Melanoma of the Scalp and Neck: A Population-Based Analysis of Survival and Treatment Patterns

• Published in: Cancers Vol. 14; no. 24; p. 6052
• Main Authors: Scampa, Matteo, Mégevand, Vladimir, Viscardi, Juan A, Giordano, Salvatore, Kalbermatten, Daniel F, Oranges, Carlo M
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.12.2022; MDPI
• Subjects: Care and treatment; Chemotherapy; Demography; Disease; Epidemiology; Gender; Head and neck cancer; Lymphatic system; Medical prognosis; Melanoma; Metastasis; Neck; Patients; Population; Prognosis; Scalp; Skin cancer; Statistical analysis; Statistical power; Surgery; Survival; Survival analysis; Tumors; Variables; Switzerland; United States > US; epidemiology; scalp; surgical margin; survival; SEER; melanoma; neck
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers14246052

Introduction: Melanoma is an aggressive skin cancer. Large demographic and clinic-pathologic studies are required to identify variations of tumour behavior. The aim of our study was to offer updated epidemiologic data on the scalp and neck melanoma with an overall survival analysis. Method: The SEER database was searched for all scalp and neck melanoma in adult patients between 2000 and 2019. Demographic and clinic-pathologic variables were described. Their impact on overall survival was assessed with the log-rank test after Kaplan−Meier model. A multivariable cox-regression was conducted to identify predictors of decreased survival. A p-value of <0.005 was considered statistically significant. Results: 20,728 Melanomas of the scalp and neck were identified. Mean age was 62.5 years. Gender ratio was 76.3% males. 79% of the tumours were localized at diagnosis. Increasing age, male gender, tumour ulceration, high mitotic rate or nodular subtype were independent prognostic factors of decreased overall survival. Surgery with less than 1 cm margin is associated with the best overall survival in this cohort. No significant difference in OS was seen between less than 1 cm and 1 to 2 cm margins. Conclusion: Knowledge of negative prognostic factors might help identify subgroups at risk and adapt their oncologic treatment.