Clinical predictive models for individualized treatment of hepatocellular carcinoma

Hepatocellular carcinoma ( HCC) is one of the most common malignant tumors in China and has high incidence and mortality rates. HCC is often accompanied by hepatitis and liver cirrhosis, and therefore, there is high demand for precise treatment based on disease stage, tumor location, and liver function. Various diagnostic and treatment methods used in clinical practice have a certain therapeutic effect on HCC, and the issue of effective prognostic analysis and selection of individualized treatment regimen needs to be solved urgently. There are many predictive systems for the prognosis of HCC, among which nomogram can better help with the individualized analysis of HCC patients and has thus attracted more and more attention. At present, various nomographic predictive models have been established for different types of HCC; such models integrate some clinical and pathological indices, such as tumor markers, liver function, HBV indices, and microvascular tumor thrombus, and then risk score is calculated for each patient to predict prognosis. Meanwhile, clinicians can select the appropriate therapeutic method and postoperative anti-recurrence treatment based on the level of risk to achieve the goal of individualized treatment.