| 胡政,李想,冯茂辉,储君君,谢伟.乳腺癌风险评估与预测的模型及应用[J].中华流行病学杂志,2009,30(10):1073-1077 |
| 乳腺癌风险评估与预测的模型及应用 |
| Models for risk assessment and prediction in breast cancer |
| 收稿日期:2009-03-03 出版日期:2014-09-18 |
| DOI： |
| 中文关键词: 乳腺肿瘤 风险因子 评估与预测 数学模型 |
| 英文关键词: Breast neoplasms Risk factor Assessment and prediction Mathematical model |
| 基金项目:1. 国家高技术研究发展计划(863计划)；2. 科技部国际科技合作项目 |
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| 中文摘要: |
| 乳腺癌风险评估与预测可以帮助临床医生评估采取预防性化疗或手术的必要性,并指导受试者的口常生活,达到减小患乳腺癌风险的目的.Gail、Claus、BRCAPRO和Cuzick-Tyrer模型是常见的4种风险评估模型.文章对上述4种模型的建立、使用、优缺点及应用范围进行论述,并使用各模型对一名有乳腺癌家族史的受试者进行风险评估;各模型预测结果差异有统计学意义;到45岁,以上4种模型预测值及人群平均累积发病概率分别为1.9%、11.8%、2.5%、5.0%和1.6%;而到75岁,分别为20.2%、32.5%、13.1%、25.0%和8.5%,受试者有较高的乳腺癌发病风险.新模犁的建立需要综合考虑各方面重要的风险因子,并进行大规模人群的验证研究. |
| 英文摘要: |
| In the areas of prevention and life skills counseling for breast cancer, risk assessment and prediction can assist clinicians to decide if chemoprevention or prophylactic surgery is needed or suggestions on improving the quality of life for their clients. Several mathematical models, namely Gail Model, Claus Model, BRCAPRO Model and Cuzick-Tyrer Model etc. have been developed to make predictions, clinically. This paper has reviewed the development, operation, advantage versus disadvantage and areas of application for the four models. Having family history of breast cancer, one subject was calculated on the risks by the four models and different Results were found. Up to 45 years old, the accumulative risks from the four models and population risk were 1.9%, 11.8%, 2.5%, 5.0% and i.6%, respectively. To 75 years old, they were 20.2%,32.5%, 13.1%, 25.0% and 8.5%, respectively. The subject had a relatively high breast cancer risk during her lifetime. A new model is supposed to include a variety of important risk factors and to be validated by large scale of case-control samples. Incidence of breast cancer in China had significantly increased during the last ten years, but the research on developing assessment Methods of breast cancer risk had never been reported, suggesting that the development of models for Chinese population is necessary. |
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