ArticleBreast cancer (Dove Medical Press)2022
Establishment and Validation of a Model for Disease-Free Survival Rate Prediction Using the Combination of microRNA-381 and Clinical Indicators in Patients with Breast Cancer.
Article in Breast cancer (Dove Medical Press), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 4 citations in OpenAlex.
- Development and validation of a nomogram prediction model for osteoporotic vertebral compression re-fracture after percutaneous kyphoplasty based on lumbar local fat parameters.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Article
- Advances in research regarding epithelial-mesenchymal transition and prostate cancer.Frontiers in cell and developmental biology · 2025Review
- Elevated Risk of Adverse Prognosis in Patients with T2-3 Stage Breast Cancer Exhibiting Non-Pathological Complete Response Following Neoadjuvant Chemotherapy: Significance of Regenerating Islet-Derived Family Member 4.Breast cancer (Dove Medical Press) · 2024Article
- Development and validation of a nomogram to predict the recurrence of eyelid sebaceous gland carcinoma.Cancer medicine · 2023Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: We have found that miR-381 can regulate the proliferation of breast cancer cells by regulating TWIST protein, it can serve as a potential marker for the tumor progression. Thus, we herein establishment and validation of a model for predicting disease progression in patients with breast cancer using a combination of microRNA-381 (miR-381) and clinical indicators. Methods: Data from 160 breast cancer patients in the First People's Hospital of Lianyungang were collected, The relationship between miR-381 expression and tumor subtype was analyzed. The Kaplan-Meier (K-M) curve method was used to investigate the disease-free survival rate, while multivariate Cox regression analysis was used to investigate the risk factors affecting the prognosis of the patients. A model for predicting disease progression was subsequently established and validated. Results: The miR-381 was significantly higher in the stage I patients than stage II/III patients. The miR-381 level of triple-negative breast cancer (TNBC) type was significantly decreased. The miR-381 could be used to effectively predict the prognosis, using cut-off value of 0.2515, with a sensitivity of 65.38% (51.8-76.85%), specificity of 75.00% (46.77-91.11%). The K-M survival curve indicated that the patients with higher miR-381 expression had a better prognosis. The miR-381+Ki-67+TN model and TN (T and N in TNM staging) model were established and subsequently compared. The TN model had an area under the curve (AUC) of 0.479 (95% CI 0.329, 0.629); in comparison, the our model had an AUC of 0.719 (95% CI 0.580, 0.857), showing better performance. Conclusion: The miR-381 expression was correlated with different (TNM) stages and tumor subtypes. The higher the TNM stage, the lower the miR-381 expression in the tumor tissue, while it was significantly decreased in TNBC. A prediction model consisting of combination of miR-381 and Ki-67 and TN indicators could predict disease progression more effectively.
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