A new nomogram for prognosis of hepatocellular carcinoma.
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ABSTRACT:
SUBMITTER: Dai Y
PROVIDER: S-EPMC10932674 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
Publications
A new nomogram for prognosis of hepatocellular carcinoma.
Journal of gastrointestinal oncology 20240222 1
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Project description:Background and aimHepatocellular carcinoma is a common malignant tumor of the digestive system with a poor prognosis. The high recurrence rate and metastasis after surgery reduce the survival time of patients. Therefore, assessing the overall survival of patients with hepatocellular carcinoma after hepatectomy is critical to clinicians' clinical decision-making. Conventional hepatocellular carcinoma assessment systems (such as tumor lymph node metastasis and Barcelona clinical hepatocellular carcinoma) are obviously insufficient in assessing the overall survival rate of patients. This research is devoted to the development of nomogram assessment tools to assess the overall survival probability of patients undergoing liver resection.MethodsWe collected the clinical and pathological information of 438 hepatocellular carcinoma patients undergoing surgery from The Cancer Genome Atlas (TCGA) database, then excluded 87 patients who did not meet inclusion criteria. Univariate and multivariate analyses were performed on patient characteristics and related pathological factors. Finally, we developed a nomogram model to predict patient's prognosis.ResultsA retrospective analysis of 438 consecutive samples from the TCGA database of patients with hepatocellular carcinoma who underwent potentially curative liver resections. Six risk factors were included in the final model. In the training set, the discriminative ability of the nomogram was very good (concordance index = 0.944), and the external verification method (concordance index = 0.962) was used for verification. At the same time, the internal and external calibration of the model was verified, showing that the model was well calibrated. The calibration between the evaluation of the nomogram and the actual observations was good. According to the patient's risk factors, we determined the patient's Kaplan-Meyer survival analysis curve. Finally, the clinical decision curve was used to compare the benefits of two different models in evaluating patients' clinical outcomes.ConclusionsThe nomogram can be used to evaluate the post-hepatectomy 1-, 3-, and 5-year survival rates of patients with hepatocellular carcinoma. The Kaplan-Meyer curve can intuitively display the survival differences among patients with various risk factors. The clinical decision curve is a good reference guide for clinical application.
| S-EPMC8450568 | biostudies-literature
Project description:BackgroundEmerging evidence suggests that long non-coding RNA (lncRNA) plays a crucial part in the development and progress of hepatocellular carcinoma (HCC). The objective was to develop novel molecular-clinicopathological prediction methods for overall survival (OS) and recurrence of HCC.ResultsAn 8-lncRNA-based classifier for OS and a 14-lncRNA-based classifier for recurrence were developed by LASSO COX regression analysis, both of which had high accuracy. The tdROC of OS-nomogram and recurrence-nomogram indicates the satisfactory accuracy and predictive power. The classifiers and nomograms for predicting OS and recurrence of HCC were validated in the Test and GEO cohorts.ConclusionsThese two lncRNA-based classifiers could be independent prognostic factors for OS and recurrence. The molecule-clinicopathological nomograms based on the classifiers could increase the prognostic value.MethodsHCC lncRNA expression profiles from the cancer genome atlas (TCGA) were randomly divided into 1:1 training and test cohorts. Based on least absolute shrinkage and selection operator method (LASSO) COX regression model, lncRNA-based classifiers were established to predict OS and recurrence, respectively. OS-nomogram and recurrence-nomogram were developed by combining lncRNA-based classifiers and clinicopathological characterization to predict OS and recurrence, respectively. The prognostic value was accessed by the time-dependent receiver operating characteristic (tdROC) and the concordance index (C-index).
