A new model based inflammatory index and tumor burden score (TBS) to predict the recurrence of hepatocellular carcinoma (HCC) after liver resection

Magnetic resonance imaging radiomics based on artificial intelligence is helpful to evaluate the prognosis of single hepatocellular carcinoma

Background

Previous studies mostly use single-type features to establish a prediction model. We aim to develop a comprehensive prediction model that effectively identify patients with poor prognosis for single hepatocellular carcinoma (HCC) based on artificial intelligence (AI). Patients and methods: 236 single HCC patients were studied to establish a comprehensive prediction model. We collected the basic information of patients and used AI to extract the features of magnetic resonance (MR) images.

Results

The clinical model based on linear regression (LR) algorithm (AUC: 0.658, 95%CI: 0.5021-0.8137), the radiomics model and deep transfer learning (DTL) model based on light gradient-boosting machine (Light GBM) algorithm (AUC: 0.761, 95%CI: 0.6326-0.8886 and AUC: 0.784, 95%CI: 0.6587-0.9087, respectively) were the optimal prediction models. A comparison revealed that the integrated nomogram had the largest area under the receiver operating characteristic curve (AUC) (all P < 0.05). In the training cohort, the integrated nomogram was predictive of recurrence-free survival (RFS) as well as overall survival (OS) (C-index: 0.735 and 0.712, P < 0.001). In the test cohort, the integrated nomogram also can predict RFS and OS (C-index: 0.718 and 0.740, P < 0.001) in patients.

Conclusion

The integrated nomogram composed of signatures in the prediction models can not only predict the postoperative recurrence of single HCC patients but also stratify the risk of OS after the operation.

Prognostic value of preoperative systemic immune-inflammation index/albumin for patients with hepatocellular carcinoma undergoing curative resection

BACKGROUND

Hepatocellular carcinoma (HCC) is a major factor for cancer-associated mortality globally. Although the systemic immune-inflammation index (SII) and albumin (ALB) show individual prognostic value for various cancers, their combined significance (SII/ALB) in HCC patients undergoing curative hepatectomy is still unknown. It is hypothesized that a higher SII/ALB ratio correlates with poorer outcomes with regard to overall survival (OS) and recurrence-free survival (RFS).

AIM

To investigate the effect of preoperative SII/ALB in predicting the prognosis of HCC patients undergoing hepatectomy.

METHODS

Patients who received curative surgery for HCC at a single institution between 2014 and 2019 were retrospectively analyzed. Cox proportional hazards models and Kaplan-Meier curves were utilized to estimate OS and RFS. A nomogram was created using prognostic factors determined by the least absolute shrinkage and selection operator method and analyzed using multivariate Cox regression. This nomogram was assessed internally through the calibration plots, receiver operating characteristic (ROC) analysis, decision curve analysis (DCA) and the concordance index (C-index).

RESULTS

This study enrolled 1653 HCC patients. Multivariate analyses demonstrated that SII/ALB independently predicted OS [hazard ratio (HR) = 1.22, 95%CI: 1.03-1.46, P = 0.025] and RFS (HR = 1.19, 95%CI: 1.03-1.38, P = 0.022). Age, alpha-fetoprotein, hepatitis B surface antigen, albumin-bilirubin grade, tumor diameter, portal vein tumor thrombus, tumor number, and SII/ALB were incorporated into the nomogram to predict OS. The nomogram had a C-index of 0.73 (95%CI: 0.71-0.76) and 0.71 (95%CI: 0.67-0.74) for the training and validation cohorts, respectively. The area under the ROC curve, DCA and calibration curves demonstrated high accuracy and clinical benefits.

CONCLUSION

The SII/ALB may independently predict outcomes in HCC patients who receive curative surgical treatment. In addition, the nomogram can be used in HCC treatment decision-making.

Nomogram for prediction of hepatocellular carcinoma recurrence after liver resection

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy with high mortality. Liver resection (LR) is a curative treatment for early-stage HCC, but the prognosis of HCC patients after LR is unsatisfactory because of tumor recurrence. Prognostic prediction models with great performance are urgently needed. The present study aimed to establish a novel prognostic nomogram to predict tumor recurrence in HCC patients after LR.

METHODS

We retrospectively analyzed 726 HCC patients who underwent LR between October 2011 and December 2016. Patients were randomly divided into the training cohort (n = 508) and the testing cohort (n = 218). The protein expression of 14 biomarkers in tumor tissues was assessed by immunohistochemistry. The nomogram predicting recurrence-free survival (RFS) was established by a multivariate Cox regression analysis model and was evaluated by calibration curves, Kaplan-Meier survival curves, time-dependent areas under the receiver operating characteristic (ROC) curves (AUCs), and decision curve analyses in both the training and testing cohorts.

