Comparative Analyses
Quantifying the role of prostate-specific antigen (PSA) screening in U.S. prostate cancer mortality
The value of PSA screening remains uncertain. Even before randomized clinical trials on the potential benefits of PSA screening on prostate cancer mortality began, the test was rapidly adopted in several countries including the United States. However, while there is a general consensus that PSA screening explains much of the decline in the incidence of distant prostate cancers, there is still considerable debate about its role in the observed mortality decline. Two models were used to determine the plausible contribution of PSA screening in the decline of U.S. mortality. The researchers used common estimates of PSA screening rates and assumed that, by shifting the disease from a distant to a localized/regionalized clinical stage, screening does result in a corresponding improvement in disease-specific survival and mortality. The researchers concluded that PSA screening may account for much but not all of the observed reduction in prostate cancer mortality. Other factors, such as changing treatment practices, also may have played a role in improving prostate cancer outcomes (Etzioni, Tsodikov 2008).
Prostate Cancer Mortality Rates: Results From Two CISNET Models
Results from two models: U.S. observed prostate cancer mortality rates (red) compared to estimated rates in the absence of PSA screening (green) and in the presence of the U.S. observed PSA screening patterns (blue).
Reconciling differing estimates of lead time and overdiagnosis due to PSA screening
Lead time and overdiagnosis are unobservable quantities that are key to evaluating the trade-offs between the potential benefits and harms of PSA screening. Previous studies, including two CISNET studies (Tsodikov 2006; Etzioni, Penson 2002), published mean lead time estimates that ranged from 3 to 7 years and overdiagnosis estimates that ranged from 25% to 84% of all screen-detected cases. These prior estimates were highly disparate because they were developed under differing systems of practice of PSA use (e.g., PSA cutoffs and biopsy practices), different populations, as well as different assumptions and definitions of lead time and overdiagnosis. CISNET investigators seized this opportunity to bring order to this disparate literature by developing estimates using U.S. practice patterns and a consistent set of definitions. By standardizing in this manner, three CISNET modeling groups were able to dramatically reduce the range of estimates. The two major randomized trials of prostate cancer screening (PLCO and ERSPC) use considerably different PSA cutoff scores and biopsy practices. When the results of both these trials become available, this type of systematic modeling will be necessary to reconcile inevitable differences between the two trials and assist in translating them to public health guidelines for the use of PSA screening.
The Iceberg Effect
Extent to which PSA screening reaches the reservoir of latent prostate cancer based on overdiagnosis estimates of 29%.
Explaining observed declines in prostate cancer mortality
Prostate cancer death rates have declined by more than one-third since the early 1990s. Many assume that PSA screening, which became popular in the early 1990s, is responsible for this drop in prostate cancer deaths. However, treatment for prostate cancer has also been changing. In the 1980s, radical prostatectomy increased in prominence, while, during the 1990s, hormonal therapies, previously reserved for advanced disease, were added to treatment regimens for localized tumors. This work aims to quantify the fraction of the mortality decline attributable to screening versus treatment. A previous study modeling only screening with two models showed that screening could plausibly account for 45-70% of the mortality decline. Three independently developed models of prostate cancer progression will be used in this study to determine whether treatment changes can account for the mortality decline not explained by screening, and similarly, whether screening can account for the mortality decline not explained by treatment. By isolating and quantifying the effects on mortality of treatment changes, we will be able to more clearly quantify the likely role of PSA screening, and to determine the likely benefits of PSA screening in the population setting.
