4.5 Article

Merkel cell carcinoma: Identification of prognostic factors unique to tumors located in the head and neck based on analysis of SEER data

Journal

LARYNGOSCOPE
Volume 122, Issue 6, Pages 1283-1290

Publisher

WILEY-BLACKWELL
DOI: 10.1002/lary.23222

Keywords

Merkel cell carcinoma; head and neck; cutaneous malignancies; elderly; prognostic factors

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Objectives/Hypothesis: Merkel cell carcinoma (MCC) is an aggressive cutaneous neoplasm that occurs most frequently in the head and neck region. Because of its rarity, prognostic factors are poorly characterized. Head and neck MCC (HN-MCC) may require separate consideration from MCC that occurs in other anatomic regions. Our objective was to determine the relevance of clinicopathologic parameters as prognostic factors in a large series of patients with HN-MCC and to compare these to a series of patients with nonhead and neck MCC (NHN-MCC). Study Design: Retrospective analysis of large population database. Methods: Patients with MCC were identified using the Surveillance, Epidemiology, and End Results database and categorized according to tumor location either 1) within or 2) outside of the head and neck region. Clinicopathologic data were compared between groups. Retrospective univariable and multivariable analyses of factors associated with disease-specific survival (DSS) were performed. Results: We identified 2,104 patients with HN-MCC and 2,272 with NHN-MCC. DSS was similar between groups. Independent prognostic factors in HN-MCC are male sex (P < .001), lip primary site (P = .005), tumor extension beyond the dermis (P = .03), histologically confirmed nodal disease (P < .001), absence of histologic lymph node evaluation (P = .01), and distant metastasis (P = .001). Male sex and tumor extension limited to the subcutis are prognostic factors that are unique to HN-MCC. Conclusions: Because independent markers of aggressive disease appear to be unique in HN-MCC, it is important that future studies provide separate consideration for HN-MCC to allow for the most accurate identification of prognostic indicators and assessment of treatment outcomes accordingly.

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