SynthesisJournal of advanced research2025
ARTEMIS: An independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions.
Synthesis in Journal of advanced research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Development and independent validation of a hypoxemia risk prediction model (HAPPY-12K) for sedated gastrointestinal endoscopy: a multicentre prospective cohort study.EClinicalMedicine · 2026Article
- TTPAL inhibits the progression of breast cancer and reprograms tumor-associated macrophages by inhibiting JAK2/STAT3 signaling pathway.Breast cancer research : BCR · 2026Article
- The mechanisms and therapeutic advances of interactions between breast cancer and cardiovascular diseases.Frontiers in pharmacology · 2026Review
- Analysis of factors affecting axillary lymph node metastasis in breast cancer and the establishment and validation of a predictive model.Scientific reports · 2025Article
- Impact of HMGA1 on tumorigenesis, prognosis and immune microenvironment in HNSCC: a multi-omics study.NPJ precision oncology · 2025Article
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Authors and funding
13 authors.
Funding
Abstract
introductionBreast cancer, a heterogeneous disease, is influenced by multiple genetic and epigenetic factors. The majority of prognostic models for breast cancer focus merely on the main effects of predictors, disregarding the crucial impacts of gene-gene interactions on prognosis.
objectivesUsing DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy. ARTEMIS was evaluated for discrimination ability using area under the receiver operating characteristics curve (AUC), and calibration using expected and observed (E/O) ratio. Additionally, we conducted decision curve analysis to evaluate its clinical efficacy by net benefit (NB) and net reduction (NR). Furthermore, we conducted a systematic review to compare its performance with existing models.
resultsARTEMIS exhibited excellent risk stratification ability in identifying patients at high risk of mortality. Compared to those below the 25th percentile of ARTEMIS scores, patients with above the 90th percentile had significantly lower overall survival time (HR = 15.43, 95% CI: 9.57-24.88, P = 3.06 × 10
conclusionARTEMIS is an efficient and practical tool for breast cancer prognostic prediction.
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