HCC is aggressive cancer that displays high molecular diversity and a propensity for postoperative relapse [2]. The survival outcomes of HCC patients are heavily influenced by complex tumor characteristics and the wide range of therapeutic modalities [3]. To date, few accurate and user-friendly models exist for predicting the prognosis of HCC. In this study, we developed clinical prognostic nomograms of HCC patients utilizing multiple clinicopathological variables obtained from the SEER database. The results of AIC, BIC, C-index, AUC, calibration curves, and DCA curves validated the robust discrimination and superior net benefit of our nomograms in the prognosis of HCC patients. According to the model, HCC patients could be effectively divided into three groups (high-, intermediate-, and low-risk groups) with significant OS and CSS. In addition, the results of the subgroup survival curves demonstrate that nomograms can provide reliable risk stratification of HCC patients.

In this study, we identified the independent prognostic factors for the OS and CSS of HCC patients. From the perspective of the patient’s condition, we found that age was one of the prognostic factors in HCC patients. Our survival analysis revealed that older age was significantly associated with shorter OS, but did not exhibit such a correlation with CSS. Cumulative survival diminishes with increase in patient age, and survival was inversely associated with age at diagnosis, which was in agreement with the results of a previous retrospective study [23]. The potential reason for the reduced survival rate in elderly HCC patients may be the cumulative impact of liver damage due to chronic liver disease, as well as other risk factors such as obesity and diabetes, which are commonly encountered in the elderly population [24].

From the perspective of the tumor, tumor size, T stage, N stage, M stage, histological grade, distant lymph node metastasis, and AFP level were identified as independent prognostic factors of HCC. Tumor size, tumor stage, and degree of differentiation are closely related to the biological behavior of the malignant tumor. Generally, larger tumors tend to result in worse clinical outcomes, higher risk of recurrence, and increased mortality than smaller ones [25]. In addition, tumor size is also an important factor to select the treatment for HCC [26]. Small tumors may be more effectively treated with curative treatments such as surgery, and radiofrequency ablation, while large tumors may require more intensive treatments such as transarterial chemoembolization (TACE), systemic chemotherapy, or radiation therapy [27]. Our study further confirmed that tumor size is an independent prognostic factor for HCC patients, which may provide a useful reference in predicting mortality risk and selecting appropriate treatment. The histological grade is also crucial in assessing the aggressiveness of HCC, selecting treatment options, and predicting outcomes [28]. HCCs are typically graded on a scale of 1–4, with a higher grade indicating a more aggressive neoplasm. Previous studies have shown a strong correlation between high histological grade and poor survival [29]. Our study verified the prognostic value of histological grade for HCC, which facilitates the assessment of the aggressiveness of cancer. Regarding distant lymph node metastasis, it is recognized as an important route of HCC dissemination, thereby serving as an important marker of invasiveness [30]. Previous studies have indicated that HCC patients with lymph node metastasis have worse prognoses compared to those without metastasis [31]. Early management of lymph nodes has the potential to prolong survival [30]. Our survival analysis further validated that distant lymph node metastasis is an independent prognostic factor for HCC patients, which may guide early intervention. AFP, a glycoprotein, has been widely utilized as a diagnostic and prognostic biomarker in HCC patients [32]. Elevated AFP levels correlate with larger tumor sizes and poorer prognosis [33]. Consistent with previous observations, our findings suggest that AFP is a prognostic factor in HCC and that increased AFP levels are negatively associated with both overall survival and cancer-specific survival. The T stage denotes the magnitude and extent of the primary tumor in the liver. The T stage (tumor size) has consistently been regarded as a vital prognostic factor for HCC and has been extensively incorporated in various conventional HCC staging systems for guiding therapy [34]. For instance, early-stage HCC may be eligible for surgery, while advanced-stage HCC may necessitate systemic therapy [35]. Vascular invasion of multiple tumors in hepatocellular carcinoma (HCC) may herald advanced T stage. The vascular invasion has the potential to promote the spread of malignant cells to distant organs via the bloodstream, thereby enhancing tumor growth and metastasis [36]. Metastatic disease (including lymph node metastasis and distant metastasis) was regarded as a sign of advanced stage [37]. The presence of metastases is associated with a worse outcome than HCC without metastases. One reason for the difference in outcome is that metastatic disease often implies that cancer has extended beyond the liver and is affecting other vital organs, such as the lungs or bones [12]. This can make treatment more difficult and may limit the options available. In addition, metastatic HCC is more likely to be associated with underlying liver dysfunction, such as cirrhosis, which can further complicate treatment and contribute to a poor outcome. Another factor that may explain the worse outcome of metastatic HCC is that it tends to be less responsive to treatment than localized HCC [38]. We included T, N, and M stages in the nomograms and found that risk scores were higher for T3–T4, N1, and M1 stages than for T1–T2, N0, and M0 stages, indicating a worse prognosis.

