Evidence map›Paper›PMID 27683459›Full record

ArticleEJIFCC2014

Urothelial Bladder Cancer Urinary Biomarkers.

Aidan P Noon, Alexandre R Zlotta

Open access · greenAbstract read
In one paragraph

Article in EJIFCC, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. 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

2 authors at 1 institution in 1 country.

Aidan P NoonThe University of Toronto, Department of Surgery, Division of Urology, Toronto, Ontario; Princess Margaret Cancer Hospital, Department of Surgical Oncology, Division of Urology, Toronto, Ontario.
Alexandre R ZlottaThe University of Toronto, Department of Surgery, Division of Urology, Toronto, Ontario; Princess Margaret Cancer Hospital, Department of Surgical Oncology, Division of Urology, Toronto, Ontario; Mount Sinai Hospital, Department of Urology, Department of Surgery, Division of Urology, Toronto, Ontario.
University of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urothelial bladder cancer is the fourth most prevalent male malignancy in the United States and also one of the ten most lethal. Superficial or non-muscle-invasive bladder cancer has a high rate of recurrence and can progress to muscle invasive disease. Conventional surveillance requires regular cystoscopy and is used often with urinary cytology. Unfortunately, the cystoscopy procedure is invasive for patients and costly for health care providers. Urinary biomarkers have the potential to improve bladder cancer diagnosis, the efficiency and also the cost-effectiveness of follow up. It may also be possible for urinary biomarkers to help prognosticate particularly for patients with high-grade bladder cancer who may want enhanced assessment of their risk of disease progression. In this review the important historical urinary biomarkers and the newly emerging biomarkers are discussed. As will be presented, although many of the tests have good performance characteristics, unfortunately no single test can fulfill all the roles currently provided by cystoscopy and cytology. It is likely that in the future, urinary biomarker testing will be used selectively in a personalized manner to try and improve prognostication or reduce the necessity for invasive cystoscopy in patients understanding the limits of the test.

Indexed as

BiomarkerBladderCarcinomaUrinaryUrothelial

Identifiers

PMID27683459
PMCPMC4975193
OpenAlexW2551174420

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.