Este archivo ha sido creado el 29-08-2024 por Jorge García Gutiérrez GENERAL INFORMATION ------------------ 1. Dataset title: Immunohistochemistry of Invasive Ductal Carcinoma of the Breast for Survival and Mortality (Dataset) 2. Authorship: Name: Laura Macías García Institution: Universidad de Sevilla Email: lmacias@us.es ORCID: 0000-0003-3412-8435 Name: Antonio Robles Frías Institution: Servicio Andaluz de Salud Email: lmacias@us.es ORCID: 0009-0003-3295-2890 Name: Jorge García Gutiérrez Institution: Universidad de Sevilla Email: jorgarcia@us.es ORCID: 0000-0002-1300-4647 DESCRIPTION ---------- 1. Dataset language: Spanish 2. Abstract: Base de datos de 234 pacientes diagnosticadas de Carcinoma Ductal Infiltrante de mama que recoge un estudio observacional retrospectivo de 5 años donde se estudia en primer lugar la presencia o no de recidiva y/o mortalidad durante el período de estudio (5 años), permitiendo establecer variables independientes como la supervivencia y la mortalidad. En segundo lugar, se realiza un estudio y valoración de la expresión de diversos y distintos marcadores inmunohistoquímicos con el objetivo de correlacionar la expresión de cada una de las moléculas de Inmunohistoquímicas, unas con otras, así como, con la intención de obtener resultados concluyentes que apoyen una relación significativa de la expresión de alguna de éstas moléculas con el riesgo de recidiva (tiempo libre de enfermedad), así como con el riesgo de mortalidad (tiempo de supervivencia). El objetivo principal de esta base de datos es: Definir un perfil de biomarcadores inmunohistoquímicos con valor predictivo en el carcinoma ductal infiltrante de mama. El estudio pretende demostrar el posible valor pronóstico de cada molécula, valorándolo en función de la evolución (que vendrá determinada por la recidiva y la mortalidad), así como con factores pronósticos conocidos como: tamaño, edad, estadio inicial, ganglios y grado de Escala Bloom-Richardson y Escala de Nottingham. Database of 234 patients diagnosed with Breast Invasive Ductal Carcinoma. This observational retrospective study spans 5 years and primarily examines the presence or absence of recurrence and/or mortality during the study period (5 years). This allows for the establishment of independent variables such as survival and mortality. Secondly, the study includes an analysis and evaluation of the expression of various immunohistochemical biomarkers with the goal of correlating the expression of each molecule with one another, as well as obtaining conclusive results that support a significant relationship between the expression of any of these molecules and the risk of recurrence (disease-free survival), as well as the risk of mortality (survival time). The main objective of this database is to define a profile of immunohistochemical biomarkers with predictive value in invasive ductal carcinoma of the breast. The study aims to demonstrate the potential prognostic value of each molecule, evaluating it in relation to evolution (which will be determined by recurrence and mortality), as well as known prognostic factors such as: tumor size, age, initial stage, lymph nodes, and grade on the Bloom-Richardson Scale and Nottingham Scale. --- 3. Keywords: cancer de mama, carcinoma, biomarcadores inmunohistoquímicos breast cancer, carcinoma, immunohistochemical biomarkers 4. Date of data collection (fecha única o rango de fechas): Del 01-01-2013 al 01-01-2016 From 01-01-2013 to 01-01-2016 5. Publication Date: 31/07/2024 6. Grant information: Grant Agency: Ministerio de Economía y Competitividad Grant Number: TIN2014-55894-C2-1-R ACCESS INFORMATION ------------------------ 1. Creative Commons License of the dataset: CC-BY 2. Dataset DOI: https://doi.org/10.12795/11441/161794 3. Related publication: Laura Macías-García, José María Luna-Romera, Jorge García-Gutiérrez, María Martínez-Ballesteros, José C. Riquelme-Santos, Ricardo González-Cámpora. A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation, Journal of Biomedical Informatics, Volume 72, 2017, Pages 33-44, ISSN 1532-0464, https://doi.org/10.1016/j.jbi.2017.06.020. VERSIONING AND PROVENANCE --------------- 1. Last modification date: 01-01-2016 2. Were data derived from another source?: No METHODOLOGICAL INFORMATION ----------------------- Database of 234 patients diagnosed with Infiltrating Ductal Carcinoma of the breast, collected in a 5-year retrospective observational study. The study initially examines the presence or absence of recurrence and/or mortality during the study period (5 years), allowing for the establishment of independent variables such as survival and mortality. Subsequently, a study and evaluation of the expression of various immunohistochemical markers were conducted to correlate the expression of each molecule with the risk of recurrence (disease-free time) and mortality risk (survival time). Finally, other known prognostic factors were generated, such as size, age, initial stage, lymph nodes, and the Bloom-Richardson Scale and Nottingham Scale grade, for comparison with the immunohistochemical markers. 1. Description of the methods used to collect and generate the data: The description of the data collection is in the following articles: Macías-García, Laura, et al. "FOXA1 Expression as a Prognostic Factor of Invasive Breast Carcinoma That Argues Against the Use of Adjuvant Chemotherapy in ER-Positive/Lymph-Node-Negative Patients" Anal. Quant. Cytopathol. Histol 38.4 (2016): 205-211. Macías-García, Laura, et al. "An immunohistochemical profile predictive of recurrence and/or mortality in patients with non-special type invasive mammary carcinoma" Anal. Quant. Cytopathol. Histol 38.3 (2016): 159-167 Laura Macías-García, José María Luna-Romera, Jorge García-Gutiérrez, María Martínez-Ballesteros, José C. Riquelme-Santos, Ricardo González-Cámpora. A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation, Journal of Biomedical Informatics, Volume 72, 2017, Pages 33-44, ISSN 1532-0464, https://doi.org/10.1016/j.jbi.2017.06.020. 2. Data processing methods: Los datos sensibles de los pacientes se anonimizaron eliminando cualquier elemento sensible. FILE OVERVIEW ---------------------- 1. Explain the file naming conversion: Name: breast + _ + year.xlsx 2. File list: File name: breast_2016.xlsx Description: Dataset in excel format 3. File format: Excel 2023 format