Development and external validation of prognostic nomograms in hepatocellular carcinoma patients: a population based study
Authors Xiao Z, Yan Y, Zhou Q, Liu H, Huang P, Zhou Q, Lai C, Zhang J, Wang J, Mao K
Received 18 October 2018
Accepted for publication 25 February 2019
Published 10 April 2019 Volume 2019:11 Pages 2691—2708
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 4
Editor who approved publication: Dr Kenan Onel
Zhiyu Xiao1,2,*, Yongcong Yan1,2,*, Qianlei Zhou1,2,*, Haohan Liu1,2, Pinbo Huang1,2, Qiming Zhou1,2, Changliang Lai1,2, Jianlong Zhang1,2, Jie Wang1,2, Kai Mao1,2
1Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People’s Republic of China; 2Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People’s Republic of China
*These authors contributed equally to this work
Background: We attempted to construct and validate novel nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with hepatocellular carcinoma (HCC).
Methods: Models were established using a discovery set (n=10,262) obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Based on univariate and multivariate Cox regression analyses, we identified independent risk factors for OS and CSS. Concordance indexes (c-indexes) and calibration plots were used to evaluate model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis (DCA).
Results: Our OS nomogram with a c-index of 0.753 (95% confidence interval (CI), 0.745–0.761) was based on age, sex, race, marital status, histological grade, TNM stage, tumor size, and surgery performed, and it performed better than TNM stage. Our CSS nomogram had a c-index of 0.748 (95% CI, 0.740–0.756). The calibration curves fit well. DCA showed that the two nomograms provided substantial clinical value. Internal validation produced c-indexes of 0.758 and 0.752 for OS and CSS, respectively, while external validation in the Sun Yat-sen Memorial Hospital (SYMH) cohort produced a c-indexes of 0.702 and 0.686 for OS and CSS, respectively.
Conclusions: We have developed nomograms that enable more accurate individualized predictions of OS and CSS to help doctors better formulate individual treatment and follow-up management strategies.
Keywords: surveillance, epidemiology and end results, overall survival, cancer-specific survival, decision curve analysis
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