Background Intrahepatic cholangiocarcinoma (ICC) is a highly malignant tumor with a poor prognosis. This study aimed to investigate whether Hemoglobin, Albumin, Lymphocytes, and Platelets (HALP) score and Tumor Burden Score (TBS) serves as independent influencing factors following radical resection in patients with ICC. Furthermore, we sought to evaluate the predictive capacity of the combined HALP and TBS grade, referred to as HTS grade, and to develop a prognostic prediction model. Methods Clinical data for ICC patients who underwent radical resection were retrospectively analyzed. Univariate and multivariate Cox regression analyses were first used to find influencing factors of prognosis for ICC. Receiver operating characteristic (ROC) curves were then used to find the optimal cut-off values for HALP score and TBS and to compare the predictive ability of HALP, TBS, and HTS grade using the area under these curves (AUC). Nomogram prediction models were constructed and validated based on the results of the multivariate analysis. Results Among 423 patients, 234 (55.3%) were male and 202 (47.8) were aged ≥ 60 years. The cut-off value of HALP was found to be 37.1 and for TBS to be 6.3. Our univariate results showed that HALP, TBS, and HTS grade were prognostic factors of ICC patients (all P < 0.05), and ROC results showed that HTS had the best predictive value. The Kaplan–Meier curve showed that the prognosis of ICC patients was worse with increasing HTS grade. Additionally, multivariate regression analysis showed that HTS grade, carbohydrate antigen 19–9 (CA19-9), tumor differentiation, and vascular invasion were independent influencing factors for Overall survival (OS) and that HTS grade, CA19-9, CEA, vascular invasion and lymph node invasion were independent influencing factors for recurrence-free survival (RFS) (all P < 0.05). In the first, second, and third years of the training group, the AUCs for OS were 0.867, 0.902, and 0.881, and the AUCs for RFS were 0.849, 0.841, and 0.899, respectively. In the first, second, and third years of the validation group, the AUCs for OS were 0.727, 0.771, and 0.763, and the AUCs for RFS were 0.733, 0.746, and 0.801, respectively. Through the examination of calibration curves and using decision curve analysis (DCA), nomograms based on HTS grade showed excellent predictive performance. Conclusions Our nomograms based on HTS grade had excellent predictive effects and may thus be able to help clinicians provide individualized clinical decision for ICC patients.

Abstract Background Tumor morphology, immune function, inflammatory levels, and nutritional status play critical roles in the progression of intrahepatic cholangiocarcinoma (ICC). This multicenter study aimed to investigate the association between markers related to tumor morphology, immune function, inflammatory levels, and nutritional status with the prognosis of ICC patients. Additionally, a novel tumor morphology immune inflammatory nutritional score (TIIN score), integrating these factors was constructed. Methods A retrospective analysis was performed on 418 patients who underwent radical surgical resection and had postoperative pathological confirmation of ICC between January 2016 and January 2020 at three medical centers. The cohort was divided into a training set (n = 272) and a validation set (n = 146). The prognostic significance of 16 relevant markers was assessed, and the TIIN score was derived using LASSO regression. Subsequently, the TIIN-nomogram models for OS and RFS were developed based on the TIIN score and the results of multivariate analysis. The predictive performance of the TIIN-nomogram models was evaluated using ROC survival curves, calibration curves, and clinical decision curve analysis (DCA). Results The TIIN score, derived from albumin-to-alkaline phosphatase ratio (AAPR), albumin–globulin ratio (AGR), monocyte-to-lymphocyte ratio (MLR), and tumor burden score (TBS), effectively categorized patients into high-risk and low-risk groups using the optimal cutoff value. Compared to individual metrics, the TIIN score demonstrated superior predictive value for both OS and RFS. Furthermore, the TIIN score exhibited strong associations with clinical indicators including obstructive jaundice, CEA, CA19-9, Child–pugh grade, perineural invasion, and 8th edition AJCC N stage. Univariate and multivariate analysis confirmed the TIIN score as an independent risk factor for postoperative OS and RFS in ICC patients (p < 0.05). Notably, the TIIN-nomogram models for OS and RFS, constructed based on the multivariate analysis and incorporating the TIIN score, demonstrated excellent predictive ability for postoperative survival in ICC patients. Conclusion The development and validation of the TIIN score, a comprehensive composite index incorporating tumor morphology, immune function, inflammatory level, and nutritional status, significantly contribute to the prognostic assessment of ICC patients. Furthermore, the successful application of the TIIN-nomogram prediction model underscores its potential as a valuable tool in guiding individualized treatment strategies for ICC patients. These findings emphasize the importance of personalized approaches in improving the clinical management and outcomes of ICC.

