Clinical features and prognostic factors of patients with inoperable hepatocellular carcinoma treated with chemotherapy: a population-based study.

Abstract

In inoperable hepatocellular carcinoma (HCC), chemotherapy is a common treatment strategy. However, there is a lack of reliable methods to predict the prognosis of patients with inoperable HCC after chemotherapy. Therefore, the aim of this study was to identify the clinical characteristics of patients with inoperable HCC and to establish and validate nomogram models for predicting the survival outcomes in this patient group following chemotherapy. The data of patients diagnosed with HCC from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively collected. Logistic regression analyses were used to identify potential factors for inoperability in patients with HCC. Kaplan-Meier analyses were applied to evaluate the impact of chemotherapy on prognosis. Additionally, Cox regression analyses were performed to identify the potential risk factors associated with overall survival (OS) and cancer-specific survival (CSS) in patients with inoperable HCC treated with chemotherapy. Finally, we constructed prognostic nomograms for predicting the 1- and 3-year survival probabilities. A total of 3,519 operable patients with HCC and 4,656 patients with inoperable HCC were ultimately included in this study. Logistic regression analyses revealed a significant association between patient age, gender, race, tumor, node, metastasis (TNM) stage, tumor size, pretreatment alpha fetoprotein (AFP) levels, and marital status with inoperability. Moreover, Kaplan-Meier analyses revealed a significant improvement in both OS and CSS with the administration of chemotherapy. Moreover, 1,456 patients with inoperable HCC were enrolled in the training group and 631 patients with inoperable HCC were enrolled in the validation group to develop and validate the prognostic models. Cox regression models indicated that TNM stage, tumor size, and pretreatment AFP were independent risk factors for predicting OS and CSS in patients with inoperable HCC receiving chemotherapy. These factors were subsequently integrated into the predictive nomograms. We preliminarily developed survival models with strong predictive capabilities for estimating survival probabilities in patients with HCC following chemotherapy. These models hold potential for clinical application and warrant further exploration through additional studies.