The Kings Score refines prognostic prediction in hepatocellular carcinoma: a novel application

Predictors of Mortality in Patients with Advanced Cancer-A Systematic Review and Meta-Analysis

To timely initiate advance care planning in patients with advanced cancer, physicians should identify patients with limited life expectancy. We aimed to identify predictors of mortality. To identify the relevant literature, we searched Embase, MEDLINE, Cochrane Central, Web of Science, and PubMed databases between January 2000-April 2020. Identified studies were assessed on risk-of-bias with a modified QUIPS tool. The main outcomes were predictors and prediction models of mortality within a period of 3-24 months. We included predictors that were studied in ≥2 cancer types in a meta-analysis using a fixed or random-effects model and summarized the discriminative ability of models. We included 68 studies (ranging from 42 to 66,112 patients), of which 24 were low risk-of-bias, and 39 were included in the meta-analysis. Using a fixed-effects model, the predictors of mortality were: the surprise question, performance status, cognitive impairment, (sub)cutaneous metastases, body mass index, comorbidity, serum albumin, and hemoglobin. Using a random-effects model, predictors were: disease stage IV (hazard ratio [HR] 7.58; 95% confidence interval [CI] 4.00-14.36), lung cancer (HR 2.51; 95% CI 1.24-5.06), ECOG performance status 1+ (HR 2.03; 95% CI 1.44-2.86) and 2+ (HR 4.06; 95% CI 2.36-6.98), age (HR 1.20; 95% CI 1.05-1.38), male sex (HR 1.24; 95% CI 1.14-1.36), and Charlson comorbidity score 3+ (HR 1.60; 95% CI 1.11-2.32). Thirteen studies reported on prediction models consisting of different sets of predictors with mostly moderate discriminative ability. To conclude, we identified reasonably accurate non-tumor specific predictors of mortality. Those predictors could guide in developing a more accurate prediction model and in selecting patients for advance care planning.

Development of novel biological resection criteria for safe and oncologically satisfying resection of hepatocellular carcinoma

OBJECTIVE

To develop criteria for safe and oncologically satisfying liver resection in case of early hepatocellular carcinoma with a 5-year overall survival (OS) similar to liver transplantation.

SUMMARY BACKGROUND DATA

Liver resection (LR) and liver transplantation (LT) are potentially curative treatment options for hepatocellular carcinoma. Generally, LT achieves better OS. Due to organ shortage, however not all patients can receive a LT.

METHODS

To decide which patients to resect and which to transplant we have developed biological resection criteria (BRC) as a compound out of mGPS (modified Glascow Prognostic Scale) and the Kings-Score (for HCV cirrhosis). These are based on routine clinical values that reflect both liver function and tumor biology/immunology.

RESULTS

276 patients were analyzed. Patients undergoing LR within BRC (_inBRC) had a significantly better overall (73.6% vs. 35.4%, (p < 0.001)) and disease-free survival (54.7% vs. 17.2%, (p < 0.001)) as compared to patients outside the BRC (_outBRC). The predictive value of BRC was independent of tumor burden. In a subgroup analysis _outBRC patients had significantly worse outcome after major resection. In LT patients BRC had no predictive value.

CONCLUSIONS

BRC may be a valuable tool to predict survival after LR for HCC. Patients resected _inBRC may achieve comparable survival as LT. LR in _outBRC patients are unlikely to be curative. All _outBRC patients should be monitored closely for salvage LT.

Comparison of twelve liver functional reserve models for outcome prediction in patients with hepatocellular carcinoma undergoing surgical resection

Various noninvasive liver functional reserve models have been proposed, but their prognostic ability in patients with hepatocellular carcinoma (HCC) is unclear. We aimed to investigate the performance of twelve noninvasive liver reserve models in HCC patients undergoing surgical resection. A total of 645 patients undergoing resection were prospectively identified and retrospectively analyzed. Tumor recurrence, overall survival, and independent prognostic factors were evaluated by the Cox proportional hazards model. Of the twelve models, the King’s score showed the highest homogeneity and lowest corrected Akaike information criterion (AICc) value, suggesting a better predictive ability for tumor recurrence. In multivariate Cox analysis, we confirmed that King’s score, tumor size and serum alpha-fetoprotein level were independent predictors associated with recurrence. In survival prediction, albumin-bilirubin (ALBI) revealed the highest homogeneity and lowest value among twelve invasive models, indicating a better prognostic performance. In the Cox model, ALBI grade, tumor burden, alpha-fetoprotein, vascular invasion, diabetes mellitus and performance status were independent predictors linked with overall survival. In summary, the currently used liver function models have differential predictive ability for HCC patients undergoing surgical resection. The King’s score is a feasible tool to predict tumor recurrence, whereas ALBI grade is a more robust model for prognostic prediction.

Prognostic Performance of Ten Liver Function Models in Patients with Hepatocellular Carcinoma Undergoing Radiofrequency Ablation

Liver functional capacity is a crucial survival determinant for hepatocellular carcinoma (HCC). Noninvasive models were proposed to assess hepatic reserve, but their performance in outcome prediction is unclear. We aimed to investigate 10 currently used liver function models in HCC patients undergoing radiofrequency ablation (RFA). A total 499 HCC patients were prospectively identified. Homogeneity and corrected Akaike information criteria (AICc) were compared. Cox proportional hazards model was used to identify independent survival predictors. Significance survival differences were found across 10 noninvasive models (all p < 0.001) except for GUCI and APRI grade 2 vs 3, and King’s score grade 1 vs 2. Among these models, ALBI grade showed the highest homogeneity and lowest AICs value, indicating a better prognostic performance. Within Child-Turcotte-Pugh (CTP) score 5 group, significant survival difference was demonstrated between ALBI grade 1 and 2 (p < 0.001); for those with CTP score 6 or higher, only ALBI grade 2 and 3 showed survival difference (p < 0.001). Cox analysis disclosed that ALBI grade, tumor size and performance status were independent prognostic predictors. There was significant correlation between CTP score and other 9 models. We conclude that ALBI grade may serve as objective and feasible surrogate for prognostic prediction in HCC patients undergoing RFA.