ArticleInternational journal of molecular epidemiology and genetics2012
Transcriptional output in a prospective design conditionally on follow-up and exposure: the multistage model of cancer.
Article in International journal of molecular epidemiology and genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle.BMC medical research methodology · 2016Article
- A processual model for functional analyses of carcinogenesis in the prospective cohort design.Medical hypotheses · 2015Article
- Prediagnostic transcriptomic markers of Chronic lymphocytic leukemia reveal perturbations 10 years before diagnosis.Annals of oncology : official journal of the European Society for Medical Oncology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcriptomics as the analysis of mRNA and microRNA could be implemented in prospective studies both in peripheral blood and tissues. Its application in cancer epidemiology could provide a new understanding of the functional changes underlying the multistage model of carcinogenesis, as well as the relationship between these changes and exposure to carcinogens. Transcriptomics is not merely another -omics technology for risk assessment in traditional prospective studies. Instead, this novel approach has the potential to estimate the distribution of gene expression conditionally on different exposures, and to study the length of the different stages of carcinogenesis. If it proves to be a valid approach, transcriptomics could be an opportunity to make meaningful advances in our understanding of the carcinogenic process.
Indexed as
Identifiers
22724047PMC3376922What OpenQuestion holds
Registered trials
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.