http://repub.eur.nl/res/aut/2002/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/39092/ 2012-08-16T00:00:00Z 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.) Copyright http://repub.eur.nl/res/pub/33285/ 2011-09-27T00:00:00Z Background: The optimal interval between two consecutive mammograms is uncertain. The UK Frequency Trial did not show a significant difference in breast cancer mortality between screening every year (study group) and screening every 3 years (control group). In this study, the trial is simulated in order to gain insight into the results of the trial and to predict the effect of different screening intervals on breast cancer mortality. Methods: UK incidence, life tables and information from the trial were used in the microsimulation model MISCAN-Fadia to simulate the trial and predict the number of breast cancer deaths in each group. To be able to replicate the trial, a relatively low sensitivity had to be assumed. Results: The model simulated a larger difference in tumour size distribution between the two groups than observed and a relative risk (RR) of 0.83 of dying from breast cancer in the study group compared with the control group. The predicted RR is lower than that reported from the trial (RR 0.93), but within its 95% confidence interval (0.63-1.37). Conclusion: The present study suggests that there is benefit of shortening the screening interval, although the benefit is probably not large enough to start annual screening. http://repub.eur.nl/res/pub/33305/ 2011-09-01T00:00:00Z Objective: Digital mammography has been shown to increase the detection of ductal carcinoma. in situ (DCIS) compared to screen-film mammography. The benefits and risks of such an increase were assessed. Methods: Breast cancer detection rates were compared between 502,574 screen-film and 83,976 digital mammograms performed between 2004 and 2006 among Dutch screening participants. The detection rates were then modeled using a baseline model and two extreme models that respectively assumed a high rate of progression and no progression of preclinical DCIS to invasive cancer. With these models, breast cancer mortality and overdiagnosis were predicted. Results: The DCIS detection rate was significantly higher at digital mammography (1.2 per 1000 mammograms (95% C.I. 1.0-1.5)) than at screen-film mammography (0.7 per 1000 mammograms (95% C.I. 0.6-0.7)). Consequently, 287 (range progressive- non progressive model: 1-598) extra breast cancer deaths per 1,000,000 women (a 4.4% increase) were predicted to be prevented. An extra 401 (range: 165-2271) cancers would be overdiagnosed (a 21% increase). Conclusion: Modeling predicted that digital mammography screening would further reduce breast cancer mortality by 4.4%, at a 21% increased overdiagnosis rate. The consequences of digital screening, however, are sensitive to underlying assumptions on the natural history of DCIS. http://repub.eur.nl/res/pub/33664/ 2011-07-01T00:00:00Z 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. http://repub.eur.nl/res/pub/33760/ 2011-07-01T00:00:00Z Background. Simulation models are essential tools for estimating benefits of cancer screening programs. Such models include a screening-effect model that represents how early detection by screening followed by treatment affects disease-specific survival. Two commonly used screening-effect models are the stage-shift model, where mortality benefits are explained by the shift to more favorable stages, and the cure model, where early detection enhances the chances of cure from disease. Objective. This article describes commonly used screening-effect models and analyses their predicted mortality benefit in a model for prostate cancer screening. Method. The MISCAN simulation model was used to predict the reduction of prostate cancer mortality in the European Randomized Study of Screening for Prostate Cancer (ERSPC) Rotterdam. The screening-effect models were included in the model. For each model the predictions of prostate cancer mortality reduction were calculated. The study compared 4 screening-effect models, which are versions of the stage-shift model or the cure model. Results. The stage-shift models predicted, after a follow-up of 9 years, reductions in prostate cancer mortality varying from 38% to 63% for ERSPC-Rotterdam compared with a 27% reduction observed in the ERSPC. The cure models predicted reductions in prostate cancer mortality varying from 21% to 27%. Conclusions. The differences in predicted mortality reductions show the importance of validating models to