ArticlePloS one2015
Prediction of breast cancer survival using clinical and genetic markers by tumor subtypes.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Associations between genetic polymorphisms of membrane transporter genes and prognosis after chemotherapy: meta-analysis and finding from Seoul Breast Cancer Study (SEBCS).The pharmacogenomics journal · 2018Pooled it
- A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study.Cancer research communications · 2023Article
- Development and testing of a polygenic risk score for breast cancer aggressiveness.NPJ precision oncology · 2023Article
- UACA locus is associated with breast cancer chemoresistance and survival.NPJ breast cancer · 2022Article
- Breast Cancer-Related Low Penetrance Genes.Advances in experimental medicine and biology · 2021Article
- Use of clinical nomograms for predicting survival outcomes in young women with breast cancer.Oncology letters · 2019Article
- Subtype-specific associations between breast cancer risk polymorphisms and the survival of early-stage breast cancer.Journal of translational medicine · 2018Article
- Revisiting Neutrophil Gelatinase-Associated Lipocalin (NGAL) in Cancer: Saint or Sinner?Cancers · 2018Review
- Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks.Scientific reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo identify the genetic variants associated with breast cancer survival, a genome-wide association study (GWAS) was conducted of Korean breast cancer patients.
methodsFrom the Seoul Breast Cancer Study (SEBCS), 3,226 patients with breast cancer (1,732 in the discovery and 1,494 in the replication set) were included in a two-stage GWAS on disease-free survival (DFS) by tumor subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). The associations of the re-classified combined prognostic markers through recursive partitioning analysis (RPA) of DFS for breast cancer were assessed with the Cox proportional hazard model. The prognostic predictive values of the clinical and genetic models were evaluated by Harrell's C.
resultsIn the two-stage GWAS stratified by tumor subtypes, rs166870 and rs10825036 were consistently associated with DFS in the HR+ HER2- and HR- HER2- breast cancer subtypes, respectively (Prs166870 = 2.88 × 10(-7) and Prs10825036 = 3.54 × 10(-7) in the combined set). When patients were classified by the RPA in each subtype, genetic factors contributed significantly to differentiating the high risk group associated with DFS inbreast cancer, specifically the HR+ HER2- (P discovery=1.18 × 10(-8) and P replication = 2.08 × 10(-5)) and HR- HRE2- subtypes (P discovery = 2.35 × 10(-4) and P replication = 2.60 × 10(-2)). The inclusion of the SNPs tended to improve the performance of the prognostic models consisting of age, TNM stage and tumor subtypes based on ER, PR, and HER2 status.
conclusionCombined prognostic markers that include clinical and genetic factors by tumor subtypes could improve the prediction of survival in breast cancer.
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.