Dataset Information

Evaluation of Preoperative Inflammation-Based Prognostic Scores in Patients With Intrahepatic Cholangiocarcinoma: A Multicenter Cohort Study.

ABSTRACT:

Background

Accumulating evidence has indicated the vital role of inflammation-based score (IBS) in predicting the prognostic outcome of cancer patients. Otherwise, their value in intrahepatic cholangiocarcinoma (iCCA) remains indistinct. The present study aimed to evaluate whether IBSs were related to survival outcomes in iCCA patients.

Method

Clinical characteristics were retrospectively collected in 399 patients diagnosed with iCCA from cohorts of Sun Yat-sen University Cancer Center (SYSUCC) and the First Hospital of Dalian Medical University (FHDMU). The survival curves were constructed with the Kaplan-Meier method and compared with the log-rank test. Univariate and multivariate analyses were conducted to determine the prognostic factors of overall survival (OS) and progression-free survival (PFS). The concordance index and the area under the time-dependent receiver operating characteristic (ROC) curves (AUROCs) were used to compare the predictive value of inflammation-based scores in terms of survival outcomes.

Results

The significant survival differences in OS and DFS were observed when patients were stratified by the modified Glasgow Prognostic Score (mGPS) (p<0.001). Multivariate analysis demonstrated that higher mGPS score was independently associated with poor OS and DFS (p<0.001). The predictive accuracy of the mGPS was superior to other IBSs (all p<0.001) in survival prediction in iCCA patients. The findings were further supported by the external validation cohort.

Conclusion

The mGPS is a sensitive, efficient, simple and widely applicable preoperative prognostic factor for iCCA patients. Thus, more effective therapy and frequent surveillance should be conducted after surgical resection in iCCA patients with higher mGPS scores.

SUBMITTER: He C

PROVIDER: S-EPMC8247471 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAppropriate preoperative identification of iCCA subtype is essential for personalized management, so the aim of this study is to investigate the role of MR imaging features in preoperatively differentiating the iCCA subtype.MethodsNinety-three patients with mass-forming intrahepatic cholangiocarcinoma (iCCA, 63 small duct type and 30 large duct type) were retrospectively enrolled according to the latest 5th WHO classification (mean age, males vs. females: 60.66 ± 10.53 vs. 61.88 ± 12.82, 50 men). Significant imaging features for differentiating large duct iCCA and small duct iCCA were identified using univariate and multivariate logistic regression analyses, and a regression-based predictive model was then generated. Furthermore, diagnostic performance parameters of single significant imaging features and the predictive model were obtained, and corresponding receiver operating characteristic (ROC) curves were subsequently presented.ResultsThe univariate analysis showed that tumor in vein, arterial phase hypoenhancement, intrahepatic duct dilatation, lack of targetoid restriction and lack of targetoid appearance in T2 were predictors of large duct type iCCA. Arterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction were independent predictors for large duct type iCCA in multivariate analysis. The regression-based predictive model has achieved the best preoperative prediction performance in iCCA subcategorization so far. The area under the ROC curve of the regression-based predictive model was up to 0.91 (95% CI: 0.85, 0.98), and it was significantly higher than every single significant imaging feature.ConclusionsArterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction could be considered reliable MR imaging indicators of large duct type iCCA. MR imaging features can facilitate noninvasive prediction of iCCA subtype with satisfactory predictive performance.

Project description:BackgroundLiver resection is the most effective treatment for intrahepatic cholangiocarcinoma. Recurrent disease is frequent; however, recurrence patterns are ill-defined and prognostic models are lacking.Study designA primary cohort of 189 patients who underwent resection for intrahepatic cholangiocarcinoma was used for recurrence patterns analysis within and after 24 months. Based on independent factors for disease-free survival identified in Cox regression analysis, preoperative and postoperative models were developed using a recursive partitioning method. Models were externally validated using a multicenter cohort of 522 resected patients (Association Française de Chirurgie intrahepatic cholangiocarcinoma study group).ResultsRecurrence within 24 months most often involved the liver (82.7%), and most recurrences after 24 months were strictly extrahepatic (61.1%). In multivariable analysis of the primary cohort, independent preoperative factors for disease-free survival were tumor size and multifocality (based on imaging); tumor size, multifocality, vascular invasion, and lymph node metastases (based on pathology) were independent postoperative factors. The preoperative model allowed patient classification into low-risk and high-risk groups for recurrence. In the validation cohort (n = 522), high-risk patients had a greater likelihood of recurrence (hazard ratio = 2.17; 95% CI, 1.74-2.72; p < 0.001). The postoperative model included tumor size, vascular invasion, and positive nodal disease on pathology and classified patients in low-, intermediate-, and high-risk groups in the primary cohort. As compared with low-risk patients in the validation cohort, intermediate- and high-risk patients were more likely to experience recurrence (hazard ratio = 1.9; 95% CI, 1.41-2.47; p < 0.001 and hazard ratio = 2.99; 95% CI, 2.08-4.31; p < 0.001, respectively).ConclusionsRecurrence patterns are time dependent. Both models as developed and validated in this study classified patients in distinct recurrence risk groups, which can guide treatment recommendations.