From the perspective of therapies, resection, lobectomy, hepatectomy, transplant, and surgery to lymph nodes were independent favorable factors for HCC patients. These methods had a superior ability to improve the prognosis of HCC patients compared to no treatment. Furthermore, patients who had liver resection had a better prognosis, followed by liver transplantation, confirming the previous finding [39,40,41]. Surgical resection seems to be the optimal treatment strategy for HCC, especially for early-stage patients [42]. Additionally, the application of lymph node surgery can also improve the prognosis of HCC patients, which should be related to reducing tumor distant metastasis [43]. It is noteworthy that adjuvant therapies, such as chemotherapy and radiotherapy, are usually deemed to prolong the survival of cancer patients [44, 45]. However, there has been some controversy surrounding this idea. A meta-analysis indicated that fluorouracil-based adjuvant chemotherapy does not improve overall survival in patients with colorectal cancer [46]. So far, severe lymphocyte depletion induced by radiotherapy was an unfavorable prognostic factor for overall survival in lung cancer patients [47]. In our study, radiotherapy and chemotherapy were also not identified as independent prognostic factors for HCC patients. Therefore, the benefit of chemotherapy and radiotherapy in HCC patients still needs further investigation.

Compared with previous studies, this study made the following improvements. Firstly, subgroup analysis results manifested that our nomograms had high accuracy in each subgroup, such as in predicting the prognosis of AFP-positive and elderly HCC [48, 49]. Second, we employed the competing risk model and the LASSO method to select the prognostic factors. The competing risk model offers a solution to the limitation of the Cox risk model, which is typically employed in etiological studies, as it allows for the simultaneous and more accurate consideration of multiple endpoint events. Moreover, the LASSO regression can address the issue of overfitting [50]. Thirdly, our study selected patients with AFP tests during 2010–2017 for analysis [51]. We found that AFP was indeed an important prognostic factor for HCC, providing higher predictive accuracy. Fourthly, we employed several novel indicators to assess the performance of our study, including C-index, AUC, NRI, IDI, AIC, and BIC. These indicators provided compelling evidence that our model is excellent in predicting the prognosis of patients with hepatocellular carcinoma. Finally, liver resection and liver transplantation are important current treatments for HCC [50], and liver resection can be divided into lobectomy and hepatectomy, with patient prognostic outcomes likely to vary depending on the surgery chosen. If the information on surgery is dichotomized, then the impact of different surgical approaches on the prognosis of HCC patients cannot be studied. Our study divided surgical treatment into multiple variables, but not a binary variable. We examined the impact of different treatment approaches on HCC and obtained a more comprehensive prognostic analysis. Our developed nomograms improve on the inherent deficiencies of AJCC staging by incorporating several important HCC risk factors such as age, grade, and AFP [52]. In addition, the developed nomograms can stratify risk compared to AJCC staging. Tumor stratification may enable clinicians to devise tailored therapeutic approaches to achieve improved clinical outcomes for patients.

Our study is based on SEER data [13]. Owing to big data, the diagnosis of patients is precisely categorized, eliminating the interference of their malignant tumor history. Moreover, the number of HCC patients recorded in the SEER database is immense, which facilitates us to construct a more accurate model. In addition, the items incorporated in our nomograms are common clinically, easily accessible, and comprehensible items that can be easily implemented even in primary hospitals.

This study represented one of the largest cohorts focusing on the prognosis of HCC patients. The data were collected from multiple centers, and heterogeneity in various centers could be successfully resolved. However, our study has some limitations. First, this large-sample retrospective study was based on the SEER database, which may have some inherent biases. Second, data regarding several potentially important prognosis-related factors such as microvascular invasion, hepatitis status, performance status, Child score, MELD score, and anti-viral therapy were not available in the SEER database. Third, the predictive model was developed based on data obtained from the SEER database, which cannot represent the global population. Although our nomograms did not integrate all the prognostic factors mentioned above, they still achieved a relatively specific prediction of the prognosis of HCC patients and had a significantly higher C-index than the conventional staging systems. Our nomograms were internally validated, and it needs to be validated externally using other populations.