| S-EPMC7377850 | biostudies-literature
Project description:PurposeThe prognosis of liver cancer remains unfavorable nowadays, making the search for predictive biomarkers of liver cancer prognosis of paramount importance to guide clinical diagnosis and treatment. This study was conducted to explore more prognostic markers for most HCC.Patients and methodsA total of 330 patients were enrolled in this study according to the inclusion and exclusion criteria. Follow-up data were collected for all patients until the cutoff date of the study, February 2023. In addition, patient outcomes were assessed with progression-free survival (PFS) and overall survival (OS). All statistical analysis was conducted using R 4.2.0 software.ResultsUnivariate analysis illustrated that the GD [the product of gamma-glutamyl transpeptidase (GGT) concentration and D-dimer concentration, GD=GGT*D-dimer] levels were related to PFS (p<0.05) and OS (p<0.05). Kaplan-Meier survival curves and log-rank tests indicated a significant difference among different levels of GD (p<0.001). Multivariate analysis demonstrated GD as an independent prognostic factor for HCC. The C-indexes of nomogram were 0.77 and 0.76 in the training or validation cohort, respectively. Area Under the Curve (AUC) of 1-, 2-, 3-, and 4-year OS showed satisfactory accuracy, and the calibration curve illustrated brilliant consistence between the ideal and predicted values.ConclusionsHerein, it was demonstrated that GD was an independent prognostic factor for HCC and revealed the potential to predict the PFS and OS in patients with HCC. Moreover, the nomogram based on GD illustrated a satisfactory prediction ability in comparison to other models without GD.
| S-EPMC10646613 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) ranks prominently in cancer-related mortality globally. Surgery remains the main therapeutic option for the treatment of HCC, but high post-operative recurrence rate makes prognostic prediction challenging. The quest for a reliable model to predict HCC recurrence continues to enhance prognosis. We aim to develop a nomogram with multiple factors to accurately estimate the risk of post-operative recurrence in patients with HCC.MethodsA single-center retrospective study on 262 patients who underwent partial hepatectomy for HCC at the Eastern Hepatobiliary Surgery Hospital from May 2010 to April 2013 was conducted where immunohistochemistry assessed Yes-associated protein (YAP) expression in HCC. In the training cohort, a nomogram that incorporated YAP expression and clinicopathological features was constructed to predict 2-, 3-, and 5-year recurrence-free survival (RFS). The performance of the nomogram was assessed with respect to discrimination calibration, and clinical usefulness with external validation.ResultsA total of 262 patients who underwent partial hepatectomy for HCC at the Eastern Hepatobiliary Surgery Hospital were included in our study. HCC patients with high YAP expression exhibited significantly higher recurrence and reduced overall survival (OS) rates compared to those with low YAP expression (P<0.001). YAP was significantly associated with alpha-fetoprotein (AFP) (P=0.03), microvascular invasion (MVI) (P<0.001), and tumor differentiation grade (P<0.001). In the training cohort, factors like YAP expression, hepatitis B surface antigen (HBsAg), hepatitis B virus deoxyribonucleic acid (HBV-DNA), Child-Pugh stage, tumor size, MVI, and tumor differentiation were identified as key elements for the predictive model. Two YAP-centric Nomograms were developed, with one focused on predicting postoperative OS and the other on RFS. The calibration curve further confirmed the model's accuracy in the training cohort. The validation cohort confirmed the model's predictive accuracy.ConclusionsThe proposed nomogram combining the YAP, a predictor of HCC progression, and clinical features achieved more-accurate prognostic prediction for patients with HCC after partial hepatectomy, which may help clinicians implement more appropriate interventions.
| S-EPMC11399831 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) remains one of the most common malignancies worldwide, ranking as the third leading cause of cancer-related death. With recent advances in understanding HCC biology, progress has been made in early detection and management of HCC; however, its prognosis remains dismal. Novel biomarkers for HCC that are acceptable for clinical utility are urgently in need. Recently, miRNA has emerged as an important class of gene regulator that controls various cellular processes including cancer development. In HCC, miRNAs are frequently dysregulated, and studies have shown great promises of miRNAs as biomarkers for tumor classification, diagnosis and prognosis. Given miRNAs are highly stable in blood plasma and serum, they are suggested as a new class of noninvasive biomarker for detection of HCC. In this article, we provide an up-to-date review of the recent findings of the use of miRNAs in molecular classification of HCC tumors, diagnosis and prognosis.
