Trial reportCancer2022
A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large-scale, multicenter cohort study.
Trial report in Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- Progress and current trends in prediction models for the occurrence and prognosis of cancer and cancer-related complications: a bibliometric and visualization analysis.Frontiers in oncology · 2025Pooled it
- Evolution of Breast Cancer Recurrence Risk Prediction: A Systematic Review of Statistical and Machine Learning-Based Models.JCO clinical cancer informatics · 2023Pooled it
- Trial
- Prognostic value of whole lymph node molecular analysis in colorectal cancer: a prospective multicenter study.Clinical and experimental medicine · 2025Observational
- One-Step Nucleic Acid Amplification Analysis of Sentinel Lymphatic Nodes in Endometrial Cancer Patients (EU-OSNA): A European Multicenter Diagnostic Accuracy Study.Cancer medicine · 2025Article
- Assessing the prognosis mortality in patients with cutaneous verrucous carcinoma using Lasso-cox regression model: a retrospective study.Discover oncology · 2025Article
- A practical recurrence risk model based on Lasso-Cox regression for gastric cancer.Journal of cancer research and clinical oncology · 2023Article
- Reply to "Survival analysis in a prediction model for early systemic recurrence in breast cancer".Cancer · 2022Article
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Authors and funding
20 authors at 15 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe one-step nucleic acid amplification (OSNA) assay can quantify the cytokeratin 19 messenger RNA copy number as a proxy for sentinel lymph node (SN) metastasis in breast cancer. A large-scale, multicenter cohort study was performed to determine the prognostic value of the SN tumor burden based on a molecular readout and to establish a model for the prediction of early systemic recurrence in patients using the OSNA assay.
methodsSN biopsies from 4757 patients with breast cancer were analyzed with the OSNA assay. The patients were randomly assigned to the training or validation cohort at a ratio of 2:1. On the basis of the training cohort, the threshold SN tumor burden value for stratifying distant recurrence was determined with Youden's index; predictors of distant recurrence were investigated via multivariable analyses. Based on the selected predictors, a model for estimating 5-year distant recurrence-free survival was constructed, and predictive performance was measured with the validation cohort.
resultsThe prognostic cutoff value for the SN tumor burden was 1100 copies/μL. The following variables were significantly associated with distant recurrence and were used to construct the prediction model: SN tumor burden, age, pT classification, grade, progesterone receptor, adjuvant cytotoxic chemotherapy, and adjuvant anti-human epidermal growth factor receptor 2 therapy. The values for the area under the curve, sensitivity, specificity, and accuracy of the prediction model were 0.83, 63.4%, 81.7%, and 81.1%, respectively.
conclusionsUsing the OSNA assay, the molecular readout-based SN tumor burden is an independent prognostic factor for early breast cancer. This model accurately predicts early systemic recurrence and may facilitate decision-making related to treatment.
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