ArticleJournal of breast cancer2023
Prediction of Oncotype DX Recurrence Score Using Clinicopathological Variables in Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer.
Article in Journal of breast cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A Simplified Novel Algorithm to Predict the 21-Gene Recurrence Score.World journal of oncology · 2025Article
- Clinical Usefulness of a Multigene Testing in Patients with Special Histologic Type Breast Cancer.Yonsei medical journal · 2025Article
- Development of a nomogram to predict recurrence scores obtained using Oncotype DX in Japanese patients with breast cancer.Breast cancer (Tokyo, Japan) · 2024Article
- Development and validation of a clinical breast cancer tool for accurate prediction of recurrence.NPJ breast cancer · 2024Article
- Prediction of Oncotype DX Recurrence Score Based on Systematic Evaluation of Ki-67 Scores in Hormone Receptor-Positive Early Breast Cancer.Journal of breast cancer · 2024Article
- Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence.Cancers · 2024Review
- The added value of ultrasound imaging biomarkers to clinicopathological factors for the prediction of high-risk Oncotype DX recurrence scores in patients with breast cancer.Quantitative imaging in medicine and surgery · 2024Article
- A simplified risk scoring system for predicting high-risk groups in gene expression tests for patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and node-positive breast cancer.Annals of surgical treatment and research · 2023Article
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeOncotype DX (ODX) is a well-validated multigene assay that is increasingly used in Korean clinical practice. This study aimed to develop a clinicopathological prediction (CPP) model for the ODX recurrence scores (RSs).
methodsA total of 297 patients (study group, n = 175; external validation group, n = 122) with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, T1-3N0-1M0 breast cancer, and available ODX test results were included in the study. Risk categorization as determined by ODX RSs concurred with the TAILORx study (low-risk, RS ≤ 25; high-risk, RS > 25). Univariate and multivariate logistic regression analyses were used to assess the relationships between clinicopathological variables and risk stratified by the ODX RSs. A CPP model was constructed based on regression coefficients (β values) for clinicopathological variables significant by multivariate regression analysis.
resultsProgesterone receptor (PR) negativity, high Ki-67 index, and nuclear grade (NG) 3 independently predicted high-risk RS, and these variables were used to construct the CPP model. The C-index, which represented the discriminatory ability of our CPP model for predicting a high-risk RS, was 0.915 (95% confidence interval [CI], 0.859-0.971). When the CPP model was applied to the external validation group, the C-index was 0.926 (95% CI, 0.873-0.978).
conclusionOur CPP model based on PR, Ki-67 index, and NG could aid in the selection of patients with breast cancer requiring an ODX test.
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