Objective:To study the factors influencing survival after radical resection in patients with intrahepatic cholangiocarcinoma (ICC), and to construct a nomogram on survival prediction.Methods:The clinical data of 139 patients with ICC who underwent radical resection at the People's Hospital of Zhengzhou University from June 2018 to December 2021 were retrospectively analyzed. There are 69 males and 70 females, aged (59.5±10.2) years old. These patients were divided into two groups based on a 3: 1 ratio by using the random number method: the test group ( n=104) and the validation group ( n=35). Data from the test group was used to construct a nomagram and data from the validation group was used to validate the predictive power of the nomagram. Univariate and multivariate Cox regression analyses were used to analyse factors influencing survival on the test group patients and to construct a nomogram. The predictive accuracy of the nomogram was determined by receiver operating characteristic (ROC) curves, concordance index (C-index) and calibration curves. Results:The results of the multivariate regression analysis showed that a combined hemoglobin, albumin, lymphocyte and platelet immunoinflammation (HALP) score <37.1 ( HR=1.784, 95% CI: 1.047-3.040), CA19-9 > 35U/ml ( HR=2.352, 95% CI: 1.139-4.857), poorly differentiated tumor ( HR=2.475, 95% CI: 1.237-4.953) and vascular invasion ( HR=1.897, 95% CI: 1.110-3.244) were independent risk factors that affected prognosis of patients with ICC after radical resection (all P<0.05). The AUCs of the nomogram in the test group in predicting the overall survival at 1, 2 and 3 years of patients with ICC after radical resection were 0.808, 0.853 and 0.859, respectively. There was good consistency between the prediction of the nomogram and actual observation. The predicted C-index of the total survival period of the test group was 0.765 (95% CI: 0.704-0.826), and the C-index of the validation group was 0.759 (95% CI: 0.673-0.845). Conclusion:A HALP score <37.1, CA19-9>35 U/ml, poorly differentiated tumour and vascular invasion were independent risk factors for prognosis of ICC patients after radical resection. The nomogram was established based on the above factors and showed good performance in predicting overall survival after radical resection in patients with ICC.

Background:The degree of inflammation and immune status is widely recognized to be associated with intrahepatic cholangiocarcinoma (ICC) and is closely linked to poor postoperative survival. The purpose of this study was to evaluate whether the systemic immune-inflammatory index (SII) and the albumin bilirubin (ALBI) grade together exhibit better predictive strength compared to SII and ALBI separately in patients with ICC undergoing curative surgical resection.Methods:A retrospective analysis was performed on a cohort of 374 patients with histologically confirmed ICC who underwent curative surgical resection from January 2016 to January 2020 at three medical centers. The cohort was divided into a training set comprising 258 patients and a validation set consisting of 116 patients. Subsequently, the prognostic predictive abilities of three indicators, namely SII, ALBI, and SII+ALBI grade, were evaluated. Independent risk factors were identified through univariate and multivariate analyses. The identified independent risk factors were then utilized to construct a nomogram prediction model, and the predictive strength of the nomogram prediction model was assessed through Receiver Operating Characteristic (ROC) survival curves and calibration curves.Results:Univariate analysis of the training set, consisting of 258 eligible patients with ICC, revealed that SII, ALBI, and SII+ALBI grade were significant prognostic factors for overall survival (OS) and recurrence-free survival (RFS) (p < 0.05). Multivariate analysis revealed the independent significance of SII+ALBI grade as a risk factor for postoperative OS and RFS (p < 0.05). Furthermore, we conducted an analysis of the correlation between SII, ALBI, SII+ALBI grade, and clinical features, indicating that SII+ALBI grade exhibited stronger associations with clinical and pathological characteristics compared to SII and ALBI. We constructed a predictive model for postoperative survival in ICC based on SII+ALBI grade, as determined by the results of multivariate analysis. Evaluation of the model's predictive strength was performed through ROC survival curves and calibration curves in the training set and validation set, revealing favorable predictive performance.Conclusion:The SII+ALBI grade, a novel classification based on inflammatory and immune status, serves as a reliable prognostic indicator for postoperative OS and RFS in patients with ICC.

