J. Michael Guenther, Andrew Ward, Brian J. Martin, Mark Cripe, Timothy Beard, Oliver Wisco, Rohit Sharma, Stanley P. Leong, Richard Essner, Joseph I. Clark, John Hamner, Brenda Sickle-Santanello, Maki Yamamoto
{"title":"A Prospective, Multicenter Analysis of Recurrence-Free Survival After Sentinel Lymph Node Biopsy Decisions Influenced by the 31-GEP","authors":"J. Michael Guenther, Andrew Ward, Brian J. Martin, Mark Cripe, Timothy Beard, Oliver Wisco, Rohit Sharma, Stanley P. Leong, Richard Essner, Joseph I. Clark, John Hamner, Brenda Sickle-Santanello, Maki Yamamoto","doi":"10.1002/cam4.70839","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Although most patients with cutaneous melanoma (CM) will have a negative sentinel lymph node biopsy (SLNB), up to 20%–30% of these patients will recur. The 31-gene expression profile (31-GEP) test has been prospectively validated to identify patients at low (Class 1A), intermediate (Class 1B/2A), and high (Class 2B) risk of SLN positivity and recurrence.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>DECIDE is a prospective, multicenter study to assess the effect of 31-GEP testing on SLNB performance rates in patients with T1–T2 tumors considering SLNB and to study long-term outcomes. Here, we assessed outcomes in patients with a Class 1A 31-GEP result (<i>n</i> = 130).</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Of Class 1A patients, 63 had an SLNB, with a 3.2% SLN positivity rate (2/63). No Class 1A patients, regardless of SLN status, experienced a recurrence (2-year median follow-up).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>These results are consistent with previous studies that showed the 31-GEP can identify patients at low risk of SLN positivity and recurrence.</p>\n </section>\n </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"14 7","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.70839","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cam4.70839","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Although most patients with cutaneous melanoma (CM) will have a negative sentinel lymph node biopsy (SLNB), up to 20%–30% of these patients will recur. The 31-gene expression profile (31-GEP) test has been prospectively validated to identify patients at low (Class 1A), intermediate (Class 1B/2A), and high (Class 2B) risk of SLN positivity and recurrence.
Methods
DECIDE is a prospective, multicenter study to assess the effect of 31-GEP testing on SLNB performance rates in patients with T1–T2 tumors considering SLNB and to study long-term outcomes. Here, we assessed outcomes in patients with a Class 1A 31-GEP result (n = 130).
Results
Of Class 1A patients, 63 had an SLNB, with a 3.2% SLN positivity rate (2/63). No Class 1A patients, regardless of SLN status, experienced a recurrence (2-year median follow-up).
Conclusions
These results are consistent with previous studies that showed the 31-GEP can identify patients at low risk of SLN positivity and recurrence.
期刊介绍:
Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas:
Clinical Cancer Research
Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations
Cancer Biology:
Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery.
Cancer Prevention:
Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach.
Bioinformatics:
Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers.
Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.