Prognostic nomogram for patients with unresectable hepatocellular carcinoma after transcatheter arterial chemoembolization

Machine learning-based model for predicting tumor recurrence after interventional therapy in HBV-related hepatocellular carcinoma patients with low preoperative platelet-albumin-bilirubin score

Introduction

This study aimed to develop a prognostic nomogram for predicting the recurrence-free survival (RFS) of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients with low preoperative platelet-albumin-bilirubin (PALBI) scores after transarterial chemoembolization (TACE) combined with local ablation treatment.

Methods

We gathered clinical data from 632 HBV-related HCC patients who received the combination treatment at Beijing You'an Hospital, affiliated with Capital Medical University, from January 2014 to January 2020. The patients were divided into two groups based on their PALBI scores: low PALBI group (n=247) and high PALBI group (n=385). The low PALBI group was then divided into two cohorts: training cohort (n=172) and validation cohort (n=75). We utilized eXtreme Gradient Boosting (XGBoost), random survival forest (RSF), and multivariate Cox analysis to pinpoint the risk factors for RFS. Then, we developed a nomogram based on the screened factors and assessed its risk stratification capabilities and predictive performance.

Results

The study finally identified age, aspartate aminotransferase (AST), and prothrombin time activity (PTA) as key predictors. The three variables were included to develop the nomogram for predicting the 1-, 3-, and 5-year RFS of HCC patients. We confirmed the nomogram's ability to effectively discern high and low risk patients, as evidenced by Kaplan-Meier curves. We further corroborated the excellent discrimination, consistency, and clinical utility of the nomogram through assessments using the C-index, area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

Conclusion

Our study successfully constructed a robust nomogram, effectively predicting 1-, 3-, and 5-year RFS for HBV-related HCC patients with low preoperative PALBI scores after TACE combined with local ablation therapy.

Construction of a prognostic model for hepatocellular carcinoma patients receiving transarterial chemoembolization treatment based on the Tumor Burden Score

BACKGROUND

Patients with hepatocellular carcinoma (HCC) who undergo transarterial chemoembolization (TACE) may have varied outcomes based on their liver function and tumor burden diversity. This study aims to assess the prognostic significance of the tumor burden score (TBS) in these patients and develop a prognostic model for their overall survival.

METHODS

The study involved a retrospective analysis of 644 newly diagnosed HCC patients undergoing TACE treatment. The individuals were assigned randomly to a training cohort (n = 452) and a validation cohort (n = 192). We utilized a multivariate Cox proportional risk model to identify independent preoperative predictive factors. We then evaluated model performance using the area under the curve (AUC), consistency index (c-index), calibration curve, and decision curve analysis (DCA) methods.

RESULTS

The multivariate analysis revealed four prognostic factors associated with overall survival: Tumor Burden Score, Tumor Extent, Types of portal vein invasion (PVI), and Child-Pugh score. The total score was calculated based on these factors. The model demonstrated strong discriminative ability with high AUC values and c-index, providing high net clinical benefits for patients. Based on the model's scoring results, patients were categorized into high, medium, and low-risk groups. These results were validated in the validation cohort.

CONCLUSIONS

The tumor burden score shows promise as a viable alternative prognostic indicator for assessing tumor burden in cases of HCC. The new prognostic model can place patients in one of three groups, which will estimate their individual outcomes. For high-risk patients, it is suggested to consider alternative treatment options or provide the best supportive care, as they may not benefit significantly from TACE treatment.

Prognostic value of preoperative serum ferritin in hepatocellular carcinoma patients undergoing transarterial chemoembolization

The present study investigated the prognostic impact of preoperative serum ferritin (SF) levels on the survival of patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). Clinicopathological characteristics and laboratory biomarkers of 223 patients with HCC who underwent TACE were retrospectively reviewed. The Kaplan-Meier method was used to calculate the overall survival (OS), and the log-rank test was used to evaluate statistical significance. Univariate and multivariate analyses were performed using Cox proportional hazards regression to evaluate the prognostic impact of SF in these patients. The present findings identified extrahepatic metastases [hazard ratio (HR)=0.490,95%; confidence interval (CI)=0.282-0.843; P=0.010)] and vascular invasion (HR=0.373; 95% CI=0.225-0.619; P<0.0001) as independent prognostic factors for OS. However, preoperative SF levels could not independently predict OS when compared with other prognostic factors (HR=0.810; 95% CI=0.539-1.216; P=0.309). In conclusion, preoperative SF level is an unreliable biochemical predictor of survival in patients with HCC undergoing TACE.

Transcatheter Arterial Chemoembolization for Treatment-Naive Hepatocellular Carcinoma Has Different Treatment Effects Depending on Central or Peripheral Tumor Location

Introduction

The purpose of this study was to evaluate the treatment efficacy of transcatheter arterial chemoembolization (TACE) for treatment-naive hepatocellular carcinoma (HCC) according to tumor location and burden.

Methods

Between 2010 and 2019, consecutive patients who underwent TACE as the first treatment were enrolled. Tumors were classified into two categories based on their location, as central or peripheral tumors. Tumors in the central zone, which is within 1 cm of the main trunk or the first branch of the portal vein, were classified as central tumors, while those located in the peripheral zone were classified as peripheral tumors. Patients were grouped according to the HCC location and up-to-7 criteria. Patients with central tumors were classified into the central arm and those with only peripheral tumors were classified into the peripheral arm. Patients within and beyond the up-to-7 criteria were classified into the up-to-7 in and up-to-7 out-groups, respectively. Local recurrence-free survival (LRFS) and progression-free survival (PFS) were compared per nodule (central tumor vs. peripheral tumor) and per patient (central arm vs. peripheral arm), respectively. The prognostic factors of LRFS and PFS were analyzed by univariate and multivariate analyses.

Results

A total of 174 treatment-naive patients with 352 HCCs were retrospectively enrolled. Ninety-six patients and 130 lesions were selected by propensity score matching. Median LRFS was longer for peripheral tumors than central tumors (not reached vs. 3.3 months, p < 0.001). Median PFS was 17.1 months (8.3-24.9) in the peripheral arm and up-to-7 in, 7.0 months (3.3-12.7) in the peripheral arm and up-to-7 out, 8.4 months (4.0-12.6) in the central arm and up-to-7 in, and 3.0 months (1.2-4.9) in the central arm and up-to-7 out-groups. The peripheral arm and up-to-7 in-groups had significantly longer PFS than the other three groups (p = 0.013, p = 0.015, p < 0.001, respectively). Multivariate analysis confirmed that the central zone and central arm were associated with high adjusted hazard ratios for tumor recurrence or death (2.87, p < 0.001; 2.89, p < 0.001, respectively).

Conclusion

Treatment-naive HCCs in the peripheral zone had a longer LRFS and PFS following TACE compared to those in the central zone.

Prediction model of no-response before the first transarterial chemoembolization for hepatocellular carcinoma: TACF score

Previous clinic models for patients with hepatocellular carcinoma (HCC) receiving transarterial chemoembolization (TACE) mainly focused on the overall survival, whereas a simple-to-use tool for predicting the response to the first TACE and the management of risk classification before TACE are lacking. Our aim was to develop a scoring system calculated manually for these patients. A total of 437 patients with hepatocellular carcinoma (HCC) who underwent TACE treatment were carefully selected for analysis. They were then randomly divided into two groups: a training group comprising 350 patients and a validation group comprising 77 patients. Furthermore, 45 HCC patients who had recently undergone TACE treatment been included in the study to validate the model's efficacy and applicability. The factors selected for the predictive model were comprehensively based on the results of the LASSO, univariate and multivariate logistic regression analyses. The discrimination, calibration ability and clinic utility of models were evaluated in both the training and validation groups. A prediction model incorporated 3 objective imaging characteristics and 2 indicators of liver function. The model showed good discrimination, with AUROCs of 0.735, 0.706 and 0.884 and in the training group and validation groups, and good calibration. The model classified the patients into three groups based on the calculated score, including low risk, median risk and high-risk groups, with rates of no response to TACE of 26.3%, 40.2% and 76.8%, respectively. We derived and validated a model for predicting the response of patients with HCC before receiving the first TACE that had adequate performance and utility. This model may be a useful and layered management tool for patients with HCC undergoing TACE.

Development and Validation of Nomograms to Predict the Prognosis of Patients With Unresectable Hepatocellular Carcinoma Receiving Transarterial Chemoembolization

Background

Recent studies have shown that inflammatory indicators are closely related to the prognosis of patients with hepatocellular carcinoma, and they can serve as powerful indices for predicting recurrence and survival time after treatment. However, the predictive ability of inflammatory indicators has not been systematically studied in patients receiving transarterial chemoembolization (TACE). Therefore, the objective of this research was to determine the predictive value of preoperative inflammatory indicators for unresectable hepatocellular carcinoma treated with TACE.

Methods

Our retrospective research involved 381 treatment-naïve patients in 3 institutions, including the First Affiliated Hospital of Soochow University, Nantong First People's Hospital, and Nantong Tumor Hospital, from January 2007 to December 2020 that received TACE as initial treatment. Relevant data of patients were collected from the electronic medical record database, and the recurrence and survival time of patients after treatment were followed up. Least absolute shrinkage and selection operator (LASSO) algorithm was used to compress and screen the variables. We utilized Cox regression to determine the independent factors associated with patient outcomes and constructed a nomogram based on multivariate results. Finally, the nomogram was verified from discriminability, calibration ability, and practical applicability.

Results

Multivariate analysis revealed that the levels of aspartate aminotransferase-to-platelet ratio index (APRI) and lymphocyte count were independent influential indicators for overall survival (OS), whereas the levels of platelet-to-lymphocyte ratio (PLR) was an independent influential index for progression. Nomograms exhibited an excellent concordance index (C-index), in the nomogram of OS, the C-index was 0.753 and 0.755 in training and validation cohort, respectively; and in the nomogram of progression, the C-index was 0.781 and 0.700, respectively. The time-dependent C-index, time-dependent receiver operating characteristic (ROC), and time-dependent area under the curve (AUC) of the nomogram all exhibited ideal discrimination ability. Calibration curves significantly coincided with the standard lines, which indicated that the nomogram had high stability and low degree of over-fitting. Decision curve analysis revealed a wider range of threshold probabilities and could augment net benefits. The Kaplan-Meier curves for risk stratification indicated that the prognosis of patients varied significantly between risk categories (P < .0001).

