Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data

Oncotype DX (ODX) (Genomic Health, Redwood City, CA) is a commercially available 21-gene breast cancer recurrence score assay, which has both prognostic and predictive value for estrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-)/lymph node-negative breast cancer patients [1]. The ODX recurrence score predicts benefit of adding adjuvant chemotherapy to hormonal manipulation [2]. ODX testing is currently endorsed by American Society of Clinical Oncology (ASCO), the National Comprehensive Cancer Network (NCCN), and others for routine guideline application [3, 4, 5].

ODX is costly, a factor which contributes to the test being performed in only approximately one-third of eligible breast cancer patients in the United States [6]. It is estimated that ODX is used in less than 20% of patients in European countries due to limited access and reimbursement [7]. Disparities of its use in the United States have recently been published [6, 8, 9, 10].

A few recent institution-based studies attempted to predict the results of ODX test using a limited number of respective institutions’ patients tested with ODX [11, 12, 13, 14, 15]. They correlated the results with certain histopathologic variables available from pathology reports such as immunohistochemical expressions of ER and progesterone receptor (PR), immunohistochemical expression or fluorescence in situ hybridization results for HER2, as well as tumor grade, and tumor size [11, 12, 13, 14, 15]. A majority of the models also used immunohistochemical expression of Ki-67 proliferation index in spite of its controversy in routine testing of breast cancers [16].

The objective of our study is to develop user-friendly nomograms to be used as surrogate prediction models for a high-risk or a low-risk ODX recurrence score test results. The nomogram development is based on the large breast cancer dataset from the National Cancer Data Base (NCDB), using six common and readily available clinicopathologic variables established in clinical practice as prognostic and/or predictive. These variables are: age, tumor size, tumor grade, PR status, lymph-vascular invasion (LVI), and histologic type of breast cancer (four most common types).

In multivariate logistic regression analysis, age, tumor size, tumor grade, PR status, LVI, and histologic tumor type were significantly associated with a low-risk or a high-risk ODX recurrence score test result (Online Resource tables A1 through A4). The tumor grade and PR status showed the highest odds ratios: for example, grade 1 tumor was 49.42 times more likely to be associated with a low-risk recurrence score than a grade 3 tumor (95% CI 41.37–59.03, p < .001, commercial cut-off values); negative PR was 0.052 times less likely to be associated with a low-risk recurrence score (95% CI .046–.059, p < .001; Table A1). In Appendix online only Tables A1 through A4, the results of the final logistic regression analysis of six clinicopathologic variables used for creation of the nomograms are listed including β values.

Four nomograms were developed based on these analyses in the original cohort group (n = 27,685 for commercial ODX cut-off values; n = 15,623 for TAILORx-trial ODX cut-off values; points assigned for nomograms shown in Online Resource Tables A5 and A6. There was no evidence of multicollinearity found in our model. The overall predictive accuracy of the model (c-index) measured by the ROC curve was .887 (95% CI .880–.893) for commercial ODX cut-off recurrence score values and .851 (95% CI .845–.857) for TAILORx-trial cut-off values.

Four nomograms in the external validation group were developed (n = 12,685 for commercial ODX cut-off values; n = 7454 for TAILORx-trial ODX cut-off values) and are shown in Figs. 1, 2, 3, and 4; points assigned for nomograms are shown in Online Resource Tables A5 and A6. Source code is presented in Online Resource document A1. There was no evidence of multicollinearity. The overall predictive accuracy of the model (c-index) measured by the ROC curve was .89 (95% CI .88–.90) for commercial ODX cut-off values and .852 (95% CI .842–.861) for TAILORx-trial ODX cut-off values.

Open image in new window

Open image in new window

Open image in new window

Open image in new window

It was established that from six chosen clinicopathologic variables, tumor grade and PR status had the highest significant impact on predicting a high-risk or a low-risk ODX recurrence score with either commercial cut-off values or TAILORx-trial cut-off values, followed by age, histologic tumor type and tumor size, while LVI had minimal impact (Figs. 1, 2, 3 and 4 and Online Resource Tables A5 and A6).

