The mortality of ovarian cancer is higher than any other female genital malignant tumors, while there exists a strong correlation between early-stage detection and cure for it. CA125 and HE4 are two most common and ef...The mortality of ovarian cancer is higher than any other female genital malignant tumors, while there exists a strong correlation between early-stage detection and cure for it. CA125 and HE4 are two most common and effective serum markers in recent screening research of ovarian cancer. This paper derives a sequential screening strategy for ovarian cancer by jointly modeling the longitudinal profiles of CA125 and HE4. We construct a Bayesian hierarchical mixture model with changepoint, and propose two approaches for diagnosis： the risk of cancer index and the hypothesis test on the true incidence time. We simulated a 7-year sequential screening research and compared with the standard approach based on a fixed cutoff level. Our approach achieves a 15% higher sensitivity for a fixed specificity, indicating that the sequential strategy combining multiple markers is more effective in the early-stage detection of ovarian cancer.展开更多
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 wel...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.展开更多
基金Supported by the the National Natural Science Foundation of China(Grant No.11171007)Ph.D. Programs Foundation of Ministry of Education of China(No.20090001110005)
文摘The mortality of ovarian cancer is higher than any other female genital malignant tumors, while there exists a strong correlation between early-stage detection and cure for it. CA125 and HE4 are two most common and effective serum markers in recent screening research of ovarian cancer. This paper derives a sequential screening strategy for ovarian cancer by jointly modeling the longitudinal profiles of CA125 and HE4. We construct a Bayesian hierarchical mixture model with changepoint, and propose two approaches for diagnosis： the risk of cancer index and the hypothesis test on the true incidence time. We simulated a 7-year sequential screening research and compared with the standard approach based on a fixed cutoff level. Our approach achieves a 15% higher sensitivity for a fixed specificity, indicating that the sequential strategy combining multiple markers is more effective in the early-stage detection of ovarian cancer.
基金supported by the Ph.D. Programs Foundation of Ministry of Education of China under Grant No.20090001110005the National Natural Science Foundation of China under Grant No.11171007
文摘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.
