Risk and prognostic nomograms for hepatocellular carcinoma with newly-diagnosed pulmonary metastasis using SEER data
Author(s) -
Guanzhi Ye,
Lin Wang,
Zhengyang Hu,
Jiaqi Liang,
Yunyi Bian,
Cheng Zhan,
Zongwu Lin
Publication year - 2019
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.7496
Subject(s) - nomogram , medicine , hepatocellular carcinoma , oncology , proportional hazards model , brain metastasis , stage (stratigraphy) , metastasis , multivariate analysis , logistic regression , epidemiology , t stage , cancer , paleontology , biology
Purpose This research aimed to identify risk factors of pulmonary metastasis (PM) from hepatocellular carcinoma (HCC) and prognostic factors of patients with PM from HCC at initial diagnosis. Methods Patients diagnosed with HCC between 2010 and 2015 were reviewed retrospectively in the Surveillance, Epidemiology, and End Results (SEER) database. Patients with PM from HCC at initial diagnosis were identified from the entire cohort. Predictors for PM from HCC were identified by multivariate logistic regression analysis. Independent prognostic factors for patients with PM were determined by univariate and multivariate Cox regression analysis. Nomograms were also constructed for quantifying risk of metastasis and overall survival estimation visually. Results Our research included 30,641 patients diagnosed with HCC, of whom 1,732 cases were with PM from HCC at initial diagnosis. The risk factors causing PM from HCC were age ( P = 0.001), race ( P < 0.001), primary tumor size ( P < 0.001), T stage ( P < 0.001), N stage ( P < 0.001), alpha-fetoprotein ( P < 0.001), bone metastasis ( P < 0.001), brain metastasis ( P < 0.001), and intrahepatic metastasis ( P < 0.001). The significantly prognostic factors for overall survival were age ( P = 0.014), T stage ( P = 0.009), surgical approach ( P < 0.001), and chemotherapy ( P < 0.001). Harrell’s C-index statistics of two nomograms were 0.768 and 0.687 respectively, indicating satisfactory predictive power. Conclusions This research provided evaluation of risk factors and prognosis for patients with PM from HCC. Two nomograms we developed can be convenient individualized tools to facilitate clinical decision-making.
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