Related Experiment Videos
Effect of Implementing Population-Based Prostate-Specific Antigen Screening on Testing Rates and Prostate Cancer
Andrew J Vickers1, Veeru Kasivisvanathan2,3, Adam R Brentnall4
1Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Abstract:
We undertook a statistical modeling study to determine the effect of implementing population-based prostate-specific antigen (PSA) screening in England on overdiagnosis and PSA testing rates in comparison with the current opportunistic testing policy. Our model merged English data on life expectancy, rates of PSA testing and incidence of prostate cancer by stage with epidemiological data on lead time. In the base scenario, introduction of population-based screening led to an approximate 25% reduction in both PSA testing and overdiagnosis in the population compared with the current policy. This was due to the anticipated decrease in PSA testing and overdiagnosis in men aged 70+ years being larger than the projected increase in PSA testing and overdiagnosis in men 50-69 years. The overall incidence of early-stage prostate cancer was similar. Population-based screening was found to detect more early-stage cancers that were not overdiagnosed, and is therefore likely to have a greater impact on prostate-cancer mortality than current policy. Findings were robust in sensitivity analyses including an entirely independent modeling approach based on the UK Cluster Randomized Trial of PSA Testing for Prostate Cancer (CAP). In conclusion, opportunistic screening policies in England have led to high rates of overdiagnosis and PSA testing. A risk-adapted, population-based prostate cancer screening program would likely reduce the number of PSA tests and overdiagnoses, and increase benefits of PSA testing from reduced prostate-cancer mortality. Population health in England would be improved by adopting an organized PSA screening program and policies to reduce opportunistic PSA testing.
Related Concept Videos
Cancer Survival Analysis
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...