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Case-control study of metabolic syndrome and ovarian cancer in Chinese population

Chen, Ying, Zhang, Lei, Liu, Wenxin, Wang, Ke
Nutrition & metabolism 2017 v.14 no.1 pp. 21
blood glucose, body mass index, case-control studies, chi-square distribution, diabetes, diastolic blood pressure, epithelium, high density lipoprotein cholesterol, histology, hospitals, interviews, lymph nodes, metabolic syndrome, metastasis, models, ovarian neoplasms, patients, prognosis, regression analysis, risk factors, systolic blood pressure, triacylglycerols, China
BACKGROUND: Recent studies have proved metabolic syndrome (MetS) was linked to cancer risks. However, few data has examined the relationship between MetS and epithelial ovarian cancer (EOC). METHODS: We conducted a population-based case-control study in Tianjin Medical University Cancer Institute and Hospital, China (2010–2015) that enrolled 573 EOC patients and 1146 matched controls. Data were collected through in-person interviews, anthropometric measurement, and 8-h fasting bloods drawn. MetS was estimated by Chinese Diabetes Society (CDS) definition requiring presence of ≥3 of the following risk factors: 1) body mass index (BMI) ≥25.0 kg/m²,2) fasting plasma glucose ≥6.1 mmol/L or 2-h plasma glucose ≥ 7.8 mmol/L, 3) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, 4) triglyceride (TG) ≥1.70 mmol/L or high-density lipoprotein cholesterol (HDL-C) < 1.0 mmol/L. Statistics were completed using chi-square tests and logistic regression analysis. The survival analysis was conducted by the Kaplan-Meier method and Cox proportional hazard regression models. RESULTS: MetS was significantly more prevalent among EOC (25.13%) than controls (6.89%). A statistically significant increase risk for EOC was observed for MetS (multivariable-adjusted OR = 3.187; 95% CI: 2.135–4.756). MetS was significantly associated with histological grade (P < 0.001), FIGO stage (P = 0.003), and lymph node (LN) status (P = 0.002) of EOC. In binary logistic regression analysis, the presence of MetS predicts the risk of advanced FIGO stage (OR = 2.155, 95% CI: 1.327–3.498, P = 0.002), lower differentiation (OR = 2.472, 95% CI: 1.164–5.250, P = 0.019), and LN metastasis (OR = 2.590, 95% CI: 1.089–6.160, P = 0.031) of EOC. Moreover, MetS is the independent factor for the evaluation of PFS and OS of EOC patients (both of them P < 0.001) in Cox proportional hazard model. CONCLUSION: MetS is obviously related to increased EOC risk. EOC patients with MetS in Chinese population were found to have statistically significant tumor advanced stage, low differentiation, LN metastasis and poor prognosis.