ArticleOncotarget2018
A nomogram prediction for the survival of patients with triple negative breast cancer.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Utility of CA-125 for diagnosis and prognosis of breast cancer: a systematic review.Exploration of targeted anti-tumor therapy · 2025Pooled it
- Survival prediction in triple-negative breast cancer: a Cox model with fairness assessment using ISO/IEC TR 24027:2021 in a MENA cohort.Exploration of targeted anti-tumor therapy · 2026Article
- Deep learning for survival prediction in triple-negative breast cancer: development and validation in real-world cohorts.Scientific reports · 2025Article
- Development and validation of nomograms of outcomes for first-line platinum-based chemotherapy for metastatic triple-negative breast cancer: patient-level analysis of five prospective clinical trials in China.Therapeutic advances in medical oncology · 2025Article
- Article
- Circulating proteins as predictive and prognostic biomarkers in breast cancer.Clinical proteomics · 2022Review
- GATA1-Activated HNF1A-AS1 Facilitates the Progression of Triple-Negative Breast Cancer via Sponging miR-32-5p to Upregulate RNF38.Cancer management and research · 2021Article
- Development and validation of a nomogram in survival prediction among advanced breast cancer patients.Annals of translational medicine · 2020Article
- Clinical value of CTLA4 combined with clinicopathological factors in evaluating the prognosis of breast cancer.Gland surgery · 2020Article
- A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer.Contrast media & molecular imaging · 2020Article
- LncRNA LUCAT1 facilitates tumorigenesis and metastasis of triple-negative breast cancer through modulating miR-5702.Bioscience reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis. In this study, we aimed to conduct a nomogram to predict the survival of individual with TNBC by incorporating significant clinical and laboratory parameters. 404 TNBC patients from the Affiliated Union Hospital of Fujian Medical University between 2006 and 2012 were selected in the training cohort. Cox univariate and multivariate regression analyses were adopted to identify independent prognostic factors. The predictive accuracy and discriminative ability of this nomogram were evaluated by concordance index (C-index) and calibration curve. The accuracy of this nomogram was also compared with the 8
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.