ArticleCancer medicine2020
A methylomics-associated nomogram predicts recurrence-free survival of thyroid papillary carcinoma.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Analysing DNA methylation and transcriptomic signatures to predict prostate cancer recurrence risk.Discover oncology · 2025Article
- A novel DNA methylation signature to improve survival prediction of progression-free survival for testicular germ cell tumors.Scientific reports · 2023Article
- Construction of DNA methylation-based nomogram for predicting biochemical-recurrence-free survival in prostate cancer.Medicine · 2022Article
- A novel prognostic model for papillary thyroid cancer based on epithelial-mesenchymal transition-related genes.Cancer medicine · 2022Article
- Methylation-Driven Gene PLAU as a Potential Prognostic Marker for Differential Thyroid Carcinoma.Frontiers in cell and developmental biology · 2022Article
- A methylomics-associated nomogram predicts recurrence-free survival of thyroid papillary carcinoma.Cancer medicine · 2020Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundThyroid papillary carcinoma (TPC) is the most common type of thyroid cancer (TC). The prognosis of TPC patients with tumor-cell metastasis is poor. Therefore, this study aims to develop a model for predicting TPC patients' recurrence-free survival (RFS).
methodsWe included 546 TPC patients who were clinically and pathologically diagnosed with TPC. The methylation biomarkers that associate with RFS were explored. These 546 samples were divided into training dataset (first 70%) and validation dataset (remaining 30%) randomly. The training dataset was used to identify prognostic biomarkers and construct risk prediction model, in addition, the validation dataset was used to verify the predictive performance of the model. We used Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to identify the significant predictive biomarkers, and establish the relapse risk prediction model from the identified biomarkers.
resultsA 6-DNA methylation signature yielded a high evaluative performance for RFS. The Kaplan-Meier analysis indicated that the 6-DNA methylation signature could significantly distinguish the high- and low-risk patients in training, validation and entire sets. In addition, a nomogram was constructed based on risk score, metastasis status and residual tumor status, and C-index, receiver operating characteristic (ROC) and the calibration plots analysis which demonstrated the good performance and clinical utility of the nomogram.
conclusionsThe results suggested that the 6-DNA methylation signature is the independent prognostic marker for RFS and functioned as a significant tool for guiding the clinical treatment of TPC patients.
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