期刊文献+

上海妇女乳腺癌危险度评价模型的初步研究 被引量:4

Preliminary study on risk assessment model of breast cancer in Shanghai
下载PDF
导出
摘要 目的:筛选上海妇女患乳腺癌的危险因素,初步建立符合上海乳腺癌危险度评价模型,探讨乳腺癌低、中、高危险人群区分的分界点;并用该模型评估上海女性具备特定危险因素下患乳腺癌的机率。方法:采用Logistic回归法筛选乳腺癌的危险因素,以此建立乳腺癌危险度评价模型。判别分析评价模型;计算ROC曲线下面积观察此效能,并利用ROC曲线寻找乳腺癌低、中、高危险性的合适分界点。结果:乳腺癌调查人群可能的主要危险因素有:文化程度、乳腺疾病、乳腺疾病手术史、粗粮、蔬菜食品、雌激素药品、缺乏锻炼及熬夜。危险度评价模型预测低、中、高危人群,以预测概率值P≤0.076判为低危险性人群,预测概率值P≥0.243判为高危险性人群,0.076<预测概率值P<0.243判为中危险性人群。结论:该模型可评估上海女性具备特定危险因子情况下患乳腺癌的机率,为建立筛查标准提供一定依据。 Objective:To screen risk factors of breast cancer in Shanghai women,the risk assessment model of breast cancer is initially established,which is distinguished by cut-off point with low,medium and high risk groups in Shanghai.The probability of breast cancer is also assessed by the risk assessment model.Methods:The risk factors for breast cancer were screened by Logistic regression.Moreover the risk assessment model is established and evaluated by discriminant analysis.The performance of the calculated area under the ROC curve was observed.The appropriate low,medium and high risk cut-off points were distinguished by the ROC curve.Results:The risk factors of breast cancer in surveyed population include:education,breast disease,surgery,whole grains,vegetables food,estrogen drugs,lacking of exercise and late staying up.Risk assessment models predict the low,medium and high-risk groups with probability value P≤0.076 for low-risk sub-populations,P≥0.243 for high-risk sub-populations,0.076〈 P〈0.243 for medium.Conclusion:The model can assess the probability of breast cancer of Shanghai women with specific risk factors as well as provide the probable basis for screening criteria.
出处 《现代肿瘤医学》 CAS 2012年第11期2293-2296,共4页 Journal of Modern Oncology
基金 上海卫生局课题(编号:2008y078) 上海第一妇婴保健院院内课题资助(编号:2008-B-07)
关键词 乳腺癌 危险度评价模型 LOGISTIC回归模型 判别分析 breast cancer risk assessment model for risk factor Logistic regression model discriminant analysis
  • 相关文献

参考文献8

  • 1Matthew E,Mealiffe Renee,P Stokowski. Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information[J].Journal of the National Cancer Institute,2010,(21):1605-1606.
  • 2Lambrechts S,Decloedt J,Neven P. Breast cancer prevention:lifestyle changes and chemoprevention[J].Acta Clinica Belgica,2011,(04):283-292.
  • 3Lech R,Przemys O. Ginekol Pol.Epidemiological models for breast cancer risk estimation[J].Cancer,2011,(06):451-454.
  • 4Amir E,Freedman OC,Seruga B. Assessing women at high risk of breast cancer:a review of risk assessment models[J].Journal of the National Cancer Institute,2010,(10):680.
  • 5Judy C Boughey,Lynn C Hartmann,Stephanie S. Evaluation of the Tyrer-Cuzick (International Breast Cancer Intervention Study) model for breast cancer risk prediction in women with atypical hyperplasia[J].Journal of Clinical Oncology,2010,(22):3591-3596.
  • 6Narod SA,Salmena L. BRCA1 and BRCA2 mutations and breast cancer[J].Discov Med,2011,(66):445-453.
  • 7Laino C. 21-Gene panel predicts which node-positive breast cancer patients[J].Chemother Oncol Times,2008,(09):26.
  • 8Mook S,Schmidt MK,Viale G. The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study[J].Breast Cancer Research and Treatment,2009,(02):295-302.

同被引文献48

引证文献4

二级引证文献19

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部