Conclusions

The developed prognostic nomograms based on preoperative inflammatory indicators revealed high predictive accuracy for survival and recurrence. It can be a valuable clinical instrument for guiding individualized treatment and predicting prognosis.

Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study

BACKGROUND

To establish a prognostic model to predict the overall survival (OS) in patients with unresectable hepatocellular carcinoma (HCC) treated with intensity modulated radiotherapy (IMRT).

METHODS

The unresectable HCC patients treated with IMRT were retrospectively analyzed and randomized into development cohort (n = 237) and validation cohort (n = 103) in a 7:3 ratio. We developed a prognosis model with the multivariate Cox regression analysis in the development cohort to derive the predictive nomogram, which was then validated in the validation cohort. Model performance was evaluated by the c-index, the area under curve(AUC) and the calibration plot.

RESULTS

A total of 340 patients were enrolled. Tumor numbers > 3 (HR = 1.69, 95% CI = 1.21-2.37), AFP ≥ 400 ng/ml (HR = 1.52, 95% CI = 1.10-2.10), PLT < 100 × 10^9(HR = 1.7495% CI = 1.11-2.73), ALP > 150U/L (HR = 1.65, 95% CI = 1.15-2.37) and prior surgery (HR = 0.63, 95% CI = 0.43-0.93) were independent prognostic factors. The nomogram based on independent factors was constructed. The c-index for OS prediction was 0.658 (95% CI, 0.647-0.804) and 0.683 (95% CI, 0.580-0.785) in the development and validation cohort, respectively. The nomogram demonstrated good discriminative ability with AUC rates of 0.726, 0.739 and 0.753 at 1-year, 2-year and 3-year models in the development cohort, and 0.715, 0.756 and 0.780 in the validation cohort, respectively. Additionally, good prognostic discrimination of the nomogram is also reflected in stratifying patients into two subgroups with distinct prognosis.

CONCLUSIONS

We constructed a prognostic nomogram for predicting the survival of patients with unresectable HCC treated with IMRT.

Prognosis and conditional nomogram of cervical spine fracture in patients with severe spinal cord injury: a multicenter retrospective study

INTRODUCTION

Cervical spine fractures with severe spinal cord injury (SCI) are common following cervical spine trauma and are associated with a high mortality rate. Understanding the mortality patterns of patients with cervical spine fractures and severe SCI can offer valuable evidence to surgeons and family members who are required to make critical healthcare decisions. The authors aimed to evaluate the instantaneous death risk and conditional survival (CS) of such patients and developed conditional nomograms to account for different periods of survivors and predict the survival rates.

METHODS

Their instantaneous death risks were calculated using the hazard function, and the Kaplan-Meier method was used to evaluate the survival rates. Cox regression was used to choose the variables for the construction of the nomograms. The area under the receiver operating characteristic curve and calibration plots were used to validate the performance of the nomograms.

RESULTS

The authors finally included 450 patients with cervical spine fractures and severe SCI using propensity score matching. The instantaneous death risk was the highest during the first 12 months after injury. Surgical treatment can help decrease the instantaneous death risk quickly, especially in early-term surgery. The 5-year CS increased constantly from 73.3% at baseline to 88.0% after 2 years of survival. Conditional nomograms were constructed at baseline and in those who survived for 6 and 12 months. The area under the receiver operating characteristic curve and calibration curves indicated that the nomograms had a good performance.

CONCLUSION

Their results improve our understanding of the instantaneous death risk of patients in different periods following injury. CS demonstrated the exact survival rate among medium-term and long-term survivors. Conditional nomograms are suitable for different survival periods in predicting the probability of survival. Conditional nomograms help in understanding the prognosis and improve the shared decision-making approaches.

Improved diagnosis of histological capsule in hepatocallular carcinoma by using nonenhancing capsule appearance in addition to enhancing capsule appearance in gadoxetic acid-enhanced MRI

To assess the value of nonenhancing capsule by adding to enhancing capsule in gadoxetic acid-enhanced MRI (EOB-MRI) in comparison with contrast-enhanced CT (CE-CT) for diagnosing histological capsule in hepatocellular carcinoma (HCC). One-hundred fifty-one patients with HCC who underwent both CE-CT and EOB-MRI were retrospectively reviewed. Liver Imaging-Reporting and Data System (LI-RADS) v2018 imaging features, including enhancing and nonenhancing capsule were evaluated by two readers in CE-CT and EOB-MRI. Frequencies of each imaging feature were compared between CE-CT and EOB-MRI. The area under the receiver operating characteristic (AUC) curve for the diagnosis of histological capsule was compared across the following three imaging criteria: (1) enhancing capsule in CE-CT, (2) enhancing capsule in EOB-MRI, and (3) enhancing/nonenhancing capsule in EOB-MRI. Enhancing capsule in EOB-MRI was significantly less frequently depicted than that in CE-CT (p < 0.001 and = 0.016 for reader 1 and 2). Enhancing/nonenhancing capsule in EOB-MRI achieved a similar frequency of enhancing in CE-CT (p = 0.590 and 0.465 for reader 1 and 2). Adding nonenhancing capsule to enhancing capsule in EOB-MRI significantly increased AUCs (p < 0.001 for both readers) and achieved similar AUCs compared with enhancing capsule in CE-CT (p = 0.470 and 0.666 for reader 1 and 2). Adding nonenhancing capsule to the definition of capsule appearance can improve the diagnosis of capsule in EOB-MRI for the diagnosis of histological capsule in HCC and decrease discordance of capsule appearance between EOB-MRI and CE-CT.

Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI

OBJECTIVES

This study compared the accuracy of predicting transarterial chemoembolization (TACE) outcomes for hepatocellular carcinoma (HCC) patients in the four different classifiers, and comprehensive models were constructed to improve predictive performance.

METHODS

The subjects recruited for this study were HCC patients who had received TACE treatment from April 2016 to June 2021. All participants underwent enhanced MRI scans before and after intervention, and pertinent clinical information was collected. Registry data for the 144 patients were randomly assigned to training and test datasets. The robustness of the trained models was verified by another independent external validation set of 28 HCC patients. The following classifiers were employed in the radiomics experiment: machine learning classifiers k-nearest neighbor (KNN), support vector machine (SVM), the least absolute shrinkage and selection operator (Lasso), and deep learning classifier deep neural network (DNN).

RESULTS

DNN and Lasso models were comparable in the training set, while DNN performed better in the test set and the external validation set. The CD model (Clinical & DNN merged model) achieved an AUC of 0.974 (95% CI: 0.951-0.998) in the training set, superior to other models whose AUCs varied from 0.637 to 0.943 (p < 0.05). The CD model generalized well on the test set (AUC = 0.831) and external validation set (AUC = 0.735).

CONCLUSIONS

DNN model performs better than other classifiers in predicting TACE response. Integrating with clinically significant factors, the CD model may be valuable in pre-treatment counseling of HCC patients who may benefit the most from TACE intervention.

Predictors of liver failure after transarterial chemoembolization in patients with spontaneously ruptured hepatocellular carcinoma: A retrospective study

Background

Spontaneously ruptured hepatocellular carcinoma (rHCC) is a life-threatening condition. Transarterial chemoembolization (TACE) is a widely accepted treatment; however, it can lead to serious complications, especially liver failure. We sought to identify preoperative predictors of liver failure in patients with rHCC undergoing TACE.

Methods

Patients with rHCC who received TACE as the initial therapy were retrospectively studied at our institution between January 2016 and December 2021. Based on the occurrence of liver failure after TACE, the patients were divided into liver failure and no-liver failure groups. Predictors of liver failure after TACE were analyzed using univariate and multivariate regression analyses. The predictive performance was assessed using the area under the curve (AUC). Delong's test was used to compare predictive efficiency.

Results

Sixty patients (19 and 41 in the liver failure and non-liver failure groups, respectively) were included. Multivariate analysis showed that preoperative prothrombin activity (PTA) level (odds ratio [OR], 0.956; 95% confidence interval [CI], 0.920-0.994; P ​= ​0.024) and Child-Pugh grade B (OR, 6.419; 95% CI, 1.123-36.677; P ​= ​0.037) were independent predictors of liver failure after TACE in patients with rHCC. The AUCs of the preoperative PTA levels and Child-Pugh grade B for predicting liver failure after TACE in patients with rHCC were 0.783 and 0.764, respectively.

Conclusion

Preoperative PTA level and Child-Pugh grade B were significant independent risk factors for liver failure after TACE in patients with rHCC. These can be used to predict liver failure after TACE in patients with rHCC for individual decision-making regarding treatment planning.

Association between early response of alpha-fetoprotein and treatment efficacy of systemic therapy for advanced hepatocellular carcinoma: A multicenter cohort study from China

Background

Alpha-fetoprotein (AFP) is a well-identified biomarker in hepatocellular carcinoma (HCC). However, only limited AFP-related studies have evaluated its early response to systemic therapy. This study was performed with the aim of assessing the value of early AFP response in predicting overall survival (OS) and progression-free survival (PFS) in advanced HCC patients receiving systemic therapy.

Methods

This cohort study included HCC patients with baseline AFP ≥ 200 ng/ml and no prior treatment history. A > 20% decline in the serum AFP level from baseline to the first follow-up (i.e., 4~6 weeks after treatment) was defined as an early AFP response. Patient demographic information, clinical characteristics, radiological response, and survival rates were compared between patients with early AFP response and patients without early AFP response. We further utilized multivariate Cox regression to seek characteristics related to OS and PFS.