ODX was the most commonly utilized breast cancer genomic assay in the United States recorded by the NCDB in the time period 2010–2012: from 202,075 ER+/HER2-negative/lymph node-negative breast cancer patients, 69,415 (34%) had genomic tests performed with 97% of tests being ODX. ODX is expensive (the current estimated cost is ~$4000 [22]), a factor which contributes to the test being performed in only approximately one-third of breast cancer patients in the USA [6] and in <20% of patients in European countries [7]. Several recent institution-based studies performed on a limited number of patients have used some of the pathologic variables routinely available from pathology reports in order to predict ODX test results [11, 12, 13, 15, 23, 24, 25, 26, 27]. Some of these studies have suggested that ordering ODX test in certain cases would not significantly contribute to clinical management decisions [11, 15, 27]. However, all of these studies were performed on a limited number of patients (institution based). A couple of studies used “H-score” for ER and PR scoring system [12, 27] which is more prone to interobserver variability. Kim et al. used a different low-risk and high-risk scoring system [15] in which a low-risk recurrence score incorporated TAILORx-trial low and intermediate recurrence scores (≤25), and a high score represented TAILORx-trial high-risk recurrence score (≥26) [28]. The majority of these studies also used Ki-67 proliferation index, in spite of the lack of consensus on scoring [16], which is also recognized by the newest 8^th edition of the American Joint Commission on Cancer (AJCC), which will be in use from January 2018 [29]. Ki-67 proliferation index has only “AJCC Level of Evidence: III” in the new AJCC edition.

We have developed novel, user-friendly nomograms as a surrogate prediction model for ODX test based on the large dataset from the NCDB of ODX-tested ER +/HER2-/lymph node-negative breast cancer patients. We used age, tumor size, tumor grade, PR status, LVI, and the four most common histologic types of breast cancer for predicting ODX test results. These six clinicopathologic variables were established in clinical practice as prognostic and/or predictive and are available from any pathology report. We found that tumor grade and PR status carried the highest predictive value for a low-risk or a high-risk ODX score, which is concordant with results reported by Gage et al. [11] in 540 patients gathered from three different institutions. Finding the grade as the highest predictor for ODX score is not surprising, since the grade was recognized as a significant predictor of breast cancer prognosis many years ago by the Nottingham Prognostic Index [30, 31] as well as the surrogate of proliferation at the St. Gallen Consensus Conference in 2011 [32]. In addition, high tumor grade and the 21-gene recurrence score were found as significant predictors of distant recurrence in the founding study of ODX test reported by Paik et al. [1].

PR was also a major predictor of a high-risk or a low-risk ODX recurrence score in our study, confirming recent observation by Chaudhary et al. in which PR-negative status was associated with higher ODX scores [14]. Our study is the first to show the predictive value of histologic tumor type, age, and tumor size to predict ODX test results. Older patients were less likely to have a high-risk score; larger tumors were more likely to have a high-risk score in our study. These observations were not described in the original study of 21-multigene assay [1], or in a recently published study on optimizing the use of gene expression profiling by Kim et al. [15] perhaps due to the relatively small number of tested patients in those studies in comparison to number of patients in our study. LVI had minimal impact on prediction of ODX test results in our model.

Our nomograms can be used for predicting ODX test results with both TAILORx-trial and commercial cut-off score models. These nomograms therefore accommodate for the differences of ODX scoring results currently in use and allow the interchangeable use of our nomograms/calculators to the clinician’s preferences. We believe that these options give our study advantage over other studies which did not use both commercial and TAILORx-trial cut-off values [11, 12, 15].

ER and PR positivity in our study was established based on the ASCO/CAP guidelines as ≥1% of positive staining cells [33] (guidelines followed by NCDB registrars). ER and PR status was recorded as either positive or negative in the NCDB without associated levels of positivity. While this could be considered as a weakness of our study, we believe that it was actually a strength, since it confirmed the robustness of our prediction model even without use of additional information such as level of positive expression or the intensity of immunohistochemical staining of ER and PR. Another strength of our study is supported by the large datasets from the National Cancer Data Base. Large number of patients in both the original and the external validation cohorts (27,685 and 12,763, respectively) were used to develop nomograms which had high, acceptable C-indexes (.85–.89). This is the first study of this scale showing confidently that clinicopathologic variables can be used for prediction of low-risk or high-risk ODXRS using our nomogram models.

In the 8th edition of the American Joint Commission on Cancer (AJCC), which will be in use beginning of January 2018, hormone receptor-positive/HER2-negative and lymph node-negative breast cancer patients with a low-risk recurrence score of multigene breast cancer prognostic panels, such as ODX, Mammaprint, EndoPredict, PAM 50, and Breast Cancer Index, have been placed into the same prognostic category as T1a-T1b N0 M0 tumors, regardless of T size. This intent together with the newest 2016 ASCO clinical practice guidelines for use of biomarkers to guide clinical decisions regarding the use of adjuvant systemic therapy for women with early-stage invasive breast carcinoma has embraced the use of genomic prognostic assays as an ideal way of practicing personalized medicine for each breast cancer patient. Unfortunately, these tests are expensive and are not affordable or available for the majority of the breast cancer patients globally. Therefore, our nomograms which predict for a high-risk or a low-risk ODX recurrence score will be useful tools to assist providers in selecting patients for which further ODX testing may or may not be necessary. They also may serve as a surrogate for patients for which ODX testing is not affordable or available.