Image_7_A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy.jpeg

IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.</p

Image_1_A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy.jpeg

IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.</p

Image_6_A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy.jpeg

IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.</p

Image5_External validation and improvement of the scoring system for predicting the prognosis in hepatocellular carcinoma after interventional therapy.tiff

BackgroundCurrently, locoregional therapies, such as transarterial chemoembolization (TACE) and ablation, play an important role in the treatment of Hepatocellular carcinoma (HCC). However, an easy-to-use scoring system that predicts recurrence to guide individualized management of HCC with varying risks of recurrence remains an unmet need.MethodsA total of 483 eligible HCC patients treated by TACE combined with ablation from January 1, 2017, to December 31, 2019, were included in the temporal external validation cohort and then used to explore possibilities for refinement of the original scoring system. We investigated the prognostic value of baseline variables on recurrence-free survival (RFS) using a Cox model and developed the easily applicable YA score. The performances of the original scoring system and YA score were assessed according to discrimination (area under the receiver operating curve [AUROC] and Harrell's concordance index [C-statistic]), calibration (calibration curves), and clinical utility [decision curve analysis (DCA) curves]. Finally, improvement in the ability to predict in the different scoring systems was assessed using the Net Reclassification Index (NRI). The YA score was lastly compared with other prognostic scores.ResultsDuring the median follow-up period of 35.6 months, 292 patients experienced recurrence. In the validation cohort, the original scoring system exhibited high discrimination (C-statistic: 0.695) and calibration for predicting the prognosis in HCC. To improve the prediction performance, the independent predictors of RFS, including gender, alpha-fetoprotein (AFP) and des-γ-carboxyprothrombin (DCP), tumor number, tumor size, albumin-to-prealbumin ratio (APR), and fibrinogen, were incorporated into the YA score, an improved score. Compared to the original scoring system, the YA score has better discrimination (c-statistic: 0.712VS0.695), with outstanding calibration and the clinical net benefit, both in the training and validation cohorts. Moreover, the YA score accurately stratified patients with HCC into low-, intermediate- and high-risk groups of recurrence and mortality and outperformed other prognostic scores.ConclusionYA score is associated with recurrence and survival in early- and middle-stage HCC patients receiving local treatment. Such score would be valuable in guiding the monitoring of follow-up and the design of adjuvant treatment trials, providing highly informative data for clinical management decisions.</p

Image_3_A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy.jpeg

IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.</p

Image7_External validation and improvement of the scoring system for predicting the prognosis in hepatocellular carcinoma after interventional therapy.tif

BackgroundCurrently, locoregional therapies, such as transarterial chemoembolization (TACE) and ablation, play an important role in the treatment of Hepatocellular carcinoma (HCC). However, an easy-to-use scoring system that predicts recurrence to guide individualized management of HCC with varying risks of recurrence remains an unmet need.MethodsA total of 483 eligible HCC patients treated by TACE combined with ablation from January 1, 2017, to December 31, 2019, were included in the temporal external validation cohort and then used to explore possibilities for refinement of the original scoring system. We investigated the prognostic value of baseline variables on recurrence-free survival (RFS) using a Cox model and developed the easily applicable YA score. The performances of the original scoring system and YA score were assessed according to discrimination (area under the receiver operating curve [AUROC] and Harrell's concordance index [C-statistic]), calibration (calibration curves), and clinical utility [decision curve analysis (DCA) curves]. Finally, improvement in the ability to predict in the different scoring systems was assessed using the Net Reclassification Index (NRI). The YA score was lastly compared with other prognostic scores.ResultsDuring the median follow-up period of 35.6 months, 292 patients experienced recurrence. In the validation cohort, the original scoring system exhibited high discrimination (C-statistic: 0.695) and calibration for predicting the prognosis in HCC. To improve the prediction performance, the independent predictors of RFS, including gender, alpha-fetoprotein (AFP) and des-γ-carboxyprothrombin (DCP), tumor number, tumor size, albumin-to-prealbumin ratio (APR), and fibrinogen, were incorporated into the YA score, an improved score. Compared to the original scoring system, the YA score has better discrimination (c-statistic: 0.712VS0.695), with outstanding calibration and the clinical net benefit, both in the training and validation cohorts. Moreover, the YA score accurately stratified patients with HCC into low-, intermediate- and high-risk groups of recurrence and mortality and outperformed other prognostic scores.ConclusionYA score is associated with recurrence and survival in early- and middle-stage HCC patients receiving local treatment. Such score would be valuable in guiding the monitoring of follow-up and the design of adjuvant treatment trials, providing highly informative data for clinical management decisions.</p

