Developing and validating a preoperative risk score to predict 90-day mortality after liver resection

Dynamic ALBI score and FIB-4 index trends to predict complications after resection of hepatocellular carcinoma: A K-means clustering approach

BACKGROUND

Severe postoperative complications still occur following hepatectomy among patients with hepatocellular carcinoma (HCC). There is a need to identify high-risk patients for severe complications to enhance patient safety. We sought to evaluate the combined impact of pre- and postoperative albumin-bilirubin (ALBI) score and Fibrosis-4 (FIB-4) index trends to predict severe complications after HCC resection.

METHOD

Patients with HCC undergoing curative-intent hepatectomy (2000-2023) were identified from an international, multi-institutional database. The cohort was divided into training (n = 439) and testing (n = 651) sets. ALBI score and FIB-4 index trends from preoperative to postoperative days 1, 3, and 5 were used for K-means clustering (K = 3). A logistic regression model was developed using the training set, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC) in both cohorts.

RESULTS

Severe complications (Clavien-Dindo Grade ≥ IIIa) occurred in 118 patients (10.8 %); 43 (9.8 %) in training and 75 (11.5 %) in testing set (p = 0.42). K-means clustering identified three groups: Cluster1 (low), Cluster2 (intermediate), and Cluster3 (high), which was associated with a progressively increasing risk of complications (p < 0.01). On multivariable logistic regression, patients in ALBI Cluster1 had 76 % decreased odds (odds ratio[OR] 0.24, 95 % CI 0.07-0.83, p = 0.02) of postoperative complications relative to Cluster3 patients. Individuals categorized into FIB-4 Cluster1 had 85 % decreased odds (OR 0.15, 95 % CI 0.02-1.24, p = 0.07) versus patients in FIB-4 Cluster3. A new prediction model incorporating ALBI and FIB-4 index clusters achieved an AUC of 0.71, outperforming models based on preoperative data. A tool was made available at https://nm49jf-miho-akabane.shinyapps.io/HCC_ALBI/.

CONCLUSION

A dynamic ALBI score and FIB-4 index trend tool improved risk stratification of patients undergoing resection of HCC relative to severe complications.

Machine learning models including preoperative and postoperative albumin-bilirubin score: short-term outcomes among patients with hepatocellular carcinoma

BACKGROUND

We sought to assess the impact of various perioperative factors on the risk of severe complications and post-surgical mortality using a novel maching learning technique.

METHODS

Data on patients undergoing resection for HCC were obtained from an international, multi-institutional database between 2000 and 2020. Gradient boosted trees were utilized to construct predictive models.

RESULTS

Among 962 patients who underwent HCC resection, the incidence of severe postoperative complications was 12.7% (n = 122); in-hospital mortality was 2.9% (n = 28). Models that exclusively used preoperative data achieved AUC values of 0.89 (95%CI 0.85 to 0.92) and 0.90 (95%CI 0.84 to 0.96) to predict severe complications and mortality, respectively. Models that combined preoperative and postoperative data achieved AUC values of 0.93 (95%CI 0.91 to 0.96) and 0.92 (95%CI 0.86 to 0.97) for severe morbidity and mortality, respectively. The SHAP algorithm demonstrated that the factor most strongly predictive of severe morbidity and mortality was postoperative day 1 and 3 albumin-bilirubin (ALBI) scores.

CONCLUSION

Incorporation of perioperative data including ALBI scores using ML techniques can help risk-stratify patients undergoing resection of HCC.

Predictive factors of 90-day mortality after curative hepatic resection for hepatocellular carcinoma: a western single-center observational study

PURPOSE

The aim of this study was to identify predictive risk factors associated with 90-day mortality after hepatic resection (HR) in hepatocellular carcinoma (HCC).

METHODS

All patients undergoing elective resection for HCC from a single- institutional and prospectively maintained database were included. Multivariate regression analysis was conducted to identify pre- and intraoperative as well as histopathological predictive factors of 90-day mortality after elective HR.

RESULTS

Between August 2004 and October 2021, 196 patients were enrolled (148 male /48 female). The median age of the study cohort was 68.5 years (range19-84 years). The rate of major hepatectomy (≥ 3 segments) was 43.88%. Multivariate analysis revealed patient age ≥ 70 years [HR 2.798; (95% CI 1.263-6.198); p = 0.011], preoperative chronic renal insufficiency [HR 3.673; (95% CI 1.598-8.443); p = 0.002], Child-Pugh Score [HR 2.240; (95% CI 1.188-4.224); p = 0.013], V-Stage [HR 2.420; (95% CI 1.187-4.936); p = 0.015], and resected segments ≥ 3 [HR 4.700; (95% 1.926-11.467); p = 0.001] as the major significant determinants of the 90-day mortality.