Results

Among 154 patients, 69 patients (44.8%) showed an early AFP response. The disease control rate (76.8 vs. 54.1%; P = 0.003) and objective response rate (38.4 vs. 11.8%; P = 0.001) were significantly higher in patients with an early AFP response. By performing multivariate analysis, early AFP response remained a prognostic factor for longer PFS (HR 0.546; 95% CI 0.371-0.804; P = 0.002) and longer OS (HR 0.529; 95% CI 0.335-0.834; P = 0.006).

Conclusion

An early AFP response is correlated with longer overall survival and progression-free survival for advanced HCC patients receiving systemic therapy. Moreover, an early AFP response is an independent prognostic factor for longer OS and PFS.

Hepatic arterial infusion chemotherapy and sequential ablation treatment in large hepatocellular carcinoma

AIM

To investigate the individualized survival benefit of hepatic arterial infusion chemotherapy (HAIC) and sequential ablation treatment in large hepatocellular carcinoma (HCC) patients.

METHODS

Between February 2016 and December 2020, a total of 228 HCC patients (diameter > 5 cm) who underwent HAIC alone (HAIC group, n = 135) or HAIC and sequential ablation (HAIC-ablation group, n = 93) treatment were reviewed. We applied the inverse probability of treatment weighting (IPTW) to adjust for potential bias of two treatment groups. The overall survival (OS) and progression-free survival (PFS) were compared with Kaplan-Meier curves. The Cox regression model was used to identify independent prognostic factors. And a prediction nomogram based on these independent prognostic factors was built, aiming to make probabilistic survival predictions and estimate personalized ablation benefits.

RESULTS

After a median follow-up of 17.9 months, HCC patients in the HAIC-ablation group have longer significantly OS and PFS than those in the HAIC alone group (median OS: 22.2 months vs. 14.5 months; median PFS: 8.5 months vs. 4.6 months; both, p < 0.001). The IPTW-adjusted analysis revealed similar findings (both, p < 0.001). Tumor size, tumor number, and treatment modality were identified as independent prognostic factors for OS. The nomogram based on these factors showed favorable discrimination and well calibration.

CONCLUSIONS

HAIC and sequential ablation provided significant survival benefits in patients with large HCC. The nomogram could help predict individual survival probabilities and estimate personalized sequential ablation benefits.

The C-Reactive Protein to Albumin Ratio Is an Independent Prognostic Factor in Patients with Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization: A Large Cohort Study

BACKGROUND

This study aimed to investigate the prognostic value of C-reactive protein to albumin ratio (CAR) in hepatocellular carcinoma (HCC) patients after transcatheter chemoembolization (TACE).

METHODS

Totally, 958 HCC patients with Barcelona Clinic Liver Cancer (BCLC) stage B were incorporated into the secondary analysis. X-Tile software was applied to determine the optimal cutoff point for CAR, and the total patients were divided into two groups. Cox proportional hazard regression models and Kaplan-Meier analyses were used to estimate the relationship between CAR and overall survival (OS). Stratified analyses were performed to evaluate the prognostic role of CAR in subgroups of major confounding factors, such as alpha-fetoprotein (AFP), diameter of the main tumor, Glasgow prognostic score (GPS) and modified GPS (mGPS).

RESULTS

The optimal cutoff level for the CAR was 0.06. There was a direct correlation between an elevated CAR (≥ 0.06) and shorter OS after adjustment (HR:1.580; 95%CI:1.193-2.092). Kaplan-Meier analysis and log-rank test showed a significant difference in OS curves between the two groups (P < 0.001). CAR showed the distinct value of prognostic stratification in most subgroups, especially in the subgroup of GPS-0 (HR:1.966; 95%CI:1.453-2.660), mGPS-0 (HR:1.984; 95%CI:1.509-2.608) and AFP ≤ 400 ng/ml (HR:1.925; 95%CI:1.393-2.659).

CONCLUSION

The CAR was one of the prognostic factors for HCC patients undergoing TACE treatment. CAR could also provide further prognostic stratification for HCC patients who appear to have a good prognosis, such as patients with AFP-negative, GPS-0 or mGPS-0 to identify patients at a higher risk of death for closer follow-up or more aggressive treatment.

LEVEL OF EVIDENCE

Level 3, Cohort Study.

Development and Validation of a Nomogram for Predicting Generalization in Patients With Ocular Myasthenia Gravis

Background

This study aims to develop and validate a nomogram for predicting 1- and 2-year generalization probabilities in patients with ocular myasthenia gravis (OMG).

Methods

In total, 501 eligible patients with OMG treated at seven tertiary hospitals in China between January 2015 and May 2019 were included. The primary outcome measure was disease generalization. A nomogram for predicting 1- and 2-year generalization probabilities was constructed using a stepwise Cox regression model. Nomogram performance was quantified using C-indexes and calibration curves. Two-year cumulative generalization rates were analyzed using the Kaplan−Meier method for distinct nomogram-stratified risk groups. The clinical usefulness of the nomogram was evaluated using decision curve analysis (DCA).

Result

The eligible patients were randomly divided into a development cohort (n=351, 70%) and a validation cohort (n=150, 30%). The final model included five variables: sex, onset age, repetitive nerve stimulation findings, acetylcholine receptor antibody test results, and thymic status. The model demonstrated good discrimination (C-indexes of 0.733 and 0.788 in the development and validation cohorts, respectively) and calibration, with good agreement between actual and nomogram-estimated generalization probabilities. Kaplan−Meier curves revealed higher 2-year cumulative generalization rates in the high-risk group than that in the low-risk group. DCA demonstrated a higher net benefit of nomogram-assisted decisions compared to treatment of all patients or none.

Conclusion

The nomogram model can predict 1- and 2-year generalization probabilities in patients with OMG and stratified these patients into distinct generalization risk groups. The nomogram has potential to aid neurologists in selecting suitable patients for initiating immunotherapy and for enrolment in clinical trials of risk-modifying treatments.

Tumor Response and Nomogram-Based Prognostic Stratification for Hepatocellular Carcinoma After Drug-Eluting Beads Transarterial Chemoembolization

Purpose

To explore the tumor response and propose a nomogram-based prognostic stratification for hepatocellular carcinoma (HCC) after drug-eluting beads transarterial chemoembolization (DEB-TACE).

Patients and Methods

From the database of two centers, patients who received DEB-TACE as an initial treatment were enrolled and divided into the training and validation sets. The tumor response after DEB-TACE was estimated according to the Modified Response Evaluation Criteria in Solid Tumors. Using the independent survival predictors in the training set, a nomogram was constructed and validated internally and externally by measuring concordance index (C-index) and calibration. A prognostic stratification based on the nomogram was established.

Results

A total of 335 patients met the inclusion criteria for the study. Alkaline phosphatase level, tumor maximum diameter, tumor capsule and portal vein invasion were interrelated with the achievement of complete release after DEB-TACE. Alpha-fetoprotein level, Child-Pugh class, tumor maximum diameter, tumor number, tumor extent and portal vein invasion were integrated into the nomogram. The nomogram demonstrated good calibration and discrimination, with C-indexes of 0.735 and 0.854 and higher area under the curve (AUC) than BCLC and CNLC staging systems in the internal and external validation sets. The prognostic stratification classified patients into three different risk groups, which had significant differences in survival, complete release and objective response rate between any two groups (P < 0.05).

Conclusion

The nomogram-based prognostic stratification has a good distinction and may help to identify the patients benefiting from DEB-TACE.

Clinicopathologic features, treatment, survival, and prognostic factors of combined hepatocellular and cholangiocarcinoma: A nomogram development based on SEER database and validation in multicenter study

PURPOSE

The aim of the study was to comprehensively understand the combined hepatocellular and cholangiocarcinoma (CHC) and develop a nomogram for prognostic prediction of CHC.

METHODS

Data were collected from the Surveillance, Epidemiology and End Results (SEER) database (year 2004-2014). Propensity-score matching (PSM) was used to match the demographic characteristic of the CHC versus hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). A nomogram model was established to predict the prognosis in terms of cancer specific survival (CSS). The established nomogram was externally validated by a multicenter cohort.

RESULTS

A total of 71,756 patients enrolled in our study including 62,877 HCC patients, 566 CHC patients, and 8303 ICC patients. The CHC, HCC, and ICC are not exactly similar in clinical characteristic. After PSM, the CSS of CHC was better than HCC but comparable to ICC. Tumor size, M stage, surgery, chemotherapy, and surgery were independently prognostic factors of CHC and were included in the establishment of novel nomogram. The c-index of the novel nomogram in SEER training set and multicenter validation was 0.779 and 0.780, respectively, which indicated that the model was with better discrimination power. In addition, decision curve analyses proved the favorable potential clinical effect of the predictive model. Lastly, a risk classification based on nomogram also verified the reliability of the model.

CONCLUSION

CHC had better survival than HCC but was comparable to ICC. The nomogram was established based on tumor size, M stage, chemotherapy, surgery, and radiotherapy and well validated by external multicenter cohort.

Tumor burden score as a new prognostic marker for patients with hepatocellular carcinoma undergoing transarterial chemoembolization

BACKGROUND AND AIM

Size and number are major determinants of tumor burden in hepatocellular carcinoma (HCC). Patients with HCC undergoing transarterial chemoembolization (TACE) have variable outcomes due to heterogeneity of tumor burden. Recently, tumor burden score (TBS) was proposed to evaluate the extent of tumor involvement. However, the prognostic accuracy of TBS has not been well evaluated in HCC. This study aimed to assess its prognostic role in HCC patients undergoing TACE.

METHODS

A total of 935 treatment-naïve HCC patients receiving TACE were retrospectively analyzed. Multivariate Cox proportional hazards model was used to determine independent prognostic predictors.

