Prediction of Oncotype DX Recurrence Score Using Clinicopathological Variables in Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer

Kim, Min Chong; Kwon, Sun Young; Choi, Jung Eun; Kang, Su Hwan; Bae, Young Kyung

doi:10.4048/jbc.2023.26.e19

Cited by 9 publications

(12 citation statements)

References 35 publications

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“…Similarly, Kim et al also developed a model with good discriminatory ability (AUC = 0.926) using NG, Ki67 index, and PgR level [25]. Lee et al developed a nomogram based on data from 485 patients with breast cancer metastases in 0-3 axillary lymph nodes.…”

Section: Discussionmentioning

confidence: 99%

“…In the TAILORx study, chemotherapy could be safely omitted in the low-risk group (RS, 0-10) of patients without axillary lymph node metastases. The intermediate-risk group (RS, [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] revealed no effect of adding chemotherapy to endocrine therapy, while an RS within the range of 16-25 was associated with a prognostic benefit of chemotherapy only in patients under 50 years of age [7][8][9]. This indicated that in patients without axillary lymph node metastasis, a significant additive effect of chemotherapy existed if the RS was ≥ 26 and ≥16 in those with age > 50 years and ≦ 50 years, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Development of a nomogram to predict recurrence scores obtained using Oncotype DX in Japanese patients with breast cancer

SHIBATA,

Tamura,

Kinowaki

et al. 2024

Preprint

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Background Chemotherapy is crucial for hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, and its survival benefit may outweigh adverse events. Oncotype DX (ODX) assesses this balance; however, it is expensive. Using nomograms to identify cases requiring ODX may be economically beneficial. We aimed to identify clinicopathological variables that correlated with the recurrence score (RS) and develop a nomogram that predicted the RS. Methods We included 457 patients with estrogen receptor-positive, HER2-negative breast cancer with metastases in less than four axillary lymph nodes who underwent surgery and ODX at our hospital between 2007 and 2023. We developed nomograms and internally validated them in 310 patients who underwent surgery between 2007 and 2021 and validated the model’s performance in 147 patients who underwent surgery between 2022 and 2023. Results Logistic regression analysis revealed that progesterone receptor (PgR) level, histological grade (HG), and Ki67 index independently predicted the RS. A nomogram was developed using these variables to predict the RS (area under the curve [AUC], 0.870; 95% confidence interval [CI], 0.82–0.92). The nomogram was applied to the model validation group (AUC, 0.877; 95% CI, 0.80–0.95). When the sensitivity of the nomogram was 90%, the model was able to identify 52.3% low-RS and 41.2% high-RS cases not requiring ODX. Conclusions This was the first nomogram model developed based on data from a cohort of Japanese women. It may help determine the indications for ODX and the use of nomogram to identify cases requiring ODX may be economically beneficial.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of a nomogram to predict recurrence scores obtained using Oncotype DX in Japanese patients with breast cancer

SHIBATA,

Tamura,

Kinowaki

et al. 2024

Preprint

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“…It has previously been shown to be an independent prognostic variable, with a negative PR score associated with poor prognosis [ 48 ]. We are not the first to report an association between the PR score and the RS [ [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] , [58] , [59] , [60] ], however the key Oncotype trials did not look at the PR score and therefore this relationship has only been shown by real world data out with clinical trial settings. We have one of the larger datasets showing this association.…”

Section: Discussionmentioning

confidence: 99%

Enhancing clinical decision support with genomic tools in breast cancer: A Scottish perspective

Peters,

Hall,

Jordan

et al. 2024

The Breast

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“…However, quantitative values for ER/PR expression were not available at the time of development of this nomogram. Yoo et al and Kim et al also developed logistic regression models incorporating nuclear grade, PR status, and Ki-67% 19 , 25 . In another study, Kim et al applied decision jungles and neural networks for the prediction of high-risk ODX using ER/PR status, HER2 status, Ki-67 index, grade, and histologic subtype 20 .…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a clinical breast cancer tool for accurate prediction of recurrence

Dhungana,

Vannier,

Zhao

et al. 2024

npj Breast Cancer

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Given high costs of Oncotype DX (ODX) testing, widely used in recurrence risk assessment for early-stage breast cancer, studies have predicted ODX using quantitative clinicopathologic variables. However, such models have incorporated only small cohorts. Using a cohort of patients from the National Cancer Database (NCDB, n = 53,346), we trained machine learning models to predict low-risk (0-25) or high-risk (26-100) ODX using quantitative estrogen receptor (ER)/progesterone receptor (PR)/Ki-67 status, quantitative ER/PR status alone, and no quantitative features. Models were externally validated on a diverse cohort of 970 patients (median follow-up 55 months) for accuracy in ODX prediction and recurrence. Comparing the area under the receiver operating characteristic curve (AUROC) in a held-out set from NCDB, models incorporating quantitative ER/PR (AUROC 0.78, 95% CI 0.77–0.80) and ER/PR/Ki-67 (AUROC 0.81, 95% CI 0.80–0.83) outperformed the non-quantitative model (AUROC 0.70, 95% CI 0.68–0.72). These results were preserved in the validation cohort, where the ER/PR/Ki-67 model (AUROC 0.87, 95% CI 0.81–0.93, p = 0.009) and the ER/PR model (AUROC 0.86, 95% CI 0.80–0.92, p = 0.031) significantly outperformed the non-quantitative model (AUROC 0.80, 95% CI 0.73–0.87). Using a high-sensitivity rule-out threshold, the non-quantitative, quantitative ER/PR and ER/PR/Ki-67 models identified 35%, 30% and 43% of patients as low-risk in the validation cohort. Of these low-risk patients, fewer than 3% had a recurrence at 5 years. These models may help identify patients who can forgo genomic testing and initiate endocrine therapy alone. An online calculator is provided for further study.

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Prediction of Oncotype DX Recurrence Score Using Clinicopathological Variables in Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer

Cited by 9 publications

References 35 publications

Development of a nomogram to predict recurrence scores obtained using Oncotype DX in Japanese patients with breast cancer

Development of a nomogram to predict recurrence scores obtained using Oncotype DX in Japanese patients with breast cancer

Enhancing clinical decision support with genomic tools in breast cancer: A Scottish perspective

Development and validation of a clinical breast cancer tool for accurate prediction of recurrence

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