observed trial mortality data. The stage-shift models considerably overestimated the mortality reduction. Therefore, the stage-shift models should be used with care, especially when modeling the effect of screening for cancers with long lead times, such as prostate cancer. http://repub.eur.nl/res/pub/25855/ 2011-05-01T00:00:00Z Background: Making an informed decision about treating a prostate cancer detected after a routine prostate-specific antigen (PSA) test requires knowledge about disease natural history, such as the chances that it would have been clinically diagnosed in the absence of screening and that it would metastasize or lead to death in the absence of treatment. Methods: We use three independently developed models of prostate cancer natural history to project risks of clinical progression events and disease-specific deaths for PSA-detected cases assuming they receive no primary treatment. Results: The three models project that 20%-33% of men have preclinical onset; of these 38%-50% would be clinically diagnosed and 12%-25% would die of the disease in the absence of screening and primary treatment. The risk that men age less than 60 at PSA detection with Gleason score 2-7 would be clinically diagnosed in the absence of screening is 67%-93% and would die of the disease in the absence of primary treatment is 23%-34%. For Gleason score 8 to 10 these risks are 90%-96% and 63%-83%. Conclusions: Risks of disease progression among untreated PSA-detected cases can be nontrivial, particularly for younger men and men with high Gleason scores. Model projections can be useful for informing decisions about treatment. Impact: This is the first study to project population-based natural history summaries in the absence of screening or primary treatment and risks of clinical progression events following PSA detection in the absence of primary treatment. http://repub.eur.nl/res/pub/34212/ 2011-05-01T00:00:00Z http://repub.eur.nl/res/pub/33493/ 2011-03-29T00:00:00Z 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. http://repub.eur.nl/res/pub/34254/ 2011-01-01T00:00:00Z Background: U.S. Black women have higher breast cancer mortality rates than White women despite lower incidence. The aim of this study is to investigate how much of the mortality disparity can be attributed to racial differences in natural history, uptake of mammography screening, and use of adjuvant therapy. Methods: Two simulation models use common national race, and age-specific data for incidence, screening and treatment dissemination, stage distributions, survival, and competing mortality from 1975 to 2010. Treatment effectiveness and mammography sensitivity are assumed to be the same for both races. We sequentially substituted Black parameters into the White model to identify parameters that drive the higher mortality for Black women in the current time period. Results: Both models accurately reproduced observed breast cancer incidence, stage and tumor size distributions, and breast cancer mortality for White women. The higher mortality for Black women could be attributed to differences in natural history parameters (26-44%), use of adjuvant therapy (11-19%), and uptake of mammography screening (7-8%), leaving 38% to 46% unexplained. Conclusion: Black women appear to have benefited less from cancer control advances than White women, with a greater race-related gap in the use of adjuvant therapy than screening. However, a greater portion of the disparity in mortality appears to be due to differences in natural history and undetermined factors. http://repub.eur.nl/res/pub/27479/ 2010-03-01T00:00:00Z Dissemination of prostate-specific antigen (PSA) testing in the United States coincided with an increasing incidence of prostate cancer, a shift to earlier stage disease at diagnosis, and decreasing prostate cancer mortality. We compared PSA screening performance with respect to prostate cancer detection in the US population vs in the Rotterdam section of the European Randomized Study of Screening for Prostate Cancer (ERSPC-Rotterdam). We developed a simulation model for prostate cancer and PSA screening for ERSPC-Rotterdam. This model was then adapted to the US population by replacing demography parameters with US-specific ones and the screening protocol with the frequency of PSA tests in the US population. We assumed that the natural progression of prostate cancer and the sensitivity of a PSA test followed by a biopsy were the same in the United States as in ERSPC-Rotterdam. The predicted prostate cancer incidence peak in the United States