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Recurrence Patterns and Disease-Free Survival after Resection of Intrahepatic Cholangiocarcinoma: Preoperative and Postoperative Prognostic Models.

ABSTRACT: Liver resection is the most effective treatment for intrahepatic cholangiocarcinoma. Recurrent disease is frequent; however, recurrence patterns are ill-defined and prognostic models are lacking.A 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).Recurrence 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).Recurrence 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.

SUBMITTER: Doussot A

PROVIDER: S-EPMC5003652 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Recurrence Patterns and Disease-Free Survival after Resection of Intrahepatic Cholangiocarcinoma: Preoperative and Postoperative Prognostic Models.

Doussot Alexandre A Gonen Mithat M Wiggers Jimme K JK Groot-Koerkamp Bas B DeMatteo Ronald P RP Fuks David D Allen Peter J PJ Farges Olivier O Kingham T Peter TP Regimbeau Jean Marc JM D'Angelica Michael I MI Azoulay Daniel D Jarnagin William R WR

Journal of the American College of Surgeons 20160611 3

<h4>Background</h4>Liver resection is the most effective treatment for intrahepatic cholangiocarcinoma. Recurrent disease is frequent; however, recurrence patterns are ill-defined and prognostic models are lacking.<h4>Study design</h4>A 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, preopera ...[more]

PMID: 27296525

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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:ImportanceAlthough 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.ObjectiveTo 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 participantsPatients 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 measuresTwo 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.ResultsAmong 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 relevanceAn 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.

Project description:Background and aimsThe prognosis of intrahepatic cholangiocarcinoma (ICC) after radical resection is far from satisfactory; however, the clinical value of adjuvant therapy (AT) remains controversial. This multicenter study aimed to evaluate the clinical value of AT and identify potential patients who would be benefited from AT.MethodsData from ICC patients who underwent radical resection were retrospectively collected from 12 hepatobiliary centers in China between December 2012 and December 2015. Patients were divided into AT and non-AT groups based on whether AT was administered or not. Overall survival (OS) and disease-free survival (DFS) were analyzed using the Kaplan-Meier method before and after 1:2 propensity score matching (PSM). Subgroup analyses were conducted based on the established staging systems.ResultsA total of 412 patients were enrolled in this study, and 77 patients (18.9%) received AT, including 32 (7.8%) patients who received transarterial chemoembolization (TACE), 21 (5.1%) patients who received chemotherapy, 10 (2.4%) patients who received radiotherapy, and 14 (3.4%) patients who received adjuvant chemoradiotherapy. The median OS and DFS were both longer in the AT group than in the non-AT group (43.0 months vs 21.0 months, P = .015; 16.0 months vs 11.0 months, P = .045, respectively), and the advantage of AT was confirmed for both the OS and DFS (P = .023; P = .046, respectively) after 1:2 PSM. Furthermore, based on the established nomogram, only "middle-risk" patients receiving AT cherished a longer median OS (43.0 months vs 20.0 months, P = .033). In subgroup analyses that were stratified by different AT strategies, patients receiving postoperative chemotherapy had a longer median OS (37.0 months vs 21.0 months, P = .039), while patients receiving postoperative TACE had a longer median DFS (50.0 months vs 11.0 months, P = .007).ConclusionWith the current data, we conclude that AT benefits ICC patients following radical resection, especially those "middle-risk" patients, as evaluated by the established nomogram. However, exactly which patients are the most suitable for AT requires further study and validation.

Dataset Information

Recurrence Patterns and Disease-Free Survival after Resection of Intrahepatic Cholangiocarcinoma: Preoperative and Postoperative Prognostic Models.

Publications

Recurrence Patterns and Disease-Free Survival after Resection of Intrahepatic Cholangiocarcinoma: Preoperative and Postoperative Prognostic Models.

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