Evidence map›Paper›PMID 24199178›Full record

ArticleResearch and reports in urology2012

Detection of low frequency FGFR3 mutations in the urine of bladder cancer patients using next-generation deep sequencing.

John M Millholland, Shuqiang Li, Cecilia A Fernandez, Anthony P Shuber

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Research and reports in urology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
0.3field-weighted citation impact, top 34% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.

  1. Pooled it
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  7. Article
  8. Metastatic Melanoma: Liquid Biopsy as a New Precision Medicine Approach.International journal of molecular sciences · 2023
    Review
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  14. Detection of Promoter DNA Methylation in Urine and Plasma Aids the Detection of Non-Small Cell Lung Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

John M MillhollandPredictive Biosciences Inc, Lexington, MA, USA.
Shuqiang Li
Cecilia A Fernandez
Anthony P Shuber
Predictive Science (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological fluid-based noninvasive biomarker assays for monitoring and diagnosing disease are clinically powerful. A major technical hurdle for developing these assays is the requirement of high analytical sensitivity so that biomarkers present at very low levels can be consistently detected. In the case of biological fluid-based cancer diagnostic assays, sensitivities similar to those of tissue-based assays are difficult to achieve with DNA markers due to the high abundance of normal DNA background present in the sample. Here we describe a new urine-based assay that uses ultradeep sequencing technology to detect single mutant molecules of fibroblast growth factor receptor 3 (FGFR3) DNA that are indicative of bladder cancer. Detection of FGFR3 mutations in urine would provide clinicians with a noninvasive means of diagnosing early-stage bladder cancer. The single-molecule assay detects FGFR3 mutant DNA when present at as low as 0.02% of total urine DNA and results in 91% concordance with the frequency that FGFR3 mutations are detected in bladder cancer tumors, significantly improving diagnostic performance. To our knowledge, this is the first practical application of next-generation sequencing technology for noninvasive cancer diagnostics.

Indexed as

bladder cancerFGFR3mutationsequencingsingle moleculeurine

Identifiers

PMID24199178
PMCPMC3806441
OpenAlexW2097035472

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.