The effects of population-based mammography screening starting between age 40 and 50 in the presence of adjuvant systemic therapy.

Adjuvant systemic therapy has been shown to be effective in reducing breast cancer mortality. The additional effect of mammography screening remains uncertain, in particular for women aged 40-49 years. We therefore assessed the effects of screening starting between age 40 and 50, as compared to the effects of adjuvant systemic therapy. The use of adjuvant endocrine therapy, chemotherapy and the combination of endocrine- and chemotherapy, as well as the uptake of mammography screening in the Netherlands was modeled using micro-simulation. The effects of screening and treatment were modeled based on randomized controlled trials. The effects of adjuvant therapy, biennial screening between age 50 and 74 in the presence of adjuvant therapy, and extending the screening programme by starting at age 40 were assessed by comparing breast cancer mortality in women aged 0-100 years in scenarios with and without these interventions. In 2008, adjuvant treatment was estimated to have reduced the breast cancer mortality rate in the simulated population by 13.9%, compared to a situation without treatment. Biennial screening between age 50 and 74 further reduced the mortality rate by 15.7%. Extending screening to age 48 would lower the mortality rate by 1.0% compared to screening from age 50; 10 additional screening rounds between age 40 and 49 would reduce this rate by 5.1%. Adjuvant systemic therapy and screening reduced breast cancer mortality in similar amounts. Expanding the lower age limit of screening would further reduce breast cancer mortality.

A note on the catch-up time method for estimating lead or sojourn time in prostate cancer screening.

Models of cancer screening assume that cancers are detectable by screening before being diagnosed clinically through symptoms. The duration of this preclinical phase is called sojourn time, and it determines how much diagnosis might be advanced in time by the screening test (lead time). In the catch-up time method, mean sojourn time or lead time are estimated as the time needed for cumulative incidence in an unscreened population to catch up with the detection rate (prevalence) at a first screening test. The method has been proposed as a substitute of the prevalence/incidence ratio in the case of prostate cancer where incidence cannot be treated as a constant. A model is proposed to justify this estimator. It is shown that this model is different from classic Markov-type models developed for breast cancer screening. In both models, the catch-up time method results in biased estimates of mean sojourn time.

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.).

Differences in natural history between breast cancers in BRCA1 and BRCA2 mutation carriers and effects of MRI screening-MRISC, MARIBS, and Canadian studies combined.

BACKGROUND: It is recommended that BRCA1/2 mutation carriers undergo breast cancer screening using MRI because of their very high cancer risk and the high sensitivity of MRI in detecting invasive cancers. Clinical observations suggest important differences in the natural history between breast cancers due to mutations in BRCA1 and BRCA2, potentially requiring different screening guidelines. METHODS: Three studies of mutation carriers using annual MRI and mammography were analyzed. Separate natural history models for BRCA1 and BRCA2 were calibrated to the results of these studies and used to predict the impact of various screening protocols on detection characteristics and mortality. RESULTS: BRCA1/2 mutation carriers (N = 1,275) participated in the studies and 124 cancers (99 invasive) were diagnosed. Cancers detected in BRCA2 mutation carriers were smaller [80% ductal carcinoma in situ (DCIS) or ≤10 mm vs. 49% for BRCA1, P < 0.001]. Below the age of 40, one (invasive) cancer of the 25 screen-detected cancers in BRCA1 mutation carriers was detected by mammography alone, compared with seven (three invasive) of 11 screen-detected cancers in BRCA2 (P < 0.0001). In the model, the preclinical period during which cancer is screen-detectable was 1 to 4 years for BRCA1 and 2 to 7 years for BRCA2. The model predicted breast cancer mortality reductions of 42% to 47% for mammography, 48% to 61% for MRI, and 50% to 62% for combined screening. CONCLUSIONS: Our studies suggest substantial mortality benefits in using MRI to screen BRCA1/2 mutation carriers aged 25 to 60 years but show important clinical differences in natural history. IMPACT: BRCA1 and BRCA2 mutation carriers may benefit from different screening protocols, for example, below the age of 40.

The prostate cancer conundrum revisited: treatment changes and prostate cancer mortality declines.

