Dataset Information

Very Early Recurrence After Liver Resection for Intrahepatic Cholangiocarcinoma: Considering Alternative Treatment Approaches.

ABSTRACT:

Importance

Although surgery offers the best chance of a potential cure for patients with localized, resectable intrahepatic cholangiocarcinoma (ICC), prognosis of patients remains dismal largely because of a high incidence of recurrence.

Objective

To predict very early recurrence (VER) (ie, recurrence within 6 months after surgery) following resection for ICC in the pre- and postoperative setting.

Design, setting, and participants

Patients who underwent curative-intent resection for ICC between May 1990 and July 2016 were identified from an international multi-institutional database. The study was conducted at The Ohio State University in collaboration with all other participating institutions. The data were analyzed in December 2019.

Main outcomes and measures

Two logistic regression models were constructed to predict VER based on pre- and postoperative variables. The final models were used to develop an online calculator to predict VER and the tool was internally and externally validated.

Results

Among 880 patients (median age, 59 years [interquartile range, 51-68 years]; 388 women [44.1%]; 428 [50.2%] white; 377 [44.3%] Asian; 27 [3.2%] black]), 196 (22.3%) developed VER. The 5-year overall survival among patients with and without VER was 8.9% vs 49.8%, respectively (P < .001). A preoperative model was able to stratify patients relative to the risk for VER: low risk (6-month recurrence-free survival [RFS], 87.7%), intermediate risk (6-month RFS, 72.3%), and high risk (6-month RFS, 49.5%) (log-rank P < .001). The postoperative model similarly identified discrete cohorts of patients based on probability for VER: low risk (6-month RFS, 90.0%), intermediate risk (6-month RFS, 73.1%), and high risk (6-month RFS, 48.5%) (log-rank, P < .001). The calibration and predictive accuracy of the pre- and postoperative models were good in the training (C index: preoperative, 0.710; postoperative, 0.722) as well as the internal (C index: preoperative, 0.715; postoperative, 0.728; bootstrapping resamples, n = 5000) and external (C index: postoperative, 0.672) validation data sets.

Conclusion and relevance

An easy-to-use online calculator was developed to help clinicians predict the chance of VER after curative-intent resection for ICC. The tool performed well on internal and external validation. This tool may help clinicians in the preoperative selection of patients for neoadjuvant therapy as well as during the postoperative period to inform surveillance strategies.

SUBMITTER: Tsilimigras DI

PROVIDER: S-EPMC7344787 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo predict the very early recurrence (VER) of patients with intrahepatic cholangiocarcinoma (ICC) based on TLSs and MVI status, and further perform prognosis stratifications.MethodsA total of 160, 51 ICC patients from two institutions between May 2012 and July 2022 were retrospectively included as training, external validation cohort. Clinical, radiological and pathological variables were evaluated and collected. Univariate and multivariate analysis were applied to select the significant factors related to VER of ICC. The factors selected were combined to perform stratification of overall survival (OS) using the Kaplan-Meier method with the log-rank test.ResultsOverall, 39 patients (24.4%) had VER, whereas 121 (75.6%) did not (non-VER group). In the training cohort, the median OS was 40.5 months (95% CIs: 33.2-47.7 months). The VER group showed significantly worse OS than the non-VER group (median OS: 14.8, 95% CI:11.6-18.0 months vs. 53.4, 34.3-72.6 months; p<0.001), and it was confirmed in the validation cohort (median OS: 22.1, 95% CI: 8.8-35.4 months vs. 40.1, 21.2-59.0 months; p = 0.003). According to the univariate analysis, four variables were significantly different between the VER group and non-VER group (TLSs status, p = 0.028; differentiation, p = 0.023; MVI status, p = 0.012; diameter, p = 0.028). According to the multivariate analysis, MVI-positive status was independently associated with a higher probability of VER (odds ratio [OR], 2.5; 95% CIs,1.16-5.18; p = 0.018), whereas intra-tumoral TLSs-positive status was associated with lower odds of VER (OR, 0.43; 95% CIs, 0.19-0.97; p = 0.041). Based on the TLSs and MVI status, patients of ICC were categorized into four groups: TLSs-positive and MVI-negative (TP/MN); TLSs-negative and MVI-negative (TN/MN); TLSs-positive and MVI-positive (TP/MP), TLSs-negative and MVI-positive groups (TN/MP). In the training cohort, the four groups could be correlated with OS significantly (p<0.001), and it was confirmed in the validation cohort (p<0.001).ConclusionIntra-tumoral TLSs and MVI status are independent predictive factors of VER after surgery, based on which immunovascular stratifications are constructed and associated with OS significantly of resectable intrahepatic cholangiocarcinoma.

