Predictors and patterns of recurrence after radiofrequency ablation for hepatocellular carcinoma within up-to-seven criteria: A multicenter retrospective study

Yang, Yi; Chen, Yi; Zhang, Mengjie; Xin, Yujing; Wang, Yanan; Li, Xiao; Fan, Qi-Wen; Zhou, Xiang; Ye, Feng

doi:10.1016/j.ejrad.2021.109623

Cited by 16 publications

(11 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…of 2.46 (95% C.I. 1.60–3.79) for early recurrence after ablation treatment [ 48 ], while Bae et al [ 49 ] found that male gender has an H.R. of 1.35 (95% C.I.…”

Section: Discussionmentioning

confidence: 99%

Predictors of Hepatocellular Carcinoma Early Recurrence in Patients Treated with Surgical Resection or Ablation Treatment: A Single-Center Experience

et al. 2022

View full text Add to dashboard Cite

Introduction: Hepatocellular carcinoma (HCC) is the sixth most diagnosed malignancy and the fourth leading cause of cancer-related death worldwide, with poor overall survival despite available curative treatments. One of the most crucial factors influencing survival in HCC is recurrence. The current study aims to determine factors associated with early recurrence of HCC in patients with BCLC Stage 0 or Stage A treated with surgical resection or local ablation. Materials and Methods: We retrospectively enrolled 58 consecutive patients diagnosed with HCC within BCLC Stage 0 or Stage A and treated either by surgical resection or local ablation with maximum nodule diameter < 50 mm. In the first year of follow-up after treatment, imaging was performed regularly one month after treatment and then every three months. Each case was discussed collectively by the Liver Multidisciplinary Group to decide diagnosis, treatment, follow-up, and disease recurrence. Variables resulting in statistically significant difference were then studied by Cox regression analysis; univariately and then multivariately based on forward stepwise Cox regression. Results are represented in hazard ratio (H.R.) with 95% confidence interval (C.I.). Results: There was no statistically significant difference in recurrence rates (34.8 vs. 45.7%, log-rank test, p = 0.274) between patients undergoing surgical resection and local ablation, respectively. Early recurrence was associated with male gender (HR 2.5, 95% C.I. 1.9–3.1), nodule diameter > 20 mm (HR 4.5, 95% C.I. 3.9–5.1), platelet count < 125 × 103 cell/mm3 (HR 1.6, 95% C.I. 1.2–1.9), platelet-lymphocyte ratio < 95 (HR 2.1, 95% C.I. 1.7–2.6), lymphocyte-monocyte ratio < 2.5 (HR 1.9, 95% C.I. 1.4–2.5), and neutrophil-lymphocyte ratio > 2 (HR 2.7, 95% C.I. 2.2–3.3). Discussion and Conclusions: Our results are in line with the current literature. Male gender and tumor nodule dimension are the main risk factors associated with early HCC recurrence. Platelet count and other combined scores can be used as predictive tools for early HCC recurrence, although more studies are needed to define cut-offs.

show abstract

“…of 2.46 (95% C.I. 1.60–3.79) for early recurrence after ablation treatment [ 48 ], while Bae et al [ 49 ] found that male gender has an H.R. of 1.35 (95% C.I.…”

Section: Discussionmentioning

confidence: 99%

Predictors of Hepatocellular Carcinoma Early Recurrence in Patients Treated with Surgical Resection or Ablation Treatment: A Single-Center Experience

et al. 2022

View full text Add to dashboard Cite

show abstract

“…To date, several studies have published risk scoring systems combining some demographic and clinical data (5)(6)(7). Nevertheless, most of the screening processes of parameters are based on univariate and multivariate analyses, which has some limitations in dealing with multicollinearity between variables.…”

Section: Introductionmentioning

confidence: 99%

Nomogram established on account of Lasso-Cox regression for predicting recurrence in patients with early-stage hepatocellular carcinoma

et al. 2022

View full text Add to dashboard Cite

PurposeTo investigate the risk factors for recurrence in patients with early-stage hepatocellular carcinoma (HCC) after minimally invasive treatment with curative intent, then to construct a prediction model based on Lasso-Cox regression and visualize the model built.MethodsClinical data were collected from 547 patients that received minimally invasive treatment in our hospital from January 1, 2012, to December 31, 2016. Lasso regression was used to screen risk factors for recurrence. Then we established Cox proportional hazard regression model and random survival forest model including several parameters screened by Lasso regression. An optimal model was selected by comparing the values of C-index, then the model was visualized and the nomogram was finally plotted.ResultsThe variables screened by Lasso regression including age, gender, cirrhosis, tumor number, tumor size, platelet-albumin-bilirubin index (PALBI), and viral load were incorporated in the Cox model and random survival forest model (P<0.05). The C-index of these two models in the training sets was 0.729 and 0.708, and was 0.726 and 0.700 in the validation sets, respectively. So we finally chose Lasso-Cox regression model, and the calibration curve in the validation set performed well, indicating that the model built has a better predictive ability. And then a nomogram was plotted based on the model chosen to visualize the results.ConclusionsThe present study established a nomogram for predicting recurrence in patients with early-stage HCC based on the Lasso-Cox regression model. This nomogram was of some guiding significance for screening populations at high risk of recurrence after treatment, by which doctors can formulate individualized follow-up strategies or treatment protocols according to the predicted risk of relapse for patients to improve the long-term prognosis.

show abstract

“…The factors with statistical significance (p < 0.05) were further subjected to multifactor logistic regression analysis to determine the risk factors for early recurrence. The multifactor logistic regression model was used to construct the prediction equation and nomogram (Yang et al 2021a(Yang et al , 2021b, and the verification group was used to verify the equation. According to the prediction results, two sets of receiver operating characteristic (ROC) curves and the area under the curve (AUC) were obtained to evaluate the universality of the prediction model, and the calibration curve was used to assess the calibration degree of the prediction model.…”

Section: Discussionmentioning

confidence: 99%

“…Hepatocellular carcinoma (HCC) ranks fifth among the most common cancers globally and third among the causes of cancer deaths (Fitzmaurice et al 2019). HCC accounts for more than 75% of all liver cancers (Yang et al 2021a(Yang et al , 2021b. For the choice of liver cancer treatment, it is necessary to comprehensively evaluate the size, number, location and situation of the patient's liver lesions (Forner et al 2018;Villanueva et al 2019aVillanueva et al , 2019b.…”

Section: Introductionmentioning

confidence: 99%

Prediction Model and Nomogram of Early Recurrence of Hepatocellular Carcinoma after Radiofrequency Ablation Based on Logistic Regression Analysis

et al. 2022

Ultrasound in Medicine & Biology

View full text Add to dashboard Cite

Predictors and patterns of recurrence after radiofrequency ablation for hepatocellular carcinoma within up-to-seven criteria: A multicenter retrospective study

Cited by 16 publications

References 30 publications

Predictors of Hepatocellular Carcinoma Early Recurrence in Patients Treated with Surgical Resection or Ablation Treatment: A Single-Center Experience

Predictors of Hepatocellular Carcinoma Early Recurrence in Patients Treated with Surgical Resection or Ablation Treatment: A Single-Center Experience

Nomogram established on account of Lasso-Cox regression for predicting recurrence in patients with early-stage hepatocellular carcinoma

Prediction Model and Nomogram of Early Recurrence of Hepatocellular Carcinoma after Radiofrequency Ablation Based on Logistic Regression Analysis

Contact Info

Product

Resources

About