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Article: Impact of the EndoPredict genomic assay on treatment decisions for oestrogen receptor-positive early breast cancer patients: benefits of physician selective testing

TitleImpact of the EndoPredict genomic assay on treatment decisions for oestrogen receptor-positive early breast cancer patients: benefits of physician selective testing
Authors
KeywordsEarly breast cancer
Endocrine therapy
EndoPredict
Prognosis
Prognostic signatures
Treatment decision
Issue Date2022
Citation
Breast Cancer Research and Treatment, 2022, v. 191, n. 3, p. 501-511 How to Cite?
AbstractPurpose: Genomic tests improve accuracy of risk prediction for early breast cancers but these are expensive. This study evaluated the clinical utility of EndoPredict®, in terms of impact on adjuvant therapy recommendations and identification of parameters to guide selective application. Methods: Patients with ER-positive, HER2-negative, and early-stage invasive breast cancer were tested with EndoPredict®. Two cohorts were recruited: one consecutively and another at clinical team discretion. Systemic treatment recommendations were recorded before and after EndoPredict® results were revealed to the multidisciplinary team. Results: 233 patients were recruited across five sites: 123 consecutive and 110 at clinical team discretion. In the consecutive cohort 50.6% (62/123) cases were classified high risk of recurrence by EndoPredict®, compared with 62.7% (69/110) in the selective cohort. A change in treatment recommendation was significantly more likely (p < 0.0001) in the selective cohort (43/110, 39.1%) compared to the consecutive group (11/123, 8.9%). The strongest driver of selective recruitment was intermediate grade histology, whilst logistic regression modelling demonstrated that nodal status (p < 0.001), proliferative rate (p = 0.001), and progesterone receptor positivity (p < 0.001) were the strongest discriminators of risk. Conclusion: Whilst molecular risk can be predicted by traditional variables in a high proportion of cases, EndoPredict® had a greater impact on treatment decisions in those cases selected for testing at team discretion. This is indicative of the robust ability of the clinical team to identify cases most likely to benefit from testing, underscoring the value of genomic tests in the oncologists’ tool kit.
Persistent Identifierhttp://hdl.handle.net/10722/326510
ISSN
2023 Impact Factor: 3.0
2023 SCImago Journal Rankings: 1.267
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDinh, Phuong-
dc.contributor.authorGraham, J. Dinny-
dc.contributor.authorElder, Elisabeth N.-
dc.contributor.authorKabir, Masrura-
dc.contributor.authorDoan, Tram B.-
dc.contributor.authorFrench, James-
dc.contributor.authorMeybodi, Farid-
dc.contributor.authorHui, Rina-
dc.contributor.authorWilcken, Nicholas R.-
dc.contributor.authorHarnett, Paul R.-
dc.contributor.authorHsu, Jeremy-
dc.contributor.authorStuart, Kirsty E.-
dc.contributor.authorWang, Tim-
dc.contributor.authorAhern, Verity-
dc.contributor.authorBrennan, Meagan-
dc.contributor.authorFox, Stephen B.-
dc.contributor.authorDear, Rachel F.-
dc.contributor.authorLim, Elgene-
dc.contributor.authorWhite, Michelle-
dc.contributor.authorMann, G. Bruce-
dc.contributor.authorPathmanathan, Nirmala-
dc.date.accessioned2023-03-10T02:19:47Z-
dc.date.available2023-03-10T02:19:47Z-
dc.date.issued2022-
dc.identifier.citationBreast Cancer Research and Treatment, 2022, v. 191, n. 3, p. 501-511-
dc.identifier.issn0167-6806-
dc.identifier.urihttp://hdl.handle.net/10722/326510-
dc.description.abstractPurpose: Genomic tests improve accuracy of risk prediction for early breast cancers but these are expensive. This study evaluated the clinical utility of EndoPredict®, in terms of impact on adjuvant therapy recommendations and identification of parameters to guide selective application. Methods: Patients with ER-positive, HER2-negative, and early-stage invasive breast cancer were tested with EndoPredict®. Two cohorts were recruited: one consecutively and another at clinical team discretion. Systemic treatment recommendations were recorded before and after EndoPredict® results were revealed to the multidisciplinary team. Results: 233 patients were recruited across five sites: 123 consecutive and 110 at clinical team discretion. In the consecutive cohort 50.6% (62/123) cases were classified high risk of recurrence by EndoPredict®, compared with 62.7% (69/110) in the selective cohort. A change in treatment recommendation was significantly more likely (p < 0.0001) in the selective cohort (43/110, 39.1%) compared to the consecutive group (11/123, 8.9%). The strongest driver of selective recruitment was intermediate grade histology, whilst logistic regression modelling demonstrated that nodal status (p < 0.001), proliferative rate (p = 0.001), and progesterone receptor positivity (p < 0.001) were the strongest discriminators of risk. Conclusion: Whilst molecular risk can be predicted by traditional variables in a high proportion of cases, EndoPredict® had a greater impact on treatment decisions in those cases selected for testing at team discretion. This is indicative of the robust ability of the clinical team to identify cases most likely to benefit from testing, underscoring the value of genomic tests in the oncologists’ tool kit.-
dc.languageeng-
dc.relation.ispartofBreast Cancer Research and Treatment-
dc.subjectEarly breast cancer-
dc.subjectEndocrine therapy-
dc.subjectEndoPredict-
dc.subjectPrognosis-
dc.subjectPrognostic signatures-
dc.subjectTreatment decision-
dc.titleImpact of the EndoPredict genomic assay on treatment decisions for oestrogen receptor-positive early breast cancer patients: benefits of physician selective testing-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10549-021-06456-5-
dc.identifier.pmid34853987-
dc.identifier.scopuseid_2-s2.0-85120374553-
dc.identifier.volume191-
dc.identifier.issue3-
dc.identifier.spage501-
dc.identifier.epage511-
dc.identifier.eissn1573-7217-
dc.identifier.isiWOS:000724637200001-

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