Dataset Information

Diagnostic and prognostic nomograms for bone metastasis in hepatocellular carcinoma.

ABSTRACT: BACKGROUND:Bone metastasis (BM) is one of the common sites of hepatocellular carcinoma (HCC), and the prognosis of BM patients is worse than patients without it. Our study aimed to identify predictors and prognostic factors of BM in HCC patients and develop two nomograms to quantify the risk of BM and the prognosis of HCC patients with BM. METHODS:We retrospectively reviewed the data of patients who were diagnosed as HCC between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. Independent predictors for BM from HCC patients were determined by the univariate and multivariate logistic regression analysis. Independent prognostic factors for HCC patients with BM were identified by univariate and multivariate Cox regression analysis. Two nomograms were established and evaluated by calibration curves, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). RESULTS:Nine thousand and forty-seven patients were included. The independent risk factors of BM in newly diagnosed HCC patients are sex, grade, T stage, and N stage. The independent prognostic factors for HCC patients with BM are radiotherapy, chemotherapy, and lung metastasis. The AUC of diagnostic nomogram were 0.726 in the training set and 0.629 in the testing set. For the prognostic nomogram, the AUCs of 6-, 9-, and 12-months were 0.753, 0.799, and 0.732 in the training set and 0.698, 0.770, and 0.823 in the validation set. The calibration curve and DCA indicated the good performance of the nomogram. CONCLUSIONS:Two nomograms were established to predict the incidence of BM in HCC patients and the prognosis of HCC patients with BM, respectively. Both nomograms have satisfactory accuracy, and clinical utility may benefit for clinical decision-making.

SUBMITTER: Hu C

PROVIDER: S-EPMC7268752 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Diagnostic and prognostic nomograms for bone metastasis in hepatocellular carcinoma.

Hu Chuan C Yang Jiaxin J Huang Zhangheng Z Liu Chuan C Lin Yijun Y Tong Yuexin Y Fan Zhiyi Z Chen Bo B Wang Cailin C Zhao Cheng-Liang CL

BMC cancer 20200601 1

<h4>Background</h4>Bone metastasis (BM) is one of the common sites of hepatocellular carcinoma (HCC), and the prognosis of BM patients is worse than patients without it. Our study aimed to identify predictors and prognostic factors of BM in HCC patients and develop two nomograms to quantify the risk of BM and the prognosis of HCC patients with BM.<h4>Methods</h4>We retrospectively reviewed the data of patients who were diagnosed as HCC between 2010 and 2015 in the Surveillance, Epidemiology, and ...[more]

PMID: 32487048

Similar Datasets

Project description:BackgroundThe aim of the present study was to develop an improved diagnostic and prognostic model for HBV-associated HCC by combining AFP with PIVKA-II and other potential serum/plasma protein biomarkers.MethodsA total of 578 patients, including 352 patients with HBV-related HCC, 102 patients with HBV-associated liver cirrhosis (LC), 124 patients with chronic HBV, and 127 healthy subjects (HS), were enrolled in the study. The serum levels of AFP, PIVKA-II, and other laboratory parameters were collected. Univariate and multivariate logistic regression and Cox regression analyses were performed to identify independent diagnostic and prognostic factors, respectively. The diagnostic efficacy of the nomogram was evaluated using receiver operator curve (ROC) analysis and the prognostic performance was measured by Harrell's concordance index (C-index).ResultsAFP and PIVKA-II levels were significantly increased in HBV-related HCC, compared with those in HBV-associated LC and chronic HBV participants (p < 0.05 and p < 0.001, respectively). The diagnostic nomogram, which included age, gender, AFP, PIVKA-II, prothrombin time (PT), and total protein (TP), discriminated patients with HBV-HCC from those with HBV-LC or chronic HBV with an AUC of 0.970. In addition, based on the univariate and multivariate Cox regression analysis, PIVKA-II, γ-glutamyl transpeptidase, and albumin were found to be significantly associated with the prognosis of HBV-related HCC and were incorporated into a nomogram. The C-index of the nomogram for predicting 3-year survival in the training and validation groups was 0.75 and 0.78, respectively. The calibration curves for the probability of 3-year OS showed good agreement between the nomogram prediction and the actual observation in the training and the validation groups. Furthermore, the nomogram had a higher C-index (0.74) than that of the Child-Pugh grade (0.62), the albumin-bilirubin (ALBI) score (0.64), and Barcelona Clinic Liver Cancer (0.56) in all follow-up cases.ConclusionOur study suggests that the nomograms based on AFP, PIVKA-II, and potential serum protein biomarkers showed a better performance in the diagnosis and prognosis of HCC, which may help to guide therapeutic strategies and assess the prognosis of HCC.

