[Population-based breast cancer screening is not worthwhile. Screening has little effect on mortality]. / Bevolkingsonderzoek naar borstkanker loont niet. Screening heeft nauwelijks invloed op sterfte.

Comparison of breast cancer mortality between pairs of similar countries (Sweden and Norway, Northern Ireland and the Irish Republic, the Netherlands and Belgium or Flanders), each of which had implemented its population-wide breast cancer screening programme at a different point in time, demonstrated little effect of screening on mortality. In the Netherlands, a well-organised population-wide screening programme was started in the early nineties, ten years before such a programme was introduced in Flanders. We used the 1989-1992 period as a baseline and compared breast cancer mortality in the Netherlands with that in Flanders during the 2005-2008 period. The added value of organised screening was low: 11% in the target age group of 55-79 years, or 180 prevented breast-cancer deaths annually. A total of 5000 screening mammograms were needed to prevent one death from breast cancer. Breast cancer screening is not a public health priority. Impartial and transparent information on the disadvantages and benefits of breast cancer screening is urgently needed.

Mortality in 272 European regions, 2002-2004. An update.

This paper presents a comprehensive update of life expectancy and mortality in 2002-2004 in the modern European Union (EU-27) and EFTA countries. We focus on causes of death at younger ages (0-64 year). EUROSTAT delivered updated population numbers and mortality data by sex, age and cause of death for 272 NUTS-2 regions. We compared mortality by life tables, cause decomposition life tables and age standardized rates. Gini coefficients estimated inequity of death rates over the regions. Life expectancy at birth in the EU-27 was 75.1 years (men) and 81.3 years (women). The difference between the 10th and 90th percentile of 272 regions was 8.0 (men) and 5.6 years (women). Men lived 6.1 years shorter in the new member states (NMS, new members since 2004) than in the EU-15 (members before 2004), women 3.9 years. 60% (men) and 33% (women) of the differences in life expectancy between EU 15 and NMS were explained by mortality under age 65. The main causes explaining differences in life expectancy were ischemic and other heart disease, stroke, alcohol related mortality, lung cancer and injuries. The fraction of ill defined causes of death was large and very variable between countries. Mortality differences in the EU-27 are dominated by smoking, alcohol, diseases related to diet and a sedentary lifestyle, unsafe roads and differences in health care performance. Closing the health gap is feasible and ought to be a major target of the European Union, but monitoring will need better registration of causes of death.

Smoking kills, obesity disables: a multistate approach of the US Health and Retirement Survey.

Increasing BMI causes concerns about the consequences for health care. Decreasing cardiovascular mortality has lowered obesity-related mortality, extending duration of disability. We hypothesized increased duration of disability among overweight and obese individuals. We estimated age-, risk-, and state-dependent probabilities of activities of daily living (ADL) disability and death and calculated multistate life tables, resulting in the comprehensive measure of life years with and without ADL disability. We used prospective data of 16,176 white adults of the Health and Retirement Survey (HRS). Exposures were self-reported BMI and for comparison smoking status and levels of education. Outcomes were years to live with and without ADL disability at age 55. The reference categories were high normal weight (BMI: 23-24.9), nonsmoking and high education. Mild obesity (BMI: 30-34.9) did not change total life expectancy (LE) but exchanged disabled for disability-free years. Mild obesity decreased disability-free LE with 2.7 (95% confidence limits 1.2; 3.2) year but increased LE with disability with 2.0 (0.6; 3.4) years among men. Among women, BMI of 30 to 34.9 decreased disability-free LE with 3.6 (2.1; 5.1) year but increased LE with disability with 3.2 (1.6;4.8) years. Overweight (BMI: 25-29.9) increases LE with disability for women only, by 2.1 (0.8; 3.3) years). Smoking compressed disability by high mortality. Smoking decreased LE with 7.2 years, and LE with disability with 1.3 (0.5; 2.5) years (men) and 1.4 (0.3; 2.6) years (women). A lower education decreased disability-free life, but not duration of ADL disability. In the aging baby boom, higher BMI will further increase care dependence.

Evidence-based guidelines, time-based health outcomes, and the Matthew effect.

BACKGROUND: Cardiovascular risk management guidelines are 'risk based'; health economists' practice is 'time based'. The 'medical' risk-based allocation model maximises numbers of deaths prevented by targeting subjects at high risk, for example, elderly and smokers. The time-based model maximises numbers of life years gained by treating the young and non-smokers, or 'the one who has will be given more' (Matthew 25:29). We explored practical consequences of risk- or time-based allocation. METHODS: We used epidemiological modelling to generate semi-quantitative scenarios comparing the distributional effects of allocating a fixed number of prescriptions of a (hypothetical) preventive cardiovascular drug ('CVStop') either to avert the maximum number of deaths (risk-based) or to save the maximum number of life years (time based) in the male Dutch population. We subsequently asked 123 Dutch guideline developers which distribution they preferred. RESULTS: Time- and risk-based allocations resulted in different distributions of the drug across the population. There were also differences in absolute numbers of life years gained and deaths averted, and in the distribution of these across the population. For example, risk-based allocation of 'CVStop' resulted in preferential treatment of elderly, leading to more deaths averted (mostly among 70 and above) but fewer life years gained, if compared with time-based allocation. The guideline developers experienced the choice dilemmas as difficult. No priority choice was dominant among the respondents. CONCLUSION: In evidence-based resource allocation the choice to save time or to avert deaths may introduce moral choices because of the various origins of increased disease risk. Evidence-based guideline development inevitably has moral implications.