Objective:A predictive nomogram model for the prognosis of intrahepatic cholangiocarcinoma (ICC) patients after curative resection was constructed based on the albumin-bilirubin score and tumor burden score (ATS) grade, and the predictive performance of the nomogram model was evaluated.Methods:Retrospective analysis of clinical data was made, from ICC patients who underwent curative resection at Zhengzhou University People's Hospital and Zhengzhou University Cancer Hospital from January 2016 to January 2020. A total of 258 patients were included in the study, with 140 males and 118 females, with an average age of (56.5±9.5) years. The 258 ICC patients were randomly divided into a training set ( n=174) and a testing set ( n=84) in a 7∶3 ratio. Single-factor and multi-factor Cox regression analyses were performed to identify prognostic factors for ICC patients of the training set, and then a nomogram model was constructed. The performance of the nomogram model was evaluated by using the concordance index (C-index), calibration curve, and risky decision curve analysis. Results:In the training set, univariate Cox regression analysis indicated that albumin-bilirubin (ALBI), tumor burden score (TBS), carcinoembryonic antigen (CEA), tumor differentitation, lymphvascular invasion and ATS significantly influenced overall survival after radical resection for ICC (all P<0.05). Multifactorial Cox regression analysis revealed that ATS grade, CEA, tumor differentiation, lymphovascular invasion, and AJCC N stage are independent risk factors for the prognosis of ICC patients after curative resection (all P<0.05). Assessment of the postoperative survival prediction model based on multifactorial Cox regression yielded a C-index of 0.775(95% CI: 0.747-0.841) for the training set and 0.731(95% CI: 0.668-0.828) for the testing set. The calibration curves for both the training and testing sets indicated strong predictive capability of the model. Additionally, the risk decision curve also suggested high net benefit of the model. Conclusions:The preoperative ATS grade is an independent factor affecting the survival after ICC radical resection. The nomogram model constructed based on ATS grade demonstrates excellent predictive value for postoperative prognosis in ICC patients.

Radiomics was proposed by Lambin et al. in 2012 and since then there has been an explosion of related research. There has been significant interest in developing high-throughput methods that can automatically extract a large number of quantitative image features from medical images for better diagnostic or predictive performance. There have also been numerous radiomics investigations on intrahepatic cholangiocarcinoma in recent years, but no pertinent review materials are readily available. This work discusses the modeling analysis of radiomics for the prediction of lymph node metastasis, microvascular invasion, and early recurrence of intrahepatic cholangiocarcinoma, as well as the use of deep learning. This paper briefly reviews the current status of radiomics research to provide a reference for future studies.

