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Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
PURPOSE: More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here, we describe a model that combines clinicopathologic and molecular variables to identify patients with thin- and intermediate-thickness melanomas who may forgo the SLN biopsy procedure beca...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Clinical Oncology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220172/ https://www.ncbi.nlm.nih.gov/pubmed/32405608 http://dx.doi.org/10.1200/PO.19.00206 |
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author | Bellomo, Domenico Arias-Mejias, Suzette M. Ramana, Chandru Heim, Joel B. Quattrocchi, Enrica Sominidi-Damodaran, Sindhuja Bridges, Alina G. Lehman, Julia S. Hieken, Tina J. Jakub, James W. Pittelkow, Mark R. DiCaudo, David J. Pockaj, Barbara A. Sluzevich, Jason C. Cappel, Mark A. Bagaria, Sanjay P. Perniciaro, Charles Tjien-Fooh, Félicia J. van Vliet, Martin H. Dwarkasing, Jvalini Meves, Alexander |
author_facet | Bellomo, Domenico Arias-Mejias, Suzette M. Ramana, Chandru Heim, Joel B. Quattrocchi, Enrica Sominidi-Damodaran, Sindhuja Bridges, Alina G. Lehman, Julia S. Hieken, Tina J. Jakub, James W. Pittelkow, Mark R. DiCaudo, David J. Pockaj, Barbara A. Sluzevich, Jason C. Cappel, Mark A. Bagaria, Sanjay P. Perniciaro, Charles Tjien-Fooh, Félicia J. van Vliet, Martin H. Dwarkasing, Jvalini Meves, Alexander |
author_sort | Bellomo, Domenico |
collection | PubMed |
description | PURPOSE: More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here, we describe a model that combines clinicopathologic and molecular variables to identify patients with thin- and intermediate-thickness melanomas who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. PATIENTS AND METHODS: Genes with functional roles in melanoma metastasis were discovered by analysis of next-generation sequencing data and case-control studies. We then used polymerase chain reaction to quantify gene expression in diagnostic biopsy tissue across a prospectively designed archival cohort of 754 consecutive thin- and intermediate-thickness primary cutaneous melanomas. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. A penalized maximum likelihood estimation algorithm was used to train logistic regression models in a repeated cross-validation scheme to predict the presence of SLN metastasis from molecular, clinical, and histologic variables. RESULTS: Expression of genes with roles in epithelial-to-mesenchymal transition (glia-derived nexin, growth differentiation factor 15, integrin-β3, interleukin 8, lysyl oxidase homolog 4, transforming growth factor-β receptor type 1, and tissue-type plasminogen activator) and melanosome function (melanoma antigen recognized by T cells 1) were associated with SLN metastasis. The predictive ability of a model that only considered clinicopathologic or gene expression variables was outperformed by a model that included molecular variables in combination with the clinicopathologic predictors Breslow thickness and patient age (area under the receiver operating characteristic curve, 0.82; 95% CI, 0.78 to 0.86; SLN biopsy reduction rate, 42%; negative predictive value, 96%). CONCLUSION: A combined model that included clinicopathologic and gene expression variables improved the identification of patients with melanoma who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. |
format | Online Article Text |
id | pubmed-7220172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Society of Clinical Oncology |
record_format | MEDLINE/PubMed |
spelling | pubmed-72201722020-05-13 Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma Bellomo, Domenico Arias-Mejias, Suzette M. Ramana, Chandru Heim, Joel B. Quattrocchi, Enrica Sominidi-Damodaran, Sindhuja Bridges, Alina G. Lehman, Julia S. Hieken, Tina J. Jakub, James W. Pittelkow, Mark R. DiCaudo, David J. Pockaj, Barbara A. Sluzevich, Jason C. Cappel, Mark A. Bagaria, Sanjay P. Perniciaro, Charles Tjien-Fooh, Félicia J. van Vliet, Martin H. Dwarkasing, Jvalini Meves, Alexander JCO Precis Oncol Original Reports PURPOSE: More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here, we describe a model that combines clinicopathologic and molecular variables to identify patients with thin- and intermediate-thickness melanomas who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. PATIENTS AND METHODS: Genes with functional roles in melanoma metastasis were discovered by analysis of next-generation sequencing data and case-control studies. We then used polymerase chain reaction to quantify gene expression in diagnostic biopsy tissue across a prospectively designed archival cohort of 754 consecutive thin- and intermediate-thickness primary cutaneous melanomas. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. A penalized maximum likelihood estimation algorithm was used to train logistic regression models in a repeated cross-validation scheme to predict the presence of SLN metastasis from molecular, clinical, and histologic variables. RESULTS: Expression of genes with roles in epithelial-to-mesenchymal transition (glia-derived nexin, growth differentiation factor 15, integrin-β3, interleukin 8, lysyl oxidase homolog 4, transforming growth factor-β receptor type 1, and tissue-type plasminogen activator) and melanosome function (melanoma antigen recognized by T cells 1) were associated with SLN metastasis. The predictive ability of a model that only considered clinicopathologic or gene expression variables was outperformed by a model that included molecular variables in combination with the clinicopathologic predictors Breslow thickness and patient age (area under the receiver operating characteristic curve, 0.82; 95% CI, 0.78 to 0.86; SLN biopsy reduction rate, 42%; negative predictive value, 96%). CONCLUSION: A combined model that included clinicopathologic and gene expression variables improved the identification of patients with melanoma who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. American Society of Clinical Oncology 2020-04-14 /pmc/articles/PMC7220172/ /pubmed/32405608 http://dx.doi.org/10.1200/PO.19.00206 Text en © 2020 by American Society of Clinical Oncology https://creativecommons.org/licenses/by/4.0/ Licensed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Original Reports Bellomo, Domenico Arias-Mejias, Suzette M. Ramana, Chandru Heim, Joel B. Quattrocchi, Enrica Sominidi-Damodaran, Sindhuja Bridges, Alina G. Lehman, Julia S. Hieken, Tina J. Jakub, James W. Pittelkow, Mark R. DiCaudo, David J. Pockaj, Barbara A. Sluzevich, Jason C. Cappel, Mark A. Bagaria, Sanjay P. Perniciaro, Charles Tjien-Fooh, Félicia J. van Vliet, Martin H. Dwarkasing, Jvalini Meves, Alexander Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title | Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_full | Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_fullStr | Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_full_unstemmed | Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_short | Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_sort | model combining tumor molecular and clinicopathologic risk factors predicts sentinel lymph node metastasis in primary cutaneous melanoma |
topic | Original Reports |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220172/ https://www.ncbi.nlm.nih.gov/pubmed/32405608 http://dx.doi.org/10.1200/PO.19.00206 |
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