ReviewFrontiers in medicine2018
An Update on Breast Cancer Multigene Prognostic Tests-Emergent Clinical Biomarkers.
Review in Frontiers in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
90 citing papers in PubMed, 3 syntheses or guidelines pooled it, 172 citations in OpenAlex.
- A systematic review of progress toward unlocking the power of epigenetics in breast cancer: latest updates and perspectives.Frontiers in pharmacology · 2025Pooled it
- Biomarkers predictive of a response to extended endocrine therapy in breast cancer: a systematic review and meta-analysis.Breast cancer research and treatment · 2024Pooled it
- Pathological Diagnosis, Work-Up and Reporting of Breast Cancer 1st Central-Eastern European Professional Consensus Statement on Breast Cancer.Pathology oncology research : POR · 2022Pooled it
- The spatially informed mFISHseq assay resolves biomarker discordance and predicts treatment response in breast cancer.Nature communications · 2025Trial
- Multi-omic Profiling of Recurrence Risk Across Breast Cancer Subtypes.medRxiv : the preprint server for health sciences · 2026Article
- Ensemble Machine Learning on Bulk RNA-Seq Identifies 17-Gene Signature Predicting Neoadjuvant Chemotherapy Response in Breast Cancer.Current issues in molecular biology · 2026Article
- Article
- Computational prediction of diagnostic biomarker candidates and prognostic gene signature from DNA replication-related genes in breast cancer.Discover oncology · 2025Article
- [Pathological diagnosis, work-up and reporting of breast cancer. Recommendations of the 5th Hungarian Consensus Conference on Breast Cancer].Magyar onkologia · 2025Article
- H&E to IHC virtual staining methods in breast cancer: an overview and benchmarking.NPJ digital medicine · 2025Review
- Landscape of lncRNAs expressed in Mexican patients with triple‑negative breast cancer.Molecular medicine reports · 2025Article
- Genetic Signature of Breast Cancer Defines Therapeutic Interventions and Indicates Early Drug Resistance.Journal of cellular and molecular medicine · 2025Review
- Immunohistochemical Breast Cancer Profiling Among Iraqi Women: Molecular Subtype Classification, Clinicopathology Associations, and Treatment-Decision Making Tools: A Cross-Sectional Study.Health science reports · 2025Article
- Article
- CD4Science advances · 2025Article
- Identification of iron metabolism-related key genes and exploration of their potential mechanisms in hemophagocytic lymphohistiocytosis based on transcriptome sequencing.Frontiers in medicine · 2025Article
- Article
- Predictive models and biomarkers for survival in stage III breast cancer: a review of clinical applications and future directions.Annals of medicine and surgery (2012) · 2024Review
- A triple hormone receptor ER, AR, and VDR signature is a robust prognosis predictor in breast cancer.Breast cancer research : BCR · 2024Article
- Combining Molecular and Traditional Prognostic Factors: A Holistic Approach to Breast Cancer Prognostication.Diagnostics (Basel, Switzerland) · 2024Article
30 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multigene signatures generate crucial prognostic information particularly useful for cancer patients where clinical parameters and traditional immunohistochemical markers alone lead to equivocal prognosis. Clinicians are now provided with molecular tools that assist in the outline of adjuvant therapies, namely helping decide on the extension of adjuvant endocrine therapy or on suppressing adjuvant chemotherapy in patients were toxic effects are particularly deleterious or when this treatment is fundamentally not needed. The importance of cancer multigene prognostic signatures is well elucidated in the guidelines for adjuvant systemic therapy in early-stage breast cancer and the guidelines on disease staging that are progressively integrating gene expression assays as classification biomarkers. In addition to the predictive and prognostic value, some genetic tests provide intrinsic subtyping classification. Herewith, we compare the molecular tests OncotypeDX, MammaPrint, Prosigna, EndoPredict, Breast Cancer Index, Mammostrat, and IHC4 and report the eligibility of each one in the suitable setting. Through to now, there is not a commercially available multigene test that makes recommendations regarding adjuvant treatment for HER-2 and triple negative breast cancers. Thus, these patients still receive adjuvant chemotherapy. Importantly, triple negative carcinomas are very heterogeneous regarding prognosis and new molecular signatures that decipher this very heterogeneous subgroup of breast cancer may improve the clinical management of the disease.
Indexed as
Identifiers
What OpenQuestion holds
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.