RESULTS

Tumor burden score tended to increase with increasing size and number of tumors in study patients. The Cox model showed that serum creatinine ≥ 1.2 mg/dL (hazard ratio [HR]: 1.296, 95% confidence interval [CI]: 1.077-1.559, P = 0.006), serum α-fetoprotein ≥ 400 ng/dL (HR: 2.245, 95% CI: 1.905-2.645, P < 0.001), vascular invasion (HR: 1.870, 95% CI: 1.520-2.301, P < 0.001), medium TBS (HR: 1.489, 95% CI: 1.206-1.839, P < 0.001) and high TBS (HR: 2.563, 95% CI: 1.823-3.602, P < 0.001), albumin-bilirubin (ALBI) grade 2-3 (HR: 1.521, 95% CI: 1.291-1.792, P < 0.001), and performance status 1 (HR: 1.362, 95% CI: 1.127-1.647, P < 0.001) and status 2 (HR: 1.553, 95% CI: 1.237-1.948, P < 0.001) were associated with increased mortality. Patients with high TBS had poor overall survival in Barcelona Clinic Liver Cancer stage B/C and different ALBI grades.

CONCLUSIONS

Tumor burden score is a feasible new prognostic surrogate marker of tumor burden in HCC and can well discriminate survival in patients undergoing TACE across different baseline characteristics.

A New Clinical Nomogram From the TCGA Database to Predict the Prognosis of Hepatocellular Carcinoma

Background and Aim

Hepatocellular 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.

Methods

We 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.

Results

A 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.

Conclusions

The 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.

Prognostic Value of Serum Apolipoprotein B to Apolipoprotein A-I Ratio in Hepatocellular Carcinoma Patients Treated with Transcatheter Arterial Chemoembolization: A Propensity Score-Matched Analysis

INTRODUCTION

The prognosis of advanced hepatocellular carcinoma (HCC) varies in patients receiving transcatheter arterial chemoembolization (TACE). In this study, we aimed to assess the prognostic value of serum apolipoprotein B (ApoB)/apolipoprotein A-I (ApoA-I) in this group of patients.

METHODS

The serum lipid levels of HCC patients undergoing TACE were obtained from routine preoperative blood lipid examination. A propensity score-matched (PSM) analysis was used to eliminate the imbalance of baseline characteristics of the high and low ApoB/ApoA-I groups. Then, univariate and multivariate analysis were conducted to evaluate the prognostic value of ApoB/ApoA-I.

RESULTS

In 455 HCC patients treated with TACE, ApoB/ApoA-I was positively correlated with AFP, T stage, distant metastasis, and TNM stage (p < 0.05). Patients with high ApoB/ApoA-I had a significantly shorter overall survival (OS) than those with low ApoB/ApoA-I (median OS, 21.7 vs. 39.6 months, p < 0.001). Multivariate analysis indicated that ApoB/ApoA-I was an independent prognostic index for OS (hazard ratio [HR] = 1.42, p = 0.008). After baseline characteristics were balanced, 288 patients were included in the PSM cohort. In this cohort, high ApoB/ApoA-I still predicted inferior OS in both univariate analysis (median OS, 27.6 vs. 39.3 months, p = 0.002) and multivariate analysis (HR = 1.58, p = 0.006).

CONCLUSION

Serum ApoB/ApoA-I is a useful biomarker in predicting aggressive clinicopathological characteristics and poor prognosis in HCC patients treated with TACE.

Effect of Diameter and Number of Hepatocellular Carcinomas on Survival After Resection, Transarterial Chemoembolization, and Ablation

INTRODUCTION

Most studies predicting survival after resection, transarterial chemoembolization (TACE), and ablation analyzed diameter and number of hepatocellular carcinomas (HCCs) as dichotomous variables, resulting in an underestimation of risk variation. We aimed to develop and validate a new prognostic model for patients with HCC using largest diameter and number of HCCs as continuous variables.

METHODS

The prognostic model was developed using data from patients undergoing resection, TACE, and ablation in 645 Japanese institutions. The model results were shown after balanced using the inverse probability of treatment-weighted analysis and were externally validated in an international multi-institution cohort.

RESULTS

Of 77,268 patients, 43,904 patients, including 15,313 (34.9%) undergoing liver resection, 13,375 (30.5%) undergoing TACE, and 15,216 (34.7%) undergoing ablation, met the inclusion criteria. Our model (http://www.u-tokyo-hbp-transplant-surgery.jp/about/calculation.html) showed that the 5-year overall survival (OS) in patients with HCC undergoing these procedures decreased with progressive incremental increases in diameter and number of HCCs. For patients undergoing resection, the inverse probability of treatment-weighted-adjusted 5-year OS probabilities were 10%-20% higher compared with patients undergoing TACE for 1-6 HCC lesions <10 cm and were also 10%-20% higher compared with patients undergoing ablation when the HCC diameter was 2-3 cm. For patients undergoing resection and TACE, the model performed well in the external cohort.

DISCUSSION

Our novel prognostic model performed well in predicting OS after resection and TACE for HCC and demonstrated that resection may have a survival benefit over TACE and ablation based on the diameter and number of HCCs.

Identification and Validation of Autophagy-Related Gene Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

Autophagy is a process of engulfing one's own cytoplasmic proteins or organelles and coating them into vesicles, fusing with lysosomes to form autophagic lysosomes, and degrading the contents it encapsulates. Increasing studies have shown that autophagy disorders are closely related to the occurrence of tumors. However, the prognostic role of autophagy genes in cervical cancer is still unclear. In this study, we constructed risk signatures of autophagy-related genes (ARGs) to predict the prognosis of cervical cancer. The expression profiles and clinical information of autophagy gene sets were downloaded from TCGA and GSE52903 queues as training and validation sets. The normal cervical tissue expression profile data from the UCSC XENA website (obtained from GTEx) were used as a supplement to the TCGA normal cervical tissue. Univariate COX regression analysis of 17 different autophagy genes was performed with the consensus approach. Tumor samples from TCGA were divided into six subtypes, and the clinical traits of the six subtypes had different distributions. Further absolute shrinkage and selection operator (LASSO) and multivariable COX regression yielded an autophagy genetic risk model consisting of eight genes. In the training set, the survival rate of the high-risk group was lower than that of the low-risk group (p < 0.0001). In the validation set, the AUC area of the receiver operating characteristic (ROC) curve was 0.772 for the training set and 0.889 for the verification set. We found that high and low risk scores were closely related to TNM stage (p < 0.05). The nomogram shows that the risk score combined with other indicators, such as G, T, M, and N, better predicts 1-, 3-, and 5-year survival rates. Decline curve analysis (DCA) shows that the risk model combined with other indicators produces better clinical efficacy. Immune cells with an enrichment score of 28 showed statistically significant differences related to high and low risk. GSEA enrichment analysis showed the main enrichment being in KRAS activation, genes defining epithelial and mesenchymal transition (EMT), raised in response to the low oxygen level (hypoxia) gene and NF-kB in response to TNF. These pathways are closely related to the occurrence of tumors. Our constructed autophagy risk signature may be a prognostic tool for cervical cancer.

Albumin-Bilirubin (ALBI) Grade-Based Nomogram for Patients with Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization

BACKGROUND/AIM

The prognosis of patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) is highly heterogeneous because of variable characteristics of tumor burden and liver dysfunction. We aimed to propose and validate an albumin-bilirubin (ALBI) grade-based prognostic nomogram for HCC patients undergoing TACE.

METHODS

A total of 1051 patients with HCC undergoing TACE were randomly assigned to derivation (n = 525) and validation (n = 526) set in this retrospective study based on prospective data. The multivariate Cox proportional hazards model in derivation set was used to generate the nomogram. The predictive accuracy of the nomogram was evaluated by discrimination and calibration tests.

RESULTS

In multivariate analysis, presence of ascites, ALBI grade 2-3, serum ɑ-fetoprotein level ≥ 400 ng/mL, total tumor volume ≥ 396 cm³, presence of vascular invasion, and poor performance status were independently associated with decreased survival of patients in the derivation set. Each patient had an individualized score from 0 to 41 by adding up the points from these six prognostic predictors. The nomogram generated from the derivation set had a concordance index of 0.72 (95% confidence interval [CI] 0.63-0.82). Discrimination test in the validation set provided a good concordance index 0.72 (95% CI 0.62-0.81), and the calibration plots consistently matched the ideal 45-degree reference line for 3- and 5-year survival prediction.

CONCLUSIONS

The ALBI grade-based prognostic model can well discriminate the survival in HCC patients undergoing TACE. The proposed easy-to-use nomogram may accurately predict the survival at 3 and 5 years for individual HCC patient in the precision medicine era.

Gene Polymorphism of MUC15, MMP14, BRAF, and COL1A1 Is Associated with Capsule Formation in Hepatocellular Carcinoma

BACKGROUND

The presence of a capsule is an important prognostic factor in hepatocellular carcinoma (HCC). Capsule formation is affected by tumor-host interaction, which may include collagen deposition and extracellular matrix (ECM) degradation.

PURPOSE

This study aimed to examine whether single-nucleotide polymorphisms (SNPs) in the genes for COL1A1 MUC15, MMP14, CD97, SMYD3, BRAF, and transforming growth factor beta 1 (TGF-β) are related to capsule formation.

METHODS

We prospectively recruited and analyzed 185 patients with HCC with or without a capsule between 2019 and 2020. The SNPs involved were analyzed by polymerase chain reaction. Differences in the allele and genotype frequency between the cases and controls were evaluated using the chi-square test. Odds ratios and 95% confidence intervals were calculated by logistic regression analysis with adjustment for age and sex. Stratification analyses were also performed with preselected variables.

RESULTS

The single-locus analysis showed that the presence of a capsule was significantly associated with five SNPs : MUC15 rs17309195 (P=0.01), rs12271124 (P= 0.02), rs10430847 (P=0.04), MMP14 rs17884816 (P=0.01), and BRAF rs74512895 (P=0.03). Adjusted logistic regression revealed that the decreased capsule formation was statistically significantly associated with BRAF rs76603725, COL1A1 rs2269336, and MUC15 rs17309195, while MMP14 rs17884816 and MUC15 rs10430847, rs2063278, and rs967490 were associated with increased capsule formation. The MUC15 block 2 haplotype was associated with increased capsule formation.

