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Establishment and validation of a prognostic nomogram for patients with resectable perihilar cholangiocarcinoma.

ABSTRACT: As the conventional staging systems have poor prognosis prediction ability for patients with perihilar cholangiocarcinoma (pCCA), we established and validated an effective prognostic nomogram for pCCA patients based on their personal and tumor characteristics. A total of 235 patients who received curative intent resections at the Eastern Hepatobiliary Surgery Hospital from 2000 to 2009 were recruited as the primary training cohort. Age, preoperative CA19-9 levels, portal vein involvement, hepatic artery invasion, lymph node metastases, and surgical treatment outcomes (R0 or R1/2) were independent prognostic factors for pCCA patients in the primary cohort as suggested by the multivariate analyses and these were included in the established nomogram. The calibration curve showed good agreement between overall survival probability of pCCA patients for the nomogram predictions and the actual observations and the concordance index (C-index) was 0.68 (95% CI, 0.61-0.71). The C-index values and time-dependent ROC tests suggested that the nomogram is superior to the conventional staging systems including the Bismuth-Corlette, Gazzaniga, Memorial Sloan Kettering Cancer Center (MSKCC), American Joint Committee on Cancer (AJCC) TNM 7th edition, and Mayo Clinic. The nomogram also performed better than the traditional staging system in the internal cohort with 93 pCCA patients from the same institution and an external validation cohort including 84 pCCA patients from another institution in predicting the overall survival of the pCCA patients as suggested by the C-index values and the time-dependent ROC tests. In summary, the proposed nomogram has superior predictive accuracy of prognosis for resectable pCCA patients.

SUBMITTER: Chen P

PROVIDER: S-EPMC5095079 | biostudies-other | 2016 Jun

REPOSITORIES: biostudies-other

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Establishment and validation of a prognostic nomogram for patients with resectable perihilar cholangiocarcinoma.

Chen Peizhan P Li Bin B Zhu Yan Y Chen Wei W Liu Xin X Li Mian M Duan Xiaohua X Yi Bin B Wang Jinghan J Liu Chen C Luo Xiangji X Li Xiaoguang X Li Jingquan J Liang Lijian L Yin Xiaoyu X Wang Hui H Jiang Xiaoqing X

Oncotarget 20160601 24

As the conventional staging systems have poor prognosis prediction ability for patients with perihilar cholangiocarcinoma (pCCA), we established and validated an effective prognostic nomogram for pCCA patients based on their personal and tumor characteristics. A total of 235 patients who received curative intent resections at the Eastern Hepatobiliary Surgery Hospital from 2000 to 2009 were recruited as the primary training cohort. Age, preoperative CA19-9 levels, portal vein involvement, hepati ...[more]

PMID: 27144432

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Project description:Simple summaryAccurately estimate the prognosis of patients with ECCA is important. However, the TNM system has some limitations, such as low accuracy, exclusion of other factors (e.g., age and sex), and poor performance in predicting individual survival risk. In contrast, a nomogram-based clinical model related to a comprehensive analysis of all risk factors is intuitive and straightforward, facilitating the probabilistic analysis of tumor-related risk factors. Simultaneously, a nomogram can also effectively drive personalized medicine and facilitate clinicians for prognosis prediction. Therefore, we construct a novel practical nomogram and risk stratification system to predict CSS in patients with ECCA.BackgroundAccurately estimate the prognosis of patients with extrahepatic cholangiocarcinoma (ECCA) was important, but the existing staging system has limitations. The present study aimed to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in ECCA patients.Methods3415 patients diagnosed with ECCA between 2010 and 2015 were selected from the SEER database and randomized into a training cohort and a validation cohort at 7:3. The nomogram was identified and calibrated using the C-index, receiver operating characteristic curve (ROC), and calibration plots. Decision curve analysis (DCA), net reclassification index (NRI), integrated discrimination improvement (IDI) and the risk stratification were used to compare the nomogram with the AJCC staging system.ResultsNine variables were selected to establish the nomogram. The C-index (training cohort:0.785; validation cohort:0.776) and time-dependent AUC (>0.7) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. The NRI (training cohort: 1-, 2-, and 3-year CSS:0.27, 0.27,0.52; validation cohort:1-,2-,3-year CSS:0.48,0.13,0.34), IDI (training cohort: 1-, 2-, 3-year CSS:0.22,0.18,0.16; validation cohort: 1-,2-,3-year CSS:0.18,0.16,0.17), and DCA indicated that the established nomogram significantly outperformed the AJCC staging system (P<0.05) and had better recognition compared to the AJCC staging system.ConclusionsWe developed a practical prognostic nomogram to help clinicians assess the prognosis of patients with ECCA.

Project description:BackgroundThis study aimed to explore the prognostic role of DNA methylation pattern in endometrial cancer (EC) patients.MethodsDifferentially methylated genes (DMGs) of EC patients with distinct survival from The Cancer Genome Atlas (TCGA) database were analyzed to identify methylated genes as biomarkers for EC prognosis. The Least Absolute Shrinkage and Selection Operator (LASSO) analysis was used to construct a risk score model. A nomogram was built based on analysis combining the risk score model with clinicopathological signatures together, and then verified in the validation cohort and patients in our own center.ResultsIn total, 157 DMGs were identified between different prognostic groups. Based on the LASSO analysis, five genes (GBP4, OR8K3, GABRA2, RIPPLY2, and TRBV5-7) were screened for the establishment of risk score model. The model outperformed in prognostic accuracy at varying follow-up times (AUC for 3 years: 0.824, 5 years: 0.926, and 7 years: 0.853). Multivariate analysis identified four independent risk factors including menopausal status (HR = 3.006, 95%CI: 1.062-8.511, p = 0.038), recurrence (HR = 2.116, 95%CI: 1.061-4.379, p = 0.046), lymph node metastasis (LNM, HR = 3.465, 95%CI: 1.225-9.807, p = 0.019), and five-DNA methylation risk model (HR = 3.654, 95%CI: 1.458-9.161, p = 0.006) in training cohort. The performance of the nomogram was good in the training (AUC = 0.828), validation (AUC = 0.866) and the whole cohorts (AUC = 0.843). Furthermore, we verified the nomogram with 24 patients in our center and the Kaplan-Meier survival curve also proved to be significantly different (p < 0.01). The subgroup analysis in different stratifications indicated that the accuracy was high in different subgroups for age, histological type, tumor grade, and clinical stage (all p < 0.01).ConclusionsBriefly, our work established and verified a five-DNA methylation risk model, and a nomogram merging the model with clinicopathological characteristics to facilitate individual prediction of EC patients for clinicians.

Project description:ObjectivesTo establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).MethodsWe performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell's index (C-index) and decision curve analysis, and the results were validated using a validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves.ResultsA total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the cHCC-score. The nomogram had a good discriminating capability, with a C-index of 0.796 (95% CI, 0.752-0.840). The calibration plot for distinguishing cHCC from iCCA showed optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness.ConclusionThe nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.

Dataset Information

Establishment and validation of a prognostic nomogram for patients with resectable perihilar cholangiocarcinoma.

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Establishment and validation of a prognostic nomogram for patients with resectable perihilar cholangiocarcinoma.

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