Héloïse Bourien, Véronique Quillien, Florence Godey, Christophe Perrin, Fanny Le Du, Sophie Guillermet, Jérôme Blanchot, Vincent Lavoué, Boris Campillo-Gimenez, Angélique Brunot, Laurence Crouzet, Thibault De la Motte Rouge, Véronique Diéras, Claudia Lefeuvre-Plesse
{"title":"Impact of EPclin on adjuvant therapeutic decision making and comparison of EPclin to the PREDICT tool.","authors":"Héloïse Bourien, Véronique Quillien, Florence Godey, Christophe Perrin, Fanny Le Du, Sophie Guillermet, Jérôme Blanchot, Vincent Lavoué, Boris Campillo-Gimenez, Angélique Brunot, Laurence Crouzet, Thibault De la Motte Rouge, Véronique Diéras, Claudia Lefeuvre-Plesse","doi":"10.1177/17246008211012424","DOIUrl":null,"url":null,"abstract":"Purpose: Genomic signatures, such as EndoPredict®, may help clinicians to decide which adjuvant treatment is the most appropriate. Methods: We propose the EndoPredict® assay for unclear cases of adjuvant treatment in patients treated in our comprehensive cancer center. We prospectively and retrospectively report the decision of adjuvant treatment before and after the EndoPredict® assay, respectively, compared to the PREDICT’s tool scores. Results: From November 2016 to March 2019, 159 breast cancer tumors were analyzed and presented before and after the EndoPredict® assay. Before the EndoPredict® results, clinicians recommended chemotherapy for 57 patients (57/159, 36%). A total of 108 patients (108/159, 68%) were classified as EPclin high-risk score. There was only a slight agreement between clinicians’ decisions and EPclin risk score. The EPclin score led to 37% changes in treatment (59/159); chemotherapy was favored in 80% of cases (47/59). The PREDICT tool recommended chemotherapy for 16 high-risk patients (16/159, 10%). Conclusion: Although genomic tests were developed in order to de-escalate adjuvant treatment, in our comprehensive cancer center the use of the EndoPredict® assay led to an increase in prescribed chemotherapy.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/17246008211012424","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/17246008211012424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/5/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 1
Abstract
Purpose: Genomic signatures, such as EndoPredict®, may help clinicians to decide which adjuvant treatment is the most appropriate. Methods: We propose the EndoPredict® assay for unclear cases of adjuvant treatment in patients treated in our comprehensive cancer center. We prospectively and retrospectively report the decision of adjuvant treatment before and after the EndoPredict® assay, respectively, compared to the PREDICT’s tool scores. Results: From November 2016 to March 2019, 159 breast cancer tumors were analyzed and presented before and after the EndoPredict® assay. Before the EndoPredict® results, clinicians recommended chemotherapy for 57 patients (57/159, 36%). A total of 108 patients (108/159, 68%) were classified as EPclin high-risk score. There was only a slight agreement between clinicians’ decisions and EPclin risk score. The EPclin score led to 37% changes in treatment (59/159); chemotherapy was favored in 80% of cases (47/59). The PREDICT tool recommended chemotherapy for 16 high-risk patients (16/159, 10%). Conclusion: Although genomic tests were developed in order to de-escalate adjuvant treatment, in our comprehensive cancer center the use of the EndoPredict® assay led to an increase in prescribed chemotherapy.