Effect of timing of surgical resection of primary hepatocellular carcinoma on survival outcomes in elderly patients and prediction of clinical models

The impact of waiting time and delayed treatment on the outcomes of patients with hepatocellular carcinoma: A systematic review and meta-analysis

Hepatocellular carcinoma (HCC) is the sixth most diagnosed cancer worldwide. Healthcare resource constraints may predispose treatment delays. We aim to review existing literature on whether delayed treatment results in worse outcomes in HCC. PubMed, Embase, The Cochrane Library, and Scopus were systematically searched from inception till December 2022. Primary outcomes were overall survival (OS) and disease-free survival (DFS). Secondary outcomes included post-treatment mortality, readmission rates, and complications. Fourteen studies with a total of 135,389 patients (delayed n = 25,516, no delay n = 109,873) were included. Age, incidence of male patients, Child-Pugh B cirrhosis, and Barcelona Clinic Liver Cancer Stage 0/A HCC were comparable between delayed and no delay groups. Tumor size was significantly smaller in delayed versus no delay group (mean difference, -0.70 cm; 95% confidence interval [CI]: -1.14, 0.26; p = 0.002). More patients received radiofrequency ablation in delayed versus no delay group (OR, 1.22; 95% CI: 1.16, 1.27; p < 0.0001). OS was comparable between delayed and no delay in HCC treatment (hazard ratio [HR], 1.13; 95% CI: 0.99, 1.29; p = 0.07). Comparable DFS between delayed and no delay groups (HR, 0.99; 95% CI: 0.75, 1.30; p = 0.95) was observed. Subgroup analysis of studies that defined treatment delay as > 90 days showed comparable OS in the delayed group (HR, 1.04; 95% CI: 0.93, 1.16; p = 0.51). OS and DFS for delayed treatment were non-inferior compared to no delay, but might be due to better tumor biology/smaller tumor size in the delayed group.

Single-center analysis of percutaneous ablation in the treatment of hepatocellular carcinoma: long-term outcomes of a 7-year experience

PURPOSE

The objective of this study is to examine the safety and efficacy of ablative therapy for hepatocellular carcinoma (HCC).

METHODS

A retrospective review of 419 consecutive patients diagnosed with HCC, treated with percutaneous ablation at a tertiary academic medical center from June 2015 to June 2022, was conducted. Data evaluated included demographics, disease and tumor burden scores, and functional status. Procedural outcomes included procedural course, complication rates, biochemical and radiologic response, survival, and functional status.

RESULTS

A total of 419 patients, including 313 males (74.7%) and 106 females (25.3%) with a mean age of 63.8 ± 6.64 years, made up the study cohort. 120 patients (28.6%) presented with solitary lesions and 299 patients (71.4%) had multifocal involvement, with a mean tumor size of 2.3 ± 0.92 cm. A majority of the interventions performed were microwave ablations (n = 413, 98.3%), with 6 radiofrequency ablations (1.4%). Treatment response was radiographically assessed up to 6 months post-ablation and graded as complete response (96.2%), partial response (2.6%), stable disease (0%), and progressive disease (1.2%). 97 (23.2%) of the treated patients went on to receive liver transplant. The average progression-free survival in the study population was 24 months with a survival of 85.9% (n = 360), 67.8% (n = 284), and 63.2% (n = 265) at 1 year, 3 years, and 5 years respectively. Functional outcomes, as defined by ECOG scores, were maintained or improved in 383 patients (91.4%) and 349 patients (83.3%) at 6 months and 12 months respectively.

CONCLUSIONS

This large institutional experience demonstrated safety and efficacy of ablation therapies for treatment of HCC with promising tumor response rates and enduring clinical outcomes including prolonged survival and preserved functional status.

Development and validation of a nomogram for survival prediction in hepatocellular carcinoma after partial hepatectomy

BACKGROUND

The prognosis for hepatocellular carcinoma (HCC) is complex due to its high level of heterogeneity, even after radical resection. This study was designed to develop and validate a prognostic nomogram for predicting the postoperative prognosis for HCC patients following partial hepatectomy.

PATIENTS AND METHODS

We extracted data on HCC patients and randomly divided them into two groups (primary and validation cohorts), using the Surveillance, Epidemiology and End Results (SEER) database. We developed the prediction model based on the data of the primary cohort and prognostic factors were evaluated using univariate and multivariate Cox regression analysis. A nomogram was constructed for predicting the 1-, 3-, and 5-year survival probability of HCC patients after surgery based on the results of the multivariate Cox regression analysis. The performance of the nomogram was evaluated in terms of its discrimination and calibration. To validated the model, discrimination and calibration were also evaluated in the validation cohort. Decision curve analysis (DCA) was performed to assess the clinical utility of the nomogram.

RESULTS

A total of 890 patients who underwent partial hepatectomy for HCC were included in the study. The primary cohort enrolled 628 patients with a median follow-up time of 39 months, the 1-, 3-, and 5-year survival rate were 95.4%, 52.7% and 25.8% during follow-up. Multivariate Cox regression analysis showed that differentiation, tumor size, AFP and fibrosis were independently association with the prognosis of HCC patients after partial hepatectomy. The nomogram showed a moderate discrimination ith a C-index of 0.705 (95% CI 0.669 to 0.742), and good calibration. Similar discrimination with a C-index of 0.681 (95% CI 0.625 to 0.737), and calibration were also observed in the validation cohort. Decision curve analysis showed that the nomogram could be useful to predicting the prognosis in HCC patients following partial hepatectomy.

CONCLUSIONS

The proposed nomogram is highly predictive and has moderate calibration and discrimination, potentially contributing to the process of managing HCC patients after partial hepatectomy in an individualized way.

Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples

Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.