To be screened or not to be screened? Modeling the consequences of PSA screening for the individual

Abstract

Background: Screening with prostate-specific antigen (PSA) can reduce prostate cancer mortality, but may advance diagnosis and treatment in time and lead to overdetection and overtreatment. We estimated benefits and adverse effects of PSA screening for individuals who are deciding whether or not to be screened.

Methods: Using a microsimulation model, we estimated lifetime probabilities of prostate cancer diagnosis and death, overall life expectancy and expected time to diagnosis, both with and without screening. We calculated anticipated loss in quality of life due to prostate cancer diagnosis and treatment that would be acceptable to decide in favour of screening.

Results: Men who were screened had a gain in life expectancy of 0.08 years but their expected time to diagnosis decreased by 1.53 life-years. Of the screened men, 0.99% gained on average 8.08 life-years and for 17.43% expected time to diagnosis decreased by 8.78 life-years. These figures imply that the anticipated loss in quality of life owing to diagnosis and treatment should not exceed 4.8%, for screening to have a positive effect on quality-adjusted life expectancy.

Conclusion: The decision to be screened should depend on personal preferences. The negative impact of screening might be reduced by screening men who are more willing to accept the side effects from treatment.

Figure 1

Harms and benefits in prostate cancer screening. Time 0 is the time of deciding to participate or not in screening. Utility or quality of life has value 1 until the moment of a prostate cancer diagnosis (Dx); the remaining lifetime until death (Dth) has utility u<1. The figure shows hypothetical utility curves for a person without (solid) and with screening (dashes). Screening may detect prostate cancer earlier (at time (Dx’) and possibly postpone the moment of death (to time Dth’). Area I represents the gain in quality-adjusted life-years and area II the loss in quality of life due to earlier detection. The level u depends on the consequences of diagnosis and treatment. If the expected gain in quality-adjusted life-years (area I) equals the expected loss of quality of life due to earlier diagnosis (area II), the decision to participate in screening or not does not affect expected quality-adjusted life-years. The utility break-even point is the utility level corresponding to that situation.

Figure 2

Survival curves with follow-up time from the time of decision. These stacked figures show the proportion of men who are alive without diagnosed prostate cancer (white area), alive with diagnosed prostate cancer (light grey area), dead from prostate cancer (dark grey area) and dead from other causes (black area) at various points in time.