Appendix Figure 1. Life Years Gained vs. Number of Mammography Screens per Woman by Model and Screening Strategy.

The panels in this figure show an efficiency frontier graph for each model. The graph plots the average number of mammograms performed per women against the percent mortality reduction for each screening strategy (vs. no screening). We plot efficient strategies (i.e., those where increases in use of mammography resources result in greater mortality reduction than the next least intensive strategy) in all six models. We also plot “borderline” strategies (approaches that are efficient in some models but not in others). The line between strategies that is drawn represents the “efficiency frontier”. Strategies on this line would be considered efficient in that they achieve the greatest gain per use of mammography resources compared to 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 prior strategies and could indicate a point at which additional investment (use of screening) might be considered as having a low return (benefit).

To highlight efficient strategies that decision makers might want to consider, we have color coded the strategies that might be considered most efficient overall across the models. We also highlight one common current approach (annual screening 40–79), although it is below the efficiency frontier in most models.

Blue represents biennial screening from age 50–69

Green represents biennial screening from age 50–74

Pink represents biennial screening from age 50 to 79

Red represents annual screening from age 40 to 79

Model Group Abbreviations: D (Dana Farber Cancer Center), E (Erasmus Medical Center), G (Georgetown U.), M (M.D. Anderson Cancer Center), S (Stanford U.), W (U. of Wisconsin/Harvard)