2020, Number 02
Biomarkers as prediction factors of breast cancer by means of a posteriori implicative analysis
Language: Spanish
References: 14
Page: 223-234
PDF size: 1107.55 Kb.
ABSTRACT
Introduction: Biomarkers are substances that are increased in the organism if tumors exist. To demonstrate how they influence in the mortality it is necessary an analytic study where statistical techniques are involved as the implicative statistical analysis. Objectives: To determine the influence of biomarkers as prediction factors of mortality due to breast cancer and to demonstrate the validity of a posteriori analysis as a phase in the methodology of the implicative statistical analysis implementation. Methods: A cases and controls analytic study of 75 patients older than 18 years with clinical and histological diagnosis of breast cancer was carried out, they were assisted in Conrado Benítez García Teaching Provincial Cancer Hospital in Santiago de Cuba, from 2014 to 2019. The foreseen phases were followed to implement this form of analysis and the implicative grapho and the similarity and cohesion trees were obtained. Results: It was verified that the relationship between the biomarkers and the alive patients was due to B luminal subtype. Also, in the meta-rules that includes dead women, B luminal subtype was involved, while the A luminal subtype was part of this meta-rule; the other subtypes didn't form rules with any other factor. Conclusions: The necessity and importance of the posteriori analysis phase was demonstrated, where the existence of some prediction factors was confirmed and others found before were rejected.REFERENCES
Daniels B, Kiely BE, Tang M, Tervonen H, Pearson SA. Trastuzumab use in older patients with HER2-positive metastatic breast cancer: outcomes and treatment patterns in a whole-of-population Australian cohort (2003–2015). BMC Cancer 2019 [citado 10/10/2019];19(1):909. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6740010/
Healey MA, Hirko KA, Beck AH, Collins LC, Schnitt SJ, Eliassen AH, et al. Assessment of Ki67 expression for breast cancer subtype classification and prognosis in the Nurses’ Health Study. Breast Cancer Res Treat. 2017 [citado 20/06/2019];166(2):613–22. Disponible en: https://doi.org/10.1007/s10549-017-4421-3
Arnedo Franco G. Análisis de sobrevida relacionada con factores pronósticos en mujeres con cáncer de mama tratadas en un Centro Cancerológico de la ciudad de Barranquilla 2011-2016 [tesis de maestría]. Barranquilla; Universidad del Norte; 2018 [citado 20/10/2019]. Disponible en: http://manglar.uninorte.edu.co/handle/10584/8123
Panal Cusati M, Herrera de la Muela M, Hardisson Hernaez D, Choqueneira Dionisio M, Román Guindo A, de Santiago Garcia FJ. Correlación entre la expresión de Ki67 con factores clásicos pronósticos y predictivos en el cáncer de mama precoz. Rev Senol Patol Mamar. 2014 [citado 20/10/2019];27(4):163-9. Disponible en: http://dx.doi.org/10.1016/j.senol.2014.07.005