Evidence map›Paper›PMID 34978574›Full record

ArticleJournal of the National Cancer Institute2022

Molecular Biologic and Epidemiologic Insights for Preventability of Colorectal Cancer.

Edward Giovannucci

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
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

1 author at 1 institution in 1 country.

Edward GiovannucciDepartments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-6123-0219
Harvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The etiology of colorectal cancer (CRC) has been informed from both a molecular biology perspective, which concerns the study of the nature, timing, and consequences of mutations in driver genes, and epidemiology, which focuses on identifying risk factors for cancer. For the most part, these fields have developed independently, and it is thus important to consider them in a more integrated manner. The molecular mutational perspective has stressed the importance of mutations due to replication of adult stem cells, and the molecular fingerprint of most CRCs does not suggest the importance of direct carcinogens. Epidemiology has identified numerous modifiable risk factors that account for most CRCs, most of which are not direct mutagens. The distribution of CRCs across the large bowel is not uniform, which is possibly caused by regional differences in the microbiota. Some risk factors are likely to act through or interact with the microbiota. The mutational perspective informs when risk factors may begin to operate in life and when they may cease to operate. Evidence from the mutational model and epidemiology supports that CRC risk factors begin early in life and may contribute to the risk of early-onset CRC. Later in carcinogenesis, there may be a "point of no return" when sufficient mutations have accumulated, and some risk factors do not affect cancer risk. This period may be at least 5-15 years for some risk factors. A more precise knowledge of timing of risk factor to cancer is required to inform preventive efforts.

Indexed as

Biological ProductsColorectal NeoplasmsAdultCarcinogenesisHumansMutationRisk FactorsBiological Products

Identifiers

PMID34978574
PMCPMC9086743
OpenAlexW4205958378

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.