Intrahepatic cholangiocarcinoma (ICC) is the second most prevalent primary liver cancer distinguished by its aggressive nature, accounting for approximately 15–20% of all biliary malignancies (1, 2). The worldwide incidence of ICC has been consistently rising at a yearly rate of 15% over the past few decades (1). Curative surgical resection currently stands as the gold-standard treatment for ICC. However, only about 20%–40% of patients who get curative surgical resection survive 5 years or more (3, 4). Therefore, the identification of novel prognostic indicators for distinguishing ICC patients who would benefit from curative surgical resection is crucial for developing personalized treatment strategies.

Increasing evidence suggests that in addition to common factors such as lymph node metastasis, tumor size, and vascular invasion, nutritional status and inflammatory levels play a significant predictive role in the prognosis of curative surgical resection for tumors (5, 6). Among them, the Systemic Immune-Inflammation Index (SII) is a fresh quantitative indicator used to assess individual immune status and inflammation levels (7, 8). It is calculated based on parameters such as platelet, neutrophil, and lymphocyte counts. SII is frequently used to assess patients’ preoperative nutritional status and precisely evaluate their individual surgical risks (8). Additionally, the Albumin–bilirubin (ALBI) grade is a composite indicator that comprehensively evaluates patients’ liver function and reserves. Its introduction was first compared to Child-Pugh classification in hepatocellular carcinoma (HCC) patients in 2015, demonstrating superior predictive capability for survival following liver resection and postoperative liver failure (9). A growing body of literature indicates a close association between SII, ALBI, and the prediction of prognosis and survival in patients with HCC, ICC, and other malignancies (9–13). However, whether the combined application of SII and ALBI can improve the prognostic prediction in patients with ICC remains inconclusive. This research seeks to identify the combined application of SII and ALBI in predicting postoperative survival after curative resection for ICC and attempt to construct a survival prognostic model based on SII and ALBI.

A total of 374 patients (172 male and 202 female) who underwent curative surgical resection for pathologically confirmed ICC from January 2016 to January 2020 were included in this study. The median age of the patients was 59 years, ranging from 28 to 80 years. The median follow-up time was 12 months (1-91 months). The 1-year, 2-year, and 3-year OS rates were 52.1%, 23.3%, and 10.9%, respectively. The 1-year, 2-year, and 3-year RFS rates were 29.2%, 15.5%, and 5.3%, respectively. As can be seen in Table 1 , the baseline data and clinicopathological traits of the training set (n=258) and validation set (n=116) were examined for their association. The two cohorts’ distributions were balanced (p>0.05).

Curative surgical resection represents the gold standard for the treatment of ICC (14). The decision to proceed with surgical resection is often based on the patient’s imaging data and the presence of accompanying symptoms. However, even among patients with similar disease stages and grades, there exists significant heterogeneity in the prognosis and clinical response to curative surgical resection (15). Therefore, the identification of a robust intraoperative and postoperative risk prediction tool holds paramount importance.

As a composite index of platelet, lymphocyte, and monocyte counts, SII provides a direct reflection of the body’s inflammatory status. Increasing evidence suggests that platelets and monocytes can interact with tumor cells through various mechanisms, promoting tumor cell survival and metastasis, enhancing cancer cell invasion, proliferation, and immune evasion, thereby modulating the interplay between the host and tumor (16–19). On the other hand, lymphocytes play a crucial role in cell-mediated immune destruction of cancer cells by activated T cells and other lymphocytes, while tumors can also release cytokines such as IFN-γ and TNF-α to regulate various immune functions in the body (20, 21). Furthermore, numerous studies have confirmed that SII is an independent prognostic factor for postoperative survival in various digestive system malignancies, including HCC, ICC, and gallbladder cancer (8, 22–25). Similarly, in our study, a lower SII was significantly associated with improved postoperative survival and reduced recurrence rates, further validating this observation.

