Literature DB >> 26409552

Looking for optimized weights of CA125 and HE4 in early screening system of ovarian cancer for Korean patients.

Hye-Jeong Song1,2, Kyeong-Min Nam1,2, Jong-Dae Kim1,2, Chan-Young Park1,2, Yu-Seop Kim1,2.   

Abstract

We try to find out the best weight values of CA125 and HE4 in a discriminant formula classifying ovarian cancer patients from benign patients. We utilize a logistic regression analysis for the early screening system of the ovarian cancer for Korean patients. We compare our system with ROMA (Risk of Ovarian Malignancy Algorithm) of Abbot corp. In view of AUC (Area under the ROC curve), sensitivity with 95% of specificity and accuracy are considered. We performed experiments based on the logistic regression analysis separated by the case of pre- and post- menopausal stages and by the stages of progression of cancer. In our experiments, we can increase about 15.6% points of sensitivity with 95% of specificity, compared to that of ROMA. In premenopausal cases, ROMA shows 93.32% of AUC value and our system shows 97.48% of AUC, 4.1% points higher than ROMA. AUC of the ROMA for premenopausal women was 93.32%, whereas the AUC of our system was 97.48%. Furthermore, the AUC of the ROMA for early-staged ovarian cancer was 91.35%, whereas the AUC of our system was 97.22%, showing that the diagnostic performance of our system was superior over that of the ROMA in Korean patient cases.

Entities:  

Keywords:  CA125; HE4; Risk of ovarian malignancy algorithm; epithelial ovarian cancer; ovarian cancer; sensitivity; specificity; tumor marker

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Year:  2015        PMID: 26409552     DOI: 10.3233/THC-151065

Source DB:  PubMed          Journal:  Technol Health Care        ISSN: 0928-7329            Impact factor:   1.285


  1 in total

1.  The power of the Risk of Ovarian Malignancy Algorithm considering menopausal status: a comparison with CA 125 and HE4.

Authors:  Kyung Hee Han; Noh Hyun Park; Jin Ju Kim; Sunmie Kim; Hee Seung Kim; Maria Lee; Yong Sang Song
Journal:  J Gynecol Oncol       Date:  2019-11       Impact factor: 4.401

  1 in total

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