Evidence map›Paper›PMID 21547503›Full record

ArticleJournal of medical systems2012

A telematic tool to predict the risk of colorectal cancer in white men and women: ColoRectal Cancer Alert (CRCA).

Isabel de la Torre, Francisco Javier Díaz, Míriam Antón, Esteban Barragán, Joel Rodrigues, Celina Pires

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 38% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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

6 authors at 3 institutions in 2 countries.

Isabel de la TorreDepartment of Signal Theory and Communications, University of Valladolid, Paseo de Belén, Valladolid, Spain. isator@tel.uva.es
Francisco Javier Díaz
Míriam Antón
Esteban Barragán
Joel Rodrigues
Celina Pires
Universidad de Valladolid · ESInstituto de Telecomunicações · PTUniversity of Beira Interior · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer is an important disease because of its severity and also since it affects much of the population. Nothing helps patients and doctors to determine the risk of suffering from colorectal cancer during their lives, except for medical tests such as the colonoscopy. There have been several studies and research to try to estimate the relative risks of colorectal cancer based on various factors and the applications to calculate the risk of this cancer, but these are not within everyone's research. This project offers a multilingual Web tool, called ColoRectal Cancer Alert (CRCA), to calculate the risk of colorectal cancer for life in men and women of white race. With this application, doctors can carry out research in a few minutes to explore this risk when they are seeing a patient. The platform is designed in such a way that anyone can use it. It is easy to use and intuitive. We should keep in mind that this tool does not replace diagnostic tests such as the colonoscopy or the sigmoidoscopy. It is designed so that users with the assistance of their doctor know the risk and act accordingly (for example, having more checkups on the disease in case of high risk). To access the tool a computer with Internet connection will be required. Currently, 250 users of white race under the supervision of a specialist have completed the questionnaire.

Indexed as

InternetWhite PeopleColorectal NeoplasmsFemaleHealth BehaviorHumansMaleModels, TheoreticalRisk AssessmentSurveys and Questionnaires

Identifiers

PMID21547503
OpenAlexW2117518273

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.