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Figure. Percentage of breast cancer mortality reduction versus number of mammographies performed per 1000 women, by model and screening strategy

Six line graphs show the percentage of mortality reduction per number of annual mammographies per women for the following models: Dana-Farber Cancer Institute, Erasmus Medical Center, Georgetown University, M.D. Anderson Cancer Center, Stanford University, and University of Wisconsin/Harvard.

The panels show an efficiency frontier graph for each model. The graph plots the average number of mammographies performed per 1000 women against the percentage of mortality reduction for each screening strategy (vs. no screening). Strategies are denoted as annual (A) or biennial (B) with starting and stopping ages. We plot efficient strategies (that is, those in which increases in use of mammography resources result in greater mortality reduction than the next least-intensive strategy) in all 6 models. We also plot "borderline" strategies (approaches that are efficient in some models but not others). The line between strategies represents the "efficiency frontier." Strategies on this line would be considered efficient because they achieve the greatest gain per use of mammography resources compared with the point (or strategy) immediately below it. Points that fall below the line are not considered as efficient as those on the line. When the slope in the efficiency frontier plot levels off, the additional reductions in mortality per unit increase in use of mammography are small relative to the previous strategies and could indicate a point at which additional investment (use of screening) might be considered as having a low return (benefit).

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