Merkel cell carcinoma recurrence risk estimation is improved by integrating factors beyond cancer stage: a multivariable model and web-based calculator

November 18, 2023


Journal of the American Academy of Dermatology

Publication Date

November 18, 2023


McEvoy, A. M., Hippe, D. S., Lachance, K., Park, S., Cahill, K., Redman, M., Gooley, T., Kattan, M. W., & Nghiem, P. Summary

Researchers have developed an online tool, available at, to estimate the chance of Merkel cell carcinoma (MCC) coming back. This tool considers patient-specific factors such as gender, age, immunosuppression, tumor location, and time since diagnosis. Using data from 618 patients, the researchers developed a model showing that the calculator could predict MCC recurrence four times more effectively than just considering cancer stage. Accessible to both patients and doctors, this tool is valuable for assessing recurrence risk, determining suitable treatment, and planning follow-up.



Merkel cell carcinoma (MCC) recurs in 40% of patients. In addition to stage, factors known to affect recurrence risk include: sex, immunosuppression, unknown primary status, age, site of primary tumor, and time since diagnosis.


Create a multivariable model and web-based calculator to predict MCC recurrence risk more accurately than stage alone.


Data from 618 patients in a prospective cohort were used in a competing risk regression model to estimate recurrence risk using stage and other factors.


In this multivariable model, the most impactful recurrence risk factors were: AJCC stage (p<0.001), immunosuppression (hazard ratio 2.05; p<0.001), male sex (1.59; p=0.003) and unknown primary (0.65; p=0.064). Compared to stage alone, the model improved prognostic accuracy (concordance index for two-year risk, 0.66 vs. 0.70; p<0.001), and modified estimated recurrence risk by up to 4-fold (18% for low-risk stage IIIA vs. 78% for high-risk IIIA over five years).


Lack of an external data set for model validation.


/ Relevance: As demonstrated by this multivariable model, accurate recurrence risk prediction requires integration of factors beyond stage. An online calculator based on this model (at integrates time since diagnosis and provides new data for optimizing surveillance for MCC patients.

View the clinical publication