CONCLUSION

Advanced patient age, pre-existing chronic renal insufficiency, Child-Pugh Score, extended hepatic resection, and vascular tumor involvement were identified as significant predictive factors of 90-day mortality. Proper patient selection and adjustment of treatment strategies could potentially reduce short-term mortality.

Safety and benefits of major hepatectomy with extrahepatic bile duct resection in older perihilar cholangiocarcinoma patients

PURPOSE

To evaluate the safety and benefits of major hepatectomy with extrahepatic bile duct resection in older perihilar cholangiocarcinoma patients and to identify possible predictors of surgical mortality.

METHODS

We retrospectively analyzed the data of 102 consecutive patients who underwent major hepatectomy with extrahepatic bile duct resection for perihilar cholangiocarcinoma in our institution between 2004 and 2021. The patients were included and divided into two groups: older patients ≥ 75 years and non-older patients < 75 years. Patient characteristics, preoperative nutritional and operative risk scores, intraoperative details, postoperative outcomes, and long-term prognosis were compared between the groups. Univariate and multivariate analyses were used to identify the predictors of 90-day mortality after major hepatectomy with extrahepatic bile duct resection.

RESULTS

Significant differences were identified for some preoperative surgical risk scores, but not for nutritional scores. Older patients had a higher morbidity rate of respiratory complications (p = 0.016), but there were no significant differences in overall (p = 0.735) or disease-specific survival (p = 0.858). A high Dasari's score was identified as an independent predictive factor of 90-day mortality.

CONCLUSIONS

Major hepatectomy with extrahepatic bile duct resection can be performed for optimally selected older and younger patients with perihilar cholangiocarcinoma, resulting in a good prognosis. However, indications for extended surgery should be recognized. Dasari's preoperative risk score may be a good predictor of 90-day mortality.

A novel preoperative predictive model of 90-day mortality after liver resection for huge hepatocellular carcinoma

Background

Hepatectomy for huge hepatocellular carcinoma (HCC) (diameter ≥10 cm) is characterized by high mortality. This study aimed to establish a preoperative model to evaluate the risk of postoperative 90-day mortality for huge HCC patients.

Methods

We retrospectively enrolled 1,127 consecutive patients and prospectively enrolled 93 patients with huge HCC who underwent hepatectomy (training cohort, n=798; validation cohort, n=329; prospective cohort, n=93) in our institute. Based on independent preoperative predictors of 90-day mortality, we established a logistic regression model and visualized the model by nomogram.

Results

The 90-day mortality rates were 9.6%, 9.2%, and 10.9% in the training, validation, and prospective cohort. The α-fetoprotein (AFP) level, the prealbumin levels, and the presence of portal vein tumor thrombosis (PVTT) were preoperative independent predictors of 90-day mortality. A logistic regression model, AFP-prealbumin-PVTT score (APP score), was subsequently established and showed good performance in predicting 90-day mortality (training cohort, AUC =0.87; validation cohort, AUC =0.91; prospective cohort, AUC =0.93). Using a cut-off of −1.96, the model could stratify patients into low risk (≤−1.96) and high risk (>−1.96) with different 90-day mortality rates (~30% vs. ~2%). Furthermore, the predictive performance for 90-day mortality and overall survival was significantly superior to the Child-Pugh score, the model of end-stage liver disease (MELD) score, and the albumin-bilirubin (ALBI) score.

Conclusions

The APP score can precisely predict postoperative 90-day mortality as well as long-term survival for patients with huge HCC, assisting physician selection of suitable candidates for liver resection and improving the safety and efficacy of surgical treatment.

Development and validation of an individualized prediction calculator of postoperative mortality within 6 months after surgical resection for hepatocellular carcinoma: an international multicenter study

BACKGROUND

Evidence-based decision-making is critical to optimize the benefits and mitigate futility associated with surgery for patients with malignancies. Untreated hepatocellular carcinoma (HCC) has a median survival of only 6 months. The objective was to develop and validate an individualized patient-specific tool to predict preoperatively the benefit of surgery to provide a survival benefit of at least 6 months following resection.

METHODS

Using an international multicenter database, patients who underwent curative-intent liver resection for HCC from 2008 to 2017 were identified. Using random assignment, two-thirds of patients were assigned to a training cohort with the remaining one-third assigned to the validation cohort. Independent predictors of postoperative death within 6 months after surgery for HCC were identified and used to construct a nomogram model with a corresponding online calculator. The predictive accuracy of the calculator was assessed using C-index and calibration curves.

RESULTS

Independent factors associated with death within 6 months of surgery included age, Child-Pugh grading, portal hypertension, alpha-fetoprotein level, tumor rupture, tumor size, tumor number and gross vascular invasion. A nomogram that incorporated these factors demonstrated excellent calibration and good performance in both the training and validation cohorts (C-indexes: 0.802 and 0.798). The nomogram also performed better than four other commonly-used HCC staging systems (C-indexes: 0.800 vs. 0.542-0.748).

