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This variability is an indicator that the risk models provide approximate, rather than precise, estimates of breast cancer risk.
According to ACS guidelines, each of the risk models can be used for the purpose of identifying patients who would benefit from breast MRI screening (Saslow et al, 2007).
They include women with a personal history of breast cancer, carcinoma in situ, atypical hyperplasia, and extremely dense breasts on mammography.
"For the majority of women at high risk, it is critical that MRI screening be provided in addition to, not instead of, mammography, as the sensitivity and cancer yield of MRI and mammography combined is greater than for MRI alone." The guideline provides information about 3 risk assessment models available for calculating breast cancer risk (BRCAPRO, Claus model, and Tyrer-Cuzick).
Software for each model is available online (see Appendix below).
These researchers estimated summary receiver operating characteristic curves, positive predictive value (PPV), true-positive (TP) to false-positive (FP) ratio, and examined their variability according to quality criteria.
Pooled estimates of the proportion of women whose surgery was altered were calculated.