Dataset Information

Predictive value of a nomogram for hepatocellular carcinoma with brain metastasis at initial diagnosis: A population-based study.

ABSTRACT:

Background

Population-based estimates of the incidence and prognosis of brain metastases at diagnosis of hepatocellular carcinoma (HCC) are lacking. The aim of this study was to characterize the incidence proportion and survival of newly diagnosed hepatocellular carcinoma with brain metastases (HCCBM).

Materials and methods

Data from Surveillance, Epidemiology, and End Results (SEER) program between 2010 and 2014 was evaluated. Patients with HCCBM were included. Multivariable logistic and Cox regression were performed to identify predictors of the presence of brain metastases at diagnosis and prognostic factors of overall survival (OS). We also built a nomogram based on Cox model to predict prognosis for HCCBM patients.

Results

We identified 97 patients with brain metastases at the time of diagnosis of HCC, representing 0.33% of the entire cohort. Logistic regression showed patients with bone or lung metastases had greater odds of having brain metastases at diagnosis. Median OS for HCCBM was 2.40 months. Cox regression revealed unmarried and bone metastases patients suffered significantly shorter survival time. A nomogram was developed with internal validation concordance index of 0.639.

Conclusions

This study provided population-based estimates of the incidence and prognosis for HCCBM patients. The nomogram could be a convenient individualized predictive tool for prognosis.

SUBMITTER: Chen QF

PROVIDER: S-EPMC6314620 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Predictive value of a nomogram for hepatocellular carcinoma with brain metastasis at initial diagnosis: A population-based study.

Chen Qi-Feng QF Huang Tao T Shen Lujun L Li Wang W

PloS one 20190102 1

<h4>Background</h4>Population-based estimates of the incidence and prognosis of brain metastases at diagnosis of hepatocellular carcinoma (HCC) are lacking. The aim of this study was to characterize the incidence proportion and survival of newly diagnosed hepatocellular carcinoma with brain metastases (HCCBM).<h4>Materials and methods</h4>Data from Surveillance, Epidemiology, and End Results (SEER) program between 2010 and 2014 was evaluated. Patients with HCCBM were included. Multivariable logi ...[more]

PMID: 30601858

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Project description:BackgroundAn individual prognostic model that includes inflammation caused by the delayed recovery of liver function after surgery for the early recurrence of hepatocellular carcinoma (HCC) following liver transplantation (LT) has not been well determined. Our aim was to develop a nomogram model for predicting individual survival and early recurrence following LT for patients.MethodsRetrospective data, including clinical pathology and follow-up data, on HCC patients were collected between October 2016 and October 2019 at Huashan Hospital Affiliated to Fudan University. A nomogram estimating recurrence post-transplantation was constructed using multivariate Cox regression analysis.ResultsA total of 210 patients were included in the present study. The multivariate estimators of recurrence consisted of age, maximum tumor diameter, tumor thrombus, microvascular invasion (MVI), alanine aminotransferase and alpha-fetoprotein on postoperative day 7. Nomogram of recurrence-free survival was developed. The calibration and discrimination of the novel model were assessed with the calibration curves and concordance index (C-index). Its reliability and advantages were evaluated by comparing it with the conventional American Joint Committee on Cancer (AJCC) 8th edition staging system using integrated discrimination improvement (IDI) and net reclassification improvement (NRI). In comparison to the AJCC 8th edition staging system, the C-index (development set: 0.796 vs. 0.643, validation set: 0.741 vs. 0.563), the area under the receiver operating characteristic curve (AUC) of the validation set (1-year AUC: 0.732 vs. 0.586, 2-year AUC: 0.705 vs. 0.504), the development set (1-year AUC: 0.799 vs. 0.551, 2-year AUC: 0.801 vs. 0.512), and this model's calibration plots all showed improved performance. In addition, NRI and IDI verified that the nomogram is an accurate prognostic tool. Subsequently, a web calculator was generated to assess the risk of tumor recurrence post-LT.ConclusionsThe nomogram, based on clinical and pathological factors, showed good accuracy in estimating prognostic recurrence and can be used to guide individual patient follow-up and treatment.

Dataset Information

Predictive value of a nomogram for hepatocellular carcinoma with brain metastasis at initial diagnosis: A population-based study.

Background

Materials and methods

Results

Conclusions

Publications

Predictive value of a nomogram for hepatocellular carcinoma with brain metastasis at initial diagnosis: A population-based study.

Similar Datasets

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