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A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
BACKGROUND: Although sentinel lymph node biopsy (SLNB) status is a strong prognostic indicator for cutaneous melanoma, unnecessary SLNBs have substantial cost and morbidity burden. OBJECTIVE: This study was designed to develop, validate, and present a personalized, clinical, decision-making tool usi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961302/ https://www.ncbi.nlm.nih.gov/pubmed/36840860 http://dx.doi.org/10.1245/s10434-023-13220-0 |
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author | Tripathi, Raghav Larson, Karen Fowler, Graham Han, Dale Vetto, John T. Bordeaux, Jeremy S. Yu, Wesley Y. |
author_facet | Tripathi, Raghav Larson, Karen Fowler, Graham Han, Dale Vetto, John T. Bordeaux, Jeremy S. Yu, Wesley Y. |
author_sort | Tripathi, Raghav |
collection | PubMed |
description | BACKGROUND: Although sentinel lymph node biopsy (SLNB) status is a strong prognostic indicator for cutaneous melanoma, unnecessary SLNBs have substantial cost and morbidity burden. OBJECTIVE: This study was designed to develop, validate, and present a personalized, clinical, decision-making tool using nationally representative data with clinically actionable probability thresholds (Expected Lymphatic Metastasis Outcome [ELMO]). METHODS: Data from the Surveillance, Epidemiology, and End Results (SEER) Registry from 2000 to 2017 and the National Cancer Database (NCDB) from 2004 to 2015 were used to develop and internally validate a logistic ridge regression predictive model for SLNB positivity. External validation was done with 1568 patients at a large tertiary referral center. RESULTS: The development cohort included 134,809 patients, and the internal validation cohort included 38,518 patients. ELMO (AUC 0.85) resulted in a 29.54% SLNB reduction rate and greater sensitivity in predicting SLNB status for T1b, T2a, and T2b tumors than previous models. In external validation, ELMO had an accuracy of 0.7586 and AUC of 0.7218. Limitations of this study are potential miscoding, unaccounted confounders, and effect modification. CONCLUSIONS: ELMO (https://melanoma-sentinel.herokuapp.com/) has been developed and validated (internally and externally) by using the largest publicly available dataset of melanoma patients and was found to have high accuracy compared with other published models and gene expression tests. Individualized risk estimates for SLNB positivity are critical in facilitating thorough decision-making for healthcare providers and patients with melanoma. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1245/s10434-023-13220-0. |
format | Online Article Text |
id | pubmed-9961302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-99613022023-02-28 A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma Tripathi, Raghav Larson, Karen Fowler, Graham Han, Dale Vetto, John T. Bordeaux, Jeremy S. Yu, Wesley Y. Ann Surg Oncol Melanoma BACKGROUND: Although sentinel lymph node biopsy (SLNB) status is a strong prognostic indicator for cutaneous melanoma, unnecessary SLNBs have substantial cost and morbidity burden. OBJECTIVE: This study was designed to develop, validate, and present a personalized, clinical, decision-making tool using nationally representative data with clinically actionable probability thresholds (Expected Lymphatic Metastasis Outcome [ELMO]). METHODS: Data from the Surveillance, Epidemiology, and End Results (SEER) Registry from 2000 to 2017 and the National Cancer Database (NCDB) from 2004 to 2015 were used to develop and internally validate a logistic ridge regression predictive model for SLNB positivity. External validation was done with 1568 patients at a large tertiary referral center. RESULTS: The development cohort included 134,809 patients, and the internal validation cohort included 38,518 patients. ELMO (AUC 0.85) resulted in a 29.54% SLNB reduction rate and greater sensitivity in predicting SLNB status for T1b, T2a, and T2b tumors than previous models. In external validation, ELMO had an accuracy of 0.7586 and AUC of 0.7218. Limitations of this study are potential miscoding, unaccounted confounders, and effect modification. CONCLUSIONS: ELMO (https://melanoma-sentinel.herokuapp.com/) has been developed and validated (internally and externally) by using the largest publicly available dataset of melanoma patients and was found to have high accuracy compared with other published models and gene expression tests. Individualized risk estimates for SLNB positivity are critical in facilitating thorough decision-making for healthcare providers and patients with melanoma. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1245/s10434-023-13220-0. Springer International Publishing 2023-02-25 2023 /pmc/articles/PMC9961302/ /pubmed/36840860 http://dx.doi.org/10.1245/s10434-023-13220-0 Text en © Society of Surgical Oncology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Melanoma Tripathi, Raghav Larson, Karen Fowler, Graham Han, Dale Vetto, John T. Bordeaux, Jeremy S. Yu, Wesley Y. A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title | A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_full | A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_fullStr | A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_full_unstemmed | A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_short | A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma |
title_sort | clinical decision tool to calculate pretest probability of sentinel lymph node metastasis in primary cutaneous melanoma |
topic | Melanoma |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961302/ https://www.ncbi.nlm.nih.gov/pubmed/36840860 http://dx.doi.org/10.1245/s10434-023-13220-0 |
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