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

Autor: McEvoy AM; Department of Dermatology, University of Washington, Seattle, Washington; Division of Dermatology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri., Hippe DS; Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington., Lachance K; Department of Dermatology, University of Washington, Seattle, Washington., Park S; Department of Dermatology, University of Washington, Seattle, Washington., Cahill K; Department of Dermatology, University of Washington, Seattle, Washington., Redman M; Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington., Gooley T; Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington., Kattan MW; Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio., Nghiem P; Department of Dermatology, University of Washington, Seattle, Washington; Fred Hutchinson Cancer Center, Seattle, Washington. Electronic address: pnghiem@uw.edu.
Jazyk: angličtina
Zdroj: Journal of the American Academy of Dermatology [J Am Acad Dermatol] 2024 Mar; Vol. 90 (3), pp. 569-576. Date of Electronic Publication: 2023 Nov 19.
DOI: 10.1016/j.jaad.2023.11.020
Abstrakt: Background: 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.
Purpose: Create a multivariable model and web-based calculator to predict MCC recurrence risk more accurately than stage alone.
Methods: 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.
Results: In this multivariable model, the most impactful recurrence risk factors were: American Joint Committee on Cancer stage (P < .001), immunosuppression (hazard ratio 2.05; P < .001), male sex (1.59; P = .003) and unknown primary (0.65; P = .064). Compared to stage alone, the model improved prognostic accuracy (concordance index for 2-year risk, 0.66 vs 0.70; P < .001), and modified estimated recurrence risk by up to 4-fold (18% for low-risk stage IIIA vs 78% for high-risk IIIA over 5 years).
Limitations: Lack of an external data set for model validation.
Conclusion/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 merkelcell.org/recur) integrates time since diagnosis and provides new data for optimizing surveillance for MCC patients.
Competing Interests: Conflicts of interest Paul Nghiem reports personal fees from Rain Therapeutics, EMD Serono, Pfizer, and Merck; grants from EMD Serono and Bristol-Myers Squibb to his institution outside the submitted work; and a patent for Merkel cell polyomavirus T antigen–specific T-cell receptors and uses thereof pending (University of Washington), as well as a patent for novel epitopes as T-cell targets in Merkel cell carcinoma pending (University of Denmark and University of Washington). No other disclosures were reported.
(Copyright © 2023 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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