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Updated: Jan 24, 2026
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Isolation of Cancer Stem Cells From Human Prostate Cancer Samples
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PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks
Maria Cutumisu1, Catalina Vasquez1, Maxwell Uhlich
1University of Alberta, Edmonton, Alberta, Canada.
JCO Clinical Cancer Informatics
|May 23, 2019
Summary
The Predictive Research Online System Prostate Cancer Tasks (PROSPeCT) system allows clinicians and researchers to efficiently query prostate cancer data. This user-friendly tool aids in identifying patient cohorts and improving treatment strategies.
Area of Science:
- Medical Informatics
- Oncology
- Health Data Management
Background:
- High-quality prostate cancer treatment relies on efficient access to comprehensive patient data.
- Clinicians and researchers need user-friendly systems to query large, evolving prostate cancer databases.
Purpose of the Study:
- To develop and describe the Predictive Research Online System Prostate Cancer Tasks (PROSPeCT).
- To enable efficient and accurate querying of the Alberta Prostate Cancer Registry database.
- To support clinicians and researchers in identifying patient cohorts and developing treatment strategies.
Main Methods:
- PROSPeCT was designed for intuitive database querying without programming skills.
- Users can create, save, and reuse definitions to identify specific patient cohorts.
- Exemplified by creating a complex definition to identify "high-risk" prostate cancer patients.
Main Results:
- PROSPeCT minimizes user error and maximizes efficiency for both novice and expert users.
- The system facilitates cohort identification, patient care management, and survival analysis (Kaplan Meier estimates).
- PROSPeCT enables visualization of aggregated PSA data and computation of PSA-doubling time.
Conclusions:
- PROSPeCT is a valuable tool for prostate cancer clinicians and researchers.
- The system aids in identifying optimal patient treatments and formulating research hypotheses.
- The overarching goal is to improve the quality of life for prostate cancer patients.
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