{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:31:51Z","timestamp":1760243511657,"version":"3.37.3"},"reference-count":21,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2021,11,4]],"date-time":"2021-11-04T00:00:00Z","timestamp":1635984000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100005190","name":"Melanoma Research Alliance","doi-asserted-by":"publisher","award":["652760"],"award-info":[{"award-number":["652760"]}],"id":[{"id":"10.13039\/100005190","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Surgical Oncology"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background and Objectives<\/jats:title><jats:p>Of clinically node\u2010negative (cN0) cutaneous melanoma patients with sentinel lymph node (SLN) metastasis, between 10% and 30% harbor additional metastases in non\u2010sentinel lymph nodes (NSLNs). Approximately 80% of SLN\u2010positive patients have a single positive SLN.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>To assess whether state\u2010of\u2010the\u2010art clinicopathologic models predicting NSLN metastasis had adequate performance, we studied a single\u2010institution cohort of 143 patients with cN0 SLN\u2010positive primary melanoma who underwent subsequent completion lymph node dissection. We used sensitivity (SE) and positive predictive value (PPV) to characterize the ability of the models to identify patients at high risk for NSLN disease.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Across Stage III patients, all clinicopathologic models tested had comparable performances. The best performing model identified 52% of NSLN\u2010positive patients (SE\u2009=\u200952%, PPV\u2009=\u200937%). However, for the single SLN\u2010positive subgroup (78% of cohort), none of the models identified high\u2010risk patients (SE\u2009&gt;\u200920%, PPV\u2009&gt;\u200920%) irrespective of the chosen probability threshold used to define the binary risk labels. Thus, we designed a new model to identify high\u2010risk patients with a single positive SLN, which achieved a sensitivity of 49% (PPV\u2009=\u200926%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>For the largest SLN\u2010positive subgroup, those with a single positive SLN, current model performance is inadequate. New approaches are needed to better estimate nodal disease burden of these patients.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jso.26736","type":"journal-article","created":{"date-parts":[[2021,11,4]],"date-time":"2021-11-04T18:12:18Z","timestamp":1636049538000},"page":"516-524","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Clinicopathologic models predicting non\u2010sentinel lymph node metastasis in cutaneous melanoma patients: Are they useful for patients with a single positive sentinel node?"],"prefix":"10.1002","volume":"125","author":[{"given":"Barbara","family":"Rentroia\u2010Pacheco","sequence":"first","affiliation":[{"name":"Division of Bioinformatics SkylineDx B.V. Rotterdam The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"F\u00e9licia J.","family":"Tjien\u2010Fooh","sequence":"additional","affiliation":[{"name":"Division of Bioinformatics SkylineDx B.V. Rotterdam The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrica","family":"Quattrocchi","sequence":"additional","affiliation":[{"name":"Department of Dermatology Mayo Clinic Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ajdin","family":"Kobic","sequence":"additional","affiliation":[{"name":"Department of Dermatology Mayo Clinic Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renske","family":"Wever","sequence":"additional","affiliation":[{"name":"Division of Bioinformatics SkylineDx B.V. Rotterdam The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Domenico","family":"Bellomo","sequence":"additional","affiliation":[{"name":"Division of Bioinformatics SkylineDx B.V. 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