CONCLUSIONS

MUC15, MMP14, BRAF, and COL1A1 gene polymorphisms are associated with capsule formation in HCC. Studies involving larger samples are needed to confirm our results.

Selecting an Optimal Staging System for Intermediate-Stage Hepatocellular Carcinoma: Comparison of 9 Currently Used Prognostic Models

Purpose

It remains unknown which staging system is best in predicting the survival of patients with intermediate stage hepatocellular carcinoma (HCC). We aimed to investigate the performance of nine currently used HCC staging systems.

Patients and Methods

Between 2005 and 2014, a large cohort of 880 consecutive patients with intermediate stage HCC and sufficient data for utilization in all staging systems were enrolled. The prognostic performance of each staging system was compared. Independent prognostic variables were also identified.

Results

Multivariate analysis revealed that alkaline phosphatase (ALP), aspartate aminotransferase (AST), etiology, alpha-fetoprotein (AFP), Child-Pugh stage, tumor size, and tumor number were independent prognostic factors for survival. In the entire cohort, the Hong Kong Liver Cancer (HKLC) staging system was associated with the highest Harrell’s c-index and lowest Akaike information criterion value in comparison with other systems. In subgroup analysis according to treatment strategy, the HKLC staging system remained the best prognostic model in patients undergoing hepatic resection (n=222) or transarterial chemoembolization (n=658). Additional prognostic factors of AST, ALP, etiology, and AFP improved the discriminatory ability of HKLC.

Conclusion

The HKLC staging system is stable and consistently the best prognostic model in all patients with intermediate-stage HCC and in patients subjected to different treatment strategies. Selecting an optimal staging system is helpful in improving the design of future clinical trials in intermediate stage HCC.

Development of a preoperative prognostic scoring system to predict benefits of hepatic resection in advanced hepatocellular carcinoma patients

Objective: The present study aimed to identify risk factors for overall survival in advanced hepatocellular carcinoma (HCC) patients and establish a scoring system to select patients who would benefit from hepatic resection.

Methods: Survival curves were analyzed using the Kaplan–Meier method and log-rank test. The prognostic scoring system was developed from training cohort using a Cox-regression model and validated in a external validation cohort

Results: There were 401 patients in the training cohort, 163 patients in the external validation cohorts. The training cohort median survival in all patients was 12 ± 1.07 months, rate of overall survival was 49.6% at 1 year, 25.0% at 3 years, and 18.0% at 5 years. A prognostic scoring system was established based on age, body mass index, alkaline phosphatase, tumor number and tumor capsule. Patients were classified as low- risk group(≤3.5) or high-risk group(>3.5). High-risk patients had a median survival of 9 months, compared with 23 months in low-risk patients. The area under the receiver operating characteristic curve (AUC) of the prognostic scoring system was 0.747 (0.694–0.801), which is significantly better than AFP, Child-Pugh and ALBI. The AUC of validation cohorts was 0.716 (0.63–0.803).

Conclusion: A prognostic scoring system for hepatic resection in advanced HCC patients has been developed based entirely on preoperative variables. Patients classified as low risk using this system may experience better prognosis after hepatic resection.

Development of TACE Refractoriness Scores in Hepatocellular Carcinoma

Purpose: To identify the independent risk factors for transarterial embolization (TACE) refractoriness and to develop a novel TACE refractoriness score and nomogram for predicting TACE refractoriness in patients with hepatocellular carcinoma (HCC).

Methods: Between March 2006 and March 2016, HCC patients who underwent TACE monotherapy as initial treatment at two hospitals formed the study cohort and validation cohort. The criteria of TACE refractoriness followed the Japan Society of Hepatology 2014 version of TACE refractoriness. In the study cohort, the independent risk factors for TACE refractoriness were identified, and TACE refractoriness score and nomogram were then developed. The accuracy of the systems was validated externally in the validation cohort.

Results: In total, 113 patients from hospital A formed the study cohort and 122 patients from hospital B formed the validation cohort. In the study cohort, 82.3% of the patients (n = 93) developed TACE refractoriness with a median overall survival (OS) of 540 days (95% CI, 400.8–679.1), and the remaining 20 patients in the TACE-non-refractory group had a median OS of 1,257 days (95% CI, 338.8–2,175.2) (p = 0.019). The median time for developing TACE refractoriness was 207 days (95% CI, 134.8–279.2), and a median number of two TACE procedures were performed after refractoriness developed. The independent risk factors for TACE refractoriness were the number of tumors and bilobular invasion of HCC. TACE refractoriness scores <3.5 indicated a lower incidence of TACE refractoriness, whereas scores >3.5 points indicated a higher incidence (p < 0.001). In the validation cohort, 77.9% of the patients (n = 95) developed TACE refractoriness with a median OS of 568 days (95% CI, 416.3–719.7), and a median OS of 1,324 days was observed in the TACE-non-refractory group (n = 27; 95% CI, 183.5–2,464.5).

Conclusions: TACE refractoriness impairs the OS of HCC patients. The number of tumors and bilobular invasion status were independent risk factors for TACE refractoriness. The TACE refractoriness score can be an effective tool and easy approach to predict the risk of TACE refractoriness status.

A Powerful Nomogram Based on the Novel D-Index to Predict Prognosis After Surgical Resection of Hepatocellular Carcinoma

Purpose

Conventional staging and scoring systems such as the Tumor, Node, and Metastasis; Cancer of the Liver Italian Program; Barcelona Clinic Liver Cancer; and Okuda have failed to predict overall survival (OS) in patients with resected primary hepatocellular carcinoma. Thus, we aimed to establish a novel D-index and nomogram to improve prognostic accuracy.

Patients and Methods

We selected 396 patients who underwent liver resection between January 2007 and February 2015 at the First Affiliated Hospital of Wenzhou Medical University. These patients were randomly divided into the training and validation groups in a ratio of 7:3.

Results

We generated a nomogram using five independent risk factors, including the D-index (calculated by total bilirubin × tumor size/the ratio of fat-to-muscle area ^0.5) in the training set. The predictive performance of the nomogram was similar in both the training and validation cohorts according to the concordance index. The nomogram demonstrated the strongest predictive power for 1-year, 3-year, and 5-year OS, with the area under the receiving operating characteristic curve being 0.8486, 0.7785, and 0.752, respectively. The calibration curves exhibited stable capabilities in both cohorts. The stratification of the Kaplan-Meier curve was significant (P < 0.001).

Conclusion

The associated nomogram of the D-index demonstrated a powerful and accurate predictive ability for OS in patients with primary hepatocellular carcinoma.

A Prognostic Scoring System for Predicting Overall Survival of Patients with the TNM 8th Edition Stage I and II Hepatocellular Carcinoma After Surgery: A Population-Based Study

PURPOSE

Postoperative prognosis prediction models for patients with stage Ⅰ and Ⅱ hepatocellular carcinoma (HCC) according to the 8th edition of the Tumor-Node-Metastasis staging system after surgery are rare. This study aimed to build a prognostic score to predict survival outcomes and stratify these patients into different prognostic strata.

PATIENTS AND METHODS

We developed a web-based nomogram that incorporated four selected risk factors based on the multivariate Cox regression, using a training set (n=3567) from the Surveillance, Epidemiology, and End Results (SEER) database. It was validated with an independent internal set from the SEER database (n=1783) and an external validation set of 516 Chinese patients. The predictive performance and discrimination ability of our model were further evaluated and compared with those of the conventional HCC staging systems.

RESULTS

Our nomogram consistently outperformed the conventional staging systems in the training, internal validation set, and external validation set. We quantified the nomogram model into a numerical SNIG (an abbreviation of the incorporated variables - size, number, MVI, and grade) score by summing the points assigned to each incorporated variable, leading to the optimal cut-off values of 6 and 10, which could stratify patients into 3 categories (SNIG score <6, 6-10, ≥10). This yielded significantly different median overall survivals (interquartile ranges) of 42.0 (20.0-72.0) and 37.0 (17.0-67.0); 28.0 (12.0-60.0) and 42.0 (21.75-82.0); 40.0 (18.0-70.0) and 29.0 (11.5-61.0) months for the 3 categories in the entire SEER and external validation sets, respectively.

CONCLUSION

We developed a web-based SNIG model to graphically and numerically predict the overall survival of stage Ⅰ and Ⅱ HCC. This scoring system may shed light on risk stratification for these patients in clinical practice and clinical trials.

Myeloid signature reveals immune contexture and predicts the prognosis of hepatocellular carcinoma

BACKGROUNDDespite an increasing appreciation of the roles that myeloid cells play in tumor progression and therapy, challenges remain in interpreting the tumor-associated myeloid response balance and its translational value. We aimed to construct a simple and reliable myeloid signature for hepatocellular carcinoma (HCC).METHODSUsing in situ immunohistochemistry, we assessed the distribution of major myeloid subtypes in both peri- and intratumoral regions of HCC. A 2-feature-based, myeloid-specific prognostic signature, named the myeloid response score (MRS), was constructed using an L1-penalized Cox regression model based on data from a training subset (n = 244), a test subset (n = 244), and an independent internal (n = 341) and 2 external (n = 94; n = 254) cohorts.RESULTSThe MRS and the MRS-based nomograms displayed remarkable discriminatory power, accuracy, and clinical usefulness for predicting recurrence and patient survival, superior to current staging algorithms. Moreover, an increase in MRS was associated with a shift in the myeloid response balance from antitumor to protumor activities, accompanied by enhanced CD8+ T cell exhaustion patterns. Additionally, we provide evidence that the MRS was associated with the efficacy of sorafenib treatment for recurrent HCC.CONCLUSIONWe identified and validated a simple myeloid signature for HCC that showed remarkable prognostic potential and may serve as a basis for the stratification of HCC immune subtypes.FUNDINGThis work was supported by the National Science and Technology Major Project of China, the National Natural Science Foundation of China, the Science and Information Technology of Guangzhou, the Fundamental Research Funds for the Central Universities, the Guangdong Basic and Applied Basic Research Foundation, and the China Postdoctoral Science Foundation.

