ICC is a prevalent form of liver cancer, representing 5%-20% of all liver malignancies. Its occurrence is on the rise(Van Dyke et al. 2019; Wu et al. 2019). The inflammatory environment is believed to cause damage to DNA and stimulate the growth of bile duct cells, leading to a potentially harmful situation (Andersen 2015; Sia et al. 2013). The prognosis for ICC patients is generally poor, with high recurrence rates even after surgical excision. As a result, it is crucial to investigate biomarkers that can aid in risk stratification and treatment guidance.
Numerous studies have reported that inflammation is a crucial factor in the development of various types of tumors(Mei et al. 2014; Sano et al. 2018). Mezquita et al(Feng et al. 2021; Laura Mezquita et al. 2018; Obayashi et al. 2022) introduced LIPI, a novel hematologic marker based on inflammatory indicators composed of dNLR and LDH, which plays a significant role in lung cancer. He et al. demonstrated creativity by developing OIPI, a predictor specifically designed for bone tumors. They combined the role of LIPI in lung cancer to create OIPI, which plays a crucial role in predicting the prognosis and metastasis of bone tumors(He et al. "Osteosarcoma Immune Prognostic Index Can Indicate the Nature of Indeterminate Pulmonary Nodules and Predict the Metachronous Metastasis in Osteosarcoma Patients" 2022; He et al. "Prognostic Significance of Modified Lung Immune Prognostic Index in Osteosarcoma Patients" 2022). To date, there has been no reports on the prognostic effect of LIPI in patients with ICC.
This study aimed to establish a prognostic model called IIPI for ICC patients after surgery, inspired by the crucial role of LIPI in predicting prognosis and guiding immunotherapy selection in lung cancer. The study applied factors in LIPI to ICC patients and found that LDH was not effective in predicting the prognosis of ICC (Fig. 1). In this study, CA-199 and CEA biomarkers were found to be still significant in predicting the prognosis of ICC, which is consistent with the findings of Moro et al(Amika Moro et al. 2020). The study combined LIPI with CEA and CA199 to develop IIPI. The results showed that IIPI had a higher prediction efficiency than other markers of hematology and clinical characteristics, as measured by ROC. After conducting both univariate and multivariate analysis, our findings indicate that IIPI can serve as an independent risk factor for predicting the prognosis of ICC patients. It was observed that the IIPI score was able to precisely and consistently reflect the prognosis of postoperative ICC patients. Our survival analysis (refer to FIG. KM) further supports this claim, as higher IIPI scores were associated with poorer prognosis.
Since its initial proposal, the nomogram graph has become a widely utilized tool in various studies, aiding clinicians in both diagnosis and treatment of patients(Lu et al. 2021). Incorporating clinical characteristics and IIPI, we have developed an IIPI-based nomogram to predict the prognosis of ICC patients. By using individual information and corresponding values, a total score can be calculated to assess the risk of prognosis for patients. The study demonstrates the high accuracy of the IIPI-based nomogram graph in predicting 3 and 5-year metastasis rates in ICC patients. The IIPI-based nomogram graph was found to be more beneficial in prognosis predicting of postoperative ICC patients compared to the prediction model without IIPI, as confirmed by the DCA curve. Thus, the nomogram can be considered as a reliable predictor of prognosis in ICC patients.
Recent studies have focused on developing prognostic models for ICC patients. However, the traditional hematological indicators CEA and CA-199 have limited prognostic effects in predicting the prognosis of ICC patients(He et al. 2018; A. Moro et al. 2020). In recent years, there has been increasing research on the role of inflammation in the development of tumors. As a result, many studies have been conducted to explore the use of inflammatory factors as a means of predicting tumor diagnosis and prognosis(Chao et al. 2020; Qi et al. 2016). In a study analyzing data from 660 patients who underwent ICC hepatectomy, researchers developed the LabScore score by combining platelet count, CA19-9, albumin, and neutrophil to lymphocyte ratio (NLR) to predict ICC prognosis. A higher LabScore indicates a worse prognosis(Tsilimigras et al. 2020). In addition, Qiu’s(Qiu et al. 2021) study highlights the significance of aspartate amination transaminase (AST) to lymphocyte ratio index and CA19-9 level in determining the prognosis of patients with intrahepatic cholangiocarcinoma (ICC). Qiang et al.(Qiang et al. 2021) conducted a study on 237 ICC patients who underwent routine resection and used immunohistochemistry to detect glypican-1 and glypican-3. The study found that high expression of glypican-1 and glypican-3 was associated with a poor prognosis. However, these prediction models often have their own specific limitations. In this study, we utilized the predictive effect of LIPI and applied it to ICC. The results demonstrated that the new predictive model, IIPI, had excellent efficacy in ICC patients and had the strongest sensitivity compared to other features. IIPI categorized postoperative ICC patients into four groups, where high IIPI scores were strongly associated with poorer outcomes.
However, there are several limitations in this study. Firstly, the clinical features of ICC patients after surgical resection were not extensively covered, which may have introduced some bias. Secondly, the study only investigated the prognosis of ICC patients after surgical resection and did not explore the recurrence and metastasis of ICC patients. Further research is needed to address these limitations. This study has limitations due to being a single-center study, which may result in a certain degree of bias as it does not cover a large number of patients or patient information from different institutions.