Evidence map›Paper›PMID 26669451›Full record

ReviewBritish journal of cancer2015

UK BRCA mutation testing in patients with ovarian cancer.

Angela George

Open access · bronzeAbstract readReview
In one paragraph

Review in British journal of cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.2field-weighted citation impact, top 7% 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

9 citing papers in PubMed, 22 citations in OpenAlex.

  1. Observational
  2. Perspectives on Ovarian Cancer 1809 to 2022 and Beyond.Diagnostics (Basel, Switzerland) · 2022
    Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. The integration of BRCA testing into oncology clinics.British journal of nursing (Mark Allen Publishing) · 2016
    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

1 author at 1 institution in 1 country.

Angela GeorgeThe Royal Marsden NHS Foundation Trust, Fulham Road, London SW3 6JJ, UK.
Royal Marsden NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the increasing clinical importance of germline BRCA mutation status in managing women with ovarian cancer, few patients are currently being tested. The traditional means of selecting patients for BRCA mutation testing using restrictive criteria will miss many women with a mutation. To expand access to testing and streamline the testing process, several centres in the UK have been developing new models for BRCA testing. Trials with these integrated models involving closer collaborations between genetics and oncology services are now under way. In addition to testing for BRCA mutations, there is also increasing interest in testing for other genes associated with a predisposition to ovarian cancer. Advances in next-generation sequencing technology have resulted in the development of comprehensive genetic testing panels for use in the research and diagnostic settings. Interest is also increasing in expanding testing for somatic mutations in ovarian cancer, particularly for genes such as BRCA1 and BRCA2, whereby mutations may allow more patients to benefit from targeted agents, including poly(ADP-ribose) polymerase inhibitors. In this review, the issues of who should be offered testing, how testing could be delivered, when testing should occur and the technology and costs associated with genetic testing are addressed.

Indexed as

FemaleHumansMutationOvarian NeoplasmsPoly(ADP-ribose) Polymerase InhibitorsUnited KingdomPoly(ADP-ribose) Polymerase Inhibitors

Identifiers

PMID26669451
PMCPMC4816269
OpenAlexW2221469903

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.