A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma

Raghav Tripathi, Karen Larson, Graham Fowler, Dale Han, John T. Vetto, Jeremy S. Bordeaux, Wesley Y. Yu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)4321-4328
Number of pages8
JournalAnnals of surgical oncology
Volume30
Issue number7
DOIs
StatePublished - Jul 2023

ASJC Scopus subject areas

  • Surgery
  • Oncology

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