialty, university-based practice and 650 patients with melanoma from throughout Connecticut. MAIN OUTCOME MEASURE: Death from melanoma within 5 years of diagnosis. RESULTS: The c statistics for the 4-variable model were 0.86 (95% confidence interval [CI], 0.83-0.89) for the university-based practice data set and 0.81 (95% CI, 0.75-0.86) for the Connecticut data set. For thickness alone, the c statistics were 0.83 (95% CI, 0.80-0.86) and 0.79 (95% CI, 0.74-0.85), respectively. Brier scores for the 4-variable model were 0.09 (95% CI, 0.08-0.10) and 0.08 (95% CI, 0.06-0.09) and for the 1-variable model were 0.09 (95% CI, 0.08-0.10) and 0.08 (95% CI, 0.07-0.10), respectively. No significant differences exist between the data sets for the 4- and 1-variable models. CONCLUSIONS: The 4- and 1-variable models are generalizable. The simpler 1-variable model--tumor thickness--can be used with a relatively small loss in accuracy.
BACKGROUND: A "clinically accessible," 4-variable (patient age, patient sex, tumor location, and tumour thickness) prognostic model has been published previously. This model evaluated variables that were commonly available to the clinician. Because models are heuristic, validity of a prognostic model should be evaluated in a population different from the original population. OBJECTIVE: To evaluate the external validity of this 4-variable melanoma prognostic model. DESIGN: To estimate the external validity of this model, we used a population-based cohort of individuals with melanoma. We also evaluated a 1-variable model (tumor thickness). Estimates of the external validity of these logistic regression models were made using the c statistic and the Brier score. SETTINGS AND PATIENTS: A total of 1261 patients with melanoma evaluated in a multispecialty, university-based practice and 650 patients with melanoma from throughout Connecticut. MAIN OUTCOME MEASURE: Death from melanoma within 5 years of diagnosis. RESULTS: The c statistics for the 4-variable model were 0.86 (95% confidence interval [CI], 0.83-0.89) for the university-based practice data set and 0.81 (95% CI, 0.75-0.86) for the Connecticut data set. For thickness alone, the c statistics were 0.83 (95% CI, 0.80-0.86) and 0.79 (95% CI, 0.74-0.85), respectively. Brier scores for the 4-variable model were 0.09 (95% CI, 0.08-0.10) and 0.08 (95% CI, 0.06-0.09) and for the 1-variable model were 0.09 (95% CI, 0.08-0.10) and 0.08 (95% CI, 0.07-0.10), respectively. No significant differences exist between the data sets for the 4- and 1-variable models. CONCLUSIONS: The 4- and 1-variable models are generalizable. The simpler 1-variable model--tumor thickness--can be used with a relatively small loss in accuracy.
Authors: Susan A Oliveria; Jennifer L Hay; Alan C Geller; Maureen K Heneghan; Mary S McCabe; Allan C Halpern Journal: J Cancer Surviv Date: 2007-03 Impact factor: 4.442
Authors: Elliot J Coups; Jerod L Stapleton; Shawna V Hudson; Amanda Medina-Forrester; Stephen A Rosenberg; Marsha Gordon; Ana Natale-Pereira; James S Goydos Journal: J Am Acad Dermatol Date: 2012-11-19 Impact factor: 11.527
Authors: Elliot J Coups; Sharon L Manne; Paul B Jacobsen; Michael E Ming; Carolyn J Heckman; Stuart R Lessin Journal: BMC Public Health Date: 2011-11-14 Impact factor: 3.295