Simplified nomograms based on platelet-associated models for survival prediction in Asian hepatocellular carcinoma patients after surgery. (September 2019) - Gu, Jingxian; Zhang, Xing; Wang, Zhixin; Cui, Ruixia; Zhang, Jia; Jia, Yifan; Miao, Runchen; Fan, Haining; Wang, Haijiu; Li, Yiming; Zhang, Jingyao; Liu, Chang; et al.
Abstract: Background & aims: Accumulating evidence showed platelets were closely related to hepatocellular carcinoma (HCC) prognosis. We here aimed to develop two simple-to-use nomograms based on the PLT-associated modified models to refine prognostic prediction of Asian HCC. Methods: The nomograms were established using 684 eligible Asian patients who received curative resection for HCC, among which 456 and 228 were randomly assigned to the derivation and validation cohorts, respectively. Univariate and multivariate Cox analyses in the derivation set were used to identify the independent prognostic factors of the hepatectomy patients as the nomogram variables. We evaluated the discrimination and calibration of the nomograms by concordance indexes (C-index), calibration plots and Kaplan-Meier curves. The discrimination ability of the PLT-based nomograms was compared with the conventional staging systems using time-dependent receiver operating characteristic (ROC) curves. Results: The nomogram for overall survival (OS) estimation was comprised of MPV/PC [mean platelet volume/platelet count], SII [systemic immune-inflammation index], NPS [neutrophil-platelet score], PAPAS [platelet count/age/ALP/AFP/AST index] and S index. And the nomogram for recurrence-free survival (RFS) prediction was of NPS, PAPAS and S index. The C-indexes of the OS nomogram in the derivation and validation sets were 0.704 and 0.707, and those of the RFS nomogram were 0.668 and 0.703. The calibration plots fitted well. The survival curves showed great discriminatory powers. The area under the curve (AUC) of our nomograms were significantly larger than that of the three conventional models (P < 0.05). Conclusions: The two PLT-based nomograms were accurate in predicting the OS and RFS of Asian HCC patients after hepatectomy. Highlights: Two simplified nomograms based on PLT-associated models for HCC prognosis prediction were established. The PLT-based nomograms were mainly comprised of inflammation-related and fibrosis- or cirrhosis-related modified models. The ability of the nomograms in predicting the OS and RFS of hepatectomy patients was validated in the validation group. The PLT-based nomograms showed significantly better accuracy than other staging systems from the time-dependent ROC curves. These results underline the prognostic value of PLT and provide extra evidence for the treatment of HCC.