Prediction of long-term survival rates in patients undergoing curative resection for solitary hepatocellular carcinoma

Prognostic Nomograms for Patients with Hepatocellular Carcinoma After Curative Hepatectomy, with a Focus on Recurrence Timing and Post-Recurrence Management

Background

Prognoses of patients with hepatocellular carcinoma (HCC) after curative hepatectomy remain unsatisfactory because of the high incidence of postoperative recurrence. Published predictive systems focus on pre-resection oncological characteristics, ignoring post-recurrence factors.

Purpose

This study aimed to develop prognostic nomograms for 3- and 5-year overall survival (OS) of patients with HCC after curative hepatectomy, focusing on potentially influential post-recurrence factors.

Patients and Methods

Clinicopathological and postoperative follow-up data were extracted from 494 patients with HCC who underwent curative hepatectomy between January 2012 and June 2019. Early recurrence (ER) and late recurrence (LR) were defined as recurrence at ≤2 and >2 years, respectively, after curative hepatectomy. Nomograms for the prediction of 3- and 5-year OS were established based on multivariate analysis. The areas under time-dependent receiver operating characteristic curves (AUCs) for the nomograms were calculated independently to verify predictive accuracy. The nomograms were internally validated based on 2000 bootstrap resampling of 75% of the original data.

Results

In total, 494 patients with HCC who underwent curative hepatectomy met the eligibility criteria. Cox proportional hazard regression analysis identified factors potentially influencing 3- and 5-year OS. Multivariate analysis indicated that patient age, Hong Kong Liver Cancer stage, γ-glutamyl transferase (γ-GGT) level, METAVIR inflammation activity grade, ER and post-recurrence treatment modality were influencing factors for 3-year OS (AUC, 0.891; 95% CI, 0.8364-0.9447). γ-GGT > 60 U/L, hepatectomy extent, LR and post-recurrence treatment modality were influencing factors for 5-year OS (AUC, 0.864; 95% CI, 0.8041-0.9237). Calibration plots showed satisfactory concordance between the predicted and actual observation cohorts.

Conclusion

We propose new prognostic nomograms for OS prediction with a focus on the differentiation of recurrence timing and post-recurrence management. These nomograms overcome the shortcomings of previous predictive nomograms and significantly improve predictive accuracy.

Underlying liver disease and advanced stage liver cancer are associated with elevated neutrophil-lymphocyte ratio

Background/Aims

Inflammation-based scores, such as the neutrophil-to-lymphocyte ratio (NLR), have been associated with prognosis in hepatocellular carcinoma (HCC); but variable cut-off values and potential lack of specificity have limited the utility of NLR. This study evaluates NLR in a large cohort of HCC patients.

Methods

We retrospectively reviewed 789 HCC cases (1993–2017) for demographics, tumor characteristics, treatment, and survival. NLR was stratified into NLR ≥1.5 and NLR ≥3 and analyzed for correlation with American Joint Committee on Cancer (AJCC) and Barcelona Clinic Liver Cancer (BCLC) stages. In 235 patients who underwent liver resection, survival and recurrence were evaluated by NLR.

Results

In 789 HCC cases, mean NLR was increased with advanced AJCC and BCLC stages. Hepatitis C patients were less likely to have NLR ≥1.5 and ≥3. Non-alcoholic steatohepatitis patients were more likely to have NLR ≥3. Patients with tumor size >5 cm, rupture, or macrovascular invasion were more likely to have NLR ≥3. In patients treated with resection, NLR ≥3 predicted early recurrence (odds ratio [OR] 4.14, P<0.01) and overall recurrence (OR 4.05, P<0.01). Mean NLR was 4.30 in those with recurrence and 2.75 in those without recurrence. Patients with NLR ≥3 showed significantly worse survival compared to those with NLR <3 (P<0.01 by log-rank test).

Conclusions

Elevated NLR is associated with advanced cancer stage and aggressive tumor characteristics, such as large size, rupture, and invasion. NLR ≥3 was associated with early and overall recurrence after resection but varied with etiology. NLR may be a useful biomarker in predicting recurrence for HCC patients undergoing curative resection, but further studies are required to elucidate the effect of disease etiology.

Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: A prospective study

Objective

To investigate the value of whole-lesion texture analysis on preoperative gadoxetic acid enhanced magnetic resonance imaging (MRI) for predicting tumor Ki-67 status after curative resection in patients with hepatocellular carcinoma (HCC).