Project description:Introduction: The emerging field of "radiomics" has considerable potential in disease diagnosis, pathologic grading, prognosis evaluation, and prediction of treatment response. We aimed to develop a novel radiomics nomogram based on radiomics features and clinical characteristics that could preoperatively predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy. Methods: A predictive model was developed from a training cohort comprising 139 ICC patients diagnosed between January 2010 and June 2014. Radiomics features were extracted from arterial-phase image of contrast-enhanced magnetic resonance imaging. Feature selection and construction of a "radiomics signature" were through Spearman's rank correlation and least absolute shrinkage and selection operator (LASSO) logistic regression. Combined with clinical characteristics, a radiomics nomogram was developed with multivariable logistic regression. Performance of the nomogram was evaluated with regard to discrimination, calibration, and clinical utility. An independent validation cohort involving 70 patients recruited from July 2014 to March 2016 was used to evaluate the utility of the nomogram developed. Results: The radiomics signature, consisting of nine features, differed significantly between ER patients and non-ER patients in training and validation cohorts. The area under the curve (AUC) of the radiomics signature in training and validation cohorts was 0.82 (confidence interval [CI], 0.74-0.88) and 0.77 (95% CI, 0.65-0.86), respectively. The AUC of the radiomics nomogram combining the radiomics signature and clinical stage in the two cohorts was 0.90 (95%CI, 0.83-0.94) and 0.86 (95% CI, 0.76-0.93), respectively. Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram. Conclusion: The non-invasive radiomics nomogram developed using the radiomics signature and clinical stage could be used to predict ER of ICC after partial hepatectomy.

Project description:Early relapse after hepatectomy for intrahepatic cholangiocarcinoma (ICC) has a tremendous influence on the long-term survival outcomes of ICC patients. The purpose of our study was to investigate risk factors for early tumor relapse and confirm whether early relapse was correlated with ICC patients' long-term survival outcomes. Three hundred and twenty-two consecutive ICC patients undergoing partial hepatectomy at Liver Surgery Department of Zhongshan Hospital (Fudan University, Shanghai, China) between January 2005 and December 2011 were included in this retrospectively study. The definition of early relapse had been described as tumor relapse within 24 months after hepatectomy in ICC patients. We identified a total of 168 ICC patients with early relapse and 23 ICC patients with late relapse after hepatectomy. From the time of relapse, the long-term survival outcomes were worse among patients who had early vs. late relapse (median OS 16.5 vs. 44.7 months, respectively; P < 0.0001). The overall survival of the early relapse group was lower than that of the late relapse group (P < 0.0001). Multivariate Cox regression analysis indicated that multiple tumors (hazard ratio [HR], 1.951; 95% CI, 1.382-2.755; P < 0.001), lymphonodus metastasis (HR, 1.517; 95% CI, 1.061-2.168; P = 0.022), and higher serum CA19-9 levels (HR, 1.495; 95% CI, 1.095-2.039; P = 0.011) were independent risk factors of early relapse. Moreover, multiple tumors (HR, 1.641; 95% CI, 1.120-2.406; P = 0.011), lymphonodus metastasis (HR, 2.008; 95% CI, 1.367-2.949; P < 0.001), elevated NLR (HR, 1.921; 95% CI, 1.331-2.774; P < 0.001) and higher serum CA19-9 levels (HR, 1.990; 95% CI, 1.409-2.812; P < 0.001) were independent predictors of overall survival for ICC patients with early relapse. Collectively, our findings demonstrated that multiple tumors, lymphonodus metastasis, and higher serum CA19-9 levels were associated with the increased risks of early relapse and worse prognoses of ICC after curative-intent resection.

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.