AGE AS A PROGNOSTIC FACTOR IN THE MALIGNANT-MELANOMA POPULATION

Background: The incidence of malignant melanoma is increasing faster t han any other cancer, and the state of Florida has one of the highest incidence of melanoma in the United States. This increased incidence i s thought to be due to the intense sunlight exposure and ultraviolet r adiation exposure in the elderly population. With the increased emphas is on issues of aging, it is appropriate to study the role of age as a prognostic factor for malignant melanoma in the Florida population. M ethods: A retrospective, computer-aided search identified 442 consecut ively registered patients with malignant melanoma at the Cutaneous Onc ology Program. All patients had stage 1 or 2 disease (cutaneous diseas e only) at diagnosis. Prognostic variables analyzed included the most powerful factors for stage 1 and 2 melanoma, tumor thickness, ulcerati on, and Clark level of invasion. Other prognostic variables included i n the analysis were the clinical variables of sex and primary site (ax ial vs. extremity). The population was divided into patients less than or equal to 65 and > 65 years of age. Results: Significant disease-fr ee survival differences were encountered in the older population, with only 55% of the elderly population being disease free at 5 years comp ared with 65% for the younger population (p = 0.0073). However, a grea ter percentage of patients with melanoma who were > 65 years of age ha d ulcerated lesions (17.5% vs. 12.9%) and a greater percentage of thic k lesions at diagnosis (67.2% vs. 62.7%). Both of these prognostic fac tors would bias the older population with a poorer survival. A stepwis e regression analysis of the entire population was performed, treating age as a continuous variable. Surprisingly, increasing age along with tumor thickness were the only significant predictors for disease-free survival. After inclusion of these two prognostic variables, none of the other prognostic factors, including Clark revel, ulceration, sex, and primary site, added to the prognostic model. Conclusions: From thi s analysis, it is apparent that geriatric patients with melanoma have a worse prognosis than a younger control population, even after the co rrection for the more commonly cited prognostic factors. This informat ion should be used in mathematical modeling to identify high-risk popu lations who are candidates for perhaps more aggressive primary or adju vant therapies.