Risk stratification of ER-positive breast cancer patients: A multi-institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26.
Bradley M TurnerMary Ann Gimenez-SandersArmen SoukiazianAndrea C BreauxKristin SkinnerMichelle ShayneNyrie SoukiazianMarilyn LingDavid G HicksPublished in: Cancer medicine (2019)
The skyrocketing cost of health-care demands that we question when to use multigene assay testing in the planning of treatment for breast cancer patients. A previously published algorithmic model gave recommendations for which cases to send out for Oncotype DX® (ODX) testing. This study is a multi-institutional validation of that algorithmic model in 620 additional estrogen receptor positive breast cancer cases, with outcome data on 310 cases, named in this study as the Rochester Modified Magee algorithm (RoMMa). RoMMa correctly predicted 85% (140/164) and 100% (17/17) of cases to have a low- or high-risk ODX recurrence score, respectively, consistent with the original publication. Applying our own risk stratification criteria, in patients who received appropriate hormonal therapy, only one of the 45 (2.0%) patients classified as low risk by our original algorithm have been associated with a breast cancer recurrence over 5-10 years of follow-up. Eight of 116 (7.0%) patients classified as low risk by ODX have been associated with a breast cancer recurrence with up to 11 years of follow-up. In addition, 524 of 537 (98%) cases from our total population (n = 903) with an average modified Magee score ≤18 had an ODX recurrence score <26. Patients with an average modified Magee score ≤18 or >30 may not need to be sent out for ODX testing. By avoiding these cases sending out for ODX testing, the potential cost savings to the health-care system in 2018 are estimated to have been over $100,000,000.
Keyphrases
- end stage renal disease
- positive breast cancer
- newly diagnosed
- healthcare
- chronic kidney disease
- estrogen receptor
- peritoneal dialysis
- prognostic factors
- type diabetes
- stem cells
- systematic review
- young adults
- mesenchymal stem cells
- artificial intelligence
- social media
- big data
- patient reported outcomes
- health insurance
- patient reported
- clinical evaluation