BACKGROUND: Prostate cancer mortality rates in the United States declined by >40% between 1991 and 2005. The impact of changes in primary treatment and adjuvant and neoadjuvant hormone therapy on this decline is unknown. METHODS: The authors applied 3 independently developed models of prostate cancer natural history and disease detection under common assumptions about treatment patterns, treatment efficacy, and survival in the population. Primary treatment patterns were derived from the Surveillance, Epidemiology, and End Results registry; data on the frequency of hormone therapy were obtained from the CaPSURE (Cancer of the Prostate Strategic Urologic Research Endeavor) database; and treatment efficacy was based on estimates from randomized trials and comparative effectiveness studies of treatment alternatives. The models projected prostate cancer mortality without prostate-specific antigen screening and in the presence and absence of treatment benefit. The impact of primary treatment was expressed as a fraction of the difference between observed mortality and projected mortality in the absence of treatment benefit. RESULTS: The 3 models projected that changes in treatment explained 22% to 33% of the mortality decline by 2005. These contributions were accounted for mostly by surgery and radiation therapy, which increased in frequency until the 1990s, whereas hormone therapies contributed little to the mortality decline by 2005. Assuming that treatment benefit was less for older men, changes in treatment explained only 16% to 23% of the mortality decline by 2005. CONCLUSIONS: Changes in primary treatment explained a minority of the observed decline in prostate cancer mortality. The remainder of the decline probably was because of other interventions, such as prostate-specific antigen screening and advances in the treatment of recurrent and progressive disease.

Digital mammography screening: weighing reduced mortality against increased overdiagnosis.

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.

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.

What if I don't treat my PSA-detected prostate cancer? Answers from three natural history models.

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.

How does early detection by screening affect disease progression? Modeling estimated benefits in prostate cancer screening.

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.

Race-specific impact of natural history, mammography screening, and adjuvant treatment on breast cancer mortality rates in the United States.

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. IMPACT: Breast cancer mortality may be reduced substantially by ensuring that Black women receive equal adjuvant treatment and screening as White women. More research on racial variation in breast cancer biology and treatment utilization is needed.

Prostate-specific antigen screening in the United States vs in the European Randomized Study of Screening for Prostate Cancer-Rotterdam.

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.

Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms.

BACKGROUND: Despite trials of mammography and widespread use, optimal screening policy is controversial. OBJECTIVE: To evaluate U.S. breast cancer screening strategies. DESIGN: 6 models using common data elements. DATA SOURCES: National data on age-specific incidence, competing mortality, mammography characteristics, and treatment effects. TARGET POPULATION: A contemporary population cohort. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. INTERVENTIONS: 20 screening strategies with varying initiation and cessation ages applied annually or biennially. OUTCOME MEASURES: Number of mammograms, reduction in deaths from breast cancer or life-years gained (vs. no screening), false-positive results, unnecessary biopsies, and overdiagnosis. RESULTS OF BASE-CASE ANALYSIS: The 6 models produced consistent rankings of screening strategies. Screening biennially maintained an average of 81% (range across strategies and models, 67% to 99%) of the benefit of annual screening with almost half the number of false-positive results. Screening biennially from ages 50 to 69 years achieved a median 16.5% (range, 15% to 23%) reduction in breast cancer deaths versus no screening. Initiating biennial screening at age 40 years (vs. 50 years) reduced mortality by an additional 3% (range, 1% to 6%), consumed more resources, and yielded more false-positive results. Biennial screening after age 69 years yielded some additional mortality reduction in all models, but overdiagnosis increased most substantially at older ages. RESULTS OF SENSITIVITY ANALYSIS: Varying test sensitivity or treatment patterns did not change conclusions. LIMITATION: Results do not include morbidity from false-positive results, patient knowledge of earlier diagnosis, or 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. PRIMARY FUNDING SOURCE: National Cancer Institute.

Lead time and overdiagnosis in prostate-specific antigen screening: importance of methods and context.

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. RESULTS: The 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. CONCLUSION: 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.

Cost-effectiveness of opportunistic versus organised mammography screening in Switzerland.

BACKGROUND: Various centralised mammography screening programmes have shown to reduce breast cancer mortality at reasonable costs. However, mammography screening is not necessarily cost-effective in every situation. Opportunistic screening, the predominant screening modality in several European countries, may under certain circumstances be a cost-effective alternative. In this study, we compared the cost-effectiveness of both screening modalities in Switzerland. METHODS: Using micro-simulation modelling, we predicted the effects and costs of biennial mammography screening for 50-69 years old women between 1999 and 2020, in the Swiss female population aged 30-70 in 1999. A sensitivity analysis on the test sensitivity of opportunistic screening was performed. RESULTS: Organised mammography screening with an 80% participation rate yielded a breast cancer mortality reduction of 13%. Twenty years after the start of screening, the predicted annual breast cancer mortality was 25% lower than in a situation without screening. The 3% discounted cost-effectiveness ratio of organised mammography screening was euro11,512 per life year gained. Opportunistic screening with a similar participation rate was comparably effective, but at twice the costs: euro22,671-24,707 per life year gained. This was mainly related to the high costs of opportunistic mammography and frequent use of imaging diagnostics in combination with an opportunistic mammogram. CONCLUSION: Although data on the performance of opportunistic screening are limited, both opportunistic and organised mammography screening seem effective in reducing breast cancer mortality in Switzerland. However, for opportunistic screening to become equally cost-effective as organised screening, costs and use of additional diagnostics should be reduced.

