Wei Xu,1,* Bolun Li,1,* Zhanwei Yang,1,* Jingdong Li,2,* Fei Liu,1 Yu Liu3 1Department of Hepatobiliary Surgery, Hunan Provincial Peopleâs Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, Peopleâs Republic of China; 2Department of Hepatobiliary Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Peopleâs Republic of China; 3Department of Pathology, Hunan Provincial Peopleâs Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, Peopleâs Republic of China*These authors contributed equally to this workCorrespondence: Wei Xu, Department of Hepatobiliary Surgery, Hunan Provincial Peopleâs Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, Peopleâs Republic of China, Tel +8613873159491, Fax +8673182278012, Email xuwei0209@163.com Jingdong Li, Department of Hepatobiliary Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Peopleâs Republic of China, Tel +8615881750153, Fax +868172222856, Email lijingdongnc@163.comBackground: Hepatocellular carcinoma (HCC) is a prevalent and aggressive malignancy closely related to background chronic liver disease. This study aimed to explore predictive factors associated with background liver fibrosis burden in patients with HCC and sought to construct a practical predictive model for clinical use.Methods: This large two-center retrospective cohort study evaluated data from Chinese medical centers. Uni- and multivariate ordinal logistic regression analyses were performed to identify variables associated with liver fibrosis stages. Predictive models based on variables identified by multivariate analysis were established in the Derivation Cohort and subjected to internal and external validation. Model performance was evaluated for discriminative and calibration abilities.Results: Multivariate ordinal logistic regression analysis identified liver fibrosis severity score (LFSS), portal hypertension (PH) severity, plateletcrit (PCT) and model for end-stage liver disease-sodium (MELD-Na) as independent predictors of liver fibrosis stage in HCC patients. Nomograms that integrated these factors disclosed that the area under receiver operating characteristic curves (AUROCs) to predict S1 in the Derivation and External Validation cohorts were 0.850 and 0.919, respectively. Internal validation disclosed C-indexes of 0.823 and 0.833 in the Derivation and External Validation cohorts, respectively, indicating that the nomogram had good and excellent performance for distinguishing between S1 and non-S1 patients. Nomogram performance in the Derivation and External Validation cohorts, respectively, was fair and good to predict stage S2 (AUROCs 0.726, 0.806; C-indexes 0.713, 0.791); poor for S3 (AUROCs 0.648, 0.698; C-indexes 0.616, 0.666); good for S4 (AUROCs 0.812, 0.824; C-indexes 0.804, 0.792); and good for S3+S4 (AUROCs 0.806, 0.840; C-indexes 0.795, 0.811).Conclusion: We propose new predictive models for the staging of background liver fibrosis in patients with HCC that can be implemented into clinical practice as important complements to hepatic imaging to inform HCC management strategy.Keywords: hepatocellular carcinoma, liver fibrosis, portal hypertension, MELD-Na, plateletcrit