A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

Abstract

Background The 21-gene recurrence score (RS) testing can predict the prognosis for luminal breast cancer patients. Meanwhile, patients > 50 years with RS > 25 have improved survival with adjuvant chemotherapy. The current study aimed to develop a nomogram with routine parameters to predict RS. Methods We included patients diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative who underwent the 21-gene RS testing and aged > 50 years. The primary outcome was high-risk RS (> 25). Univariate and multivariate analyses were performed to identify significant predictors. A predictive nomogram based on logistic model was developed and evaluated with receiver operating characteristic (ROC) curves. The nomogram was internally validated for discrimination and calibration with bootstrapping method, and externally validated in another cohort. We then assessed the nomogram in different subgroups of patients and compared it with several published models. Results A total of 1100 patients were included. Five clinicopathological parameters were used as predictors of a high-risk RS, including tumor grade, histologic subtype, ER expression, PR expression, and Ki-67 index. The area under the curve (AUC) was 0.798 (95% CI 0.772–0.825) and optimism adjusted AUC was 0.794 (95% CI 0.781–0.822). External validation demonstrated an AUC value of 0.746 (95% CI 0.685–0.807), which had no significant difference with the training cohort (P = 0.124). Calibration plots indicated that the nomogram-predicted results were well fitted to the actual outcomes in both internal and external validation. The nomogram had better discriminate ability in patients who had tumors > 2 cm (AUC = 0.847, 95% CI 0.804–0.890). When compared with four other existing models, similar AUC was observed between our nomogram and the model constructed by discriminate Lee et al. Conclusions We developed a user-friendly nomogram to predict the high-risk RS in luminal breast cancer patients who were older than 50 years of age, which could guide treatment decision making for those who have no access to the 21-gene RS testing.

Nomogram prediction of the 70-gene signature (MammaPrint) binary and quartile categorized risk using medical history, imaging features and clinicopathological data among Chinese breast cancer patients

“…Interestingly, there were no signi cant differences in all the included imaging features of ultrasound and mammogram between 70-GS high vs low risk patients (Table 1). Not surprisingly, the most 'classic' clincopathological parameters associated with 70-GS risk were still histological grade, PR and Ki-67 index (Table 1, Figure 2, 4), which was in accordance with studies building nomogram predicting 21-gene RS [17,29,30]. Majority (71.3%) of patients were clinical high risk according to AOL model.…”

“…Study showed that the prognostic and predictive value of the 21-gene RS was consistent in different countries [27], however, there might be difference in the 21-gene assay performance across racial groups with better performance among white compared with African American and Hispanic individuals. [28] The 21-gene RS could be predicted by nomograms and machine-learning models based on clinicopathological parameters [29][30][31][32]. The 70-GS further strati es HR+/Her2-BC patients with clinically high-risk according to AOL model into binary (high vs low) or quartile categorized (ultra-high, high, low and ultra-low) risk classi cations [6,33].…”

A Novel Surrogate Nomogram Capable of Predicting OncotypeDX Recurrence Score©

“…In our multivariable analysis, a combination of menopause status, tumor grade, ER score, and PgR score independently predicted RS (accuracy: 0.800, 95% CI: 0.719–0.866) and RS > 25, respectively (accuracy: 0.858, 95% CI: 0.764–0.889). These results have been consistently observed in the previous studies which have built nomograms predictive of RS [ 42 , 50 , 51 , 56 , 57 ] and are unsurprising, as gene expression levels of ER and PgR were included in the algorithm designed by Paik et al when creating the 21-gene expression assay [ 1 ]. Moreover, menopause status independently predicted RS, an unanticipated result which is less well-described in previous studies [ 22 , 24 ].…”

“…Moreover, data from the aforementioned study suggests that LVI has potential to serve as a surrogate biomarker of RS predictive of patients with luminal A disease who may benefit from adjuvant chemotherapy prescription. Similarly, Lee et al describe Ki-67 indices as predictive correlates of RS in their nomogram, with results validated by other authors in two more recent studies which developed surrogate nomograms to RS [50,51]. This is an unsurprising finding; within the 21-gene expression assay, comparison between the 16 cancer-related and 5 reference (or "housekeeping") genes is included in an algorithm to generate the RS [1].…”

Nomogram prediction of the 70-gene signature (MammaPrint) binary and quartile categorized risk using medical history, imaging features and clinicopathological data among Chinese breast cancer patients

“…Study showed that the prognostic and predictive value of the 21-gene RS was consistent in different countries [27], however, there might be difference in the 21-gene assay performance across racial groups with better performance among white compared with African American and Hispanic individuals. [28] The 21-gene RS could be predicted by nomograms and machine-learning models based on clinicopathological parameters [29][30][31][32]. The 70-GS further stratifies HR + / Her2− BC patients with clinically high-risk according to AOL model into binary (high vs low) or quartile categorized (ultra-high, high, low and ultra-low) risk classifications [6,33].…”