The Story of the Magee Equations: The Ultimate in Applied Immunohistochemistry.

Magee equations (MEs) are a set of multivariable models that were developed to estimate the actual Onco type DX (ODX) recurrence score in invasive breast cancer. The equations were derived from standard histopathologic factors and semiquantitative immunohistochemical scores of routinely used biomarkers. The 3 equations use slightly different parameters but provide similar results. ME1 uses Nottingham score, tumor size, and semiquantitative results for estrogen receptor (ER), progesterone receptor, HER2, and Ki-67. ME2 is similar to ME1 but does not require Ki-67. ME3 includes only semiquantitative immunohistochemical expression levels for ER, progesterone receptor, HER2, and Ki-67. Several studies have validated the clinical usefulness of MEs in routine clinical practice. The new cut-off for ODX recurrence score, as reported in the Trial Assigning IndividuaLized Options for Treatment trial, necessitated the development of Magee Decision Algorithm (MDA). MEs, along with mitotic activity score can now be used algorithmically to safely forgo ODX testing. MDA can be used to triage cases for molecular testing and has the potential to save an estimated $300,000 per 100 clinical requests. Another potential use of MEs is in the neoadjuvant setting to appropriately select patients for chemotherapy. Both single and multi-institutional studies have shown that the rate of pathologic complete response (pCR) to neoadjuvant chemotherapy in ER+/HER2-negative patients can be predicted by ME3 scores. The estimated pCR rates are 0%, <5%, 14%, and 35 to 40% for ME3 score <18, 18 to 25, >25 to <31, and 31 or higher, respectively. This information is similar to or better than currently available molecular tests. MEs and MDA provide valuable information in a time-efficient manner and are available free of cost for anyone to use. The latter is certainly important for institutions in resource-poor settings but is also valuable for large institutions and integrated health systems.