Evidence map›Paper›PMID 39736907›Full record

ArticleData in brief2024

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

Belén Ríos-Sánchez, Guillermo Vigueras, Aaron García, Daniel Gómez-Bravo, Ernestina Menasalvas, María Torrente, Consuelo Parejo, Fotis Aisopos, Dimitrios Vogiatzis, Disha Purohit and 3 more

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Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Belén Ríos-SánchezUniversidad Politécnica de Madrid, Spain.
Guillermo ViguerasUniversidad Politécnica de Madrid, Spain.
Aaron GarcíaUniversidad Politécnica de Madrid, Spain.
Daniel Gómez-BravoUniversidad Politécnica de Madrid, Spain.
Ernestina MenasalvasUniversidad Politécnica de Madrid, Spain.
María TorrenteMedical Oncology Department, Puerta de Hierro University Hospital, Servicio Madrileño de Salud, Spain.
Consuelo ParejoMedical Oncology Department, Puerta de Hierro University Hospital, Servicio Madrileño de Salud, Spain.
Fotis AisoposInstitute of Informatics & Telecommunications, National Centre for Scientific Research "Demokritos", Greece.
Dimitrios VogiatzisInstitute of Informatics & Telecommunications, National Centre for Scientific Research "Demokritos", Greece.
Disha PurohitTIB-Leibniz Information for Centre for Science and Technology & Leibniz University of Hannover & L3S Research, Germany.
Mariano ProvencioMedical Oncology Department, Puerta de Hierro University Hospital, Servicio Madrileño de Salud, Spain.
María-Esther VidalTIB-Leibniz Information for Centre for Science and Technology & Leibniz University of Hannover & L3S Research, Germany.
Alejandro Rodríguez-GonzálezUniversidad Politécnica de Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Adverse effectsDiagnosisDisease evolutionLung cancerTreatment

Identifiers

PMID39736907
PMCPMC11683279

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.