Prediction of Sentinel Node Positivity Risk in Melanoma Patients: When Appropriate Statistical Methodology was Employed an i31-GEP Test Did Not Outperform a Tool that Uses Clinicopathologic Features Only

Main Article Content

Serigne Lo
Melanoma Institute Australia

Alexander Varey
Richard Scolyer
John Thompson

Keywords

melanoma, nomogram, staging

Abstract

Not applicable

References

1 Zakria D, Brownstone N, Rigel D. The Integrated 31-Gene Expression Profile (i31-GEP) Test for Cutaneous Melanoma Outperforms a Clinicopathologic-only Nomogram at Identifying Patients who can Forego Sentinel Lymph Node Biopsy. SKIN: The Journal of Cutaneous Medicine 2022; 6 (6): 463-473. https://jofskin.org/index.php/skin/article/view/1795/1476

2 Lo SN, Ma J, Scolyer RA et al. Improved Risk Prediction Calculator for Sentinel Node Positivity in Patients With Melanoma: The Melanoma Institute Australia Nomogram. J Clin Oncol 2020; 38 (24): 2719-2727.

3 Whitman ED, Koshenkov VP, Gastman BR et al. Integrating 31-Gene Expression Profiling With Clinicopathologic Features to Optimize Cutaneous Melanoma Sentinel Lymph Node Metastasis Prediction. JCO Precis Oncol 2021; 5.

4 Hosmer DW, Lemeshow S. Confidence interval estimates of an index of quality performance based on logistic regression models. Stat Med 1995; 14 (19): 2161-2172.

5 Cleveland WS, Devlin SJ. Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting. Journal of the American Statistical Association 1988; 83 (403): 596-610.

6 Härdle W, Müller M, Sperlich S et al. 3.5 Confidence Intervals and Confidence Bands. Nonparametric and Semiparametric Models, Berlin: Springer 2004.

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Published
Nov 13, 2023
DOI https://doi.org/10.25251/skin.7.6.7

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How to Cite
[1]
Lo, S., Varey, A., Scolyer, R. and Thompson, J. 2023. Prediction of Sentinel Node Positivity Risk in Melanoma Patients: When Appropriate Statistical Methodology was Employed an i31-GEP Test Did Not Outperform a Tool that Uses Clinicopathologic Features Only. SKIN The Journal of Cutaneous Medicine. 7, 6 (Nov. 2023), 1126–1130. DOI:https://doi.org/10.25251/skin.7.6.7.
Issue
Vol. 7 No. 6 (2023): November 2023 Issue
Section
Editorials
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