Validation of a melanoma prognostic model

Background: A "clinically accessible," 4-variable (patient age, patient sex , tumor location, and tumor 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 pr ognostic model. Design: To estimate the external validity of this model, we used a populati on-based cohort of individuals with melanoma. We also evaluated a 1-variabl e model (tumor thickness). Estimates of the external validity of these logi stic 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. Resu lts: The c statistics for the 4-variable model were 0.86 (95% confidence in terval [CI], 0.83-0.89) for the university-based practice data set and 0.81 (95% CI, 0.75-0.86) for the Connecticut dataset. For thickness alone, the c statistics were 0.83 (95% CI, 0.80-0.86) and 0.79 (95% CI, 0.74-0.85),re; spectively. 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 significa nt 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.