Artikel
Optimizing Prostate Cancer Screening for Individuals – A Decision-Analytic view on Personalized Benefit-Harm Balance
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Veröffentlicht: | 11. März 2013 |
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Background and Objective: Prostate cancer is the most frequently diagnosed male malignancy and the 3rd most frequent cause for male cancer death in Germany. Early detection and treatment is the only option to reduce prostate cancer mortality, but gains in life expectancy are opposed by losses in quality of life (QoL) due to overdiagnosis and overtreatment. Therefore, whether a man benefits from screening or not, might depend on his individual QoL preferences and risk factors. Decision-analytic models can help to better understand the individual and societal implications of screening and support decision making. We used the decision-analytic Oncotyrol Prostate Cancer Outcome & Policy Model (PCOP Model) to investigate the impact of individual QoL preferences on the benefit-harm balance of screening in order to support individual screening decisions.
Methods: The PCOP Model is a state-transition micro-simulation model that follows men from birth to death. During their lifetime, men may develop preclinical cancer, which over time progresses in stage and grade. Preclinical cancer can be detected due to clinical complaints or by screening. Once detected, cancer can be treated. Treatment can result in cure or not and may cause serious complications. In case of no cure, cancer continues to progress and eventually kills the patient, if he does not die from another cause before. Input parameters of the model were retrieved from the literature and from online databases. Using the model, we simulated and compared the clinical consequences of five different screening options – (1) no screening, (2, 3, 4) once-in-a lifetime PSA screening at age 55, 65, or 75 and (5) interval PSA screening every 4 years from age 55 to 75. Analytic endpoints were lifetime risks of clinical events, life expectancy, and quality-adjusted life expectancy. Sensitivity analysis was used to study the impact of QoL preferences.
Results: Our analyses show that the lifetime risk of prostate cancer diagnosis strongly increases with age at screening and screening intensity, which to a substantial part is due to overdiagnosis. All screening strategies save lives and gain additional lifetime. However, if quality of life is considered, we find that the gains in life expectancy can be outweighed by losses in quality of life. This is especially true, when screening is performed at old age or with high frequency.
Conclusions: Individual QoL preferences should be considered in personalized screening decisions.
Acknowledgment: This work was supported by the COMET Center ONCOTYROL, which is funded by the Austrian Federal Ministries BMVIT/BMWFJ (via FFG) and the Tiroler Zukunftsstiftung/Standortagentur Tirol (SAT)