Defining the high-risk category of patients with cutaneous melanoma: a practical tool based on prognostic modeling
IntroductionAlthough most cutaneous melanoma (CM) in its early stages is treatable, the risk of recurrence remains high and there is a particular ambiguity on patients prognosis. This drives to identification of prognostic biomarkers for predicting CM recurrence to guide appropriate treatment in pat...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Molecular Biosciences |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2025.1543148/full |
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| Summary: | IntroductionAlthough most cutaneous melanoma (CM) in its early stages is treatable, the risk of recurrence remains high and there is a particular ambiguity on patients prognosis. This drives to identification of prognostic biomarkers for predicting CM recurrence to guide appropriate treatment in patients with localized melanoma.AimThis study aimed to develop a prognostic model for assessing the risk of recurrence in patients with CM, enabling prompt prognosis-driven further clinical decision-making for high-risk patients.Materials and methodsThis case-control study included 172 patients with CM recurrence (high-risk group) and 30 patients with stable remission (low-risk group) 3 years after primary diagnosis. The impact of sex, age at diagnosis, anatomical site, histological characteristics (the histological type, pathological stage, ulceration; the depth of invasion, mitotic rate, lymphovascular invasion, neurotropism, association with a nevus, tumor-infiltrating lymphocyte density, tumor regression and BRAF codon 600 mutation status) on CM recurrence was evaluated.ResultsFive independent variables, including nodal status, a high mitotic rate, Breslow thickness, lymphovascular invasion, perineural invasion and regression features were identified as the most significant. A 5-factor logistic regression model was developed to assess the risk of melanoma recurrence. The sensitivity and specificity of the model were 86.1% and 72.7%, respectively.ConclusionThe developed model, which relies on routine histological features, allows the identification of individuals at high risk of CM recurrence to tailor their further management. |
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| ISSN: | 2296-889X |