Long-Term Disease-Free Survival of Non-Metastatic Breast Cancer Patients in Iran: A Survival Model with Competing Risks Taking Cure Fraction and Frailty into Account

机译：伊朗非转移性乳腺癌患者的长期无病生存：考虑治愈率和脆弱性的具有竞争风险的生存模型

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Introduction:Survival modeling is a very important tool to detect risk factors and provide a basis for health care planning. However, cancer data may have properties leading to distorted results with routine methods. Therefore, this study aimed to cover specific factors (competing risk, cure fraction and heterogeneity) with a real dataset of Iranian breast cancer patients using a competing risk-cure-frailty model.

机译：简介：生存建模是检测风险因素并为医疗保健计划提供基础的非常重要的工具。但是，癌症数据可能具有导致常规方法结果失真的特性。因此，本研究旨在使用竞争风险-治疗-脆弱模型，利用伊朗乳腺癌患者的真实数据集涵盖特定因素（竞争风险，治愈率和异质性）。

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期刊名称 Asian Pacific Journal of Cancer Prevention : APJCP
作者
Vahid Ghavami; Mahmood Mahmoudi; Abbas Rahimi Foroushani; Hossein Baghishani; Fatemeh Homaei Shandiz; Mehdi Yaseri;
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作者单位

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年(卷),期 2017(18),10
年度 2017
页码 2825–2832
总页数 8
原文格式 PDF
正文语种
中图分类肿瘤学;
关键词
Breast neoplasms competing risks cure model frailty model survival analysis;

机译：乳腺肿瘤;竞争风险;治疗模型;虚弱模型;生存分析;

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1. Long-Term Disease-Free Survival of Non-Metastatic Breast Cancer Patients in Iran: A Survival Model with Competing Risks Taking Cure Fraction and Frailty into Account [J] . Vahid Ghavami, Mahmood Mahmoudi, Abbas Rahimi Foroushani, Asian Pacific Journal of Cancer Prevention . 2017,第10期

机译：伊朗非转移性乳腺癌患者的长期无病生存：一种具有竞争风险的生存模型，其中考虑了治愈率和脆弱性
2. Use of Cox’s Cure Model to Establish Clinical Determinants of Long-Term Disease-Free Survival in Neoadjuvant-Chemotherapy-Treated Breast Cancer Patients without Pathologic Complete Response [J] . JunichiAsano, AkihiroHirakawa, ChikumaHamada, International Journal of Breast Cancer . 2013,第2期

机译：使用Cox的治愈模型建立无病理完全缓解的新辅助化疗治疗的乳腺癌患者长期无病生存的临床决定因素
3. The application of cure models in the presence of competing risks: A tool for improved risk communication in population-based cancer patient survival [J] . ElorantaS., LambertP.C., AnderssonT.M.-L., Epidemiology . 2014,第5期

机译：在存在竞争风险的情况下治愈模型的应用：改善基于人群的癌症患者生存中风险沟通的工具
4. Predicting Disease-Free Lung Cancer Survival Using Patient Reported Outcome (PRO) Measurements with Comparisons of Five Machine Learning Techniques (MLT) [C] . Jin-ah Sim, Young Ho Yun MEDINFO . 2019

机译：使用患者报告的结果（PRO）测量来预测无病的肺癌存活，并使用五种机器学习技术（MLT）进行比较
5. Early stage breast cancer and comorbidities: Their impact on breast cancer disease-free survival differences by ethnicity. [D] . Guerra, Sandra Lee. 2010

机译：早期乳腺癌和合并症：种族对乳腺癌无病生存率差异的影响。
6. Use of Coxs Cure Model to Establish Clinical Determinants of Long-Term Disease-Free Survival in Neoadjuvant-Chemotherapy-Treated Breast Cancer Patients without Pathologic Complete Response [O] . Junichi Asano, Akihiro Hirakawa, Chikuma Hamada, 2013

机译：使用Cox的治愈模型建立无病理完全缓解的新辅助化疗治疗乳腺癌患者长期无病生存的临床决定因素
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Long-Term Disease-Free Survival of Non-Metastatic Breast Cancer Patients in Iran: A Survival Model with Competing Risks Taking Cure Fraction and Frailty into Account

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