Machine-learning analysis of contrast-enhanced computed tomography radiomics predicts patients with hepatocellular carcinoma who are unsuitable for initial transarterial chemoembolization monotherapy: A multicenter study

•

Patients who are unsuitable for chemoembolization could progress with extrahepatic spread or vascular invasion after initial chemoembolization monotherapy.

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A radiomics signature based on the machine learning algorithm was identified.

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The signature combined with clinicoradiologicial predictors could predict TACE-unsuitable patients.

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The combined model showed improved predictive performance compared with the model without radiomics signature.

•

The combined model could stratify patients into three strata with a low, intermediate, or high risk in training and external testing sets.

Introduction

Due to the high heterogeneity of hepatocellular carcinoma (HCC), patients with non-advanced disease who are unsuitable for initial transarterial chemoembolization (TACE) monotherapy may have the potential to develop extrahepatic spread or vascular invasion. We aimed to develop and independently validate a radiomics-based model for predicting which patients will develop extrahepatic spread or vascular invasion after initial TACE monotherapy (EVIT).

Materials and methods

This retrospective study included 256 HCC patients (training set: n = 136; testing set: n = 120) who underwent TACE as initial therapy between April 2007 and June 2018. Clinicoradiological predictors were selected using multivariate logistic regression and a clinicoradiological model was constructed. The radiomic features were extracted from contrast-enhanced computed tomography (CT) images and a radiomics signature was constructed based on a machine learning algorithm. A combined model integrated clinicoradiological predictor and radiomics signature was developed. The predictive performance of the two models was evaluated and compared based on its discrimination, calibration, and clinical usefulness.

Results

In the training set, 34 (25.0%) patients were confirmed to have EVIT, whereas 26 (21.7%) patients in the testing set had EVIT. When the radiomics signature was added, the combined model showed improved discrimination performance compared to the clinicoradiological model (area under the curves [AUCs] 0.911 vs. 0.772 in the training set; AUCs 0.847 vs. 0.746 in the testing set) and could divide HCC patients into three strata of low, intermediate, or high risk in the two sets. Decision curve analysis demonstrated that the two models were clinically useful, and the combined model provided greater benefits for discriminating patients than the clinicoradiological model.

Conclusions

This study presents a model that integrates clinicoradiological predictors and CT-based radiomics signature that could provide a preoperative individualized prediction of EVIT in patients with HCC.

Hepatic resection versus transarterial chemoembolization in infiltrative hepatocellular carcinoma: A multicenter study

BACKGROUND AND AIM

Prognosis of infiltrative hepatocellular carcinoma (iHCC) is poor, and the treatments selection based on efficacy is unclear. We performed this multicenter study to compare the efficacy of hepatic resection and transarterial chemoembolization (TACE) in treating patients with iHCC.

METHODS

We retrospectively analyzed the overall survivals (OS) in 319 patients with iHCC who were initially treated by hepatic resection (n = 133) or TACE (n = 186) at four tertiary centers. Fifty-eight patients in the TACE group were assessed as resectable and compared with the hepatic resection group in subgroup analysis. A propensity score matched (PSM) analysis was performed to reduce selection bias. Cox regression was performed to identify significant factors associated with OS.

RESULTS

The median OS time was significantly longer in the hepatic resection group than that in the TACE group, before and after PSM (before PSM, 17.5 vs 7.3 months, P < 0.0001; after PSM, 14.0 vs 7.3 months, P < 0.0001). The multivariable analysis indicated TACE as a risk factor of OS (hazard ratio = 2.233, 95% confidence interval = 1.492 to 3.341, P < 0.0001), as well as portal venous tumor thrombosis grades 3-4 and alpha fetal protein (AFP) > 400 ng/mL. In the subgroup analysis, the better efficacy of hepatic resection over TACE persisted regardless of the grade of portal venous tumor thrombosis and the level of AFP. As for resectable patients, hepatic resection still showed significant survival benefit (before PSM, 17.5 vs 11.2 months, P = 0.0013; after PSM, 14.0 vs 10.9 months, P = 0.0304).

CONCLUSION

Hepatic resection might be the better choice for patients with iHCC due to its better survival benefit than TACE.

Recent Updates of Transarterial Chemoembolilzation in Hepatocellular Carcinoma

Transarterial chemoembolization (TACE) is a standard treatment for intermediate-stage hepatocellular carcinoma (HCC). In this review, we summarize recent updates on the use of TACE for HCC. TACE can be performed using two techniques; conventional TACE (cTACE) and drug-eluting beads using TACE (DEB-TACE). The anti-tumor effect of the two has been reported to be similar; however, DEB-TACE carries a higher risk of hepatic artery and biliary injuries and a relatively lower risk of post-procedural pain than cTACE. TACE can be used for early stage HCC if other curative treatments are not feasible or as a neoadjuvant treatment before liver transplantation. TACE can also be considered for selected patients with limited portal vein thrombosis and preserved liver function. When deciding to repeat TACE, the ART (Assessment for Retreatment with TACE) score and ABCR (AFP, BCLC, Child-Pugh, and Response) score can guide the decision process, and TACE refractoriness needs to be considered. Studies on the combination therapy of TACE with other treatment modalities, such as local ablation, radiation therapy, or systemic therapy, have been actively conducted and are still ongoing. Recently, new prognostic models, including analysis of the neutrophil-lymphocyte ratio, radiomics, and deep learning, have been developed to help predict survival after TACE.

Nomogram for prediction of the international study Group of Liver Surgery (ISGLS) grade B/C Posthepatectomy liver failure in HBV-related hepatocellular carcinoma patients: an external validation and prospective application study

BACKGROUND

To develop a nomogram for predicting the International Study Group of Liver Surgery (ISGLS) grade B/C posthepatectomy liver failure (PHLF) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients.

METHODS

Patients initially treated with hepatectomy were included. Univariate regression analysis and stochastic forest algorithm were applied to extract the core indicators and reduce redundancy bias. The nomogram was then constructed by using multivariate logistic regression, and validated in internal and external cohorts, and a prospective clinical application.

RESULTS

There were 900, 300 and 387 participants in training, internal and external validation cohorts, with the morbidity of grade B/C PHLF were 13.5, 11.0 and 20.2%, respectively. The nomogram was generated by integrating preoperative total bilirubin, platelet count, prealbumin, aspartate aminotransferase, prothrombin time and standard future liver remnant volume, then achieved good prediction performance in training (AUC = 0.868, 95%CI = 0.836-0.900), internal validation (AUC = 0.868, 95%CI = 0.811-0.926) and external validation cohorts (AUC = 0.820, 95%CI = 0.756-0.861), with well-fitted calibration curves. Negative predictive values were significantly higher than positive predictive values in training cohort (97.6% vs. 33.0%), internal validation cohort (97.4% vs. 25.9%) and external validation cohort (94.3% vs. 41.1%), respectively. Patients who had a nomogram score < 169 or ≧169 were considered to have low or high risk of grade B/C PHLF. Prospective application of the nomogram accurately predicted grade B/C PHLF in clinical practise.

CONCLUSIONS

The nomogram has a good performance in predicting ISGLS grade B/C PHLF in HBV-related HCC patients and determining appropriate candidates for hepatectomy.

Nomogram Based on Systemic Immune Inflammation Index and Prognostic Nutrition Index Predicts Recurrence of Hepatocellular Carcinoma After Surgery

Background

Surgery is a potential cure for hepatocellular carcinoma (HCC), but its postoperative recurrence rate is high, its prognosis is poor, and reliable predictive indicators are lacking. This study was conducted to develop a simple, practical, and effective predictive model.

Materials and Methods

Preoperative clinical and postoperative pathological data on patients with HCC undergoing partial hepatectomies at the Third Affiliated Hospital of Soochow University from January 2010 to December 2015 were retrospectively analyzed, and a nomogram was constructed. The model performance was evaluated using C-indexes, receiver operating characteristic curves, and calibration curves. The results were verified from validation cohort data collected at the same center from January 2016 to January 2017 and compared with the traditional staging systems.

Results

Three hundred three patients were enrolled in this study: 238 in the training cohort and 65 in the validation cohort. From the univariate and multivariate Cox regression analyses in the training cohort, six independent risk factors, i.e., age, alpha-fetoprotein (AFP), tumor size, satellite nodules, systemic immune inflammation index (SII), and prognostic nutritional index (PNI), were filtered and included in the nomogram. The C-index was 0.701 [95% confidence interval (CI): 0.654–0.748] in the training cohort and 0.705 (95% CI: 0.619–0.791) in the validation cohort. The areas under the curve for the 1- and 3-year recurrence-free survival were 0.706 and 0.716 in the training cohort and 0.686 and 0.743 in the validation cohort, respectively. The calibration curves showed good agreement. Compared with traditional American Joint Committee on Cancer 8th edition (AJCC8th) and Barcelona Clinic Liver Cancer (BCLC) staging systems, our nomogram showed better predictive ability.

Conclusion

Our nomogram is simple, practical, and reliable. According to our nomogram, predicting the risk of recurrence and stratifying HCC patient management will yield the greatest survival benefit for patients.

A nomogram to predict symptomatic epilepsy in patients with radiation-induced brain necrosis

OBJECTIVE

To develop and validate a nomogram to predict epilepsy in patients with radiation-induced brain necrosis (RN).

METHODS

The nomogram was based on a retrospective analysis of 302 patients who were diagnosed with symptomatic RN from January 2005 to January 2016 in Sun Yat-sen Memorial Hospital using the Cox proportional hazards model. Discrimination of the nomogram was assessed by the concordance index (C index) and the calibration curve. The results were internally validated using bootstrap resampling and externally validated using 128 patients with RN from 2 additional hospitals.

