Evidence map›Paper›PMID 26187155›Full record

ArticleMedical hypotheses2015

A processual model for functional analyses of carcinogenesis in the prospective cohort design.

Eiliv Lund, Sandra Plancade, Gregory Nuel, Hege Bøvelstad, Jean-Christophe Thalabard

Abstract read
In one paragraph

Article in Medical hypotheses, 2015. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Eiliv LundDepartment of Community Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway. Electronic address: eiliv.lund@uit.no.
Sandra PlancadeThe MIA-Jouy Research Unit, INRA, France. Electronic address: sandra.plancade@jouy.inra.fr.
Gregory NuelCNRS, INSMI Stochastics and Biology Group (PSB) LPMA, UPMC, Sorbonne University, France. Electronic address: nuel.gregory@math.cnrs.fr.
Hege BøvelstadDepartment of Community Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway. Electronic address: hege.m.bovelstad@uit.no.
Jean-Christophe ThalabardDepartment of Applied Mathematics, MAP5, 45 rue des Saints-Peres, University Paris Descartes, 75006 Paris, France. Electronic address: Jean-Christophe.Thalabard@math-info.univ-paris5.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditionally, the prospective design has been chosen for risk factor analyses of lifestyle and cancer using mainly estimation by survival analysis methods. With new technologies, epidemiologists can expand their prospective studies to include functional genomics given either as transcriptomics, mRNA and microRNA, or epigenetics in blood or other biological materials. The novel functional analyses should not be assessed using classical survival analyses since the main goal is not risk estimation, but the analysis of functional genomics as part of the dynamic carcinogenic process over time, i.e., a "processual" approach. In the risk factor model, time to event is analysed as a function of exposure variables known at start of follow-up (fixed covariates) or changing over the follow-up period (time-dependent covariates). In the processual model, transcriptomics or epigenetics is considered as functions of time and exposures. The success of this novel approach depends on the development of new statistical methods with the capacity of describing and analysing the time-dependent curves or trajectories for tens of thousands of genes simultaneously. This approach also focuses on multilevel or integrative analyses introducing novel statistical methods in epidemiology. The processual approach as part of systems epidemiology might represent in a near future an alternative to human in vitro studies using human biological material for understanding the mechanisms and pathways involved in carcinogenesis.

Indexed as

CarcinogenesisResearch DesignCarcinogensEpigenesis, GeneticGenome-Wide Association StudyHumansLife StyleModels, TheoreticalNeoplasmsObservational Studies as TopicProspective StudiesRegression AnalysisRisk FactorsTime FactorsTranscriptomeCarcinogens

Identifiers

PMID26187155
PMCPMC4579405

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Registered trials

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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.