Albumin-bilirubin, calculated based on serum albumin and bilirubin levels, provides an intuitive reflection of a patient’s immune status and liver function; ALBI was initially proposed by Johnson et al. in 2014 as an alternative to the Child-Pugh classification for assessing liver function in HCC patients, overcoming its limitations (26). Increasing evidence suggests that ALBI is a reliable indicator of liver functional reserve. A multicenter cohort study demonstrated that the predictive performance of the Barcelona Clinic Liver Cancer (BCLC) staging system based on ALBI score is comparable to or even superior to that based on the Child-Pugh classification (27). Subsequently, the predictive ability of ALBI for the prognosis of HCC and ICC patients has been validated in multiple independent cohorts, including those from Japan, China, and other countries (28–30). Consistent with the findings of these studies, in our research, the low ALBI group exhibited significantly higher OS and RFS rates compared to the high ALBI group.

In our study, we took into consideration the patients’ inflammatory status, immune capacity, and liver function, by combining SII and ALBI, which were categorized into three grades: A, B, and C. Through the construction of Kaplan-Meier survival curves and ROC survival curves, we found that the SII+ALBI grade had better predictive ability and discrimination when compared separately to SII and ALBI. Therefore, we included the SII+ALBI grade as an independent grade index in our model and confirmed that the nomogram predictive model incorporating SII+ALBI grade for OS and RFS demonstrated good predictive performance. Additionally, we analyzed the correlation between SII+ALBI grade and clinical and pathological characteristics. Surprisingly, for indicators such as microvascular invasion and 8th edition AJCC N stage, which showed no significant correlation with individual SII or ALBI, the SII+ALBI classification still exhibited a correlation. Therefore, we believe that the SII+ALBI classification can better reflect the patients’ clinical and pathological characteristics to a certain extent.

After reviewing relevant research, we found that our study is the first to combine SII and ALBI and construct a prognostic survival model based on SII+ALBI grade. In our model, SII+ALBI grade carries a significant weight, which is closely related to representing the immune-inflammatory status and liver function. Additionally, we plotted ROC survival curves and calibration curves for the training and validation sets based on the predictive model. The results demonstrated excellent predictive ability of the model for postoperative survival in patients with ICC.

In addition, our study has the following limitations. Firstly, although it is a multicenter retrospective study, the sample size involved in the study is relatively small, with a total of 374 cases. Secondly, due to the retrospective nature of this study, selection bias is unavoidable, and we only included patients who underwent surgical resection without receiving other treatments prior to surgery. Thirdly, despite our efforts to minimize the impact of confounding factors on the study results, individual differences in various laboratory parameters cannot be completely eliminated. Therefore, further large-scale prospective multicenter studies are still needed to validate our findings.

In conclusion, this multicenter study included a sample of 374 patients with ICC who underwent surgical resection in three tertiary hospitals. Based on univariate, multivariate, and clinical significance analyses, multiple relevant indicators incorporating the SII+ALBI grade were incorporated to construct a nomogram predictive model for OS and RFS. The model demonstrated excellent accuracy in survival prediction. To our knowledge, this is the first clinical prediction model for ICC that includes the SII+ALBI grade. We believe that this model can provide better guidance for the management of ICC and has the potential for broad application.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

This study received ethical approval from the Institutional Review Boards of Zhengzhou University People’s Hospital (Ref No. 2023-012), Zhengzhou University Cancer Hospital (Ref No. 2023-203), and Zhengzhou University First Affiliated Hospital (2021-KY-1137-002). Written informed consent was obtained from all patients prior to their participation in the study. The studies were conducted in accordance with the local legislation and institutional requirements.

HZ is the first author. HZ, QL and HY conceived and designed the study. HZ, GH, ZY, KC and BM collected and offered the data. HZ, GH and ZY performed follow-up and statistical analysis. HZ wrote the manuscript. HY critically revised the manuscript for important intellectual content. All authors contributed to the article and approved the submitted version.