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Box plots showing distribution of Oncotype DX Recurrence Scores (RSs) (A) and calculated model scores (B through D): luminal A versus luminal B tumors. Abbreviation: BCPS, breast cancer prognostic score.

Box plots showing distribution of Oncotype DX Recurrence Scores (RSs) (A) and calculated model scores (B through D): luminal A versus luminal B tumors. Abbreviation: BCPS, breast cancer prognostic score.

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Context.— The Oncotype DX Recurrence Score (RS) predicts recurrence and chemotherapy benefit in early-stage estrogen receptor positive breast cancer patients. Cost and unavailability are 2 major disadvantages of the assay. Multiple models have been developed to predict the RS. Objective.— To predict RS based on histopathologic and biomarker featur...

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... Despite its important role in current clinical practice, the inaccessibility of the Oncotype DX assay, either financially or geographically, is a major obstacle in the management of many breast cancer patients worldwide. Subsequently, multiple surrogate models have been developed to predict RS using different histopathologic tumor characteristics, and high concordance rates with the actual Oncotype DX RS have been reported [26][27][28][29]. Epidemiologic studies on the clinical course of breast cancer may be hampered by the lack of available patient outcome data and by the incomplete availability of multi-gene breast cancer assays, especially in resource-poor countries. ...
... HER2 was borderline/equivocal in 6 and over expressed/amplified in 8 cases. Using our previously published criteria [29], we classified 72% of tumors as Luminal A and 28% as Luminal B. Using the cutoffs from the TAILORx trial, 27% of cases had a RS < 11 (low risk), 60% had an intermediate RS, and 13% had a RS > 25 (high risk). The mean scores for the Oncotype RS, Magee2, and BCPS across the whole cohort were 15.7, 18.4, and 15.5, respectively. ...
... We have previously shown that both models correlate well with the actual Oncotype RS. When scores were dichotomized as high v. non-high, concordance rates approached 90% [29]. We hypothesized that these models may have utility as more global surrogates of clinical breast cancer behavior compared to individual pathologic, biomarker, or clinical prognostic indicators and that they may have utility in research studies that do not have access to actual patient outcome or clinical Oncotype DX assay results. ...
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PurposeThe Oncotype DX Recurrence Score (RS) is a widely used prognostic tool for estrogen receptor-positive breast cancer patients. Multiple surrogate models can predict RS with good accuracy. In this study we aimed to determine whether the RS and two surrogate indices were differentially distributed by age, menopausal status, race, and body mass index (BMI).Methods516 breast cancer cases treated at a single institution were analyzed. Epidemiologic data, RS, tumor size, grade, and biomarker data were abstracted. Breast Cancer Prognostic Score (BCPS) and modified Magee equation 2 were used to calculate surrogate RS. Patients were stratified into different groups based on age, menopausal status, race, BMI, or a combination of strata. Mean and standard deviation were calculated for each group/subgroup.ResultsAge below median (< 63) was associated with higher RS, especially in obese and Black patients. RS was also higher in obese and Black patients in the premenopausal subgroup. Black patients had a higher RS compared to White women in the premenopausal and non-obese subgroups. BMI < 30 was associated with higher RS, especially in older, postmenopausal, and Black patients. Some of these observations were replicated by the two surrogate models. The surrogate recurrence scores were higher in the younger age group, in non-obese older/postmenopausal women, and in younger/premenopausal obese individuals.Conclusions Higher RS was observed in younger and premenopausal breast cancer patients, especially among the Black and obese subgroups, and in non-obese patients, especially among Black and older/postmenopausal women, suggesting more aggressive disease in these subgroups. Some statistical differences could be replicated by both surrogate models, suggesting that they may have utility in breast cancer epidemiology studies that do not have access to Oncotype DX RS or patient outcome data.