Related Experiment Video
Updated: Feb 7, 2026
An Orthotopic Murine Model of Human Prostate Cancer Metastasis
Published on: September 18, 2013
Effect of implementing population-based prostate-specific antigen screening on testing rates and prostate cancer
Andrew J Vickers1, Adam Brentnall2
1Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, USA.
Objective:
To determine the potential effect of implementing population-based prostate-specific antigen (PSA) screening in England on overdiagnosis and testing rates compared with the current opportunistic testing policy.
Design:
Statistical modeling study. English data on rates of prostate cancer by stage, symptomatic and asymptomatic PSA testing, and life expectancy were merged with epidemiological assumptions on lead time to evaluate plausible overdiagnosis and PSA testing rates from an organized population-based program, in comparison with the current opportunistic policy. In the base-case scenario, organized screening increased the rate of asymptomatic PSA testing (screening) in men aged 50 - 69 year and decreased PSA testing in older men. An alternative modeling approach estimated change in overdiagnosis using data from the CAP trial, and current asymptomatic cancer detection rates.
Setting:
England, 2018/19.
Participants:
Adult men.
Main Outcome Measures:
Rates of PSA testing, early-stage prostate cancer incidence, and overdiagnosis (prostate cancer that would not be diagnosed in a man's lifetime but for the PSA test).
Results:
In the base scenario, introduction of population-based screening led to an approximate 25% reduction in both PSA testing and overdiagnosis rates in the target 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 cancer prostate cancer was similar. Population-based screening was found to detect more early-stage cancers that were not overdiagnosed, and therefore likely to have a greater impact on prostate-cancer morbidity and mortality than current policy. Findings were robust in sensitivity analyses including an entirely separate modeling approach.
Conclusion:
Opportunistic screening policies in England have led to high rates of overdiagnosis and PSA testing. In comparison with current policy, 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 could be improved by either adopting an organized program or by prohibiting PSA testing of asymptomatic men in primary care.
Related Concept Videos
01:16Statistical Hypothesis Testing
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
01:11Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
01:15Study Design in Statistics
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
01:24Testing 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...
01:21Testing a Claim about Mean: Unknown Population SD
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
02:43Mouse Models of Cancer Study
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...