Estimating the Breast Cancer Burden in Germany and Implications for Risk-based Screening.

In Germany, it is currently recommended that women start mammographic breast cancer screening at age 50. However, recently updated guidelines state that for women younger than 50 and older than 70 years of age, screening decisions should be based on individual risk. International clinical guidelines recommend starting screening when a woman's 5-year risk of breast cancer exceeds 1.7%. We thus compared the performance of the current age-based screening practice with an alternative risk-adapted approach using data from a German population representative survey. We found that 10,498,000 German women ages 50-69 years are eligible for mammographic screening based on age alone. Applying the 5-year risk threshold of 1.7% to individual breast cancer risk estimated from a model that considers a woman's reproductive and personal characteristics, 39,000 German women ages 40-49 years would additionally be eligible. Among those women, the number needed to screen to detect one breast cancer case, NNS, was 282, which was close to the NNS = 292 among all 50- to 69-year-old women. In contrast, NNS = 703 for the 113,000 German women ages 50-69 years old with 5-year breast cancer risk <0.8%, the median 5-year breast cancer risk for German women ages 45-49 years, which we used as a low-risk threshold. For these low-risk women, longer screening intervals might be considered to avoid unnecessary diagnostic procedures. In conclusion, we show that risk-adapted mammographic screening could benefit German women ages 40-49 years who are at elevated breast cancer risk and reduce cost and burden among low-risk women ages 50-69 years. PREVENTION RELEVANCE: We show that a risk-based approach to mammography screening for German women can help detect breast cancer in women ages 40-49 years with increased risk and reduce screening costs and burdens for low-risk women ages 50-69 years. However, before recommending a particular implementation of a risk-based mammographic screening approach, further investigations of models and thresholds used are needed.

Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins.

Importance: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. Objective: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. Design, Setting, and Participants: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). Main Outcomes and Measures: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). Results: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model. Conclusions and Relevance: This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.

Lifestyle risk factors and residual life expectancy at age 40: a German cohort study.

BACKGROUND: Cigarette smoking, adiposity, unhealthy diet, heavy alcohol drinking and physical inactivity together are associated with about half of premature deaths in Western populations. The aim of this study was to estimate their individual and combined impacts on residual life expectancy (RLE). METHODS: Lifestyle and mortality data from the EPIC-Heidelberg cohort, comprising 22,469 German adults ≥40 years and free of diabetes, cardiovascular disease and cancer at recruitment (1994-1998), were analyzed with multivariable Gompertz proportional hazards models to predict lifetime survival probabilities given specific baseline status of lifestyle risk factors. The life table method was then used to estimate the RLEs. RESULTS: For 40-year-old adults, the most significant loss of RLE was associated with smoking (9.4 [95% confidence interval: 8.3, 10.6] years for male and 7.3 [6.0, 8.9] years for female heavy smokers [>10 cigarettes/day]; 5.3 [3.6, 7.1] years for men and 5.0 [3.2, 6.6] years for women smoking ≤10 cigarettes/day). Other lifestyle risk factors associated with major losses of RLE were low body mass index (BMI <22.5 kg/m(2), 3.5 [1.8, 5.1] years for men; 2.1 [0.5, 3.6] years for women), obesity (BMI ≥30, 3.1 [1.9, 4.4] years for men; 3.2 [1.8, 5.1] years for women), heavy alcohol drinking (>4 drinks/day, 3.1 [1.9, 4.0] years for men), and high processed/red meat consumption (≥120 g/day, 2.4 [1.0, 3.9] years for women). The obesity-associated loss of RLE was stronger in male never smokers, while the loss of RLE associated with low BMI was stronger in current smokers. The loss of RLE associated with low leisure time physical activity was moderate for women (1.1 [0.05, 2.1] years) and negligible for men (0.4 [-0.3, 1.2] years). The combined loss of RLE for heavy smoking, obesity, heavy alcohol drinking and high processed/red meat consumption, versus never smoking, optimal BMI (22.5 to 24.9), no/light alcohol drinking and low processed/red meat consumption, was 17.0 years for men and 13.9 years for women. CONCLUSIONS: Promoting healthy lifestyles, particularly no cigarette smoking and maintaining healthy body weight, should be the core component of public health approaches to reducing premature deaths in Germany and similar affluent societies.