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dc.contributorVall d'Hebron Barcelona Hospital Campus
dc.contributor.authorBernet, L
dc.contributor.authorHardisson, David
dc.contributor.authorRodrigo, M
dc.contributor.authorCórdoba, A
dc.contributor.authorSancho, M.
dc.contributor.authorPeg, Vicente
dc.date.accessioned2023-08-30T11:37:54Z
dc.date.available2023-08-30T11:37:54Z
dc.date.issued2023-07-31
dc.identifier.citationBernet L, Hardisson D, Rodrigo M, Córdoba A, Sancho M, Peg V, et al. OSNA Total Tumor Load for the Prediction of Axillary Involvement in Breast Cancer Patients: Should We use Different Thresholds According to the Intrinsic Molecular Subtype? MOTTO Study. Clin Pathol. 2023 Jul 31;16:1-8.
dc.identifier.issn2632-010X
dc.identifier.urihttps://hdl.handle.net/11351/10185
dc.descriptionBreast cancer; Molecular subtype; Total tumor load
dc.description.abstractAims: To assess the impact of the molecular subtype (MS) on the total number of CK19 mRNA copies in all positive SLN (TTL) threshold, to predict non-SLN affectation, and to compare 5 years progression-free survival (PFS) according to the risk of recurrence (ROR) group by PAM50. Methods: Cohort with infiltrating breast cancer with intra-operative metastatic SLN detected by one-step nucleic acid amplification (OSNA) assay who underwent subsequent ALND. Logistic regression was used to assess a possible interaction between TTL and MS(Triple Negative, Her-2-Enriched, Luminal A, or Luminal B), or hormone receptors (HR: positive or negative) by immunohistochemistry (IMH). Cox regression was used to compare PFS and OS in the 3 ROR groups (high, medium, or low). Results: TTL was predictive of non-SLN affectation in both univariate (OR [95% CI]: 1.72 [1.43, 2.05], P < .001) and multivariate (1.55 [95% CI: 1.04, 2.32], P = .030) models, but MS-IMH or HR-IMH, and their interactions with TTL were not (best multivariate model: HR + main effect OR 1.16 [95% CI: 0.18, 7.64], P = .874; interaction OR: 1.04 [0.7, 1.55], P = .835; univariate model: HR + main effect OR: 1.44 [95% CI: 0.85, 2.44], P = .180). PFS was lower in the high-risk ROR group (81.1%) than in the low-risk group (93.9%) (HR: 3.68 [95 CI: 1.70, 7.94], P < .001). Conclusions: our results do not provide evidence to support the utilization of subtype-specific thresholds for TTL values to make therapeutic decisions on the axilla. The ROR group was predictive of 5 years-PFS.
dc.language.isoeng
dc.publisherSAGE Publications
dc.relation.ispartofseriesClinical Pathology;16
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.sourceScientia
dc.subjectMama - Càncer
dc.subjectMetàstasi limfàtica
dc.subjectMarcadors tumorals
dc.subject.meshBreast Neoplasms
dc.subject.meshLymphatic Metastasis
dc.subject.meshTumor Burden
dc.titleOSNA Total Tumor Load for the Prediction of Axillary Involvement in Breast Cancer Patients: Should We use Different Thresholds According to the Intrinsic Molecular Subtype? MOTTO Study
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1177/2632010X231183693
dc.subject.decsneoplasias de la mama
dc.subject.decsmetástasis linfática
dc.subject.decscarga tumoral
dc.relation.publishversionhttps://doi.org/10.1177/2632010X231183693
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.audienceProfessionals
dc.contributor.organismesInstitut Català de la Salut
dc.contributor.authoraffiliation[Bernet L] Department of Pathology, Hospital Universitario del Vinalopó, Elche, Spain. [Hardisson D] Department of Pathology, Hospital Universitario La Paz, Madrid. Hospital La Paz Institute for health Research (IdiPAZ), Universidad Autónoma de Madrid. [Rodrigo M] Department of Pathology, Hospital Universitario de Burgos, Burgos, Spain. [Córdoba A] Department of Pathology, Hospital Universitario de Navarra, Navarra, Spain. [Sancho M] Department of Pathology, Hospital Universitario de Salamanca, Salamanca, Spain. [Peg V] Servei d’Anatomia Patològica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Spanish Biomedical Research Network Centre in Oncology (CIBERONC), Madrid, Spain
dc.identifier.pmid37534372
dc.identifier.wos001040565200001
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess


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