RESULTS

Alpha-fetoprotein [hazard ratio (HR) = 1.013, P = 0.002], portal vein tumor thrombosis (HR = 1.833, P < 0.001), ascites (HR = 2.024, P = 0.014), tumor diameter (HR = 1.075, P < 0.001), E-cadherin (HR = 0.859, P = 0.011), EMA (HR = 1.196, P = 0.022), and PCNA (HR = 1.174, P = 0.031) immunohistochemistry scores were found to be independent factors for RFS. The 1-year and 3-year AUCs of the nomogram for RFS were 0.813 and 0.739, respectively. The patients were divided into the high-risk group and the low-risk group by median value which was generated from the nomogram, and Kaplan-Meier analysis revealed that the high-risk group had a shorter RFS than the low-risk group in both the training (P < 0.001) and testing cohorts (P < 0.001).

CONCLUSIONS

Our newly developed nomogram integrated clinicopathological data and key gene expression data, and was verified to have high accuracy in predicting the RFS of HCC patients after LR. This model could be used for early identification of patients at high-risk of postoperative recurrence.

High tumor burden score indicated the unfavorable prognosis in patients with hepatocellular carcinoma: A meta-analysis

BACKGROUND

Tumor burden score (TBS) based on maximum tumor diameter and number has been shown to correlate with prognosis in patients with hepatocellular carcinoma (HCC). Nevertheless, the results are conflicting. Hence, we conducted a meta-analysis to analyze the association between TBS and survival outcomes of HCC patients.

METHODS

A comprehensively search of the databases including PubMed, Embase and Web of Science was performed to retrieve studies satisfying the inclusion criteria until August 31, 2023. The hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. All the data analyses were carried out by STATA 12.0.

RESULTS

10 retrospective studies containing 25073 patients were incorporated in the study. The results demonstrated that high TBS was markedly association with poor overall survival (OS) (HR: 1.79, 95% CI: 1.45-2.23) and relapse-free survival / progression-free survival(RFS/PFS) (HR: 1.71; 95% CI: 1.42-2.07). Subgroup analysis showed that the prognostic value of TBS in HCC was not affected by any subgroup.

CONCLUSIONS

TBS may be an efficient prognostic index in HCC patients.

Decoding the Prognostic Significance and Therapeutic Implications of Inflammation-Based Scores in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, posing a significant global health challenge with an increasing incidence. In recent years, multiple staging systems and scores have been proposed, emphasising the necessity for the development of precise prognostic tools. The well-documented etiological relationship between chronic inflammation and carcinogenesis has prompted researchers to explore novel prognostic markers associated with the inflammatory status of HCC patients. This review summarises the current data about inflammation-based scores in the context of HCC. We discuss established scores like the Glasgow Prognostic Score (GPS), modified GPS (mGPS) and the neutrophil-to-lymphocyte ratio (NLR) and others not as extensively studied, examining their utility in predicting survival outcomes and treatment response in HCC patients. Furthermore, we explore emerging scores, including the prognostic nutritional index (PNI) and other lymphocyte-based scores, assessing their potential in refining risk stratification and guiding therapeutic decisions in the era of precision medicine. As research progresses and these scores undergo further refinement and integration into the evolving landscape of HCC management, they carry significant potential for improving patient outcomes.

Construction and validation of a novel tumor morphology immune inflammatory nutritional score (TIIN score) for intrahepatic cholangiocarcinoma: a multicenter study

BACKGROUND

Tumor morphology, immune function, inflammatory levels, and nutritional status play critical roles in the progression of intrahepatic cholangiocarcinoma (ICC). This multicenter study aimed to investigate the association between markers related to tumor morphology, immune function, inflammatory levels, and nutritional status with the prognosis of ICC patients. Additionally, a novel tumor morphology immune inflammatory nutritional score (TIIN score), integrating these factors was constructed.

METHODS

A retrospective analysis was performed on 418 patients who underwent radical surgical resection and had postoperative pathological confirmation of ICC between January 2016 and January 2020 at three medical centers. The cohort was divided into a training set (n = 272) and a validation set (n = 146). The prognostic significance of 16 relevant markers was assessed, and the TIIN score was derived using LASSO regression. Subsequently, the TIIN-nomogram models for OS and RFS were developed based on the TIIN score and the results of multivariate analysis. The predictive performance of the TIIN-nomogram models was evaluated using ROC survival curves, calibration curves, and clinical decision curve analysis (DCA).

