Clinical Utility of Melanoma Sentinel Lymph Node Biopsy Nomograms.

BACKGROUND: For patients with melanoma, the decision to perform sentinel lymph node biopsy (SLNB) is based on the estimated risk of lymph node metastasis. We assessed three melanoma SLNB risk-prediction models' statistical performance and their ability to improve clinical decision making (clinical utility) on a cohort of melanoma SLNB cases.

STUDY DESIGN: Melanoma patients undergoing SLNB at a single center from 2003 to 2021 were identified. The predicted probabilities of sentinel lymph node (SLN) positivity using the Melanoma Institute of Australia (MIA), Memorial Sloan Kettering Cancer Center (MSK), and Friedman nomograms were calculated. Receiver operating characteristic (ROC) and calibration curves were generated. Clinical utility was assessed via decision curve analysis, calculating the net SLNBs that could have been avoided had a given model guided selection at different risk thresholds.

RESULTS: Of 2,464 melanoma cases that underwent SLNB, 567 (23.0%) had a positive SLN. The areas under the ROC curves for the MIA, MSK, and Friedman models were 0.726 (95% confidence interval [CI], 0.702-0.750), 0.720 (95% CI, 0.697-0.744), and 0.721 (95% CI, 0.699-0.744), respectively. For all models, calibration was best at predicted positivity rates below 30%. The MSK model underpredicted risk. At a 10% risk threshold, only the Friedman model would correctly avoid a net of 6.2 SLNBs per 100 patients. The other models did not reduce net avoidable SLNBs at risk thresholds ≤10%.

CONCLUSION: The tested nomograms had comparable performance in our cohort. The only model that achieved clinical utility at risk thresholds ≤10% was the Friedman model.