Methods

This study consisted of 89 consecutive patients with surgically confirmed HCC. Texture features were extracted from multiparametric MRI based on whole-lesion regions of interest. The Ki-67 status was immunohistochemical determined and classified into low Ki-67 (labeling index ≤15%) and high Ki-67 (labeling index >15%) groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were applied for generating the texture signature, clinical nomogram and combined nomogram. The discrimination power, calibration and clinical usefulness of the three models were evaluated accordingly. Recurrence-free survival (RFS) rates after curative hepatectomy were also compared between groups.

Results

A total of 13 texture features were selected to construct a texture signature for predicting Ki-67 status in HCC patients (C-index: 0.878, 95% confidence interval: 0.791-0.937). After incorporating texture signature to the clinical nomogram which included significant clinical variates (AFP, BCLC-stage, capsule integrity, tumor margin, enhancing capsule), the combined nomogram showed higher discrimination ability (C-index: 0.936vs. 0.795, P<0.001), good calibration (P>0.05 in Hosmer-Lemeshow test) and higher clinical usefulness by decision curve analysis. RFS rate was significantly lower in the high Ki-67 group compared with the low Ki-67 group after curative surgery (63.27%vs. 85.00%, P<0.05).

Conclusions

Texture analysis on gadoxetic acid enhanced MRI can serve as a noninvasive approach to preoperatively predict Ki-67 status of HCC after curative resection. The combination of texture signature and clinical factors demonstrated the potential to further improve the prediction performance.

PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data

Background

Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis may be caused by high complexity of biological systems, where multiple biological components and their hierarchical relationships are involved. Moreover, it is challenging to develop robust computational solutions with high-dimension, low-sample size data.

Results

In this study, we propose a Pathway-Associated Sparse Deep Neural Network (PASNet) that not only predicts patients’ prognoses but also describes complex biological processes regarding biological pathways for prognosis. PASNet models a multilayered, hierarchical biological system of genes and pathways to predict clinical outcomes by leveraging deep learning. The sparse solution of PASNet provides the capability of model interpretability that most conventional fully-connected neural networks lack. We applied PASNet for long-term survival prediction in Glioblastoma multiforme (GBM), which is a primary brain cancer that shows poor prognostic performance. The predictive performance of PASNet was evaluated with multiple cross-validation experiments. PASNet showed a higher Area Under the Curve (AUC) and F1-score than previous long-term survival prediction classifiers, and the significance of PASNet’s performance was assessed by Wilcoxon signed-rank test. Furthermore, the biological pathways, found in PASNet, were referred to as significant pathways in GBM in previous biology and medicine research.

Conclusions

PASNet can describe the different biological systems of clinical outcomes for prognostic prediction as well as predicting prognosis more accurately than the current state-of-the-art methods. PASNet is the first pathway-based deep neural network that represents hierarchical representations of genes and pathways and their nonlinear effects, to the best of our knowledge. Additionally, PASNet would be promising due to its flexible model representation and interpretability, embodying the strengths of deep learning. The open-source code of PASNet is available at https://github.com/DataX-JieHao/PASNet.

Effect of KI-67 positive cellular index on prognosis after hepatectomy in Barcelona Clinic Liver Cancer stage A and B hepatocellular carcinoma with microvascular invasion

Objective

This study aimed to explore the relationship between KI-67 positive cellular index and recurrence-free survival (RFS) in Barcelona Clinic Liver Cancer (BCLC) stage A and B hepatocellular carcinoma (HCC) patients, particularly those with microvascular invasion (MVI).

Methods

A total of 333 patients who underwent curative hepatectomy had their immunohistochemistry analyzed retrospectively for KI-67 positive cellular index.

Results

In total, 41.1% (137/333) of HCC patients displayed high KI-67 positive cellular index (>35%). Patients with high KI-67 positive cellular index had poorer RFS than those with low index (P<0.0001). Patients were then subdivided into an MVI positivity group (n=192) and an MVI negativity group (n=141). In the MVI positivity group, patients with high KI-67 positive cellular index had a shorter RFS after operation as compared to those with low index (P<0.0001). However, there was no significant difference in RFS between high- and low-index subgroups within the MVI negativity group (P>0.05). Additionally, patients with high KI-67 positive cellular index combined with MVI positivity had the shortest RFS of all those with MVI negativity, regardless of KI-67 cellular index level (P<0.0001). Multivariate analysis showed that node number >1, capsule absence, high KI-67 positive cellular index, and alpha-fetoprotein >400 ng/mL were independent risk factors for a recurrence of HCC with MVI.

Conclusion

Our results suggested that high KI-67 positive cellular index may represent a poor prognostic factor in BCLC stage A and B HCC patients, especially those with MVI.