ArticleWorld journal of surgical oncology2018
Introducing novel and comprehensive models for predicting recurrence in breast cancer using the group LASSO approach: are estimates of early and late recurrence different?
Article in World journal of surgical oncology, 2018. 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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6 citing papers in PubMed.
- Evaluating the Influence of Flaxseed Oil Against Docosahexaenoic Acid on Cancer Antigen CA15-3, Biochemical and Histopathological Parameters of DMBA-Induced Mammary Tumors Female Albino Wistar Rats.Food science & nutrition · 2026Article
- Establishment of a model to predict the recurrence time of hormone receptor-positive/human epidermal growth factor receptor 2-negative breast cancer.Translational cancer research · 2026Article
- Prognostic significance of malignant pleural effusions in patients with advanced luminal B breast cancer.BMC women's health · 2024Article
- MicroRNA-26a-5p inhibits breast cancer cell growth by suppressing RNF6 expression.The Kaohsiung journal of medical sciences · 2019Article
- High-Mobility Group Box 1 (HMGB1) Promotes Angiogenesis and Tumor Migration by Regulating Hypoxia-Inducible Factor 1 (HIF-1α) Expression via the Phosphatidylinositol 3-Kinase (PI3K)/AKT Signaling Pathway in Breast Cancer Cells.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- High SLC20A1 Expression Is Associated With Poor Prognosis for Radiotherapy of Estrogen Receptor-positive Breast Cancer.Cancer diagnosis & prognosisArticle
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8 authors.
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Abstract
backgroundIn here, we constructed personalized models for predicting breast cancer (BC) recurrence according to timing of recurrence (as early and late recurrence).
methodsAn efficient algorithm called group LASSO was used for simultaneous variable selection and risk factor prediction in a logistic regression model.
resultsFor recurrence < 5 years, age (OR 0.96, 95% CI = 0.95-0.97), number of pregnancies (OR 0.94, 95% CI = 0.89-0.99), family history of other cancers (OR 0.73, 95% CI = 0.60-0.89), hormone therapy (OR 0.76, 95% CI = 0.61-0.96), dissected lymph nodes (OR 0.98, 95% CI = 0.97-0.99), right-sided BC (OR 0.87, 95% CI = 0.77-0.99), diabetes (OR 0.77, 95% CI = 0.60-0.98), history of breast operations (OR 0.38, 95% CI = 0.17-0.88), smoking (OR 5.72, 95% CI = 2.11-15.55), history of breast disease (OR 3.32, 95% CI = 1.92-5.76), in situ component (OR 1.58, 95% CI = 1.35-1.84), tumor necrosis (OR 1.87, 95% CI = 1.57-2.22), sentinel lymph node biopsy (SLNB) (OR 2.90, 95% CI = 2.05-4.11) and SLNB+axillary node dissection (OR 3.50, 95% CI = 2.26-5.42), grade 3 (OR 1.79, 95% CI = 1.46-2.21), stage 2 (OR 2.71, 95% CI = 2.18-3.35), stages 3 and 4 (OR 5.01, 95% CI = 3.52-7.13), and mastectomy+radiotherapy (OR 2.97, 95% CI = 2.39-3.68) were predictors of recurrence < 5 years. Moreover, relative to mastectomy without radiotherapy (as reference for comparison), quadrantectomy without radiotherapy had a noticeably higher odds ratio compared to quadranectomy with radiotherapy for recurrence < 5 years. (OR 17.58, 95% CI = 6.70-46.10 vs. OR: 2.50, 95% CI = 2-3.12). Accuracy, sensitivity, and specificity of the model were 82%, 75.6%, and 74.9%, respectively. For recurrence > 5 years, stage 2 cancer (OR 1.67, 95% CI = 1.31-2.14) and radiotherapy+mastectomy (OR 2.45, 95% CI = 1.81-3.32) were significant predictors; furthermore, relative to mastectomy without radiotherapy (as reference for comparison), quadranectomy without radiotherapy had a noticeably higher odds ratio compared to quadranectomy with radiotherapy for recurrence > 5 years (OR 7.62, 95% CI = 1.52-38.15 vs. OR 1.75, 95% CI = 1.32-2.32). Accuracy, sensitivity, and specificity of the model were 71%, 78.8%, and 55.8%, respectively.
conclusionFor the first time, we constructed models for estimating recurrence based on timing of recurrence which are among the most applicable models with excellent accuracy (> 80%).
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