A Personalized, Risk-Based Approach to Active Surveillance for Prostate Cancer with Takeaways from Broader Oncology Practices: A Mixed Methods Review
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View abstract on PubMed
Summary
This summary is machine-generated.Personalized active surveillance (AS) for prostate cancer (PCa) uses risk-based models to reduce follow-up burden for low-risk patients. These models, like PRIAS and Canary PASS, show moderate performance and can streamline monitoring compared to standard practices.
Area Of Science
- Urology
- Oncology
- Medical Informatics
Background
- Active surveillance (AS) for prostate cancer (PCa) is evolving towards personalized, risk-based approaches.
- Current AS protocols often lack individualization, potentially leading to unnecessary monitoring or missed progression.
- Lessons from AS in other cancers (thyroid, breast, kidney, bladder) may inform PCa strategies.
Purpose Of The Study
- To review the current state of personalized, risk-based AS for PCa.
- To identify and evaluate existing risk-based AS tools for PCa.
- To explore transferable lessons from AS in other cancer types.
Main Methods
- Mixed-methods review combining systematic and narrative approaches.
- Systematic search of multiple databases (Medline, Embase, etc.) adhering to PRISMA guidelines.
- Narrative review of AS in thyroid, breast, kidney, and bladder cancers.
Main Results
- Nine studies described four risk-based AS tools: PRIAS, Johns Hopkins, Canary PASS, and STRATCANS.
- Models primarily used PSA and biopsy data; MRI data was limited.
- Performance was moderate (AUC/C-index 0.58–0.85) with good calibration; some models reduced follow-up burden.
Conclusions
- Personalized, risk-based AS models can reduce follow-up burden for low-risk PCa patients while ensuring adequate monitoring for high-risk individuals.
- PCa AS is more advanced than in other solid tumors, but cross-cancer learning could refine selection and monitoring.
- Risk-based AS offers a more tailored approach to managing PCa.
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