Different prognosis in cutaneous early-onset and late-onset Merkel cell carcinoma: a population-based retrospective study.

ABSTRACT

BACKGROUND: Merkel cell carcinoma (MCC) is a rare and highly aggressive form of skin cancer. However, there is limited research on the clinicopathological features of early-onset MCC (EOMCC) and the differences between EOMCC and late-onset MCC (LOMCC). Our objective was to evaluate the clinicopathological features and cancer-specific survival (CSS) of EOMCC. METHODS: Our cohort study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database from January 1, 2018, to December 31, 2020. Data from 1941 patients who were diagnosed with primary cutaneous MCC were included. We then divided the patients with MCC into two groups those with EOMCC (526 patients) and those with LOMCC (1415 patients). CSS is used as the primary outcome. RESULTS: The EOMCC group exhibited trends toward advanced tumor progression, an expanded surgical scope, increased lymph node retrieval, intensified radiotherapy, greater utilization of systemic therapy, and a better prognosis. Multivariate analysis revealed that LOMCC (HR 3.305 [2.002-5.456], P < 0.001), advanced T stage (HR 1.430 [1.139-1.797], P = 0.002), advanced N stage (HR 1.522 [1.221-1.897], P < 0.001), M1 stage (HR 2.587 [1.480-4.521], P < 0.001), and radiation (HR 0.586 [0.410-0.837], P = 0.003) were significantly associated with CSS. Among these factors, EOMCC/LOMCC was most strongly associated with CSS, indicating that LOMCC is an independent risk factor for CSS. Interestingly, we found that regional EOMCC and localized or in situ LOMCC had almost completely overlapping survival curves (Plog-rank = 0.620). Additionally, we observed that the TNM staging + age model was a more accurate predictor of CSS among MCC patients than using TNM staging alone. CONCLUSIONS: We found that EOMCC has distinct clinicopathological features compared to LOMCC. EOMCC is associated with better CSS. The combination of TNM staging and age was more accurate for predicting patient outcomes than TNM staging alone.