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.$), 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.$793 per life year gained and a breast cancer mortality reduction of 2%. The cost-effectiveness ratio increased to Int.$1135 per life year gained for every-5-year CBE (age 40-60 years) and to Int.$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.

Breast cancer screening: evidence for false reassurance?

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.

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 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.

Gleason score, age and screening: modeling dedifferentiation in prostate cancer.

Tumor differentiation as measured by the Gleason score is highly predictive of the course of prostatic cancer after diagnosis. Since the introduction of the prostate-specific antigen (PSA) test tumors are diagnosed with a favorable tumor stage and differentiation grade. Does screening with PSA just detect more tumors with favorable characteristics or is dedifferentiation actually being prevented by early detection and consequent treatment? The latter option implies that tumors dedifferentiate in the preclinical screen-detectable phase. To model the natural history of prostate cancer, we analyzed the age-specific distribution of clinical stage and Gleason score of 2,204 tumors diagnosed in the ERSPC-Rotterdam trial. We fitted 2 MISCAN simulation models to the observed data: Model I where tumors dedifferentiate before becoming screen-detectable and Model II where dedifferentiation occurs during the screen-detectable preclinical phase. The hypothesis of dedifferentiation during the screen-detectable phase was tested by a goodness of fit test of both models. In ERSPC-Rotterdam, we observed a significantly more favorable distribution of Gleason scores in screen-detected cancers compared to cancers found in the control arm, and in cancers detected in the second round compared to cancers detected in the first round of screening. Also, a significant association between Gleason score and age at diagnosis was found, most notably in cancers detected in the first round of screening. These findings were reproduced by Model II and less so by Model I, with a significant difference in goodness of fit between the 2 models (p < 0.001). This study provides epidemiological evidence of dedifferentiation as a major mechanism of progression in prostate cancer. Tumors dedifferentiate during the screen-detectable phase and consequently screening with PSA and early treatment can possibly prevent dedifferentiation.

Overdiagnosis and overtreatment of breast cancer: microsimulation modelling estimates based on observed screen and clinical data.

There is a delicate balance between the favourable and unfavourable side-effects of screening in general. Overdiagnosis, the detection of breast cancers by screening that would otherwise never have been clinically diagnosed but are now consequently treated, is such an unfavourable side effect. To correctly model the natural history of breast cancer, one has to estimate mean durations of the different pre-clinical phases, transition probabilities to clinical cancer stages, and sensitivity of the applied test based on observed screen and clinical data. The Dutch data clearly show an increase in screen-detected cases in the 50 to 74 year old age group since the introduction of screening, and a decline in incidence around age 80 years. We had estimated that 3% of total incidence would otherwise not have been diagnosed clinically. This magnitude is no reason not to offer screening for women aged 50 to 74 years. The increases in ductal carcinoma in situ (DCIS) are primarily due to mammography screening, but DCIS still remains a relatively small proportion of the total breast cancer problem.

Seventy-five years is an appropriate upper age limit for population-based mammography screening.

In this study, we assessed the results of the Dutch breast cancer screening programme for women aged 70-75, and discussed the current upper age limit of the women invited. We compared the main outcome parameters of the screening programme 1998-2000 for women aged 70-75, with those in women aged 50-69. Breast cancer detection rates were also compared with prediction from 2 variants of a simulation model of breast cancer screening, assuming the mean sojourn time, i.e., the duration of the preclinical detectable phase, to increase or not with age above the age of 65. The underlying idea is that an increase of the sojourn time with age will lead to a less favourable balance between screening benefits and harms from a certain age on. Of the 315,103 women (aged 70-75) invited, 65.6% participated. The attendance increased from 1998 to 2000. For women aged 74 and 75 years, this increase was almost 10%. As a result of the 187,207 screening examinations performed within this age group, 18.3 per 1,000 women were referred and 10.3 per 1,000 breast cancer were diagnosed. Detection rates in both initial and subsequent screens increased steadily with age and got close to those model-simulated rates, which assume a continuously increasing sojourn time with age. A major finding of this study is that the screening participation among elderly women is high. The outcomes of our study suggest a steadily increasing sojourn time of breast tumours beyond the age of 69, leading to a strong increase in detection of cancers, and therefore, disfavouring the balance with the benefits of screening. At present, 75 years of age can be regarded as an appropriate upper age limit for the Dutch programme.