Evidence map›Paper›PMID 20233465›Full record

ArticleHereditary cancer in clinical practice2004

The clinical genetics of prostate cancer.

Sashi Kommu, Stephen Edwards, Rosalind Eeles

Open access · goldAbstract read
In one paragraph

Article in Hereditary cancer in clinical practice, 2004. 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, top 84% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Sashi KommuReader in Clinical Cancer Genetics, Translational Cancer Genetics Team, Institute of Cancer Research, Sutton, UK. Rosalind.Eeles@icr.ac.uk.
Stephen Edwards
Rosalind Eeles
Institute of Cancer Research · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer is the most common cancer in men and the second highest cause of cancer-related mortality in the U.K. A genetic component in predisposition to prostate cancer has been recognized for decades. One of the strongest epidemiological risk factors for prostate cancer is a positive family history. The hunt for the genes that predispose to prostate cancer in families has been the focus of many research groups worldwide for the past 10 years. Both epidemiological and twin studies support a role for genetic predisposition to prostate cancer. Familial cancer loci have been found, but the genes that cause familial prostate cancer remain largely elusive. Unravelling the genetics of prostate cancer is challenging and is likely to involve the analysis of numerous predisposition genes. Current evidence supports the hypothesis that excess familial risk of prostate cancer could be due to the inheritance of multiple moderate-risk genetic variants. Although research on hereditary prostate cancer has improved our knowledge of the genetic aetiology of the disease, a lot of questions still remain unanswered.This article explores the current evidence that there is a genetic component to the aetiology of prostate cancer and attempts to put into context the diverse findings that have been shown to be possibly associated with the development of hereditary prostate cancer. Linkage searches over the last decade are summarised. It explores issues as to why understanding the genetics of prostate cancer has been so difficult and why despite this, it is still a major focus of research. Finally, current and future management strategies of men with Hereditary Prostate Cancer (HPC) are discussed.

Identifiers

PMID20233465
PMCPMC4392519
OpenAlexW2119631700

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.