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Ovarian Cancer Screening Based on Mixture Change-Point Model

Ovarian Cancer Screening Based on Mixture Change-Point Model
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摘要 Ovarian cancer is one of the most deadly female genital malignant tumors in many regions while an effective early screening strategy can save numerous lives.CA125 and HE4 are tumor markers validated efficacious as well as most commonly used in recent screening research of ovarian cancer.In this paper,the authors construct a change-point and mixture model on the basis of longitudinal CA125 and HE4 levels and estimated parameters using maximum likelihood method with the preclinical duration assumed right-censored,which is more adaptive and yields comparable results in comparison to the Bayesian approach raised by Skates.Consistency of estimators is proved.The authors also run a 5-year simulation of sequential screening by calculating the risk of cancer and hypothesis testing the true incidence time respectively.Results show that diagnosis based on hypothesis test performs better in early detection.
机构地区 School of Mathematics
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2015年第2期471-488,共18页 系统科学与复杂性学报(英文版)
基金 supported by the Ph.D. Programs Foundation of Ministry of Education of China under Grant No.20090001110005 the National Natural Science Foundation of China under Grant No.11171007
关键词 Change-point mixture model longitudinal data analysis maximum likelihood estimation ovarian caner screening. 变点模型 混合模型 卵巢癌 筛查 参数估计 早期检测 肿瘤标志物 最大似然法
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