ArticleIn vivo (Athens, Greece)
Clinical Impact of a Novel Model Predictive of Oncotype DX Recurrence Score in Breast Cancer.
Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 4 citations in OpenAlex.
- A Simplified Novel Algorithm to Predict the 21-Gene Recurrence Score.World journal of oncology · 2025Article
- In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy.Proteomes · 2025Review
- Association Between Ki-67 Proliferative Index and Oncotype-Dx Recurrence Score in Hormone Receptor-Positive, HER2-Negative Early Breast Cancers. A Systematic Review of the Literature.Breast cancer : basic and clinical research · 2024Review
- BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images.PloS one · 2023Article
- Stratification of Prognosis by Biological Features Following Neoadjuvant Chemotherapy in Luminal Breast Cancer.In vivo (Athens, Greece)Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimOncotype DX recurrence score (RS) for breast cancer is a useful tool for determining chemotherapy indication but it is expensive and time-consuming. We determined whether four immuno-histochemical markers, namely human epidermal growth factor 2 (HER2), estrogen receptor (ER), progesterone receptor (PgR), and Ki-67, are predictive of an RS ≥26 in Japanese patients. PATIENTS AND
methodsThe study included 95 Japanese patients evaluated for RS. A predictive model was created using logistic regression analysis.
resultsThe discriminant function was calculated as follows: p=1/{1+exp [-(4.611+1.2342×HER2-0.0813×ER- 0.0489 ×PgR+0.0857×Ki67)]}. Using a probability of 0.5 as the cutoff, the accuracy, sensitivity, specificity, positive predictive and negative predictive values were 90.5%, 72.2%, 94.8%, 76.4% and 93.5%, respectively.
conclusionThe model had a high negative predictive value in predicting RS ≥26 in Japanese patients, indicating that Oncotype DX testing may be omitted in patients with a negative result according to the predictive model.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.