Exploring the relation of active surveillance schedules and prostate cancer mortality

Background: Active surveillance (AS), where treatment is deferred until cancer progression is detected by a biopsy, is acknowledged as a way to reduce overtreatment in prostate cancer. However, a consensus on the frequency of taking biopsies while in AS is lacking. In former studies to optimize biopsy schedules, the delay in progression detection was taken as an evaluation indicator and believed to be associated with the long-term outcome, prostate cancer mortality. Nevertheless, this relation was never investigated in empirical data. Here, we use simulated data from a microsimulation model to fill this knowledge gap. Methods: In this study, the established MIcrosimulation SCreening Analysis model was extended with functionality to simulate the AS procedures. The biopsy sensitivity in the model was calibrated on the Canary Prostate Cancer Active Surveillance Study (PASS) data, and four (tri-yearly, bi-yearly, PASS, and yearly) AS programs were simulated. The relation between detection delay and prostate cancer mortality was investigated by Cox models. Results: The biopsy sensitivity of progression detection was found to be 50%. The Cox models show a positive relation between a longer detection delay and a higher risk of prostate cancer death. A 2-year delay resulted in a prostate cancer death risk of 2.46%–2.69% 5 years after progression detection and a 10-year risk of 5.75%–5.91%. A 4-year delay led to an approximately 8% greater 5-year risk and an approximately 25% greater 10-year risk. Conclusion: The detection delay is confirmed as a surrogate for prostate cancer mortality. A cut-off for a “safe” detection delay could not be identified.</p

Comparative effectiveness of prostate cancer screening between the ages of 55 and 69 years followed by active surveillance

BACKGROUND: Because of the recent grade C draft recommendation by the US Preventive Services Task Force (USPSTF) for prostate cancer screening between the ages of 55 and 69 years, there is a need to determine whether this could be cost-effective in a US population setting. METHODS: This study used a microsimulation model of screening and active surveillance (AS), based on data from the European Randomized Study of Screening for Prostate Cancer and the Surveillance, Epidemiology, and End Results Program, for the natural history of prostate cancer and Johns Hopkins AS cohort data to inform the probabilities of referral to treatment during AS. A cohort of 10 million men, based on US life tables, was simulated. The lifetime costs and effects of screening between the ages of 55 and 69 years with different screening frequencies and AS protocols were projected, and their cost-effectiveness was determined. RESULTS: Quadrennial screening between the ages of 55 and 69 years (55, 59, 63, and 67 years) with AS for men with low-risk cancers (ie, those with a Gleason score of 6 or lower) and yearly biopsies or triennial biopsies resulted in an incremental cost per quality-adjusted life-year (QALY) of $51,918 or$69,380, respectively. Most policies in which screening was followed by immediate treatment were dominated. In most sensitivity analyses, this study found a policy with which the cost per QALY remained below $100,000. CONCLUSIONS: Prostate-specific antigen–based prostate cancer screening in the United States between the ages of 55 and 69 years, as recommended by the USPSTF, may be cost-effective at a$100,000 threshold but only with a quadrennial screening frequency and with AS offered to all low-risk men. Cancer 2018;124:507-13

Screening for cancers with a good prognosis:The case of testicular germ cell cancer

Background: To determine, using testicular germ cell cancer screening as an example, whether screening can also be effective for cancers with a good prognosis. Methods: Based on the Dutch incidence, stage distribution, and survival and mortality data of testicular germ cell cancer, we developed a microsimulation model. This model simulates screening scenarios varying in screening age, interval, self-examination or screening by the general practitioner (GP), and screening of a defined high-risk group (cryptorchidism). For each scenario, the number of clinically and screen-detected cancers by stage, referrals, testicular germ cell cancer deaths, and life-years gained were projected. Results: Annual self-examination from age 20 to 30 years resulted in 767 cancers detected per 100,000 men followed over life-time, of which 123 (16%) by screening. In this scenario, 19.2 men died from the disease, 4.7 (20%) less than without screening, and 230 life-years were gained. Around 14,000 visits to the GP and 2080 visits to an urologist were required. This scenario resulted in the most favorable ratio between extra visits to the GP or urologist and deaths prevented (1418 and 116 respectively). Monthly screening, or screening until age 40 resulted in less favorable ratios. Self-examination by only the high-risk population prevented 1.0 death per 100,00 men in the general population. In all scenarios, 46–50 life-years were gained for each testicular germ cell cancer death prevented. Conclusion: Despite the good prognosis, self-examination at young ages for testicular germ cell cancer could be considered

Population-based mammography screening below age 50: balancing radiation-induced vs prevented breast cancer deaths

