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Artículo

Closing the gap: Prognostic and predictive biomarker validation for personalized care in a Latin American hormone-dependent breast cancer cohort

Alves Da Quinta, Daniela BelénIcon ; Rocha, Darío Gastón; Retamales, Javier; Giunta, Diego HernanIcon ; Artagaveytia, Nora; Velazquez, Carlos; Daneri Navarro, Adrian; Müller, Bettina; Abdelhay, Eliana; Bravo, Alicia Ines; Castro, Mónica; Rosales, Cristina; Alcoba, Elsa; Acosta Haab, Gabriela; Carrizo, Fernando; Sorin, Irene; Di Sibio, Alejandro; Marques Silveira, Márcia; Binato, Renata; Caserta, Benedicta; Greif, Gonzalo; Del Toro Arreola, Alicia; Quintero Ramos, Antonio; Gómez, Jorge; Podhajcer, Osvaldo LuisIcon ; Fernandez, Elmer AndresIcon ; Llera, Andrea SabinaIcon
Fecha de publicación: 12/2024
Editorial: Alphamed Press
Revista: The Oncologist.
ISSN: 1083-7159
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Otras Ciencias Biológicas

Resumen

Background Several guidelines recommend the use of different classifiers to determine the risk of recurrence (ROR) and treatment decisions in patients with HR+HER2− breast cancer. However, data are still lacking for their usefulness in Latin American (LA) patients. Our aim was to evaluate the comparative prognostic and predictive performance of different ROR classifiers in a real-world LA cohort. Methods The Molecular Profile of Breast Cancer Study (MPBCS) is an LA case-cohort study with 5-year follow-up. Stages I and II, clinically node-negative HR+HER2− patients (n = 340) who received adjuvant hormone therapy and/or chemotherapy, were analyzed. Time-dependent receiver-operator characteristic-area under the curve, univariate and multivariate Cox proportional hazards regression (CPHR) models were used to compare the prognostic performance of several risk biomarkers. Multivariate CPHR with interaction models tested the predictive ability of selected risk classifiers. Results Within this cohort, transcriptomic-based classifiers such as the recurrence score (RS), EndoPredict (EP risk and EPClin), and PAM50-risk of recurrence scores (ROR-S and ROR-PC) presented better prognostic performances for node-negative patients (univariate C-index 0.61-0.68, adjusted C-index 0.77-0.80, adjusted hazard ratios [HR] between high and low risk: 4.06-9.97) than the traditional classifiers Ki67 and Nottingham Prognostic Index (univariate C-index 0.53-0.59, adjusted C-index 0.72-0.75, and adjusted HR 1.85-2.54). RS (and to some extent, EndoPredict) also showed predictive capacity for chemotherapy benefit in node-negative patients (interaction P = .0200 and .0510, respectively). Conclusion In summary, we could prove the clinical validity of most transcriptomic-based risk classifiers and their superiority over clinical and immunohistochemical-based methods in the heterogenous, real-world node-negative HR+HER2− MPBCS cohort.
Palabras clave: Cancer , Mama , Firmas
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution 2.5 Unported (CC BY 2.5)
Identificadores
URI: http://hdl.handle.net/11336/254671
URL: https://academic.oup.com/oncolo/article/29/12/e1701/7730117
DOI: http://dx.doi.org/10.1093/oncolo/oyae191
Colecciones
Articulos(CCT - CORDOBA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Articulos(IIBBA)
Articulos de INST.DE INVEST.BIOQUIMICAS DE BS.AS(I)
Citación
Alves Da Quinta, Daniela Belén; Rocha, Darío Gastón; Retamales, Javier; Giunta, Diego Hernan; Artagaveytia, Nora; et al.; Closing the gap: Prognostic and predictive biomarker validation for personalized care in a Latin American hormone-dependent breast cancer cohort; Alphamed Press; The Oncologist.; 29; 12; 12-2024; e1701-e1713
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