Clinical model for predicting overall survival outcomes in individuals with hepatocellular carcinoma: a retrospective...

The prognostic factors for survival outcomes in patients with hepatocellular carcinoma (HCC) are not well defined. This study aimed to identify the prognostic factors for HCC and to construct a predictive nomogram model.

A total 165 patients with HCC were identified between 25 January 2010 and 10 November 2021. Independent prognostic factors were identified using univariable and multivariable Cox regression analyses. A nomogram was constructed to predict the patient survival rate. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to assess the predictive accuracy and discrimination of the model. Decision curve analysis was used to confirm the clinical utility of the nomogram.

A total of 165 patients were randomly selected retrospectively. Univariable and multivariable analyses revealed that body mass index, albumin, carbohydrate antigen 19-9 (CA19-9), tumor size, and tumor size, lymph node, metastasis (TNM) stage were independent factors for predicting patient survival. We constructed a 1-, 3-, and 5-year survival rate prediction clinical model by using these independent prognostic factors, which yielded C-indexes of 0.838, 0.798 and 0.725, respectively. On the basis of the AUCs and calibration curve and decision curve analyses, we concluded that the prognostic model for HCC exhibited excellent performance.

The clinical model demonstrated good calibration, discrimination, clinical utility, and practical decision-making effects for the outcomes of patients with HCC. These findings may help oncologists and surgeons make better clinical decisions.