Objective:To construct a nomogram prediction model for survival after radical surgical resection of intrahepatic cholangiocarcinoma (ICC) based on the albumin-bilirubin index (ALBI), and to evaluate its predictive efficacy.Methods:From January 2016 to January 2020, 170 patients with ICC who underwent radical surgical resection at the People's Hospital of Zhengzhou University were retrospectively analyzed. There were 90 males and 80 females, aged (58.5±10.6) years old. Based on a ratio of 7∶3 by the random number table, the patients were divided into the training set ( n=117) and the internal validation set ( n=53). The training set was used for nomogram model construction, and the validation set was used for model validation and evaluation. Follow up was conducted through outpatient reexamination and telephone contact. The Kaplan-Meier method was used for survival analysis, and a nomogram was drawn based on variables with a P<0.05 in multivariate Cox regression analysis. The predictive strength of the predictive model was evaluated by analyzing the consistency index (C-index), calibration curve, and clinical decision curve of the training and validation sets. Results:Multivariate Cox regression analysis showed that carbohydrate antigen 19-9 (CA19-9) ≥37 U/ml ( HR=1.99, 95% CI: 1.10-3.60, P=0.024), ALBI≥-2.80 ( HR=2.43, 95% CI: 1.40-4.22, P=0.002), vascular tumor thrombus ( HR=2.34, 95% CI: 1.40-3.92, P=0.001), and the 8th edition AJCC N1 staging ( HR=2.18, 95% CI: 1.21-3.95, P=0.010) were independent risk factors affecting postoperative survival of ICC patients after curative resection. The predictive model constructed based on the above variables was then evaluated, and the C-index of the model was 0.76. Calibration curve showed the predicted survival curve of ICC patients at 3 years after surgery based on the model was well-fitted to the 45° diagonal line which represented actual survival. Clinical decision curve analysis showed that the model had a significant positive net benefit in both the training and validation sets. Conclusion:The nomograph model for survival rate after radical resection of ICC was constructed based on four variables: ALBI, CA19-9, vascular tumor thrombus, and AJCC N staging (8th edition) in this study. This model provided a reference for more accurate prognosis evaluation and treatment selection plan for ICC patients.

Objective:To determine the risk factors for development of combined hepatocellular-cholangiocarcinoma (CHC) and intrahepatic cholangiocarcinoma (ICC).Methods:The clinical data of patients with ICC or CHC confirmed by pathology at Henan Provincial People's Hospital from January 2012 to December 2018 were retrospectively analyzed. Of 225 patients with ICC or CHC, there were 90 males and 135 females, aged (58.7±10.4) years old. Based on the pathological type, there were 172 patients in the ICC group and 53 patients in the CHC group. The healthy control group was selected from 450 individuals who underwent routine health examination in the same hospital, and there were 189 males and 261 females, aged (56.7±9.3) years old. Univariate and multivariate logistic regression were used to analyze the risk factors of ICC and CHC.Results:The risk factors of ICC included hepatitis B surface antigen (HBsAg) (+ )/hepatitis B core antibody (anti-HBc) (+ ) ( OR=9.373, 95% CI: 4.784-18.363, P<0.001), hepatitis C virus antibody (HCV-Ab) (+ ) ( OR=7.151, 95% CI: 1.195-42.776, P=0.031), diabetes mellitus ( OR=3.118, 95% CI: 1.733-5.612, P<0.001) and hepatolithiasis ( OR=18.650, 95% CI: 5.210-66.767, P<0.001). The risk factors of CHC included HBsAg (+ )/anti-HBc(+ )( OR=54.891, 95% CI: 17.434-172.822, P<0.001) and HCV-Ab (+ ) ( OR=37.785, 95% CI: 5.720-249.611, P<0.001). Conclusion:HBV infection, HCV infection, hepatolithiasis, diabetes mellitus and cirrhosis were risk factors for ICC. HBV and HCV infection were risk factors of CHC.

Abstract Objective We assess the predictive value impacted by tumor-infiltrating lymphocytes (TILs) for overall survival (OS) and progression-free survival (PFS) in patients with intrahepatic cholangiocarcinoma (ICC) undergoing complete resection. Methods Sixty-eight patients with resectable ICC were included in this study. We studied stromal TIL density and scored it by staining sections from surgically resected ICC patients with hematoxylin and eosin (HE). The clinical data and prognosis of patients with ICC were obtained by searching clinical and follow-up records. Results A stromal TIL negative status was a predictor of poor OS (HR = 0.41, 95% CI 0.20–0.83, p = .01) and poor PFS (HR = 0.47, 95% CI 0.23–0.97, p = .04) independently. Low stromal TIL density was associated with high levels of CA125 (p = .03) and CA19-9 (p < .01). The high level of CA19-9 (p = .05), high differentiation (p = .02), a large diameter (p = .05), a positive bile duct/vascular cancer embolus (p = .03) and positive satellite nodules (p = .02) were tendencies to develop tumors for patients with a negative status of stromal TIL. Conclusion Our data prompt for the prediction of the PFS and OS of patients with ICC after complete resection, stromal TILs play an important role.