These model-based lead-time estimates support a prostate cancer screening interval of more than 1 year.

The precise definition and the population used to estimate lead time and overdiagnosis can be important drivers of study results and should be clearly specified.

Background Despite trials of mammography and widespread use, optimal screening policy is controversial. Design and Objective Six models use common data elements to evaluate US screening strategies. Data Sources The models use national data on age-specific incidence, competing mortality, mammography characteristics and treatment effects. Target Population and Time Horizon A contemporary population cohort followed over their lifetimes. Perspective We use a societal perspective for analysis. Interventions We evaluate 20 screening strategies with varying initiation and cessation ages applied annually or biennially. Outcome Measures Number of mammograms, breast cancer mortality reduction or life years gained [LYG] (vs. no screening), false positives, unnecessary biopsies and over-diagnosis. Results of Base Case The 6 models produce consistent rankings of screening strategies. Screening biennially maintains an average of 81% (range across strategies and models 67–99%) of the benefit of annual screening with almost half the number of false positives. Screening biennially from ages 50 to 69 achieves a median 16.5% (range 15%–23%) breast cancer mortality reduction vs. no screening. Initiating biennial screening at age 40 (vs. 50) reduces mortality by an additional 3% (range 1%–6%), consumes more resources and yields more false positives. Biennial screening after age 69 yields some additional mortality reduction in all models but over-diagnosis increases most substantially at older ages. Sensitivity Analysis Results Varying test sensitivity or treatment patterns do not change conclusions. Limitations Results do not include morbidity from false positives, knowledge of earlier diagnosis or under-going unnecessary treatment. Conclusion Biennial screening achieves most of the benefit of annual screening with less harm. Decisions about the best strategy depend on program and individual objectives and the weight placed on benefits, harms and resource considerations.

Background The European Randomized Study of Screening for Prostate Cancer (ERSPC) reported a 29% prostate cancer mortality reduction among screened men after 11 years. However, it is uncertain to what extent harms from overdiagnosis and treatment on quality of life counterbalance this benefit. Methods Based on ERSPC follow-up data, we used micro-simulation modeling (MISCAN) to predict the number of prostate cancers, treatments, deaths and quality-adjusted life-years (QALYs) gained following the introduction of screening. Various screening strategies, efficacies, and quality of life assumptions were modeled. Results Per 1,000 men of all ages followed for their entire lifespan we predicted for annual screening from age 55–69 years: 9 fewer deaths due to prostate cancer (28% reduction), 14 fewer men receiving palliative therapy (35% reduction), and 73 life-years gained (average 8.4 years per prostate cancer death avoided). QALYs gained were 56 (range: −21, 97), a reduction of 23% from unadjusted life-years gained. The number needed to screen (NNS) was 98 and number needed to detect (NND) 5. Also inviting men aged 70–74 resulted in more life-years (82) but similar QALYs (56). Conclusions Although NNS and NND are more favorable than previously calculated, the benefit of PSA screening is diminished by loss of QALYs, that is dependent primarily on post-diagnosis long-term effects. Longer follow-up data from both the ERSPC and quality of life are essential before making universal recommendations regarding screening.

A method to obtain the optimal selection criteria, taking into account available resources and capacity and the impact on power, is presented for the Dutch-Belgian randomised lung cancer screening trial (NELSON). NELSON investigates whether 16-detector multi-slice computed tomography screening will decrease lung cancer mortality compared to no screening. A questionnaire was sent to 335,441 (mainly) men, aged 50-75. Smoking exposure (years smoked, cigarettes/day, years quit) was determined, and expected lung cancer mortality was estimated for different selection scenarios for the 106,931 respondents, using lung cancer mortality data by level of smoking exposure (US Cancer Prevention Study I and II). Selection criteria were chosen so that the required response among eligible subjects to reach sufficient sample size was minimised and the required sample size was within our capacity. Inviting current and former smokers (quit 10 years ago) who smoked >15 cigarettes/day during >25 years or >10 cigarettes/day during >30 years was most optimal. With a power of 80%, 17,300-27,900 participants are needed to show a 20-25% lung cancer mortality reduction 10 years after randomisation. Until October 18, 2005 11,103 (first recruitment round) and 4,325 (second recruitment round) (total 5 15,428) participants have been randomised. Selecting participants for lung cancer screening trials based on risk estimates is feasible and helpful to minimize sample size and costs. When pooling with Danish trial data (n 5 64,000) NELSON is the only trial without screening in controls that is expected to have 80% power to show a lung cancer mortality reduction of at least 25% 10 years after randomisation. ' 2006 Wiley-Liss, Inc.Key words: lung cancer; screening; computed tomography; power; risk estimation Lung cancer is the most common cause of cancer-related death in men and the second most common cause of cancer-related death in women in Europe. 1 Because lung cancer is often in an advanced stage at the time of diagnosis, 5-year-survival is only 15% or less. 2 Japanese studies and the US Early Lung Cancer Action Project (ELCAP) showed that in a high-risk population more lung cancers can be detected by spiral computed tomography (CT) screening than by chest X-ray screening. 3,4 These and other observational studies with spiral CT screening showed that 55-85% of CTdetected lung cancers at baseline screening in a high-risk population of current and former smokers are at a surgically removable stage (stage I). 5 Although these results seem promising, observational studies are prone to lead-time, length-time and overdiagnosis bias. Only in a randomised design, disease-specific mortality between the screened and the unscreened population, instead of survival, can be compared. Lead-time, length-time and overdiagnosis do not bias the analysis in such comparisons. 6 Therefore, in the United States the National Lung Screening Trial (NLST) was launched in 2002 7 and in the Netherlands and Belgium, the NEL-SON trial, a Dutch acronym for ÔDutch-Belgian lu...