Age-oriented risk stratification model for basal cell carcinoma: relationship between age, skin phototype, and anatomical localization in a single-center study
- 1Odesa National Medical University, Odesa, Ukraine
- 2The Municipal Non-Profit Enterprise «Odesa Regional Clinical Antitumor Center» of the Odesa Regional Council, Odesa, Ukraine
Summary. Basal cell carcinoma is the most common malignant skin tumor, the development of which is associated with ultraviolet radiation exposure, skin phototype, and age-related changes. Objective. To determine the role of age in the clinical distribution of basal cell carcinoma with regard to tumor anatomical localization and skin phototype, and to develop an age-oriented risk stratification model for dermatologic oncology surveillance. Materials and methods. A single-center observational cross-sectional study was conducted involving 191 patients with histologically confirmed basal cell carcinoma of the skin. All patients underwent clinical examination, dermoscopy, and laboratory investigations. Age, sex, Fitzpatrick skin phototype, and tumor localization were analyzed. Statistical analysis was performed using Pearson’s χ² test, Fisher’s exact test, and binary logistic regression with calculation of odds ratios (OR) and 95% confidence intervals (CI). Results. Patients older than 60 years predominated in the cohort (77.5%). Tumors were most frequently localized on the face (61.8%), corresponding to chronic ultraviolet exposure of sun-exposed skin areas. Logistic regression analysis demonstrated a trend toward an association between age over 60 years and facial tumor localization (OR=1.76; 95% CI 0.89–3.50). No statistically significant associations were found between skin phototype and the clinical characteristics of basal cell carcinoma (p >0.05). Conclusions. Age is an important determinant of the clinical distribution of basal cell carcinoma and may be considered a marker of cumulative photodamage and mutational burden. An age-oriented risk stratification model (ARSM-BCC) was proposed, which may be used for personalized dermatologic oncology surveillance and requires further validation.
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