| S-EPMC6095413 | biostudies-other
Project description:The nomogram of the Barcelona Clinic Liver Cancer (BCLC) has accurate outcome prediction. This study aims to propose a treatment-integrated nomogram derived from BCLC for patients with hepatocellular carcinoma (HCC). A total of 3,371 patients were randomly grouped into derivation (n = 2,247) and validation (n = 1,124) sets. Multivariate Cox proportional hazards model was used to generate the nomogram from tumor burden, cirrhosis, performance status (PS) and primary anti-cancer treatments. Concordance indices and calibration plots were used to evaluate the performance of nomogram. The derivation and validation sets had the same concordance index of 0.774 (95% confidence intervals: 0.717-0.826 and 0.656-0.874, respectively). In calibration plots, survival distributions predicted by the nomogram and observed by the Kaplan-Meier method were similar at 3- and 5-year for patients from derivation and validation sets. Validation group patients divided into 10 subgroups by the original and new treatment-integrated BCLC nomogram were used to evaluate the prognostic performance of integrating primary anti-cancer treatments. Compared to the nomogram of original BCLC system, the treatment-integrated nomogram of BCLC system had larger linear trend and likelihood ratio X2. In conclusion, based on the results of concordance index tests, integrating primary anti-cancer treatments into the BCLC system provides similar discriminatory ability.
| S-EPMC5554253 | biostudies-other
Project description:Autophagy plays a vital role in hepatocellular carcinoma (HCC) pathogenesis. Long non-coding RNAs (lncRNAs) are considered regulators of autophagy, and the aim of the present study was to investigate the prognostic value of autophagy-related lncRNA (ARlncRNA) and develop a new prognostic signature to predict the 1-year and 3-year overall survival (OS) of HCC patients. Transcriptome and clinical survival information of HCC patients was obtained from The Cancer Genome Atlas database. A set of ARlncRNAs was identified by co-expression analysis, from which seven ARlncRNAs (AC005229.4, AL365203.2, AL117336.3, AC099850.3, ELFN1-AS1, LUCAT1, and AL031985.3) were selected for use as a predictive signature. Risk scores were derived for each patient, who were then divided into high-risk and low-risk groups according to the median risk value. The OS of high-risk patients was significantly lower than that of low-risk patients (P < 0.0001). The 1- and 3-year time-dependent ROC curves were used to evaluate the predictive ability of the risk score (AUC = 0.785 of 1 year, 0.710 of 3 years), and its predictive ability was found to be better than TNM stage. Moreover, the risk score was significantly, linearly related to pathological grade and TNM stage (P < 0.05). Overall, a novel nomogram to predict the 1-year and 3-year OS of HCC patients was developed, which shows good reliability and accuracy, for use in improved treatment decision-making.
| S-EPMC7793718 | biostudies-literature
Project description:BackgroundThe combined application of immune cells and specific biomarkers related to the tumor immune microenvironment has a better predictive value for the prognosis of HCC. The purpose of this study is to construct a new prognostic model based on immune-related genes that regulate cross-talk between immune and tumor cells to assess the prognosis and explore possible mechanisms.MethodThe immune cell abundance ratio of 424 cases in the TCGA-LIHC database is obtained through the CIBERSORT algorithm. The differential gene analysis and cox regression analysis is used to screen IRGs. In addition, the function of IRGs was preliminarily explored through the co-culture of M2 macrophages and HCC cell lines. The clinical validation, nomogram establishment and performing tumor microenvironment score were validated.ResultsWe identified 4 immune cells and 9 hub genes related to the prognosis. Further, we identified S100A9, CD79B, TNFRSF11B as an IRGs signature, which is verified in the ICGC and GSE76427 database. Importantly, IRGs signature is closely related to the prognosis, tumor microenvironment score, clinical characteristics and immunotherapy, and nomogram combined with clinical characteristics is more conducive to clinical promotion. In addition, after co-culture with M2 macrophages, the migration capacity and cell pseudopod of MHCC97H increased significantly. And CD79B and TNFRSF11B were significantly down-regulated in MHCC97H, Huh7 and LM3, while S100A9 was up-regulated.ConclusionWe constructed an IRGs signature and discussed possible mechanisms. The nomogram established based on IRGs can accurately predict the prognosis of HCC patients. These findings may provide a suitable therapeutic target for HCC.
