ArticleBreast cancer research : BCR2019
Development of a prediction model for breast cancer based on the national cancer registry in Taiwan.
Article in Breast cancer research : BCR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Long-term outcomes of adjuvant radiation in elderly Asians with early stage IIA breast cancer after breast-conserving surgery: a population-based study.Breast cancer (Tokyo, Japan) · 2026Article
- Survival analysis of adjuvant endocrine therapy in HER2 positive early breast cancer patients with low ER positivity.Breast cancer research : BCR · 2025Article
- Population-Based Prognostic Models for Head and Neck Cancers Using National Cancer Registry Data from Taiwan.Journal of epidemiology and global health · 2024Article
- The largest genome-wide association study for breast cancer in Taiwanese Han population.Breast cancer research and treatment · 2024Article
- Prognostic models for breast cancer: based on logistics regression and Hybrid Bayesian Network.BMC medical informatics and decision making · 2023Article
- A Comparison between the Online Prognostic Tool PREDICT and myBeST for Women with Breast Cancer in Malaysia.Cancers · 2023Article
- Development of Predictive Models for Survival among Women with Breast Cancer in Malaysia.International journal of environmental research and public health · 2022Article
- Using data mining technology to predict medication-taking behaviour in women with breast cancer: A retrospective study.Nursing open · 2022Article
- Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study.Frontiers in oncology · 2022Article
- Deep learning-based relapse prediction of neuromyelitis optica spectrum disorder with anti-aquaporin-4 antibody.Frontiers in neurology · 2022Article
- Risk evaluation of early-stage hormone receptor-positive and human epidermal growth factor receptor 2-negative breast cancer patients: a population-based study from Taiwan.Breast cancer research and treatment · 2021Article
- Molecular subtyping of breast cancer intrinsic taxonomy with oligonucleotide microarray and NanoString nCounter.Bioscience reports · 2021Article
- Article
- Cancer Incidence Characteristic Evolution Based on the National Cancer Registry in Taiwan.Journal of oncology · 2020Article
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6 authors.
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Abstract
backgroundThis study aimed to develop a prognostic model to predict the breast cancer-specific survival and overall survival for breast cancer patients in Asia and to demonstrate a significant difference in clinical outcomes between Asian and non-Asian patients.
methodsWe developed our prognostic models by applying a multivariate Cox proportional hazards model to Taiwan Cancer Registry (TCR) data. A data-splitting strategy was used for internal validation, and a multivariable fractional polynomial approach was adopted for prognostic continuous variables. Subjects who were Asian, black, or white in the US-based Surveillance, Epidemiology, and End Results (SEER) database were analyzed for external validation. Model discrimination and calibration were evaluated in both internal and external datasets.
resultsIn the internal validation, both training data and testing data calibrated well and generated good area under the ROC curves (AUC; 0.865 in training data and 0.846 in testing data). In the external validation, although the AUC values were larger than 0.85 in all populations, a lack of model calibration in non-Asian groups revealed that racial differences had a significant impact on the prediction of breast cancer mortality. For the calibration of breast cancer-specific mortality, P values < 0.001 at 1 year and 0.018 at 4 years in whites, and P values ≤ 0.001 at 1 and 2 years and 0.032 at 3 years in blacks, indicated that there were significant differences (P value < 0.05) between the predicted mortality and the observed mortality. Our model generally underestimated the mortality of the black population. In the white population, our model underestimated mortality at 1 year and overestimated it at 4 years. And in the Asian population, all P values > 0.05, indicating predicted mortality and actual mortality at 1 to 4 years were consistent.
conclusionsWe developed and validated a pioneering prognostic model that especially benefits breast cancer patients in Asia. This study can serve as an important reference for breast cancer prediction in the future.
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