was then substantially higher than the observed prostate cancer incidence peak (13.3 vs 8.1 cases per 1000 man-years). However, the actual observed incidence was reproduced by assuming a substantially lower PSA test sensitivity in the United States than in ERSPC-Rotterdam. For example, for nonpalpable local-or regional-stage cancers (ie, stage T1M0), the estimates of PSA test sensitivity were 0.26 in the United States vs 0.94 in ERSPC-Rotterdam. We conclude that the efficacy of PSA screening in detecting prostate cancer was lower in the United States than in ERSPC-Rotterdam. http://repub.eur.nl/res/pub/24593/ 2009-12-01T00:00:00Z 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. http://repub.eur.nl/res/pub/16354/ 2009-07-31T00:00:00Z http://repub.eur.nl/res/pub/16101/ 2009-03-01T00:00:00Z Background The time by which prostate-specific antigen (PSA) screening advances prostate cancer diagnosis, called the lead time, has been reported by several studies, but results have varied widely, with mean lead times ranging from 3 to 12 years. A quantity that is closely linked with the lead time is the overdiagnosis frequency, which is the fraction of screen-detected cancers that would not have been diagnosed in the absence of screening. Reported overdiagnosis estimates have also been variable, ranging from 25% to greater than 80% of screen-detected cancers.Methods We used three independently developed mathematical models of prostate cancer progression and detection that were calibrated to incidence data from the Surveillance, Epidemiology, and End Results program to estimate lead times and the fraction of overdiagnosed cancers due to PSA screening among US men aged 54-80 years in 1985-2000. Lead times were estimated by use of three definitions. We also compared US and earlier estimates from the Rotterdam section of the European Randomized Study of Screening for Prostate Cancer (ERSPC) that were calculated by use of a microsimulation screening analysis (MISCAN) model.ResultsThe models yielded similar estimates for each definition of lead time, but estimates differed across definitions. Among screen-detected cancers that would have been diagnosed in the patients' lifetimes, the estimated mean lead time ranged from 5.4 to 6.9 years across models, and overdiagnosis ranged from 23% to 42% of all screen-detected cancers. The original MISCAN model fitted to ERSPC Rotterdam data predicted a mean lead time of 7.9 years and an overdiagnosis estimate of 66%; in the model that was calibrated to the US data, these were 6.9 years and 42%, respectively.ConclusionThe precise definition and the population used to estimate lead time and overdiagnosis can be important drivers of study results and should be clearly specified. http://repub.eur.nl/res/pub/13762/ 2008-11-08T00:00:00Z Tumour stage distribution at repeated mammography screening is, unexpectedly, often not more favourable than stage distribution at first screenings. False reassurance, i.e., delayed symptom presentation due to having participated in earlier screening rounds, might be associated with this, and unfavourably affect prognosis. To assess the role of false reassurance in mammography screening, a consecutive group of 155 breast cancer patients visiting a breast clinic in Rotterdam (The Netherlands) completed a questionnaire on screening history and self-observed breast abnormalities. The length of time between the initial discovery of breast abnormalities and first consultation of a general practitioner ("symptom-GP period") was compared between patients with ("screening group") and without a previous screening history ("control group"), using Kaplan-Meier survival curves and log-rank testing. Of the 155 patients, 84 (54%) had participated in the Dutch screening programme at least once before tumour detection; 32 (38%) of whom had noticed symptoms. They did not significantly differ from control patients (n = 42) in symptom-GP period (symptom-GP period > or = 30 days: 31.2% in the symptomatic screened group, 31.0% in the control group; p = 0.9). Only 2 out of 53 patients (3.8%) with screen-detected cancer had noticed symptoms prior to screening, reporting symptom-GP periods of 2.5 and 4 years. The median period between the first GP- and breast clinic visit was 7.0 days (95% C.I. 5.9-8.1) in symptomatic screened patients and 6.0 days (95% C.I. 4.0-8.0) in control patients. Our results show that false reassurance played, at most, only a minor role in breast cancer screening. http://repub.eur.nl/res/pub/35818/ 2007-04-01T00:00:00Z In mammography screening with double reading, different strategies can be used when the readers give discordant recommendations for referral. We investigated whether the results of the Dutch breast cancer screening programme can be optimised by replacing the standard referral strategy by consensus. Twenty-six screening radiologists independently and blinded to outcome read a test set consisting of previous screening mammograms of 250 cases (screen-detected and interval cancers) and 250 controls. Their referral recommendations were paired and, in case of discrepancy, re-read according to three referral strategies: (1) decision by one of the readers; (2) arbitration by a third reader; (3) referral if both readers agree (consensus). Data allowed studying other referral strategies, including referral if any reader suggests, as well. Double reading with referral if any reader suggests resulted in a 1.03 times higher sensitivity (76.6%) and a 1.31 times higher referral rate (1.26%) than double reading with consensus. To estimate the cost-effectiveness, the outcomes were used in a microsimulation model. Even if double reading with referral if any reader suggests results in four times as high referral rates and an accompanying increase of biopsies or other invasive procedures, the cost-effectiveness of €4,190 per life-year gained may well be in the range of acceptable cost-effectiveness for Dutch health care programmes. http://repub.eur.nl/res/pub/35575/ 2007-02-15T00:00:00Z 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. http://repub.eur.nl/res/pub/10184/ 2003-01-01T00:00:00Z BACKGROUND: Screening for prostate cancer advances the time of diagnosis (lead time) and detects cancers that would not have been diagnosed in the absence of screening (overdetection). Both consequences have considerable impact on the net benefits of screening. METHODS: We developed simulation models based on results of the Rotterdam section of the European Randomized Study of Screening for Prostate Cancer (ERSPC), which enrolled 42,376 men and in which 1498 cases of prostate cancer were identified, and on baseline prostate cancer incidence and stage distribution data. The models were used to predict mean lead times, overdetection rates, and ranges (corresponding to approximate 95% confidence intervals) associated with different screening programs. RESULTS: Mean lead times and rates of overdetection depended on a man's age at screening. For a single screening test at age 55, the estimated mean lead time was 12.3 years (range = 11.6-14.1 years) and the overdetection rate was 27% (range = 24%-37%); at age 75, the estimates were 6.0 years (range = 5.8-6.3 years) and 56% (range = 53%-61%), respectively. For a screening program with a 4-year screening interval from age 55 to 67, the estimated mean lead time was 11.2 years (range = 10.8-12.1 years), and the overdetection rate was 48% (range = 44%-55%). This screening program raised the lifetime risk of a prostate cancer diagnosis from 6.4% to 10.6%, a relative increase of 65% (range = 56%-87%). In annual screening from age 55 to 67, the estimated overdetection rate was 50% (range = 46%-57%) and the lifetime prostate cancer risk was increased by 80% (range = 69%-116%). Extending annual or quadrennial screening to the age of 75 would result in at least two cases of overdetection for every clinically relevant cancer detected. CONCLUSIONS: These model-based lead-time estimates support a prostate cancer screening interval of more than 1 year. http://repub.eur.nl/res/pub/1650/ 2000-05-25T00:00:00Z Estimators of the extreme-value index are based on a set of upper order statistics. We present an adaptive method to choose the number of order statistics involved in an optimal way, balancing variance and bias components. Recently this has been achieved for the similar but somewhat less involved case of regularly varying tails (Drees and Kaufmann(1997); Danielsson et al.(1996)). The present paper follows the line of proof of the last mentioned paper. http://repub.eur.nl/res/pub/2107/ 1997-01-01T00:00:00Z In this paper we propose a graphical method based on an artificial neural network model to investigate how and when seasonal patterns in macroeconomic time series change over time. Neural networks are useful since the hidden layer units may become activated only in certain seasons or periods, and since this activity can be stepwise or smooth. The graphical method is based on the partial contribution of the hidden layer units to the overall fit. We apply our method to quarterly Industrial Production in France and Netherlands.