STUDY OBJECTIVE: To estimate quantitatively the impact of the quality of mammographic screening (in terms of sensitivity and specificity) on the effects and costs of nationwide breast cancer screening. DESIGN: Three plausible "quality" scenarios for a biennial breast cancer screening programme for women aged 50-69 in Germany were analysed in terms of costs and effects using the Microsimulation Screening Analysis model on breast cancer screening and the natural history of breast cancer. Firstly, sensitivity and specificity in the expected situation (or "baseline" scenario) were estimated from a model based analysis of empirical data from 35,000 screening examinations in two German pilot projects. In the second "high quality" scenario, these properties were based on the more favourable diagnostic results from breast cancer screening projects and the nationwide programme in The Netherlands. Thirdly, a worst case, "low quality" hypothetical scenario with a 25% lower sensitivity than that experienced in The Netherlands was analysed. SETTING: The epidemiological and social situation in Germany in relation to mass screening for breast cancer. RESULTS: In the "baseline" scenario, an 11% reduction in breast cancer mortality was expected in the total German female population, ie 2100 breast cancer deaths would be prevented per year. It was estimated that the "high quality" scenario, based on Dutch experience, would lead to the prevention of an additional 200 deaths per year and would also cut the number of false positive biopsy results by half. The cost per life year gained varied from Deutsche mark (DM) 15,000 on the "high quality" scenario to DM 21,000 in the "low quality" setting. CONCLUSIONS: Up to 20% of the total costs of a screening programme can be spent on quality improvement in order to achieve a substantially higher reduction in mortality and reduce undesirable side effects while retaining the same cost effectiveness ratio as that estimated from the German data.
STUDY OBJECTIVE: To estimate quantitatively the impact of the quality of mammographic screening (in terms of sensitivity and specificity) on the effects and costs of nationwide breast cancer screening. DESIGN: Three plausible "quality" scenarios for a biennial breast cancer screening programme for women aged 50-69 in Germany were analysed in terms of costs and effects using the Microsimulation Screening Analysis model on breast cancer screening and the natural history of breast cancer. Firstly, sensitivity and specificity in the expected situation (or "baseline" scenario) were estimated from a model based analysis of empirical data from 35,000 screening examinations in two German pilot projects. In the second "high quality" scenario, these properties were based on the more favourable diagnostic results from breast cancer screening projects and the nationwide programme in The Netherlands. Thirdly, a worst case, "low quality" hypothetical scenario with a 25% lower sensitivity than that experienced in The Netherlands was analysed. SETTING: The epidemiological and social situation in Germany in relation to mass screening for breast cancer. RESULTS: In the "baseline" scenario, an 11% reduction in breast cancer mortality was expected in the total German female population, ie 2100 breast cancer deaths would be prevented per year. It was estimated that the "high quality" scenario, based on Dutch experience, would lead to the prevention of an additional 200 deaths per year and would also cut the number of false positive biopsy results by half. The cost per life year gained varied from Deutsche mark (DM) 15,000 on the "high quality" scenario to DM 21,000 in the "low quality" setting. CONCLUSIONS: Up to 20% of the total costs of a screening programme can be spent on quality improvement in order to achieve a substantially higher reduction in mortality and reduce undesirable side effects while retaining the same cost effectiveness ratio as that estimated from the German data.
Authors: M A Koopmanschap; K T Lubbe; G J van Oortmarssen; H M van Agt; M van Ballegooijen; J K Habbema Journal: Soc Sci Med Date: 1990 Impact factor: 4.634
Authors: G J van Oortmarssen; J D Habbema; P J van der Maas; H J de Koning; H J Collette; A L Verbeek; A T Geerts; K T Lubbe Journal: Cancer Date: 1990-10-01 Impact factor: 6.860
Authors: L Nyström; L E Rutqvist; S Wall; A Lindgren; M Lindqvist; S Rydén; I Andersson; N Bjurstam; G Fagerberg; J Frisell Journal: Lancet Date: 1993-04-17 Impact factor: 79.321
Authors: H J de Koning; B M van Ineveld; G J van Oortmarssen; J C de Haes; H J Collette; J H Hendriks; P J van der Maas Journal: Int J Cancer Date: 1991-10-21 Impact factor: 7.396
Authors: H J de Koning; B M van Ineveld; J C de Haes; G J van Oortmarssen; J G Klijn; P J van der Maas Journal: Br J Cancer Date: 1992-06 Impact factor: 7.640
Authors: Joel F Wallace; Scott R Weingarten; Chiun-Fang Chiou; James M Henning; Andriana A Hohlbauch; Margaret S Richards; Nicole S Herzog; Lior S Lewensztain; Joshua J Ofman Journal: J Gen Intern Med Date: 2002-03 Impact factor: 5.128