Evidence map›Paper›PMID 33766467›Full record

ArticleUrologic oncology2021

Bladder cancer risk stratification using a urinary mRNA biomarker panel - A path towards cystoscopy triaging.

Eugene Shkolyar, Qian Zhao, Kathleen E Mach, Nikola C Teslovich, Timothy J Lee, Susanne Cox, Eila C Skinner, Ying Lu, Joseph C Liao

Abstract read
In one paragraph

Article in Urologic oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 17 citations in OpenAlex.

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  6. The roles and mechanisms of circular RNAs related to mTOR in cancers.Journal of clinical laboratory analysis · 2022
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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

9 authors at 3 institutions in 2 countries.

Eugene ShkolyarDepartment of Urology, Stanford University School of Medicine, Stanford, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, USA.
Qian ZhaoDepartment of Biomedical Data Science, Stanford University, Stanford, USA; Department of Epidemiology and Medical Statistics, School of Public Health, Guangzhou Medical University, Guangzhou, China.
Kathleen E MachDepartment of Urology, Stanford University School of Medicine, Stanford, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, USA.
Nikola C TeslovichDepartment of Urology, Stanford University School of Medicine, Stanford, USA.
Timothy J LeeDepartment of Urology, Stanford University School of Medicine, Stanford, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, USA.
Susanne CoxVeterans Affairs Palo Alto Health Care System, Palo Alto, USA.
Eila C SkinnerDepartment of Urology, Stanford University School of Medicine, Stanford, USA.
Ying LuDepartment of Biomedical Data Science, Stanford University, Stanford, USA.
Joseph C LiaoDepartment of Urology, Stanford University School of Medicine, Stanford, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, USA. Electronic address: jliao@stanford.edu.
Stanford University · USVA Palo Alto Health Care System · USGuangzhou Medical University · CN

Funding

Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI Vittorio Sebastiano · 2007 to 2026
$71.4M
NCI NIH HHS P30 CA124435
6 · The paper itself

Abstract

objectivesThe risk of bladder cancer (BCa) diagnosis and recurrence necessitates cystoscopy. Improved risk stratification may inform personalized triage and surveillance strategies. We aim to develop a urinary mRNA biomarker panel for risk stratification in patients undergoing BCa screening and surveillance. METHODS AND MATERIALS: Urine samples were collected from patients undergoing cystoscopy for BCa screening or surveillance. In patients who underwent transurethral resection of bladder tumor, urine samples were categorized based on tumor histopathology, size, and focality. Subjects with intermediate and high-risk BCa based on American Urological Association (AUA) guideline for non-muscle invasive bladder cancer were classified as "increased-risk"; those with no cancer and AUA low-risk BCa were classified as "low-risk". Urine was evaluated for ROBO1, WNT5A, CDC42BPB, ABL1, CRH, IGF2, ANXA10, and UPK1B expression. A diagnostic model to detect "increased-risk" BCa was created using forward logistic regression analysis of cycle threshold values. Model validation was performed with ten-fold cross-validation. Sensitivity and specificity for detection of "increased-risk" BCa was determined and net benefit analysis performed.

resultsUrine samples (n = 257) were collected from 177 patients (95 screening, 76 surveillance, 6 both). There were 65 diagnoses of BCa (12 low, 22 intermediate, 31 high risk). ROBO1, CRH, and IGF2 expression correlated with "increased-risk" disease yielding sensitivity of 92.5% (95% CI, 84.9%-98.1%) and specificity of 73.5% (95% CI, 67.7-79.9%). The overall calculated standardized net benefit of the model was 0.81 (95%CI, 0.71-0.90).

conclusionsA 3-marker urinary mRNA panel allows for non-invasive identification of "increased-risk" BCa and with further validation may prove to be a tool to reduce the need for cystoscopies in low-risk patients.

Indexed as

AgedBiomarkers, TumorCystoscopyFemaleFollow-Up StudiesHumansMalePrognosisRisk AssessmentRNA, MessengerSurvival RateTriageUrinary Bladder NeoplasmsBiomarkers, TumorRNA, MessengerBladder cancerCystoscopyUrinary biomarkers

Identifiers

PMID33766467
PMCPMC13271232
OpenAlexW3137301965

What OpenQuestion holds

Textmetadata
LicenceTDM
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.