RESULTS

A total of 302 patients with RN with a median follow-up of 3.43 years (interquartile range 2.54-5.45) were included in the training cohort; 65 (21.5%) developed symptomatic epilepsy during follow-up. Seven variables remained significant predictors of epilepsy after multivariable analyses: MRI lesion volume, creatine phosphokinase, the maximum radiation dose to the temporal lobe, RN treatment, history of hypertension and/or diabetes, sex, and total cholesterol level. In the validation cohort, 28 out of 128 (21.9%) patients had epilepsy after RN within a median follow-up of 3.2 years. The nomogram showed comparable discrimination between the training and validation cohort (corrected C index 0.76 [training] vs 0.72 [95% confidence interval 0.62-0.81; validation]).

CONCLUSION

Our study developed an easily applied nomogram for the prediction of RN-related epilepsy in a large RN cohort.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that a nomogram predicts post-RN epilepsy.

The prognostic value of sarcopenia combined with hepatolithiasis in intrahepatic cholangiocarcinoma patients after surgery: A prospective cohort study

INTRODUCTION

Intrahepatic Cholangiocarcinoma (ICC) is the second most common primary liver cancer with dismal survival rates. This study aimed to explore the prognostic value of sarcopenia combine with hepatolithiasis in surgically treated ICC patients and develop a prognostic nomogram to help make clinical decisions.

MATERIALS AND METHODS

A prospective cohort study was conducted including patients who underwent hepatectomy for ICC between August 2012 and October 2019. The association between the sarcopenia combined with hepatolithiasis and survival, including overall survival (OS) and recurrence-free survival (RFS) was investigated using the Kaplan-Meier (K-M) method. Univariable and multivariable Cox regression analysis was performed to determine the independent prognostic factors and a nomogram establishment was undertaken based on the multivariable analysis.

RESULTS

A total of 121 ICC patients were included in the study. K-M analysis revealed that ICC patients with sarcopenia and hepatolithiasis have worse OS and RFS than those without sarcopenias and/or hepatolithiasis (p < 0.01). Multivariable analysis showed that age, serum CEA, hepatolithiasis, sarcopenia and diabetes were independent prognostic factors for OS(p < 0.05). Finally, a nomogram with good performance in survival prediction was established (C-index was 0.721; the area under the curve of OS was 0.837). The stratified analysis based on the nomogram disclosed that the median OS was 11.9 months in high-risk patients and 51.2 months in low-risk patients (p < 0.001).

CONCLUSIONS

ICC patients with sarcopenia and hepatolithiasis have worse OS and RFS. The nomogram we developed is a practical tool that can provide a more individualized risk assessment for surgically treated ICC patients.

Prognostic Nomogram for Patients with Hepatocellular Carcinoma After Thermal Ablation

PURPOSE

To develop an effective prognostic nomogram for patients with hepatocellular carcinoma (HCC) after thermal ablation.

METHODS

A total of 772 patients with intrahepatic primary or recurrent HCC who underwent radiofrequency ablation or microwave ablation between March 2011 and October 2016 were included. 602 patients (mean age, 56.0 ± 11.9 years; 495 male/107 female) were included in the primary cohort to establish a prognostic nomogram. Significant prognostic factors for overall survival (OS) identified by Cox univariate and multivariate regression analyses were used to construct the nomogram. The remaining 170 patients (mean age, 55.9 ± 11.9 years; 145 male/25 female) were used to validate the predictive accuracy of the nomogram.

RESULTS

During a mean follow-up period of 26 months (range 1-85 months), the median OS periods were 48.6 months and 44.0 months for the primary and validation cohorts. The 1-, 3-, and 5-year OS rates were 85.5%, 61.4%, and 43.3% in the primary cohort and 84.7%, 59.6%, and 43.3% in the prospective validation cohort, respectively. Multivariate analysis found that pre-ablation treatment, AFP, CEA, CA19-9, ALBI grade, tumor number, and tumor size (hazard ratio > 1, P < 0.05) were independent risk factors for OS. A nomogram was developed based on these seven variables. The calibration curve for predicting the probability of survival showed a good agreement between the nomogram and actual observation both in the primary (concrete index: 0.699) and validation cohorts (concrete index: 0.734).

CONCLUSIONS

This simple nomogram based on seven variables including ALBI grade offers personalized prognostic data for HCC patients after ablation.

LEVEL OF EVIDENCE

Level 4, case series.

Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization

Patients with HCC receiving TACE have various clinical outcomes. Several prognostic models have been proposed to predict clinical outcomes for patients with hepatocellular carcinomas (HCC) undergoing transarterial chemoembolization (TACE), but establishing an accurate prognostic model remains necessary. We aimed to develop a radiomics signature from pretreatment CT to establish a combined radiomics-clinic (CRC) model to predict survival for these patients. We compared this CRC model to the existing prognostic models in predicting patient survival. This retrospective study included multicenter data from 162 treatment-naïve patients with unresectable HCC undergoing TACE as an initial treatment from January 2007 and March 2017. We randomly allocated patients to a training cohort (n = 108) and a testing cohort (n = 54). Radiomics features were extracted from intra- and peritumoral regions on both the arterial phase and portal venous phase CT images. A radiomics signature (Rad-signature) for survival was constructed using the least absolute shrinkage and selection operator method in the training cohort. We used univariate and multivariate Cox regressions to identify associations between the Rad- signature and clinical factors of survival. From these, a CRC model was developed, validated, and further compared with previously published prognostic models including four-and-seven criteria, six-and-twelve score, hepatoma arterial-embolization prognostic scores, and albumin-bilirubin grade. The CRC model incorporated two variables: The Rad-signature (composed of features extracted from intra- and peritumoral regions on the arterial phase and portal venous phase) and tumor number. The CRC model performed better than the other seven well-recognized prognostic models, with concordance indices of 0.73 [95% confidence interval (CI) 0.68–0.79] and 0.70 [95% CI 0.62–0.82] in the training and testing cohorts, respectively. Among the seven models tested, the six-and-12 score and four-and-seven criteria performed better than the other models, with C-indices of 0.64 [95% CI 0.58–0.70] and 0.65 [95% CI 0.55–0.75] in the testing cohort, respectively. The CT radiomics signature represents an independent biomarker of survival in patients with HCC undergoing TACE, and the CRC model displayed improved predictive performance.

Prediction of Survival Among Patients Receiving Transarterial Chemoembolization for Hepatocellular Carcinoma: A Response-Based Approach

BACKGROUND AND AIMS

The heterogeneity of intermediate-stage hepatocellular carcinoma (HCC) and the widespread use of transarterial chemoembolization (TACE) outside recommended guidelines have encouraged the development of scoring systems that predict patient survival. The aim of this study was to build and validate statistical models that offer individualized patient survival prediction using response to TACE as a variable.

APPROACH AND RESULTS

Clinically relevant baseline parameters were collected for 4,621 patients with HCC treated with TACE at 19 centers in 11 countries. In some of the centers, radiological responses (as assessed by modified Response Evaluation Criteria in Solid Tumors [mRECIST]) were also accrued. The data set was divided into a training set, an internal validation set, and two external validation sets. A pre-TACE model ("Pre-TACE-Predict") and a post-TACE model ("Post-TACE-Predict") that included response were built. The performance of the models in predicting overall survival (OS) was compared with existing ones. The median OS was 19.9 months. The factors influencing survival were tumor number and size, alpha-fetoprotein, albumin, bilirubin, vascular invasion, cause, and response as assessed by mRECIST. The proposed models showed superior predictive accuracy compared with existing models (the hepatoma arterial embolization prognostic score and its various modifications) and allowed for patient stratification into four distinct risk categories whose median OS ranged from 7 months to more than 4 years.

CONCLUSIONS

A TACE-specific and extensively validated model based on routinely available clinical features and response after first TACE permitted patient-level prognostication.

Tescalcin is an unfavorable prognosis factor that regulats cell proliferation and survival in hepatocellular carcinoma patients

Background

Hepatocellular carcinoma (HCC) is a major health problem and a primary cause of cancer‐related death worldwide. Although great advances have achieved recently by large‐scale high‐throughput analysis, the precise molecular mechanism underlying HCC progression remains to be clearly elucidated. We investigated the relationship between Tescalcin (TESC), a candidate oncogene, and clinicopathological features of HCC patients and explored the role of TECS in HCC development.

Methods

To identify new genes involved in HCC development, we analyzed The Cancer Genome Atlas liver cancer database, and TESC was selected for further investigation. HCC tissue microarray analysis for TESC and its association with clinicopathological features were performed to investigate its clinical significance. TESC was knocked down by using short‐hairpin RNAs. Cell proliferation was analyzed by WST‐1 assay and cell counting. Cell apoptosis was tested by fluorescence‐activated cell sorting. A subcutaneous xenograft tumor model in nude mice was established to determine the in vivo function of TESC. Affymetrix microarray was used to identify its molecular mechanism.

Results

TESC was significantly increased in HCC tissues compared with the adjacent normal liver tissues. High expression of TESC was detected in 61 of 172 HCC patients by tissue microarray. Large tumor (> 5 cm) and elevated total bilirubin were associated with high TESC expression (both P < 0.050). In multivariate analysis, TESC was identified as an independent prognostic factor for short overall survival of HCC patients. TESC knockdown impaired HCC cell growth in vitro and in vivo. TESC knockdown significantly increased cell apoptosis in HCC cell lines. Furthermore, Affymetrix microarray analysis revealed that TESC knockdown inhibited tumor proliferation‐related pathways while activated cell death‐related pathways.

Conclusion

TESC was identified as an independent prognostic factor for short overall survival of HCC patients, and was critical for HCC cell proliferation and survival.

Development and Validation of a Nomogram for Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

BACKGROUND

Stereotactic body radiotherapy (SBRT) is an emerging treatment modality for hepatocellular carcinoma (HCC) with promising outcome. However, appropriate survival prediction models are scarce. This study aimed to develop a simple and clinically useful prognostic nomogram for patients with nondistant metastatic Barcelona Clinic Liver Cancer (BCLC) stage C HCC undergoing SBRT.