Project description:Purpose: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. Methods and Materials: A group of 106 ICC patients, who were diagnosed between April 2011 and February 2016, was used for prediction model training. Image features were extracted from T1-weighted contrast-enhanced MR images. A support vector machine (SVM) model was built by using the most LN status-related features, which were selected using the maximum relevance minimum redundancy (mRMR) algorithm. The mRMR method ranked each feature according to its relevance to the LN status and redundancy with other features. An SVM score was calculated for each patient to reflect the LN metastasis (LNM) probability from the SVM model. Finally, a combination nomogram was constructed by incorporating the SVM score and clinical features. An independent group of 42 patients who were diagnosed from March 2016 to November 2017 was used to validate the prediction models. The model performances were evaluated on discrimination, calibration, and clinical utility. Results: The SVM model was constructed based on five selected image features. Significant differences were found between patients with LNM and non-LNM in SVM scores in both groups (the training group: 0.5466 (interquartile range (IQR), 0.4059-0.6985) vs. 0.3226 (IQR, 0.0527-0.4659), P<0.0001; the validation group: 0.5831 (IQR, 0.3641-0.8162) vs. 0.3101 (IQR, 0.1029-0.4661), P=0.0015). The combination nomogram based on the SVM score, the CA 19-9 level, and the MR-reported LNM factor showed better discrimination in separating patients with LNM and non-LNM, comparing to the SVM model alone (AUC: the training group: 0.842 vs. 0.788; the validation group: 0.870 vs. 0.787). Favorable clinical utility was observed using the decision curve analysis for the nomogram. Conclusion: The nomogram, incorporating the SVM score, CA 19-9 level and the MR-reported LNM factor, provided an individualized LN status evaluation and helped clinicians guide the surgical decisions.

Project description:BackgroundLymph node metastasis (LNM) is a well-established prognostic factor for intrahepatic cholangiocarcinoma (ICC), but there are still some controversies relating to the evaluation of nodal status. Therefore, we investigated the role of lymph node dissection (LND), compared the prognostic performances of different nodal staging systems, and then developed and validated a nomogram to predict cancer-specific survival (CSS) of ICC patients.MethodsThe study cohort was taken from the Surveillance, Epidemiology, and End Results database. Akaike information criterion, Bayesian information criterion, Harrell's C-index and area under the receiver operating characteristic curves were calculated to evaluate the different staging models. The nomogram for the CSS was constructed based on Cox regression models and validated by calibration curves. Decision curve analysis was introduced to examine the clinical value of the models.ResultsA total of 664 patients were enrolled, and 331 (51.4%) patients underwent LND. An increasing number of lymph nodes retrieved showed no oncologic benefit (P=0.876). LNM was identified in 103 (31.1%) patients, which was the cause of their poor prognoses (5-yr CSS 13.1% versus 44.9%, P<0.001). Patients without LNM could not benefit from adjuvant therapy after propensity score matching (P=0.140). Based on the Youden index, 4 or more lymph nodes retrieved might be adequate for accurate staging. The lymph node ratio (LNR) classification, with an optimal cut-off value of 0.15, displayed the best prognostic performance. Age, size, tumor number, T Stage, grade and the LNR classification were independent predictive factors for the CSS in ICC patients. The nomogram for predicting the CSS of ICC patients according to the independent factors was well calibrated and it showed better discrimination power and higher net benefits than the American Joint Committee on Cancer (8th edition) staging system.ConclusionsLNM is an independent prognostic factor in ICC. Although it shows no oncologic benefits, LND should still be considered as a method of stratifying patients, with 4 or more lymph nodes retrieved potentially enough to do so. LNR appears to be a promising and easy-to-use prognosticator for nodal staging. The constructed nomogram could serve as an effective tool to predict the CSS probabilities of ICC patients.