An in-depth prognostic analysis of baseline blood lipids in predicting postoperative colorectal cancer mortality: The FIESTA study

作者:Peng, Feng; Hu, Dan; Lin, Xiandong; Chen, Gang; Liang, Binying; Chen, Ying; Li, Chao; Zhang, Hejun; Xia, Yan; Lin, Jinxiu*; Zheng, Xiongwei*; Niu, Wenquan*
来源:Cancer Epidemiology, 2018, 52: 148-157.
DOI:10.1016/j.canep.2018.01.001

摘要

Background: Dyslipidaemia is key to colorectal carcinogenesis, and the prediction of baseline triglycerides (TG), total cholesterol (TC), high-and low-density lipoprotein cholesterol (HDLC and LDLC) for postsurgical colorectal cancer mortality has not been researched. Objectives: We attempted to re-analyse the FIESTA database to assess the prognostic value of three informative lipid derivatives - AI (atherogenic index: (TC - HDLC)/HDLC), THR (TG/HDLC) and LHR (LDLC/HDLC) in predicting colorectal cancer mortality. Methods: Based on the FIESTA database, 1318 patients received radical resection from 2000 to 2008, with the latest follow-up completed in December 2015. Median follow-up time was 58.6 months. Results: Total 1318 patients were randomly evenly divided into the derivation and validation groups. Overall, baseline AI and LHR were associated with the significantly increased risk of colorectal cancer mortality in both derivation (hazard ratio (HR): 1.41 and 1.35, respectively) and validation (HR: 1.37 and 1.32, respectively) groups (all P < 0.001). The predictive performance of AI and LHR was remarkably enhanced in patients with female gender, former/current smoking, colon cancer, early stage, positive vein tumor embolus, normal weight, preoperative hypertension or diabetes comorbidities. Calibration/discrimination analyses revealed that adding AI or LHR to the traditional model had a better fit in both groups. A prognostic nomogram was finally constructed with good predictive accuracy and discriminative capability (C-index = 0.814, P < 0.001). Conclusion: We consolidated the prognostic superiority of AI and LHR in predicting colorectal cancer mortality over TNM stage.