Evidence map›Paper›PMID 25767263›Full record

ArticleAmerican journal of epidemiology2015

Invited commentary: driving for further evolution.

Robert A Hiatt

Abstract readComment
PubMed Publisher
In one paragraph

Article in American journal of epidemiology, 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. Transdisciplinary approaches enhance the production of translational knowledge.Translational research : the journal of laboratory and clinical medicine · 2017
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Robert A Hiatt

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The concept of translational cancer epidemiology has evolved since its early beginnings in 1937 with the establishment of the National Cancer Institute. Conceptual models of cancer control research have also evolved over the last 30 years, to the point where we now have 4 stages of translational research (T0-T4). The current review by Lam et al. (Am J Epidemiol. 2015;181(7):451-458) covers cancer epidemiology research supported by the National Cancer Institute and a selected sample of the cancer epidemiology literature. It suggests that most cancer epidemiology in the last 10 years has been in pure discovery research. Current "drivers" of cancer epidemiology research, including new technologies, team science multilevel research, and knowledge integration, are not strongly represented in the review. However, the use of epidemiology in the latter stages of translation may not have been captured by the scope of this review. The closer epidemiologists get to advanced stages of translation, the more likely they are to work with investigators in other disciplines in other sectors of society. An argument can be made that regardless of whether this kind of research is not happening or was just missed by the current review, the field of cancer epidemiology can expand its scope and further evolve towards more effective applications in population health.

Indexed as

Biomedical TechnologyHumansNational Cancer Institute (U.S.)NeoplasmsResearch Support as TopicTranslational Research, Biomedicalcancerepidemiologysystematic reviewstranslational science

Identifiers

PMID25767263

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.