Evidence map›Paper›PMID 39452927›Full record

ArticleMetabolites2024

Detection and Validation of Organic Metabolites in Urine for Clear Cell Renal Cell Carcinoma Diagnosis.

Kiana L Holbrook, George E Quaye, Elizabeth Noriega Landa, Xiaogang Su, Qin Gao, Heinric Williams, Ryan Young, Sabur Badmos, Ahsan Habib, Angelica A Chacon and 1 more

Abstract read
In one paragraph

Article in Metabolites, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. 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

11 authors.

Kiana L HolbrookDepartment of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA.ORCID 0000-0001-8018-2091
George E QuayeDivision of Health Services and Outcomes Research, Children's Mercy Kansas City, Kansas City, MO 64108, USA.ORCID 0000-0001-7020-2116
Elizabeth Noriega LandaDepartment of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA.
Xiaogang SuDepartment of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968, USA.
Qin GaoBiologics Analytical Operations, Gilead Sciences Incorporated, Oceanside, CA 94404, USA.
Heinric WilliamsDepartment Urology, Geisinger Clinic, Danville, PA 17822, USA.
Ryan YoungDepartment Urology, Geisinger Clinic, Danville, PA 17822, USA.
Sabur BadmosDepartment of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA.
Ahsan HabibDepartment of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA.ORCID 0000-0003-3563-4276
Angelica A ChaconDepartment of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA.
Wen-Yee LeeDepartment of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA.ORCID 0000-0002-1568-5546

Funding

UTEP Border Biomedical Research CenterU54MD007592 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI Michael J Kenney · 2019 to 2026
$35.1M
TCCG12MD007592 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI KIRKEN, ROBERT A. · 2012 to 2018
$19.4M
RISE Scholars Program at UTEPR25GM069621 · NIGMS · UNIVERSITY OF TEXAS EL PASO · PI AGUILERA, RENATO J · 2004 to 2021
$11.2M
G-RISE at the University of Texas at El PasoT32GM144919 · NIGMS · UNIVERSITY OF TEXAS EL PASO · PI AGUILERA, RENATO J · 2022 to 2024
$1.5M
Urinary biomarkers for prostate cancer diagnosis and risk assessmentSC1CA245675 · NCI · UNIVERSITY OF TEXAS EL PASO · PI LEE, WEN-YEE · 2019 to 2023
$1.5M
NCI NIH HHS SC1 CA245675NIGMS NIH HHS R25 GM069621NIGMS NIH HHS T32 GM144919NIH HHS 1T32GM144919NIH HHS 2U54MD007592NIH HHS 5R25GM69621NIH HHS SC1CA245675NIMHD NIH HHS G12 MD007592NIMHD NIH HHS U54 MD007592
6 · The paper itself

Abstract

backgroundClear cell renal cell carcinoma (ccRCC) comprises the majority, approximately 70-80%, of renal cancer cases and often remains asymptomatic until incidentally detected during unrelated abdominal imaging or at advanced stages. Currently, standardized screening tests for renal cancer are lacking, which presents challenges in disease management and improving patient outcomes. This study aimed to identify ccRCC-specific volatile organic compounds (VOCs) in the urine of ccRCC-positive patients and develop a urinary VOC-based diagnostic model.

methodsThis study involved 233 pretreatment ccRCC patients and 43 healthy individuals. VOC analysis utilized stir-bar sorptive extraction coupled with thermal desorption gas chromatography/mass spectrometry (SBSE-TD-GC/MS). A ccRCC diagnostic model was established via logistic regression, trained on 163 ccRCC cases versus 31 controls, and validated with 70 ccRCC cases versus 12 controls, resulting in a ccRCC diagnostic model involving 24 VOC markers.

resultsThe findings demonstrated promising diagnostic efficacy, with an Area Under the Curve (AUC) of 0.94, 86% sensitivity, and 92% specificity.

conclusionsThis study highlights the feasibility of using urine as a reliable biospecimen for identifying VOC biomarkers in ccRCC. While further validation in larger cohorts is necessary, this study's capability to differentiate between ccRCC and control groups, despite sample size limitations, holds significant promise.

Indexed as

ccRCCdiagnostic modelGC-MSmetabolomicsrenal cancer carcinomastir-bar sorptive extractionurinaryVOCs

Identifiers

PMID39452927
PMCPMC11509871

What Socratic 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 Socratic graph.