Gerrit Draisma

EFFECTS OF MAMMOGRAPHY SCREENING UNDER DIFFERENT SCREENING SCHEDULES: MODEL ESTIMATES OF POTENTIAL BENEFITS AND HARMS

To inform the USPSTF recommendations about breast cancer screening, Mandelblatt and colleagues developed 6 models of breast cancer incidence and mortality in the United States and estimated benefit...

Risk-based selection from the general population in a screening trial : Selection criteria, recruitment and power for the Dutch-Belgian randomised lung cancer multi-slice CT screening trial (NELSON)

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 = 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 = ±4,000) 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.

Quality-of-Life Effects of Prostate-Specific Antigen Screening

BACKGROUND After 11 years of follow-up, the European Randomized Study of Screening for Prostate Cancer (ERSPC) reported a 29% reduction in prostate-cancer mortality among men who underwent screening for prostate-specific antigen (PSA) levels. However, the extent to which harms to quality of life resulting from overdiagnosis and treatment counterbalance this benefit is uncertain. METHODS On the basis of ERSPC follow-up data, we used Microsimulation Screening Analysis (MISCAN) to predict the number of prostate cancers, treatments, deaths, and quality-adjusted life-years (QALYs) gained after the introduction of PSA screening. Various screening strategies, efficacies, and quality-of-life assumptions were modeled. RESULTS Per 1000 men of all ages who were followed for their entire life span, we predicted that annual screening of men between the ages of 55 and 69 years would result in nine fewer deaths from prostate cancer (28% reduction), 14 fewer men receiving palliative therapy (35% reduction), and a total of 73 life-years gained (average, 8.4 years per prostate-cancer death avoided). The number of QALYs that were gained was 56 (range, -21 to 97), a reduction of 23% from unadjusted life-years gained. To prevent one prostate-cancer death, 98 men would need to be screened and 5 cancers would need to be detected. Screening of all men between the ages of 55 and 74 would result in more life-years gained (82) but the same number of QALYs (56). CONCLUSIONS The benefit of PSA screening was diminished by loss of QALYs owing to postdiagnosis long-term effects. Longer follow-up data from both the ERSPC and quality-of-life analyses are essential before universal recommendations regarding screening can be made. (Funded by the Netherlands Organization for Health Research and Development and others.).

Interpreting Overdiagnosis Estimates in Population-based Mammography Screening

Estimates of overdiagnosis in mammography screening range from 1% to 54%. This review explains such variations using gradual implementation of mammography screening in the Netherlands as an example. Breast cancer incidence without screening was predicted with a micro-simulation model. Observed breast cancer incidence (including ductal carcinoma in situ and invasive breast cancer) was modeled and compared with predicted incidence without screening during various phases of screening program implementation. Overdiagnosis was calculated as the difference between the modeled number of breast cancers with and the predicted number of breast cancers without screening. Estimating overdiagnosis annually between 1990 and 2006 illustrated the importance of the time at which overdiagnosis is measured. Overdiagnosis was also calculated using several estimators identified from the literature. The estimated overdiagnosis rate peaked during the implementation phase of screening, at 11.4% of all predicted cancers in women aged 0–100 years in the absence of screening. At steady-state screening, in 2006, this estimate had decreased to 2.8%. When different estimators were used, the overdiagnosis rate in 2006 ranged from 3.6% (screening age or older) to 9.7% (screening age only). The authors concluded that the estimated overdiagnosis rate in 2006 could vary by a factor of 3.5 when different denominators were used. Calculations based on earlier screening program phases may overestimate overdiagnosis by a factor 4. Sufficient follow-up and agreement regarding the chosen estimator are needed to obtain reliable estimates.

Breast Cancer Screening Policies in Developing Countries: A Cost-effectiveness Analysis for India

BACKGROUND India, the largest developing country, has a steadily rising incidence of breast cancer. Estimates and comparisons of the cost-effectiveness of feasible breast cancer screening policies in developing countries and identification of the determinants of cost and efficacy are needed. METHODS A Microsimulation Screening Analysis model of breast cancer was calibrated to available data on breast cancer incidence, stage distribution, and mortality in India. The model was used to estimate the costs of screening for breast cancer in India, its effects on mortality, and its cost-effectiveness (ie, costs of screening per life-year gained or life saved). Screening using clinical breast examination (CBE) or mammography among different age groups and at various frequencies was analyzed. Costs were expressed in international dollars (Int.

Overdetection, overtreatment and costs in prostate-specific antigen screening for prostate cancer

), the currency used by the World Health Organization, which has the same purchasing power in India as the US dollar has in the United States. To determine which factors influenced cost-effectiveness, sensitivity analyses were performed. RESULTS The estimated mortality reduction was the greatest for programs targeting women between age 40 and 60 years. Using a 3% discount rate, a single CBE at age 50 had an estimated cost-effectiveness ratio of Int.

Gleason score, age and screening: Modeling dedifferentiation in prostate cancer

793 per life year gained and a breast cancer mortality reduction of 2%. The cost-effectiveness ratio increased to Int.

Recognizing changing seasonal patterns using artificial neural networks

1135 per life year gained for every-5-year CBE (age 40-60 years) and to Int.

Cost-effectiveness of opportunistic versus organised mammography screening in Switzerland

1341 for biennial CBE (age 40-60 years); the corresponding reductions in breast cancer mortality were 8.2% and 16.3%, respectively. CBE performed annually from ages 40 to 60 was predicted to be nearly as efficacious as biennial mammography screening for reducing breast cancer mortality while incurring only half the net costs. The main factors affecting cost-effectiveness were breast cancer incidence, stage distribution, and cost savings on prevented palliative care. CONCLUSION The estimated cost-effectiveness of CBE screening for breast cancer in India compares favorably with that of mammography in developed countries. However, in view of competing priorities and economic conditions, the introduction of screening in India represents a greater challenge than it has been in more developed countries.

Mammography benefit in the Canadian National Breast Screening Study-2: A model evaluation†

Background:Prostate cancer screening with prostate-specific antigen (PSA) has shown to reduce prostate cancer mortality in the European Randomised study of Screening for Prostate Cancer (ERSPC) trial. Overdetection and overtreatment are substantial unfavourable side effects with consequent healthcare costs. In this study the effects of introducing widespread PSA screening is evaluated.Methods:The MISCAN model was used to simulate prostate cancer growth and detection in a simulated cohort of 100 000 men (European standard population) over 25 years. PSA screening from age 55 to 70 or 75, with 1, 2 and 4-year-intervals is simulated. Number of diagnoses, PSA tests, biopsies, treatments, deaths and corresponding costs for 100 000 men and for United Kingdom and United States are compared.Results:Without screening 2378 men per 100 000 were predicted to be diagnosed with prostate cancer compared with 4956 men after screening at 4-year intervals. By introducing screening, the costs would increase with 100% to [euro ]60 695 000. Overdetection is related to 39% of total costs ([euro ]23 669 000). Screening until age 75 is relatively most expensive because of the costs of overtreatment.Conclusion:Introduction of PSA screening will increase total healthcare costs for prostate cancer substantially, of which the actual screening costs will be a small part.