Modeling US Prostate Cancer Trends: PSA, Treatment & Race

Principal Investigator: Ruth Etzioni
Institution: Fred Hutchinson Cancer Research Center
Grant number: 2U01CA088160-05

Awarded under CA-05-018
Originally funded under CA-99-013 (view abstract)

Abstract: This study aims to determine the population impact of changing strategies for prostate cancer control, by linking trends in disease incidence and mortality with trends in screening and treatment.

The advent of PSA screening has transformed the way in which prostate cancer is detected and managed in the US. Today, the majority of prostate cancers in this country are screen-detected and localized. Increasing numbers of newly-diagnosed cases are being treated with hormone suppression therapy (HT), which has traditionally been reserved for advanced tumors. Cause-specific survival among prostate cancer cases has increased dramatically, but the real increase in life expectancy during the PSA era remains unclear.

How have advances in screening and treatment contributed to prostate cancer death rates that have fallen by almost 30 percent since the early 1990s? And can racial disparities in patterns of care explain why mortality declines among African Americans are, only two-thirds of those among whites? We will use surveillance modeling to address these questions, building on our previous CISNET work, which modeled PSA screening. Our methods will combine simulation models and maximum likelihood analysis to address the following Specific Aims:

  • Estimate the real improvement in life expectancy among prostate cancer cases during the PSA era;
  • Quantify the contributions to mortality declines of PSA screening and HT, and evaluate whether the benefit of screening given growing use of HT exceeds the benefit that would be expected under standard therapies;
  • (Determine whether racial differences in PSA screening and HT can account for the different mortality declines experienced by whites and African Americans; and
  • Address whether disease natural history differs according to race, by estimating lead times associated with PSA screening that are consistent with incidence trends in whites and African Americans.

Our models will require reliable estimates of trends in screening and treatment, which we will obtain using SEER-Medicare data, as well as patient claims data from a large HMO based in Northern California.

Through this work, our study promises to shed light on two of the most active controversies in prostate cancer research: the value of PSA screening versus advances in prostate cancer treatment, and the link between disparities in care and racial differences in prostate cancer outcomes.

Awarded under CA-99-013
Title: PSA Screening and U.S. Prostate Cancer Trends

Abstract: The objective of this proposal is to quantify the role of PSA screening in US prostate cancer incidence and mortality trends. Prostate cancer incidence and mortality in the US have been declining since the early 1990's. The role of PSA screening in the recent trends is a subject of intense debate. Information on the efficacy of PSA testing from controlled clinical trials is lacking, and researchers and the public are divided about how much information about the test can be gleaned from the observed trends.

To address the need for a quantitative approach to linking population PSA testing and prostate cancer trends, the first specific aim of this proposal is to develop a computer microsimulation model to project the impact of PSA screening on the US prostate cancer incidence and mortality. The model will first project population prostate cancer incidence and mortality in the absence of PSA screening. The model will then superimpose dissemination of PSA screening and the modeled population trends will be compared with those observed.

Recognizing that a major driving force behind any population effect of screening is the speed with which screening is adopted in the population, the second specific aim is to model the dissemination of PSA screening in the US. We will use the SEER-Medicare data to estimate annual PSA screening rates for older men. For younger men, we will use data from a case-control study of prostate cancer incidence that interviewed participants about their PSA screening histories. The estimates of PSA dissemination will be used as inputs to the computer model.

Early detection of prostate cancer is affected not only by the extent of screening but also by the ability of the test to identify latent cancers. This depends on the growth of PSA in prostate cancer cases which has been estimated in several studies. Since these studies yield somewhat inconsistent results, the third specific aim is to conduct meta-analysis of the data available regarding PSA growth in prostate cancer cases. The results of the meta-analysis will be used to inform the microsimulation model about PSA growth in men with prostate cancer.