RESULTS

The TIIN score, derived from albumin-to-alkaline phosphatase ratio (AAPR), albumin-globulin ratio (AGR), monocyte-to-lymphocyte ratio (MLR), and tumor burden score (TBS), effectively categorized patients into high-risk and low-risk groups using the optimal cutoff value. Compared to individual metrics, the TIIN score demonstrated superior predictive value for both OS and RFS. Furthermore, the TIIN score exhibited strong associations with clinical indicators including obstructive jaundice, CEA, CA19-9, Child-pugh grade, perineural invasion, and 8th edition AJCC N stage. Univariate and multivariate analysis confirmed the TIIN score as an independent risk factor for postoperative OS and RFS in ICC patients (p < 0.05). Notably, the TIIN-nomogram models for OS and RFS, constructed based on the multivariate analysis and incorporating the TIIN score, demonstrated excellent predictive ability for postoperative survival in ICC patients.

CONCLUSION

The development and validation of the TIIN score, a comprehensive composite index incorporating tumor morphology, immune function, inflammatory level, and nutritional status, significantly contribute to the prognostic assessment of ICC patients. Furthermore, the successful application of the TIIN-nomogram prediction model underscores its potential as a valuable tool in guiding individualized treatment strategies for ICC patients. These findings emphasize the importance of personalized approaches in improving the clinical management and outcomes of ICC.

GALAD score as a prognostic model for recurrence of hepatocellular carcinoma after local ablation

BACKGROUND

Currently, the high recurrence rate still forms severe challenges in hepatocellular carcinoma (HCC) treatment. The GALAD score, including age, gender, alpha-fetoprotein (AFP), lens culinaris agglutinin-reactive AFP (AFP-L3), and des-gamma-carboxyprothrombin (DCP) was developed as a diagnostic model. However, evidence is still lacking to confirm the capability of the GALAD score to predict the recurrence of HCC.

METHODS

This study included 390 HCC patients after local ablation at Beijing You'an Hospital from January 1, 2018, to December 31, 2022. Firstly, the area under the receiver operating characteristic (ROC) curve (AUC) was calculated to assess the predictive capability of the GALAD score. Then, the Kaplan-Meier (KM) curve and log-rank test were used to compare the prognosis between two groups classified by GALAD score. Finally, a nomogram for high-risk patients was established by Lasso-Cox regression. It was assessed by ROC curves, calibration curves, and decision curve analysis (DCA).

RESULTS

The ROC curve (AUC: 0.749) and KM curve showed the GALAD score had good predictive ability and could clearly stratify patients into two groups through the risk of recurrence. Prognostic factors selected by Lasso-Cox regression contained tumor number, tumor size, and globulin. The nomogram for high-risk patients showed reliable discrimination, calibration, and clinical utility.

CONCLUSION

This research displayed that the GALAD score is an effective model for predicting the recurrence of HCC. Meanwhile, we found the poor prognosis of the high-risk group and created a nomogram for these patients.

Predictive value of HTS grade in patients with intrahepatic cholangiocarcinoma undergoing radical resection: a multicenter study from China

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is a highly malignant tumor with a poor prognosis. This study aimed to investigate whether Hemoglobin, Albumin, Lymphocytes, and Platelets (HALP) score and Tumor Burden Score (TBS) serves as independent influencing factors following radical resection in patients with ICC. Furthermore, we sought to evaluate the predictive capacity of the combined HALP and TBS grade, referred to as HTS grade, and to develop a prognostic prediction model.

METHODS

Clinical data for ICC patients who underwent radical resection were retrospectively analyzed. Univariate and multivariate Cox regression analyses were first used to find influencing factors of prognosis for ICC. Receiver operating characteristic (ROC) curves were then used to find the optimal cut-off values for HALP score and TBS and to compare the predictive ability of HALP, TBS, and HTS grade using the area under these curves (AUC). Nomogram prediction models were constructed and validated based on the results of the multivariate analysis.

