Evidence map›Paper›PMID 31285945›Full record

ReviewAmerican journal of cancer research2019

Urine protein biomarkers for the detection, surveillance, and treatment response prediction of bladder cancer.

Ashish Chakraborty, Shobha Dasari, Wang Long, Chandra Mohan

Open access · greenAbstract readReview
PubMed Full text at PMC
In one paragraph

Review in American journal of cancer research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
7.3field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.

  1. Pooled it
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  16. [Application of Raman-based technologies in the detection of urological tumors].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2022
    Article
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  18. Mucosa-interfacing electronics.Nature reviews. Materials · 2022
    Review
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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

4 authors at 2 institutions in 2 countries.

Ashish ChakrabortyDepartment of Biomedical Engineering, University of Houston Houston, TX, USA.
Shobha DasariDepartment of Biomedical Engineering, University of Houston Houston, TX, USA.
Wang LongDepartment of Urology, Xiangya Hospital, Central South University Changsha 410008, Hunan, China.
Chandra MohanDepartment of Biomedical Engineering, University of Houston Houston, TX, USA.
University of Houston · USCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The "gold standard" diagnostic procedure for bladder cancer is cystoscopy, a technique that can be invasive, expensive, and a possible cause of urinary tract infection. Unlike techniques such as histology, PCR, and staining, assays for protein biomarkers lend themselves well to the creation of efficient point-of-care tests, which are easy to use and yield fast results. A couple of urine-based tests have been approved by the U.S. FDA, but these tests suffer from low sensitivity. Hence, there is clearly a need for more reliable non-invasive biomarkers of bladder cancer. Urinary biomarkers are particularly attractive due to the direct contact of the urine with the urothelial tumor and the ease of sample collection. With these considerations, this review aims to provide a comprehensive listing of the most promising protein biomarkers of bladder cancer in urine. Biomarkers are organized by their potential role in detection, surveillance, or monitoring of treatment response. The purpose of this review is to assess progress towards the goal of identifying ideal urinary proteins for use in each of the above three biomarker applications in bladder cancer.

Indexed as

NMIBCNMP22 testPoint-of-care testsproteomicstumor recurrence

Identifiers

PMID31285945
PMCPMC6610049
OpenAlexW2981417556

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.