Evidence map›Paper›PMID 17991360›Full record

ReviewCurrent oncology reports2007

Risk assessment models to estimate cancer probabilities.

Constance M Johnson, Derek Smolenski

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current oncology reports, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Constance M JohnsonSchool of Nursing, Community and Family Medicine, Duke University, 307 Trent Drive, DUMC 3322, Durham, NC 27710, USA. constance.johnson@duke.edu
Derek Smolenski

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer risk has become a significant research topic due to an increase in statistical risk models built to predict cancer incidence or mortality. Over the past 3 years, 15 models on the development of different types of cancer, including breast, colorectal, prostate, gastric, lung, ovarian, pancreatic, testicular, and skin, have been published. Risk assessment models are dynamic; they need to be updated as often as risks are discovered or changed. Not only are cancer risk models challenging to build, but, due to literacy-related issues, the cancer risk itself is challenging to communicate to the public. Clearly, guidelines outlining how to create valid and reliable risk assessment models are needed.

Indexed as

Models, StatisticalHumansNeoplasmsProbabilityRisk AssessmentRisk Factors

Identifiers

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.