RESULTS

Among 423 patients, 234 (55.3%) were male and 202 (47.8) were aged ≥ 60 years. The cut-off value of HALP was found to be 37.1 and for TBS to be 6.3. Our univariate results showed that HALP, TBS, and HTS grade were prognostic factors of ICC patients (all P < 0.05), and ROC results showed that HTS had the best predictive value. The Kaplan-Meier curve showed that the prognosis of ICC patients was worse with increasing HTS grade. Additionally, multivariate regression analysis showed that HTS grade, carbohydrate antigen 19-9 (CA19-9), tumor differentiation, and vascular invasion were independent influencing factors for Overall survival (OS) and that HTS grade, CA19-9, CEA, vascular invasion and lymph node invasion were independent influencing factors for recurrence-free survival (RFS) (all P < 0.05). In the first, second, and third years of the training group, the AUCs for OS were 0.867, 0.902, and 0.881, and the AUCs for RFS were 0.849, 0.841, and 0.899, respectively. In the first, second, and third years of the validation group, the AUCs for OS were 0.727, 0.771, and 0.763, and the AUCs for RFS were 0.733, 0.746, and 0.801, respectively. Through the examination of calibration curves and using decision curve analysis (DCA), nomograms based on HTS grade showed excellent predictive performance.

CONCLUSIONS

Our nomograms based on HTS grade had excellent predictive effects and may thus be able to help clinicians provide individualized clinical decision for ICC patients.

PIVKA-II combined with tumor burden score to predict long-term outcomes of AFP-negative hepatocellular carcinoma patients after liver resection

BACKGROUND

This study aimed to establish a simple prognostic scoring model based on tumor burden score (TBS) and PIVKA-II to predict long-term outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients.

METHODS

511 patients were divided into the training cohort (n = 305) and the validation cohort (n = 206) at a ratio of 6:4. Receiver operating characteristic curves (ROC) were established to identify cutoff values of TBS and PIVKA-II. Kaplan-Meier curves were used to analyze survival outcomes. The multivariable Cox regression was used to identify variables independently associated with survival outcomes. The predictive performance of the TBS-PIVKA II score (TPS) model was compared with Barcelona clinic liver cancer (BCLC) stage and American Joint Committee on Cancer (AJCC TNM) stage.

RESULTS

The present study established the TPS model using a simple scoring system (0, 1 for low/high TBS [cutoff value: 4.1]; 0, 1 for low/high PIVKA-II [cutoff value: 239 mAU/mL]). The TPS scoring model was divided into three levels according to the summation of TBS score and PIVKA-II score: TPS 0, TPS 1, and TPS 2. The TPS scoring model was able to stratify OS (training: p < 0.001, validation: p < 0.001) and early recurrence (training: p < 0.001; validation: p = 0.001) in the training cohort and the validation cohort. The TPS score was independently associated with OS (TPS 1 vs. 0, HR: 2.28, 95% CI: 1.01-5.17; TPS 2 vs. 0, HR: 4.21, 95% CI: 2.01-8.84) and early recurrence (TPS 1 vs. 0, HR: 3.50, 95% CI: 1.71-7.16; TPS 2 vs. 0, HR: 3.79, 95% CI: 1.86-7.75) in the training cohort. The TPS scoring model outperformed BCLC stage and AJCC TNM stage in predicting OS and early recurrence in the training cohort and the validation cohort. But the TPS scoring model was unable to stratify the late recurrence in the training cohort (p = 0.872) and the validation cohort (p = 0.458).

CONCLUSIONS

The TPS model outperformed the BCLC stage and AJCC TNM stage in predicting OS and early recurrence of AFP-negative HCC patients after liver resection, which might better assist surgeons in screening AFP-negative HCC patients who may benefit from liver resection.

Prognostic significance of globulin/low-density lipoprotein ratio in patients with hepatocellular carcinoma after local ablative therapy: a retrospective cohort study

Background

Low-density lipoprotein (LDL) and globulin (GLOB) have been found to be predictors for some malignant tumors, but their predictive value in hepatocellular carcinoma (HCC) has hardly been elucidated. This study assessed the prognostic significance of GLOB to LDL ratio (GLR) in HCC patients before ablation.

Methods

This study analyzed 312 early-stage HCC patients who were hospitalized and underwent ablative treatment in Beijing You'an Hospital, Capital Medical University, from 1 January 2014 to 1 January 2019. The primary endpoint was the recurrence-free survival (RFS), calculated from treatment initiation to cancer recurrence, whereas the overall survival (OS) was measured from treatment initiation to death or last follow-up. Cox regression analysis was used to assess the GLR independently associated with recurrence and survival. OS and RFS were calculated by Kaplan-Meier analysis and compared between groups using the log rank test. The optimal cut-off value and prognostic role of GLR and other markers were evaluated via the receiver operating characteristic (ROC) curves and the Youden index.

