Constructing an ovarian cancer metastasis index by dissecting medical records

// Yanjun Qu 1 , Yanan He 1 , Zhangming Li 2 , Xiuwei Chen 3 , Qian Liu 4 , Shuangshuang Zou 1 , Congcong Kong 1 , Yixiu Liu 1 , Ce Gao 4 , Guangmei Zhang 1 and Wenliang Zhu 5 1 Department of Gynecology, The First Affiliated Hospital of Harbin Medical University, Harbin, China 2 Department of Pharmacy, Guangdong Hospital of Integrated Chinese and Western Medicine, Foshan, China 3 Department of Gynecology, The Third Affiliated Hospital of Harbin Medical University, Harbin, China 4 Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China 5 Department of Pharmacy, The Second Affiliated Hospital of Harbin Medical University, Institute of Clinical Pharmacy, The Heilongjiang Key Laboratory of Drug Research, Harbin Medical University, Harbin, China Correspondence to: Guangmei Zhang, email: guangmeizhang@126.com Keywords: ovarian cancer; metastasis; CA-125; model integration; ovarian cancer metastasis index Received: August 18, 2017      Accepted: September 22, 2017      Published: November 06, 2017 ABSTRACT Globally, ovarian cancer (OC) is the leading cause of gynecological cancer-associated deaths. Metastasis, especially multi-organ metastasis, determines the speed of disease progression. A multicenter retrospective study was performed to identify the factors that drive metastasis, from medical records of 534 patients with OC. The average number of target organs per patient was 3.66, indicating multi-organ metastasis. The most common sites of metastasis were large intestine and greater omentum, which were prone to co-metastasis. Results indicated that ascites and laterality, rather than age and menopausal status, were the potential drivers for multi-organ metastasis. Cancer antigen (CA) 125 (CA-125) and nine other blood indicators were found to show a significant, but weak correlation with multi-organ metastasis. A neural network cascade-multiple linear regression hybrid model was built to create an ovarian cancer metastasis index (OCMI) by integration of six multi-organ metastasis drivers including CA-125, blood platelet count, lymphocytes percentage, prealbumin, ascites, and laterality. In an independent set of 267 OC medical records, OCMI showed a moderate correlation with multi-organ metastasis (Spearman ρ = 0.67), the value being 0.72 in premenopausal patients, and good performance in identifying multi-organ metastasis (area under the receiver operating characteristic curve = 0.832), implying a potential prognostic marker for OC.