A nomogram to predict node positivity in patients with thin melanomas helps inform shared patient decision making

Area of Science:

• Oncology
• Dermatology
• Surgical Oncology

Background:

• Thin melanoma (0.5-1.0 mm) management involves assessing sentinel lymph node (SLN) status.
• Sentinel lymph node biopsy (SLNB) is a standard procedure, but its utility in low-risk cases is debated.
• Accurate risk stratification is crucial to optimize SLNB in thin melanoma.

Purpose of the Study:

• To develop and validate a nomogram for predicting the probability of positive SLN (+SLN) in thin melanoma patients.
• To assess the potential impact of this nomogram on SLNB rates.
• To improve patient selection for SLNB.

Main Methods:

• Utilized the National Cancer Database (2012-2015) for patients with thin melanoma (0.5-1.0 mm).
• Developed a multivariable logistic regression model to identify factors associated with +SLN.
• Constructed and evaluated a nomogram for predicting +SLN probability.

Main Results:

• The study included 21,971 patients; 46.0% underwent SLNB with a 4.0% +SLN rate.
• Significant predictors for +SLN included age, Breslow thickness, lymphovascular invasion, ulceration, and Clark level.
• The nomogram demonstrated moderate predictive performance (AUC 0.67).
• Applying a ≥5% +SLN probability cut-off could reduce SLNB indications by 81.3% compared to current criteria.

Conclusions:

• The developed nomogram provides a more accurate method for selecting thin melanoma patients who would benefit from SLNB.
• This tool has the potential to significantly decrease unnecessary SLNB procedures.
• Risk prediction via the nomogram aids in personalized treatment decisions for thin melanoma.