Results

Univariate and multivariate analysis found that the tumor number, tumor size, and GLR were independent risk factors of relapse, whereas etiology, tumor number, tumor size, fibrinogen (Fib), and GLR were related to OS. We classified the patients into groups with high and low levels of GLR based on the optimal cut-off value of GLR identified by ROC curve. The cumulative 1-, 3-, and 5-year RFS rates in the low GLR group were 76.4%, 53.8%, and 43.4% respectively, whereas those in the high GLR group were 71%, 31%, and 22%, respectively (P<0.001). In terms of OS, the low GLR group showed a 1-, 3-, and 5-year OS of 99.5%, 92.0%, and 80.2% respectively, and 98%, 73%, and 63% respectively for the high GLR group (P<0.001). Finally, patients were stratified by GLR and tumor size. The outcomes revealed that patients in group A (GLR <16.54 and tumor size ≤30 mm) showed better prognosis than those in group B (GLR ≥16.54 and tumor size ≤30 mm or GLR <16.54 and tumor size >30 mm) and group C (GLR ≥16.54 and tumor size >30 mm) (P<0.001).

Conclusions

Preoperative GLR ratio has predictive value for patients with HCC who have undergone complete ablation.

Tumor burden score-AFP-albumin-bilirubin grade score predicts the survival of patients with hepatocellular carcinoma after liver resection

PURPOSE

There is little information regarding the overall survival (OS) predictive ability of the combination of tumor burden score (TBS), α-fetoprotein (AFP), and albumin-bilirubin (ALBI) grade for patients with hepatocellular carcinoma (HCC). Here, we aimed to develop a model including TBS, AFP, and ALBI grade to predict HCC patient OS following liver resection.

METHODS

Patients (N = 1556) from six centers were randomly divided 1:1 into training and validation sets. The X-Tile software was used to determine the optimal cutoff values. The time-dependent area under the receiver operating characteristic curve (AUROC) was calculated to assess the prognostic ability of the different models.

RESULTS

In the training set, tumor differentiation, TBS, AFP, ALBI grade, and Barcelona Clinic Liver Cancer (BCLC) stage were independently related to OS. According to the coefficient values of TBS, AFP, and ALBI grade, we developed the TBS-AFP-ALBI (TAA) score using a simplified point system (0, 2 for low/high TBS, 0, 1 for low/high AFP and 0,1 for ALBI grade 1/2). Patients were further divided into low TAA (TAA ≤ 1), medium TAA (TAA = 2-3), and high TAA (TAA= 4) groups. TAA scores (low: referent; medium, HR = 1.994, 95% CI = 1.492-2.666; high, HR = 2.413, 95% CI = 1.630-3.573) were independently associated with patient survival in the validation set. The TAA scores showed higher AUROCs than BCLC stage for the prediction of 1-, 3-, and 5-year OS in both the training and validation sets.

CONCLUSION

TAA is a simple score that has better OS prediction performance than the BCLC stage in predicting OS for HCC patients after liver resection.

Combination of neutrophil/lymphocyte ratio and albumin/bilirubin grade as a prognostic predictor for hepatocellular carcinoma patients undergoing curative hepatectomy

BACKGROUND AND AIM

Prognosis determination is essential for hepatocellular carcinoma (HCC) patient management and treatment planning. The current study aimed to evaluate the prognosis performance of NLR, ALBI, and the combination of NLR-ALBI in determining the overall survival (OS) of HCC patients under curative hepatectomy.

METHODS

144 primary HCC patients with curative hepatectomy were recruited in the retrospective study. The clinicopathologic characteristics and OS were compared between stratified groups. The predictive performance of NLR, ALBI, and the combination of NLR-ALBI was explored by the area under the receiver operating characteristic curve (AUC). Univariate and multivariate analyses were used to determine the risk factors of OS.

RESULTS

AUC determined NLR cutoff > 2.60 for predicting prognosis. The univariate analysis indicated pathological differentiation, tumor size, AFP, TNM stage, NLR score, and ALBI grade were significant indicators of OS. However, only TMN grade, AFP, NLR score, and NLR-ALBI score were identified as independent predictors of OS in the multivariable analysis. The AUC of NLR, ALBI and the combination of NLR-ALBI was 0.618(95%CI 0.56-0.710), 0.533 (95%CI 0.437-0.629), 0.679 (95%CI 0.592-0.767) respectively. Patients with higher NLR-ALBI scores presented worse outcomes than those with lower NLR-ALBI scores.

CONCLUSION

NLR is an independent prognostic factor of HCC and a reliable biomarker in predicting the OS of HCC patients. The combination of NLR-ALBI showed a better prognostic performance than using NLR or ALBI alone, implicating the effectiveness and feasibility of combining multiple risk factors for postoperative prognosis assessment.

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

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