Project description:BackgroundHepatocellular carcinoma (HCC) most commonly develops in patients who have a viral infection, especially in the case of hepatitis B virus (HBV), and in patients with a chronic liver disease. HCC patients with bone metastasis (BM) suffer from pain and other symptoms that significantly reduce their quality of life. Identification of patients who are at high risk for BM after undergoing potentially curative treatment for HCC remains challenging. Here, we aimed to identify HCC BM-related genes and proteins to establish prediction biomarkers.MethodsRNA was extracted from 48 pairs of intratumoral and peritumoral formalin-fixed, paraffin-embedded tissue from HCC patients with and without BM. A cDNA-mediated annealing, selection, extension and ligation assay containing 502 cancer-related genes was used to identify novel BM-associated genes. An additional independent study with 350 HCC patients who had undergone hepatectomy was conducted to evaluate the expression of candidate genes at the protein level using immunohistochemistry on tissue microarrays (TMAs). Of the 350 patients, 273 (78.0%) were infected with HBV.ResultsSeven intratumoral genes and 17 peritumoral genes were overexpressed in patients with BM, whereas 15 intratumoral genes and 28 peritumoral genes were underexpressed in patients with BM. We selected the following four genes for further analysis because they were differentially expressed in the cancer gene-specific microarray and were previously reported to be associated with BM: connective tissue growth factor (CTGF), matrix metalloproteinase-1 (MMP-1), transforming growth factor β1 (TGF-β1), and interleukin-11 (IL-11). We assessed the protein expression of these selected genes using immunohistochemistry on TMAs including 350 HCC patient specimens. We determined that expression of intratumoral CTGF, intratumoral IL-11, and peritumoral MMP-1 were independent prognostic factors for developing BM in HCC patients. Combining intratumoral CTGF and IL-11 expression was also an independent risk factor for BM development.ConclusionsSixty-seven genes were differentially expressed in HCC patients with and without BM. High intratumoral CTGF, positive IL-11, and high peritumoral MMP-1 expression were associated with BM after hepatectomy. Intratumoral CTGF expression combined with IL-11 expression may serve as a useful predictive biomarker for HCC BM.

Project description:Background and aimsHepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for large hepatocellular carcinoma (HCC). However, post-HAIC prognosis can vary in different patients due to tumor heterogeneity. Herein, we established two nomogram models to assess the survival prognosis of patients after HAIC combination therapy.MethodsA total of 1082 HCC patients who underwent initial HAIC were enrolled between February 2014 and December 2021. We built two nomogram models for survival prediction: the preoperative nomogram (pre-HAICN) using preoperative clinical data and the postoperative nomogram (post-HAICN) based on pre-HAICN and combination therapy. The two nomogram models were internally validated in one hospital and externally validated in four hospitals. A multivariate Cox proportional hazards model was used to identify risk factors for overall survival (OS). The performance outcomes of all models were compared by area under the receiver operating characteristic curve (AUC) analysis with the DeLong test.ResultsMultivariable analysis identified larger tumor size, vascular invasion, metastasis, high albumin-bilirubin grade, and high alpha-fetoprotein as indicators for poor prognosis. With these variables, the pre-HAICN provided three risk strata for OS in the training cohort: low risk (5-year OS, 44.9%), middle risk (5-year OS, 20.6%), and high risk (5-year OS, 4.9%). The discrimination of the three strata was improved significantly in the post-HAICN, which included the above-mentioned factors and number of sessions, combination with immune checkpoint inhibitors, tyrosine kinase inhibitors, and local therapy (AUC, 0.802 versus 0.811, p < 0.001).ConclusionsThe nomogram models are essential to identify patients with large HCC suitable for treatment with HAIC combination therapy and may potentially benefit personalized decision-making.Lay summaryHepatic arterial infusion chemotherapy (HAIC) provides sustained higher concentrations of chemotherapy agents in large hepatocellular carcinoma (HCC) by hepatic intra-arterial, result in better objective response outperformed the intravenous administration. HAIC is significantly correlated with favorable survival outcome and obtains extensive support in the effective and safe treatment of intermediate advanced-stage HCC. In view of the high heterogeneity of HCC, there is no consensus regarding the optimal tool for risk stratification before HAIC alone or HAIC combined with tyrosine kinase inhibitors or immune checkpoint inhibitors treatment in HCC. In this large collaboration, we established two nomogram models to estimate the prognosis and evaluate the survival benefits with different HAIC combination therapy. It could help physicians in decision-making before HAIC and comprehensive treatment for large HCC patients in clinical practice and future trials.

Dataset Information

Diagnostic and prognostic nomograms for bone metastasis in hepatocellular carcinoma.

Publications

Diagnostic and prognostic nomograms for bone metastasis in hepatocellular carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets