Abstract
(1) Background: A simulation approach for prostate cancer (PrCa) with a prostate-specific antigen (PSA) test incorporating genetic information provides a new avenue for the development of personalized screening for PrCa. Going by the evidence-based principle, we use the simulation method to evaluate the effectiveness of mortality reduction resulting from PSA screening and its utilization using a personalized screening regime as opposed to a universal screening program. (2) Methods: A six-state (normal, over-detected, low-grade, and high-grade PrCa in pre-clinical phase, and low-grade and high-grade PrCa in clinical phase) Markov model with genetic and PSA information was developed after a systematic review of genetic variant studies and dose-dependent PSA studies. This gene-PSA-guided model was used for personalized risk assessment and risk stratification. A computer-based simulated randomized controlled trial was designed to estimate the reduction of mortality achieved by three different screening methods, personalized screening, universal screening, and a non-screening group. (3) Results: The effectiveness of PrCa mortality reduction for a personalized screening program compared to a non-screening group (22% (9%-33%)) was similar to that noted in the universal screening group (20% (7%-21%). However, a personalized screening program could dispense with 26% of unnecessary PSA testing, and avoid over-detection by 2%. (4) Conclusions: Gene-PSA-guided personalized screening for PrCa leads to fewer unnecessary PSA tests without compromising the benefits of mortality reduction (as happens with the universal screening program).
Original language | English |
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Article number | 641 |
Journal | Genes |
Volume | 10 |
Issue number | 9 |
DOIs | |
Publication status | Published - Sept 1 2019 |
Keywords
- Effectiveness
- Prostate cancer
- Risk stratification
- Screening
ASJC Scopus subject areas
- Genetics
- Genetics(clinical)