Evidence map›Paper›PMID 18408932›Full record

ReviewWorld journal of urology2008

What is the molecular pathology of low-risk prostate cancer?

Hemamali Samaratunga, Jonathan I Epstein

Abstract readReview
PubMed Publisher
In one paragraph

Review in World journal of urology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
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 at 2 institutions in 2 countries.

Hemamali SamaratungaDepartment of Anatomical Pathology, Sullivan Nicolaides Pathology, 134 Whitmore Street, Taringa, Brisbane, QLD, 4068, Australia. hema_samaratunga@snp.com.au
Jonathan I Epstein
Johns Hopkins University · USSullivan Nicolaides Pathology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesLow-risk prostate cancer is defined as a clinical T1c or T2a tumor with a Gleason score of </=6 and PSA <10 ng/ml. This is a pretreatment diagnosis and the patient can turn out to have either significant or insignificant disease. With methods currently available in practice it may not be possible to differentiate between these groups. Numerous molecular pathological changes have been described in prostate carcinoma. This review was to evaluate which of these changes may be useful to distinguish the group of patients likely to have significant carcinoma within the low risk category. MATERIALS AND

methodsThe literature on molecular pathology of prostate cancer was reviewed using MEDLINE and reference lists of relevant publications focusing on early and late molecular events and available molecular biomarkers in prostate cancer.

resultsThere are a variety of molecular markers with the potential to be clinically utilized for assessment of low risk prostate cancer. One of the most promising is TMPRSS2: ETS fusion, which is a homogeneous event occurring early in prostate carcinogenesis. Other promising markers include p27, EZH2 and c-MYC.

conclusionsFISH analysis or RT-PCR based assays to detect TMPRSS2: ETS fusion and immunohistochemical assessment of p27, EZH2 and c-MYC may become useful ancillary tests in patients with low risk prostate cancer. Some serum biomarkers have promise for future use. Large prospective studies followed by clinical trials are necessary before these molecular markers could be integrated into clinical practice.

Indexed as

Molecular Diagnostic TechniquesHumansMaleProstatic NeoplasmsRisk Factors

Identifiers

PMID18408932
OpenAlexW2058148868

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.