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Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection.

ABSTRACT: The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision making and prognostic evaluation. The aim of this work was to explore important factors affecting the prognosis of cHCC patients after liver resection and to develop preoperative nomograms to predict SAT and MVI in cHCC patients. The nomogram was developed using the data from 148 patients who underwent liver resection for cHCC patients at our hospital between January 2006 and December 2014. Based on the results of the multivariate analysis, a nomogram integrating all significant independent factors affecting overall survival and recurrence-free survival was constructed to predict the prognosis of cHCC. Next, risk factors for SAT and MVI were evaluated with logistic regression. Blood signatures were established using the LASSO regression, and then, we combined the clinical risk factors and blood signatures of the patients to establish predictive models for SAT and MVI. The C-index of the nomogram for predicting survival was 0.685 (95% CI, 0.638 to 0.732), which was significantly higher than the C-index for other liver cancer classification systems.

SUBMITTER: Wang T

PROVIDER: S-EPMC7467372 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection.

Wang Tao T Yang Xianwei X Tang Huairong H Kong Junjie J Shen Shu S Qiu Haizhou H Wang Wentao W

Aging 20200813 15

The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision making and prognostic evaluation. The aim of this work was to explore important factors affecting the prognosis of cHCC patients after liver resection and to develop preoperative nomograms to predict SAT ...[more]

PMID: 32788423

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Project description:ImportanceAdrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.ObjectivesTo define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.Design, setting, and participantsNomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.Main outcomes and measuresThe discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.ResultsIn total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P = .05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P = .001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P = .001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).Conclusions and relevanceIndependent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

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Project description:Background Serpin peptidase inhibitor, clade E, member 1 (SERPINE1) has been investigated as an oncogene and potential biomarker in several cancers, including gastric cancer (GC). This study aimed to investigate SERPINE1 expression and its diagnostic and prognostic value by analyzing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Methods A meta-analysis was performed to investigate SERPINE1 expression levels in GC tissues and adjacent normal tissues. Gene set enrichment, multi experiment matrix (MEM), and protein-protein interaction (PPI) network analyses were performed to identify the most enriched signaling pathways and SERPINE1-related module genes. A Cox regression model was used to develop a nomogram that was able to predict the overall survival (OS) and recurrence-free survival (RFS) of individual patients. Results Meta-analyses revealed an elevated trend in SERPINE1 expression levels in TCGA [standard mean difference (SMD) =0.95; 95% confidence interval (CI), 0.53–1.36; P<0.001]. The diagnostic meta-analysis results indicated that the area under the curve (AUC) of the summary receiver operating characteristic (SROC) was 0.80 (95% CI, 0.77–0.84). The factors identified to predict OS were age ≥60 years [hazard ratio (HR), 2.14; 95% CI, 1.45–3.16; P<0.01], R2 margins (HR, 2.70; 95% CI, 1.41–5.14; P<0.05), lymph node-positive proportion (HR, 3.38; 95% CI, 2.03–5.63; P<0.001), patient tumor status (HR, 3.33; 95% CI, 2.28–4.87; P<0.001), and OS risk score (HR, 2.72; 95% CI, 1.82–4.05; P<0.05). The following variables were associated with RFS: male sex (HR, 2.55; 95% CI, 1.46–4.45; P<0.01), R2 margins (HR, 13.08; 95% CI, 4.26–40.15; P<0.001), lymph node-positive proportion (HR, 2.55; 95% CI, 1.20–5.45; P<0.05), and RFS risk score (HR, 2.70; 95% CI, 1.82–4.06; P<0.001). The discriminative ability of the final model for OS and RFS was assessed using C statistics (0.755 for OS and 0.745 for RFS). Conclusions SERPINE1 was upregulated in GC, showed a high diagnostic value, and was associated with poorer OS and RFS. The OS and RFS risk for an individual patient could be estimated using these nomograms, which could lead to individualized therapeutic choices.

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Dataset Information

Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection.

Publications

Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection.

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