| S-EPMC8994280 | biostudies-literature
Project description:BackgroundFew studies have reported the clinical characteristics and outcomes of young adult patients diagnosed with hepatocellular carcinoma (HCC). This study aimed to formulate a nomogram to predict the prognosis of young adult HCC patients.MethodsYoung adult patients diagnosed with HCC from 2004 to 2015 were screened from the Surveillance, Epidemiology, and End Results (SEER) database. Based on the multivariate analysis results, a nomogram was constructed. The concordance index (c-index) and calibration were used to assess the predictive performance of the nomogram. The clinical benefit was measured by using decision curve analysis (DCA).ResultsThe mean follow-up time of the patients was 25.0±34.0 months. Gender, race, AFP level, Edmondson-Steiner classification, treatment and TNM stage were selected as independent prognostic factors and integrated into the nomogram. The c-indexes of the two sets were 0.786 and 0.775, respectively. The calibration curves showed good agreement between the nomogram-predicted probability and the actual observations. Furthermore, the DCA indicated that the nomogram had positive net benefits compared with the conventional staging system.ConclusionsThe nomogram could accurately predict the prognosis of young adult HCC patients.
| S-EPMC6623961 | biostudies-literature
Project description:Background: Radiotherapy is a primary treatment strategy for patients with unresectable hepatocellular carcinoma (HCC); however, the prognostic factors among HCC patients who have received radiotherapy but not undergone surgery have not been systematically studied. Thus, the prognostic factors were investigated in this study based on the Surveillance, Epidemiology, and End Results (SEER) Medicare database. Methods: A screening process was used for select cases from the SEER database. Survival was analyzed using the Kaplan-Meier method and log-rank test, the Cox proportional hazards regression model, and a competing risk model. A nomogram was established for predicting 1- and 3-year overall survival (OS) of patients. Results: A total of 1305 HCC patients who received radiotherapy but had not undergone surgery were included in this study and divided into training (n = 1175) and validation cohorts (n = 130). Patients in the training cohort had a 1-year OS rate of 30.9±1.3%, a 3-year OS rate of 10.0±1.0%, and a median survival rate of 6.0 months (range, 5.4-6.6 months). Race (p = 0.025), T stage (p < 0.001), N stage (p < 0.001), M stage (p < 0.001), and chemotherapy (p < 0.001) were identified as independent risk factors by multivariate analyses in the training cohort, while sex, age, grade, marital status, and insurance status were not independent factors. Survival in patients who received radiotherapy was worse with respect to the following characteristics: black race; higher T, N, or M stage; and no chemotherapy. A nomogram was established based on the results of the multivariate analysis, which was internally validated by a concordance index (C-index) of 0.731±0.016 and a group of calibration plots. External validation was carried out and the C-index was 0.738±0.049, which demonstrated the effectiveness of the nomogram we constructed. Conclusions: Race, T stage, N stage, M stage, and chemotherapy were independent risk factors for survival of HCC patients who received radiotherapy but had not undergone surgery. A validated nomogram was formulated to predict 1- and 3-year OS in these patients based on individual clinical characteristics.
| S-EPMC6746140 | biostudies-literature