Evidence map›Paper›PMID 21537385›Full record

ArticleInternational journal of molecular epidemiology and genetics2010

Towards a more functional concept of causality in cancer research.

Eiliv Lund, Vanessa Dumeaux

Abstract read
In one paragraph

Article in International journal of molecular epidemiology and genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Systems Epidemiology: What's in a Name?Online journal of public health informatics · 2014
    Article
  2. 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

2 authors.

Eiliv LundInstitute of Community Medicine, University of Tromsø 9037 Tromsø, Norway.
Vanessa Dumeaux

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in molecular technologies challenge the different concepts of causality in biology, epidemiology and multistage mathematical models. The lack of integration of the different aspects of causality into a common framework could postpone our attempts to build a human causal model of carcinogenesis. We present here some aspects of differences in methodology, terminology and traditions between the scientific disciplines and propose a research strategy using functional analyses of the transcriptome and epigenetics to illuminate causality in complex biological systems. Overcoming the challenges of biological material collection suitable for such analyses into a prospective design, this could give unique opportunities for verification of mechanistic information from basic biological research in a human model system. The ultimate goal is to obtain a dynamic causal description of the different carcinogenesis stages. The success of this novel approach depends on the biological relationship between the gene expression of the somatic driver mutations or co-expressed genes in tumours and the gene expressions mirrored in peripheral blood along the different stages of carcinogenesis. The use of gene expression profiles and epigenetics could produce a functional concept of causality to explain the human multistage carcinogenic process.

Indexed as

carcinogenesisCausalityepidemiologyepigeneticsmultistage modelstranscriptomic

Identifiers

PMID21537385
PMCPMC3076760

What OpenQuestion holds

Textmetadata
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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.