INTRODUCTION: Exposure to ionizing radiation at mammography screening may cause breast cancer. Because the radiation risk increases with lower exposure age, advancing the lower age limit may affect the balance between screening benefits and risks. The present study explores the benefit-risk ratio of screening before age 50. METHODS: The benefits of biennial mammography screening, starting at various ages between 40 and 50, and continuing up to age 74 were examined using micro-simulation. In contrast with previous studies that commonly used excess relative risk models, we assessed the radiation risks using the latest BEIR-VII excess absolute rate exposure-risk model. RESULTS: The estimated radiation risk is lower than previously assessed. At a mean glandular dose of 1.3 mGy per view that was recently measured in the Netherlands, biennial mammography screening between age 50 and 74 was predicted to induce 1.6 breast cancer deaths per 100 000 women aged 0-100 (range 1.3-6.3 extra deaths at a glandular dose of 1-5 mGy per view), against 1121 avoided deaths in this population. Advancing the lower age limit for screening to include women aged 40-74 was predicted to induce 3.7 breast cancer deaths per 100 000 women aged 0-100 (range 2.9-14.4) at biennial screening, but would also prevent 1302 deaths. CONCLUSION: The benefits of mammography screening between age 40 and 74 were predicted to outweigh the radiation risks. British Journal of Cancer (2011) 104, 1214-1220. doi: 10.1038/bjc.2011.67 www.bjcancer.com Published online 1 March 2011 (c) 2011 Cancer Research U

The role of modelling in the policy decision making process for cancer screening: example of prostate specific antigen screening

Although randomised controlled trials are the preferred basis for policy decisions on cancer screening, it remains diffcult to assess all downstream effects of screening, particularly when screening options other than those in the specifc trial design are being considered. Simulation models of the natural history of disease can play a role in quantifying harms and benefts of cancer screening scenarios. Recently, the US Preventive Services Task Force issued a C-recommendation on screening for prostate cancer for men aged 55–69 years, implying at le

Finding the optimal mammography screening strategy:A cost-effectiveness analysis of 920 modelled strategies

Breast cancer screening policies have been designed decades ago, but current screening strategies may not be optimal anymore. Next to that, screening capacity issues may restrict feasibility. This cost‐effectiveness study evaluates an extensive set of breast cancer screening strategies in the Netherlands. Using the Microsimulation Screening Analysis‐Breast (MISCAN‐Breast) model, the cost‐effectiveness of 920 breast cancer screening strategies with varying starting ages (40‐60), stopping ages (64‐84) and intervals (1‐4 years) were simulated. The number of quality adjusted life years (QALYs) gained and additional net costs (in €) per 1000 women were predicted (3.5% discounted) and incremental cost‐effectiveness ratios (ICERs) were calculated to compare screening scenarios. Sensitivity analyses were performed using different assumptions. In total, 26 strategies covering all four intervals were on the efficiency frontier. Using a willingness‐to‐pay threshold of €20 000/QALY gained, the biennial 40 to 76 screening strategy was optimal. However, this strategy resulted in more overdiagnoses and false positives, and required a high screening capacity. The current strategy in the Netherlands, biennial 50 to 74 years, was dominated. Triennial screening in the age range 44 to 71 (ICER 9364) or 44 to 74 (ICER 11144) resulted in slightly more QALYs gained and lower costs than the current Dutch strategy. Furthermore, these strategies were estimated to require a lower screening capacity. Findings were robust when varying attendance and effectiveness of treatment. In conclusion, switching from biennial to triennial screening while simultaneously lowering the starting age to 44 can increase benefits at lower costs and with a minor increase in harms compared to the current strategy

The comparative effectiveness of mpMRI and MRI-guided biopsy vs regular biopsy in a population-based PSA testing: a modeling study

The benefit of prostate cancer screening is counterbalanced by the risk of overdiagnosis and overtreatment. The use of a multi-parametric magnetic resonance imaging (mpMRI) test after a positive prostate-specific antigen (PSA) test followed by magnetic resona

To be screened or not to be screened Modeling the consequences of PSA screening for the individual

Background:Screening with prostate-specific antigen (PSA) can reduce prostate cancer mortality, but may advance diagnosis and treatment in time and lead to overdetection and overtreatment. We estimated benefits and adverse effects of PSA screening for individuals who are deciding whether or not to be screened.Methods:Using a microsimulation model, we estimated lifetime probabilities of prostate cancer diagnosis and death, overall life expectancy and expected time to diagnosis, both with and without screening. We calculated anticipated loss in quality of life due to prostate cancer diagnosis and treatment that would be acceptable to decide in favour of screening.Results:Men who were screened had a gain in life expectancy of 0.08 years but their expected time to diagnosis decreased by 1.53 life-years. Of the screened men, 0.99% gained on average 8.08 life-years and for 17.43% expected time to diagnosis decreased by 8.78 life-years. These figures imply that the anticipated loss in quality of life owing to diagnosis and treatment should not exceed 4.8%, for screening to have a positive effect on quality-adjusted life expectancy.Conclusion:The decision to be screened should depend on personal preferences. The negative impact of screening might be reduced by screening men who are more willing to accept the side effects from treatment