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An enhanced model that integrates non-AJCC clinical features provides clinicians with a more accurate tool for identifying high-risk patients with MCC.
Merkel cell carcinoma (MCC), a rare and aggressive skin cancer with increasing global incidence, predominantly affects older individuals and often presents at advanced stages, according to the researchers of a recent study published online in the Journal of the American Academy of Dermatology. Current prognostication relies on the American Joint Cancer Committee (AJCC) eighth edition staging system, which stratifies patients based on overall survival (OS) but does not fully account for disease-specific death (DSD) or other critical factors. For their study, researchers sought to compare DSD and OS as survival endpoints and develop an enhanced prognostic model incorporating additional non-AJCC features to improve survival predictions.
The study analyzed 10,958 patients with MCC from the US and 102 patients from the UK, using multivariable Fine and Gray (FG) competing risk models. Results showed that DSD was a more reliable endpoint than OS for MCC staging, as it better-stratified survival probabilities across stages. Additional factors significantly associated with increased DSD included truncal tumor location, advanced age (>84 years), male sex, and unmarried status. Incorporating these features into the FG model significantly improved prognostic accuracy compared to the AJCC system alone, with concordance indices of 0.75 (U.S.) and 0.77 (U.K.) for DSD predictions (Figure).
Tumor-specific features such as site, size, and level of invasion were also important predictors of survival. The authors noted that MCC tumors on the trunk were associated with the worst outcomes, likely due to diagnostic and treatment challenges. The study highlighted the prognostic significance of tumor invasion into the subcutis, a feature not currently included in AJCC staging but proposed as a high-risk factor for future revisions.
By integrating non-AJCC clinical and tumor features, the enhanced model provides clinicians with a more accurate tool for identifying high-risk patients with MCC. According to the study team, this improvement could guide personalized treatment decisions and surveillance strategies. The findings also underscored the need for future updates to MCC staging systems and prospective studies to refine these models for broader clinical application.
