A lung cancer diagnosis and treatment dataset with geno- and phenotypical characteristics of the patient

authored by

Belén Ríos-Sánchez, Guillermo Vigueras, Aaron García, Daniel Gómez-Bravo, Ernestina Menasalvas, María Torrente, Consuelo Parejo, Fotis Aisopos, Dimitrios Vogiatzis, Disha Purohit, Mariano Provencio, María Esther Vidal, Alejandro Rodríguez-González

Abstract

This dataset comprises information about 1242 lung cancer patients collected by the Medical Oncology Department of the Puerta de Hierro University Hospital of Majadahonda in Madrid, Spain. It includes information about cancer diagnosis and treatment, as well as personal and medical data recorded during anamneses. The dataset could assist in data analysis with the aim of discovering relationships between the applied treatment(s), the evolution of the disease and the associated adverse effects. A greater understanding of treatment effects based on the particular conditions of the patient and the diagnosis could directly impact the healthcare system, helping to improve expectations about lung cancer as well as reducing treatment toxicities and adverse effects.

Organisation(s)

Institute of Data Science
L3S Research Centre

External Organisation(s)

Technical University of Madrid (UPM)
Puerta de Hierro Majadahonda University Hospital
National Centre For Scientific Research Demokritos (NCSR Demokritos)
The American College of Greece (ACG)
German National Library of Science and Technology (TIB)

Type

Article

Journal

Data in Brief

Volume

57

No. of pages

7

Publication date

12.2024

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

General

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.1016/j.dib.2024.111167 (Access: Open)