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- W3109296473 abstract "More than 80% of patients undergoing sentinel lymph node (SLN) biopsy have no nodal metastasis, and are unnecessarily exposed to procedure-induced morbidity such as lymphedema. Our objective was to develop a model combining clinicopathologic and gene expression (CP-GEP) to discriminate high-risk patients from patients who can safely forego SLN biopsy, thus reducing procedure-associated morbidity, and prioritizing care for high risk patients. A panel of 108 candidate biomarkers was identified, and the expression of these genes was quantified in FFPE diagnostic biopsy tissue across a cohort of 754 patients; 128/754 (17%) SLN positive patients. All patients underwent SLN biopsy at Mayo Clinic within 90 days of diagnosis between 2004 and 2018. We trained logistic regression models, using a penalized maximum likelihood estimation algorithm, in a repeated cross-validation scheme. The CP-GEP model, combining age and Breslow depth with genes involved in extracellular matrix remodeling (glia-derived nexin, growth differentiation factor 15, integrin β3, interleukin 8, lysyl oxidase homolog 4, TGFβ receptor type 1 and tissue-type plasminogen activator), and melanosome function (antigen recognized by T-cells), outperformed models based on only clinicopathologic variables, or only on gene expression, in discriminating SLN positive and negative patients (AUC, 0.82, 95% CI 0.78-0.86). The CP-GEP model achieved a SLN biopsy reduction rate of 42% at a negative predictive value of 96%. The 5-year relapse-free survival for CP-GEP negative patients was 88% compared with 50% for CP-GEP positive and SLN positive patients, confirming the value of the CP-GEP model as a tool to inform SLN biopsy decisions." @default.
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- W3109296473 date "2020-12-01" @default.
- W3109296473 modified "2023-10-16" @default.
- W3109296473 title "18408 A combined clinicopathologic and gene expression model (CP-GEP) identifies primary cutaneous melanoma patients who can safely forgo sentinel lymph node biopsy" @default.
- W3109296473 doi "https://doi.org/10.1016/j.jaad.2020.06.482" @default.
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