Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Tripathi, Raghav, Larson, Karen, Fowler, Graham, Han, Dale, Vetto, John T., Bordeaux, Jeremy S., Yu, Wesley Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
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
_version_ 1784895720948498432
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
work_keys_str_mv AT tripathiraghav aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT larsonkaren aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT fowlergraham aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT handale aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT vettojohnt aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT bordeauxjeremys aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT yuwesleyy aclinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT tripathiraghav clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT larsonkaren clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT fowlergraham clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT handale clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT vettojohnt clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT bordeauxjeremys clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma
AT yuwesleyy clinicaldecisiontooltocalculatepretestprobabilityofsentinellymphnodemetastasisinprimarycutaneousmelanoma