Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Antiviral activity of SA-2 against influenza A virus in vitro/vivo and its inhibition of RNA polymerase.

Antiviral research·2016
Same author

Occurrence, distribution and source apportionment of polychlorinated naphthalenes (PCNs) in sediments and soils from the Liaohe River Basin, China.

Environmental pollution (Barking, Essex : 1987)·2016
Same author

High level of microsynteny and purifying selection affect the evolution of WRKY family in Gramineae.

Development genes and evolution·2016
Same author

Mutational Analysis of Glycogen Synthase Kinase 3β Protein Kinase Together with Kinome-Wide Binding and Stability Studies Suggests Context-Dependent Recognition of Kinases by the Chaperone Heat Shock Protein 90.

Molecular and cellular biology·2016
Same author

Incidence and mortality rate of esophageal cancer has decreased during past 40 years in Hebei Province, China.

Chinese journal of cancer research = Chung-kuo yen cheng yen chiu·2016
Same author

Bulk pancreatic cancer cells can convert into cancer stem cells(CSCs) in vitro and 2 compounds can target these CSCs.

Cell cycle (Georgetown, Tex.)·2015

Related Experiment Video

Updated: Jun 25, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Multifactorial diagnostic model combining SAT-PCA3 in prostate cancer.

Zeyu Luo1,2, Shengjie Dai3, Jing Jin2

  • 1Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Zhejiang, China.

Discover Oncology
|June 23, 2026
PubMed
Summary
This summary is machine-generated.

Combining urine-based SAT-PCA3 testing with clinical data significantly improves prostate cancer diagnosis accuracy. This approach offers a more reliable method for detecting prostate cancer compared to individual tests.

Keywords:
BiomarkerDiagnosisPCA3Regression modelUrine

More Related Videos

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
06:08

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

Published on: March 21, 2025

Standardized SDS-PAGE Workflow for Personalized Protein Corona Profiling in Early Cancer Detection
10:02

Standardized SDS-PAGE Workflow for Personalized Protein Corona Profiling in Early Cancer Detection

Published on: December 19, 2025

Related Experiment Videos

Last Updated: Jun 25, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
06:08

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

Published on: March 21, 2025

Standardized SDS-PAGE Workflow for Personalized Protein Corona Profiling in Early Cancer Detection
10:02

Standardized SDS-PAGE Workflow for Personalized Protein Corona Profiling in Early Cancer Detection

Published on: December 19, 2025

Area of Science:

  • Urology
  • Oncology
  • Biomarker Research

Background:

  • Prostate cancer (PCa) diagnosis relies on various clinical factors.
  • Novel biomarkers are needed to enhance diagnostic accuracy.
  • Simultaneous Amplification and Testing PCA3 (SAT-PCA3) is a promising urine-based biomarker.

Purpose of the Study:

  • To evaluate the feasibility of using SAT-PCA3 combined with clinical information for PCa diagnosis.
  • To compare the diagnostic performance of a combined model versus individual parameters.

Main Methods:

  • Retrospective analysis of 137 patients with complete clinical data.
  • Development of a multivariate diagnostic model incorporating age, DRE, PSA, PIRADS score, and SAT-PCA3.
  • Comparison of diagnostic accuracy using receiver operating characteristic (ROC) curves and area under the curve (AUC).

Main Results:

  • The multivariate model combining SAT-PCA3 and clinical data achieved an AUC of 0.912.
  • Individual parameters showed lower AUCs: SAT-PCA3 (0.786) and PIRADS score (0.795).
  • The combined model demonstrated statistically significant improvement in diagnostic accuracy (p < 0.001).

Conclusions:

  • A diagnostic model integrating SAT-PCA3 with conventional clinical information significantly enhances prostate cancer diagnostic accuracy.
  • This combined approach outperforms any single diagnostic parameter alone.
  • The findings support the utility of SAT-PCA3 as a valuable tool in PCa detection.