CONCLUSIONS

An easy-to-use online prediction calculator was able to identify patients at highest risk of death within 6 months of surgery for HCC. The proposed online calculator may help guide surgical decision-making to avoid futile surgery for patients with HCC.

Comparison of score-based prediction of 90-day mortality after liver resection

BACKGROUND

Indications for liver surgery are expanding fast and complexity of procedures increases. Preoperative mortality risk assessment by scoring systems is debatable. A previously published externally validated Mortality Risk Score allowed easy applicable and precise prediction of postoperative mortality. Aim of the study was to compare the performance of the Mortality Risk Score with the standard scores MELD and P-POSSUM.

METHODS

Data of 529 patients undergoing liver resection were analysed. Mortality Risk Score, the labMELD Score and the P-POSSUM Scores (PS, OS, P-POSSUM mortality %) were calculated. The ROC curves of the three scoring systems were computed and the areas under the curve (C-index) were calculated using logistic regression models. Comparisons between the ROC curves were performed using the corresponding Wald tests.

RESULTS

Internal validation confirmed that the risk model was predictive for a 90-day mortality rate with a C-index of 0.8421. The labMELD Score had a C-index of 0.7352 and the P-POSSUM system 0.6795 (PS 0.6953, OS 0.5413). The 90-day mortality rate increased with increasing labMELD values (p < 0.0001). Categorized according to the Mortality Risk Score Groups the labMELD Score showed a linear increase while the POSSUM Scores showed variable results.

CONCLUSIONS

By accurately predicting the risk of postoperative mortality after liver surgery the Mortality Risk Score should be useful at the selection stage. Prediction can be adjusted by use of the well-established labMELD Score. In contrast, the performance of standard P-POSSUM Scores is limited.

Comparative Analysis of the Discriminatory Performance of Different Well-Known Risk Assessment Scores for Extended Hepatectomy

The aim of this study was to assess and compare the discriminatory performance of well-known risk assessment scores in predicting mortality risk after extended hepatectomy (EH). A series of 250 patients who underwent EH (≥5 segments resection) were evaluated. Aspartate aminotransferase-to-platelet ratio index (APRI), albumin to bilirubin (ALBI) grade, predictive score developed by Breitenstein et al., liver fibrosis (FIB-4) index, and Heidelberg reference lines charting were used to compute cut-off values, and the sensitivity and specificity of each risk assessment score for predicting mortality were also calculated. Major morbidity and 90-day mortality after EH increased with increasing risk scores. APRI (86%), ALBI (86%), Heidelberg score (81%), and FIB-4 index (79%) had the highest sensitivity for 90-day mortality. However, only the FIB-4 index and Heidelberg score had an acceptable specificity (70% and 65%, respectively). A two-stage risk assessment strategy (Heidelberg–FIB-4 model) with a sensitivity of 70% and a specificity 86% for 90-day mortality was proposed. There is no single specific risk assessment score for patients who undergo EH. A two-stage screening strategy using Heidelberg score and FIB-4 index was proposed to predict mortality after major liver resection.

Propensity-matched analysis of the influence of perioperative statin therapy on outcomes after liver resection

Background

Perioperative use of statins is reported to improve postoperative outcomes after cardiac and non‐cardiovascular surgery. The aim of this study was to investigate the influence of statins on postoperative outcomes including complications of grade IIIa and above, posthepatectomy liver failure (PHLF), and 90‐day mortality rates after liver resection.

Methods

Patients who underwent hepatectomy between 2013 and 2017 were reviewed to identify statin users and non‐users (controls). Propensity matching was conducted for age, BMI, type of surgery and preoperative co‐morbidities to compare subgroups. Univariable and multivariable analyses were performed for the following outcomes: 90‐day mortality, significant postoperative complications and PHLF.

Results

Of 890 patients who had liver resection during the study period, 162 (18·2 per cent) were taking perioperative statins. Propensity analysis selected two matched groups, each comprising 154 patients. Overall, 81 patients (9·1 per cent) developed complications of grade IIIa or above, and the 90‐day mortality rate was 3·4 per cent (30 patients), with no statistically significant difference when the groups were compared before and after matching. The rate of PHLF was significantly lower in patients on perioperative statins than in those not taking statins (10·5 versus 17·3 per cent respectively; P = 0·033); similar results were found after propensity matching (10·4 versus 20·8 per cent respectively; P = 0·026).

Conclusion

The rate of PHLF was significantly lower in patients taking perioperative statins, but there was no statistically significant difference in severe complications and mortality rates.