Non-Invasive Logistic Regression Model for Predicting Regional Lymph Node Metastases in Cutaneous Melanoma

Relevance: Cutaneous melanoma is characterized by high metastatic potential, and regional lymph node involvement is a key prognostic factor.

Purpose: To develop and evaluate a non-invasive logistic regression model for predicting regional lymph node metastases.

Materials and methods: A retrospective single-center study included 121 patients. Clinical, ultrasound, elastography and scintigraphy parameters were used as predictors; morphological data were excluded.

Results: The model demonstrated a high discriminative ability (ROC AUC ≈ 0.94). At a threshold of p = 0.316, the sensitivity was ≈0.85, the specificity was ≈0.96, the accuracy was ≈0.93, at a lower threshold of p = 0.103, the sensitivity reached about 0.93 with a specificity of about 0.79.

Conclusion: The model may be used for primary risk stratification and guiding invasive staging decisions.

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