Image1_External validation and improvement of the scoring system for predicting the prognosis in hepatocellular carcinoma after interventional therapy.jpeg

BackgroundCurrently, locoregional therapies, such as transarterial chemoembolization (TACE) and ablation, play an important role in the treatment of Hepatocellular carcinoma (HCC). However, an easy-to-use scoring system that predicts recurrence to guide individualized management of HCC with varying risks of recurrence remains an unmet need.MethodsA total of 483 eligible HCC patients treated by TACE combined with ablation from January 1, 2017, to December 31, 2019, were included in the temporal external validation cohort and then used to explore possibilities for refinement of the original scoring system. We investigated the prognostic value of baseline variables on recurrence-free survival (RFS) using a Cox model and developed the easily applicable YA score. The performances of the original scoring system and YA score were assessed according to discrimination (area under the receiver operating curve [AUROC] and Harrell's concordance index [C-statistic]), calibration (calibration curves), and clinical utility [decision curve analysis (DCA) curves]. Finally, improvement in the ability to predict in the different scoring systems was assessed using the Net Reclassification Index (NRI). The YA score was lastly compared with other prognostic scores.ResultsDuring the median follow-up period of 35.6 months, 292 patients experienced recurrence. In the validation cohort, the original scoring system exhibited high discrimination (C-statistic: 0.695) and calibration for predicting the prognosis in HCC. To improve the prediction performance, the independent predictors of RFS, including gender, alpha-fetoprotein (AFP) and des-γ-carboxyprothrombin (DCP), tumor number, tumor size, albumin-to-prealbumin ratio (APR), and fibrinogen, were incorporated into the YA score, an improved score. Compared to the original scoring system, the YA score has better discrimination (c-statistic: 0.712VS0.695), with outstanding calibration and the clinical net benefit, both in the training and validation cohorts. Moreover, the YA score accurately stratified patients with HCC into low-, intermediate- and high-risk groups of recurrence and mortality and outperformed other prognostic scores.ConclusionYA score is associated with recurrence and survival in early- and middle-stage HCC patients receiving local treatment. Such score would be valuable in guiding the monitoring of follow-up and the design of adjuvant treatment trials, providing highly informative data for clinical management decisions.</p

Image_5_A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy.tiff

IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.</p

Image8_External validation and improvement of the scoring system for predicting the prognosis in hepatocellular carcinoma after interventional therapy.tif

BackgroundCurrently, locoregional therapies, such as transarterial chemoembolization (TACE) and ablation, play an important role in the treatment of Hepatocellular carcinoma (HCC). However, an easy-to-use scoring system that predicts recurrence to guide individualized management of HCC with varying risks of recurrence remains an unmet need.MethodsA total of 483 eligible HCC patients treated by TACE combined with ablation from January 1, 2017, to December 31, 2019, were included in the temporal external validation cohort and then used to explore possibilities for refinement of the original scoring system. We investigated the prognostic value of baseline variables on recurrence-free survival (RFS) using a Cox model and developed the easily applicable YA score. The performances of the original scoring system and YA score were assessed according to discrimination (area under the receiver operating curve [AUROC] and Harrell's concordance index [C-statistic]), calibration (calibration curves), and clinical utility [decision curve analysis (DCA) curves]. Finally, improvement in the ability to predict in the different scoring systems was assessed using the Net Reclassification Index (NRI). The YA score was lastly compared with other prognostic scores.ResultsDuring the median follow-up period of 35.6 months, 292 patients experienced recurrence. In the validation cohort, the original scoring system exhibited high discrimination (C-statistic: 0.695) and calibration for predicting the prognosis in HCC. To improve the prediction performance, the independent predictors of RFS, including gender, alpha-fetoprotein (AFP) and des-γ-carboxyprothrombin (DCP), tumor number, tumor size, albumin-to-prealbumin ratio (APR), and fibrinogen, were incorporated into the YA score, an improved score. Compared to the original scoring system, the YA score has better discrimination (c-statistic: 0.712VS0.695), with outstanding calibration and the clinical net benefit, both in the training and validation cohorts. Moreover, the YA score accurately stratified patients with HCC into low-, intermediate- and high-risk groups of recurrence and mortality and outperformed other prognostic scores.ConclusionYA score is associated with recurrence and survival in early- and middle-stage HCC patients receiving local treatment. Such score would be valuable in guiding the monitoring of follow-up and the design of adjuvant treatment trials, providing highly informative data for clinical management decisions.</p

Image_2_A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy.tiff

IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.</p