METHODS

The data were based on a prospective multi-institutional registry enrolling 246 patients with nondistant metastatic BCLC stage C HCC treated with SBRT between January 1, 2008 and December 31, 2016. They were randomly divided into two subsets: 164 into the development cohort and 82 into the validation cohort. We identified and included prognostic factors for survival to derive a nomogram in the development cohort. The predictability of the nomogram was evaluated in the validation cohort. The area under the receiver operating characteristic curve (AUROC) and the calibration plot were used to evaluate the performance of the nomogram.

RESULTS

The median survival was 13.5 months, with 1- and 2-year overall survival (OS) rates of 55.0 and 32.9%, respectively. Number of tumors, largest tumor size, macrovascular invasion, Child-Turcotte-Pugh class, and biologically effective dose were significantly associated with OS (p < 0.05). These predictors were included to develop a nomogram with an AUROC of 0.77 (0.73-0.87). The prediction model was well calibrated in the validation cohort. The OS for patients who were divided by their risk scores differed significantly (p < 0.001).

CONCLUSIONS

The nomogram we generated had discriminatory and satisfactory predictability for OS among nonmetastatic BCLC stage C HCC patients treated with SBRT. It demands further validations with cross-country data to confirm its worldwide usefulness.

Prediction of prognostic risk factors in hepatocellular carcinoma with transarterial chemoembolization using multi-modal multi-task deep learning

BACKGROUND

Due to heterogeneity of hepatocellular carcinoma (HCC), outcome assessment of HCC with transarterial chemoembolization (TACE) is challenging.

METHODS

We built histologic-related scores to determine microvascular invasion (MVI) and Edmondson-Steiner grade by training CT radiomics features using machine learning classifiers in a cohort of 494 HCCs with hepatic resection. Meanwhile, we developed a deep learning (DL)-score for disease-specific survival by training CT imaging using DL networks in a cohort of 243 HCCs with TACE. Then, three newly built imaging hallmarks with clinicoradiologic factors were analyzed with a Cox-Proportional Hazard (Cox-PH) model.

FINDINGS

In HCCs with hepatic resection, two imaging hallmarks resulted in areas under the curve (AUCs) of 0.79 (95% confidence interval [CI]: 0.71-0.85) and 0.72 (95% CI: 0.64-0.79) for predicting MVI and Edmondson-Steiner grade, respectively, using test data. In HCCs with TACE, higher DL-score (hazard ratio [HR]: 3.01; 95% CI: 2.02-4.50), American Joint Committee on Cancer (AJCC) stage III+IV (HR: 1.71; 95% CI: 1.12-2.61), Response Evaluation Criteria in Solid Tumors (RECIST) with stable disease + progressive disease (HR: 2.72; 95% CI: 1.84-4.01), and TACE-course > 3 (HR: 0.65; 95% CI: 0.45-0.76) were independent prognostic factors. Using these factors via a Cox-PH model resulted in a concordance index of 0.73 (95% CI: 0.71-0.76) for predicting overall survival and AUCs of 0.85 (95% CI: 0.81-0.89), 0.90 (95% CI: 0.86-0.94), and 0.89 (95% CI: 0.84-0.92), respectively, for predicting 3-year, 5-year, and 10-year survival.

INTERPRETATION

Our study offers a DL-based, noninvasive imaging hallmark to predict outcome of HCCs with TACE.

FUNDING

This work was supported by the key research and development program of Jiangsu Province (Grant number: BE2017756).

Using the Controlling Nutritional Status (CONUT) Score for Evaluating Patients with Early-Stage Hepatocellular Carcinoma After Radiofrequency Ablation: A Two-Center Retrospective Study

PURPOSE

To estimate the prognostic significance of the controlling nutritional status (CONUT) in patients with BCLC stage A hepatocellular carcinoma (HCC) after radiofrequency ablation (RFA).

MATERIALS AND METHODS

From January 2013 to December 2016, 325 patients with BCLC stage A HCC who underwent RFA at the National Cancer Center and First Hospital of Shanxi Medical University were retrospectively studied. The patients were divided into low (≤ 4) and high (≥ 5) CONUT scores for assessment of overall survival (OS) and recurrence-free survival (RFS). Several covariates, including age, sex, the diameter and number of lesions, lesion differentiation, Child-Pugh class, hepatitis B virus infection, along with blood levels of AFP, AST, ALT, γ-GT, and TBIL, were assessed using univariate and multivariate analyses.

RESULTS

The mortality rate was 17.49% (46/263) and 35.48% (22/62) in the low and high CONUT groups, respectively, with the difference being statistically significant (P = 0.033). In addition, disease recurrence was significantly higher in the high CONUT group at 70.97%, as compared to the low CONUT group at 43.35% (P = 0.041). The predictive factors were used to build the nomogram to estimate 1-, 3- and 5-year OS and RFS rates.

CONCLUSIONS

CONUT scores were found to be associated with the prognosis of patients with early-stage HCC who underwent RFA. Higher CONUT scores were associated with poor survival outcomes.

Prognostic Nomogram for Hepatitis B Virus-related Hepatocellular Carcinoma With Adjuvant Transarterial Chemoembolization After Radical Resection

OBJECTIVES

The objective of this study was to establish a reliable and effective nomogram for predicting prognosis of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) with postoperative adjuvant transarterial chemoembolization (TACE).

PATIENTS AND METHODS

A derivation cohort of 370 HCC patients treated with postoperative TACE in the Eastern Hepatobiliary Surgery Hospital from January 2009 to December 2012 were retrospectively analyzed. Univariate and multivariate analysis were performed by Cox regression and independent prognostic factors for overall survival were determined to construct the nomogram. Concordance index (C-index), calibration curve and decision curve analysis were performed to evaluate the capability of the nomogram and the established nomogram was compared with TNM stage and Barcelona Clinic Liver Cancer (BCLC) stage to identify the superior model. The results were validated in a validation cohort of 123 HCC patients in the same center.

RESULTS

Multivariate analysis indicated that γ-glutamyl transferase, α-fetoprotein, tumor number, tumor size, satellite lesions, microvascular invasion, and HBV-DNA were independent prognostic factors for overall survival in the derivation cohort, and all these factors were selected into the nomogram. The C-index was 0.755 for survival prediction of the nomogram, which was significantly higher than the TNM stage (0.636, P<0.001) and BCLC stage (0.594, P<0.001). A fair uniformity and a superior net benefit with wide range threshold probabilities were showed in the calibration curves and decision curve analysis. In the validation cohort, the C-index of the nomogram (0.785) also had a higher predictive accuracy than TNM stage (0.744, P=0.019) and BCLC stage (0.616, P<0.001).

CONCLUSIONS

The nomogram with accurate and reasonable performance was proposed for predicting survival of HBV-related HCC with postoperative adjuvant TACE.

Development and validation of a nomogram for predicting overall survival of node-negative ampullary carcinoma

BACKGROUND

The accuracy of the current staging system for predicting the overall survival (OS) of patients with ampullary carcinoma (AC) is still unsatisfactory, especially in node-negative (N0) patients. We aimed at establishing a nomogram to accurately predict OS in N0 AC.

METHODS

This study enrolled 697 N0 AC patients from the Surveillance, Epidemiology, and End Results database (design cohort [DC], n = 697) and the First Affiliated Hospital of Sun Yat-sen University (validation cohort [VC], n = 112), who underwent surgical resection. The nomogram was established by using prognostic factors determined by univariate and multivariate regression analyses.

RESULTS

The nomogram for OS was developed by using four independent prognostic factors, including age, grade, T stage, and a number of examined lymph nodes. The C-index of a nomogram for OS in DC and VC was 0.665 and 0.731, respectively. Calibration curves showed good consistency of the nomogram. The nomogram had a better accuracy in predicting OS compared with conventional staging system (P < .05). On the basis of nomogram-predicted scores, the patients were stratified into groups with different risk. The OS of low-risk patients was significantly longer than high-risk ones (P ≤ .010).

CONCLUSIONS

The nomogram could be used to predict the OS of N0 AC. It could help guide further treatment in clinical practice.

Hepatocellular carcinoma macroscopic gross appearance on imaging: predictor of outcome after transarterial chemoembolization in a real-life multicenter French cohort

BACKGROUND

Conventional transarterial chemoembolization (cTACE) with lipiodol is widely performed in patients with hepatocellular carcinoma (HCC) unsuitable for curative treatment. Additional tumor parameters such as HCC macroscopic appearance based on imaging might be helpful for transarterial chemoembolization prognostication and management.

PATIENTS AND METHODS

A total of 405 patients with HCC who underwent cTACE between 2008 and 2016 from a real-life multicenter French cohort were retrospectively reviewed. Tumors were classified into two macroscopic types according to HCC gross appearance on imaging: nodular versus non-nodular. The study population was stratified into two groups: derivation and validation cohorts. Independent prognostic factors of survival based on multivariate cox regression models were determined and then assessed in the validation set. Thereafter, time to progression (TTP) and radiological response rate were investigated for each prognostic factors of survival.

RESULTS

Median overall survival (OS) was 35 months for Barcelona Clinic Liver Cancer (BCLC) stage A, 22 months for BCLC stage B and 12 months for BCLC stage C patients (P < 0.0001). The corresponding TTP for these patients was 12 (7-17) months, 5 (3-6) months and 1.2 (1.2-3) months (P < 0.0001). Multivariate analysis revealed that tumors size and number, non-nodular type, alpha-fetoprotein, aspartate aminotransferase serum levels and impairment of performance status-1 were independent predictors of survival among the study groups. Non-nodular type was the most powerful factor that influences OS, TTP and radiological response rate for the recommended transarterial chemoembolization candidates. TTP was consistent with OS within each stage.

CONCLUSION

HCC macroscopic appearance on imaging is a determinant predictor of outcome after cTACE in a real-life multicenter cohort.