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Updated: Jul 15, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
The Integrated i31-GEP Test Outperforms the MSKCC Nomogram at Predicting SLN Status in Melanoma Patients
Michael Tassavor1, Brian J Martin2, Alex M Glazer3
1Skin Cancer Center, Cincinnati, OH, U.S.A.
Background/Aim:
Sentinel lymph node biopsy (SLNB) for patients with cutaneous melanoma is primarily a prognostic procedure that broadly identifies patients who may have disease progression and may warrant additional intervention. However, 88% of patients undergoing SLNB receive a negative result and of those, some will succumb to their disease. One clinical utility of the integrated 31-GEP test, which combines gene expression data with clinicopathologic factors to provide a personalized, precise risk of SLN positivity, is SLNB guidance. This study compared the i31-GEP for SLNB to a nomogram that predicts SLN positivity using only clinicopathologic factors.
Patients And Methods:
Patients with T1-T2 tumors and known SLN status (N=465) were analyzed by the i31-GEP for SLNB and a nomogram developed at Memorial Sloan Kettering Cancer Center (MSKCC). A 5% risk threshold was used to conform with national guidelines.
Results:
In patients with <5% predicted risk, SLN positivity was 2.7% (3/111) for i31-GEP versus 10.0% (11/110, p=0.026) for MSKCC. In each T-category, the i31-GEP maintained a false-negative rate below the 5% risk threshold in those predicted to have a <5% risk, while the MSKCC nomogram did not.
Conclusion:
Integrating the 31-GEP with traditional factors outperformed a nomogram that uses clinicopathologic factors alone to predict SLN status. Incorporating the i31-GEP into clinical practice could improve identification of patients for SLNB, resulting in better risk-aligned management.

