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According to our baseline estimate, there are 0.6 fewer deaths annually from breast cancer among women ages 40 to 64 years for every 1000 women screened under the NBCCEDP. However, we were unable to detect an effect of screening on mortality rates ��2 years in the future. To the best of our knowledge, this is the first study estimating the direct impact of the NBCCEDP on patient outcomes. Previously, Adams et al10 reported that implementation of the Breast and Cervical Cancer Prevention and Treatment Act reduced the time from diagnosis to enrollment in Medicaid by approximately 7 months. Given the low rate of breast cancer mortality among nonelderly women and the size of the NBCCED��both in relation to the entire population of women in http://www.selleckchem.com/products/ly2109761.html the target age group and in relation to the number of eligible women7��detecting an effect (assuming there is one) is difficult. The variation in within-state http://www.selleck.cn/products/Staurosporine.html trends in breast cancer mortality rates explained by the NBCCEDP is small in relation to the total variation. We also note that our estimates reflect the mix of never-screened and previously screened women among NBCCEDP participants. According to the National Health Interview Survey, 42% of women with no health insurance and family incomes http://www.selleckchem.com/products/epz-5676.html reflect a causal relation. First, is there a plausible mechanism behind the effect? There are 2 pathways by which the NBCCEDP might reduce breast cancer mortality rates. First, screening permits the detection of early stage tumors that, in the absence of early intervention, would have developed into metastatic disease. Second, the NBCCEDP facilitates access to treatment among women who are diagnosed with breast cancer. Even in patients for whom treatment does not lead ultimately to a cure, it may delay tumor progression. Second, are there omitted (ie, confounding) variables? Our models for estimating the impact of the NBCCEDP implicitly control for time-invariant factors that differ across states and years. In this context, a variable would confound the observed relation if it was changing over time in a way that is correlated with both year-to-year changes in NBCCEDP screening rates and breast cancer mortality rates within states. It is difficult to think of a variable that fits this profile. We cannot test directly the assumption of unconfoundedness (ie, the absence of variables that we do not control for but are related to both changes in screening rates and changes in breast cancer mortality rates within states). Instead, we performed falsification tests. The results from models in which we measured the impact of the NBCCEDP based on the proportion of women screened were consistent with the assumption of unconfoundedness.