ArticleNPJ breast cancer2021
Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®.
Article in NPJ breast cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guideline
- Multi-state modeling associates proliferation genes with early estrogen receptor-positive breast cancer recurrence and survival.Research square · 2026Article
- Comparative evaluation of microRNA detection in plasma, urine and liquid-based cytology for high-grade cervical intraepithelial neoplasia.Oncology letters · 2026Article
- BRCAGenie: A machine learning-driven 43-gene polygenic risk score model for precision prediction of breast cancer survival.Journal of translational medicine · 2025Article
- Modeling intratumor heterogeneity in breast cancer.Biofabrication · 2024Review
- Closing the gap: prognostic and predictive biomarker validation for personalized care in a Latin American hormone-dependent breast cancer cohort.The oncologist · 2024Article
- Clinical bioinformatics desiderata for molecular tumor boards.Briefings in bioinformatics · 2024Review
- Differences in 21-Gene and PAM50 Recurrence Scores in Younger and Black Women With Breast Cancer.JCO precision oncology · 2024Article
- The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy.International journal of molecular sciences · 2024Review
- Incorporating clinicopathological and molecular risk prediction tools to improve outcomes in early HR+/HER2- breast cancer.NPJ breast cancer · 2023Review
- A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer.International journal of molecular sciences · 2023Review
- Article
- Extended Adjuvant Endocrine Treatment in Luminal Breast Cancers in the Era of Genomic Tests.International journal of molecular sciences · 2022Review
- Impact of Duration of Neoadjuvant Aromatase Inhibitors on Molecular Expression Profiles in Estrogen Receptor-positive Breast Cancers.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- Oncotype DX Recurrence Score in premenopausal women.Therapeutic advances in medical oncology · 2022Review
- Impact of the menstrual cycle on commercial prognostic gene signatures in oestrogen receptor-positive primary breast cancer.Breast cancer research and treatment · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2- breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (r
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