Perioperative mortality for management of hepatic neoplasm: a simple risk score. Ann Surg. 2009;250:929-934. [PMID: 19855257 DOI: 10.1097/sla.0b013e3181bc9c2f]

Model for estimating the risk of postoperative morbidity and optimizing patients' management after hepatectomy

BACKGROUND

Early detection of major complications and immediate therapeutic interventions may improve patient outcome after hepatectomy. The aim of the present study was to develop a model predicting the risk of postoperative complications after hepatectomy and help identify patients who require close-monitoring in intensive care unit (ICU).

METHODS

Patients underwent hepatectomy at Humanitas Research Hospital, Italy, between 2010 and 2021 were considered. We used preoperative, intraoperative and combined predictors to build three models predicting Clavien-Dindo III-V complications. Model performances was evaluated internally via bootstrapping.

RESULTS

Of 1497 patients, 7% had Clavien-Dindo III-V complications. Tumor pathology, tumor burden, previous chemotherapy, liver characteristics, clinical portal hypertension, cardiopathy, creatinine and total protein level were incorporated in the preoperative model. In addition to these variables, type of hepatectomy, operation time, additional surgical procedure, and transfusion were incorporated into the combined model. The bootstrap corrected C-indices for preoperative, intraoperative and combined models were 0.68, 0.70 and 0.72. The median predicted probability of major complications over-1000 bootstraps was close to observed probabilities for all models.

CONCLUSION

These prognostic models may help identify patients at high-risk of major complication and guide decision-making for individual patients and postoperative ICU-care assessment. Observed optimism in model performance necessitates external validation.

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.

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 of an Integer-based Risk Score to Predict 90-Day Mortality After Hepatectomy in Patients With Hepatocellular Carcinoma

BACKGROUND

The incidence of liver cancer has more than tripled since 1980. Hepatectomy represents the major curative treatment for liver cancer. The risk factors associated with 90-day mortality after hepatectomy are not well understood and there are currently no good prediction models for this outcome. The objectives of the current study were to identify risk factors of 90-day mortality after hepatectomy in patients with hepatocellular carcinoma and to develop an integer-based risk score using the National Cancer Database.

METHODS

Hepatectomies recorded in the National Cancer Database during 2004-2012 were reviewed for 90-day mortality. Risk factors were identified by multivariate logistic regression models. An integer-based risk score was developed using the β coefficients derived from the logistic regression model and tested for discriminatory ability. According to the total risk score, patients were grouped into 4 risk groups.

RESULTS

The overall 90-day mortality was 10.2%. Ten risk factors were identified, which included sex, age, race/ethnicity, insurance status, education, annual hospital volume, stage, tumor grade, Charlson-Deyo Score, and surgical procedure. The risk of 90-day mortality was stratified into 4 groups. The calculated 90-day mortality rates were 2.47%, 5.88%, 12.58%, and 24.67% for low-risk, medium-risk, high-risk, and excessive-risk groups, respectively. An area under the receiver operating characteristic curve of 0.69 was obtained for model discrimination.

CONCLUSIONS

The integer-based risk score we developed could easily quantify each patient's risk level and predict 90-day mortality after hepatectomy. The stratified risk score could be a useful addition to perioperative risk management and a tool to improve 90-day mortality after hepatectomy.

Predictive Value of the Age-Adjusted Charlson Comorbidity Index for Outcomes After Hepatic Resection of Hepatocellular Carcinoma

BACKGROUND

This study aimed to evaluate the impact of the age-adjusted Charlson comorbidity index (ACCI) on outcomes after hepatic resection for hepatocellular carcinoma (HCC).

METHODS

We assessed 763 patients who underwent hepatic resection for HCC. The ACCI scores were categorized as follows: ACCI ≤ 5, ACCI = 6, and ACCI ≥ 7.

RESULTS

A multivariate analysis showed that the odds ratios for postoperative complications in ACCI = 6 and ACCI ≥ 7 groups, with reference to ACCI ≤ 5 group, were 0.71 (p = 0.41) and 4.15 (p < 0.001), respectively. The hazard ratios for overall survival of ACCI = 6 and ACCI ≥ 7 groups, with reference to ACCI ≤ 5 group, were 1.52 (p = 0.023) and 2.45 (p < 0.001), respectively. The distribution of deaths due to HCC-related, liver-related, and other causes was 68.2%, 11.8%, and 20% in ACCI ≤ 5 group, 47.2%, 13.9%, and 38.9% in ACCI = 6 group, and 27.3%, 9.1%, and 63.6% in ACCI ≥ 7 group (p = 0.053; ACCI ≤ 5 vs. = 6, p = 0.19; ACCI = 6 vs. ≥ 7, p < 0.001; ACCI ≤ 5 vs. ≥ 7). In terms of the treatment for HCC recurrence in ACCI ≤ 5, ACCI = 6, and ACCI ≥ 7 groups, adaptation rate of surgical resection was 20.1%, 7.3%, and 11.1% and the rate of palliative therapy was 4.3%, 12.2%, and 22.2%, respectively.

CONCLUSIONS

The ACCI predicted the short-term and long-term outcomes after hepatic resection of HCC. These findings will help physicians establish a treatment strategy for HCC patients with comorbidities.

Prediction early recurrence of hepatocellular carcinoma eligible for curative ablation using a Radiomics nomogram

BACKGROUND

Predicting early recurrence (ER) after radical therapy for HCC patients is critical for the decision of subsequent follow-up and treatment. Radiomic features derived from the medical imaging show great potential to predict prognosis. Here we aim to develop and validate a radiomics nomogram that could predict ER after curative ablation.

METHODS

Total 184 HCC patients treated from August 2007 to August 2014 were included in the study and were divided into the training (n = 129) and validation(n = 55) cohorts randomly. The endpoint was recurrence free survival (RFS). A set of 647 radiomics features were extracted from the 3 phases contrast enhanced computed tomography (CECT) images. The minimum redundancy maximum relevance algorithm (MRMRA) was used for feature selection. The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to build a radiomics signature. Recurrence prediction models were built using clinicopathological factors and radiomics signature, and a prognostic nomogram was developed and validated by calibration.

RESULTS

Among the four radiomics models, the portal venous phase model obtained the best performance in the validation subgroup (C-index = 0.736 (95%CI:0.726-0.856)). When adding the clinicopathological factors to the models, the portal venous phase combined model also yielded the best predictive performance for training (C-index = 0.792(95%CI:0.727-0.857) and validation (C-index = 0.755(95%CI:0.651-0.860) subgroup. The combined model indicated a more distinct improvement of predictive power than the simple clinical model (ANOVA, P < 0.0001).

CONCLUSIONS

This study successfully built a radiomics nomogram that integrated clinicopathological and radiomics features, which can be potentially used to predict ER after curative ablation for HCC patients.

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

BACKGROUND

Hepatobiliary surgeons continue to expand the pool of patients undergoing liver resection using combinations of surgical and interventional procedures with chemotherapy. Improved perioperative care allows for operation on higher risk surgical patients. Postoperative outcomes, including 90-day mortality that improved over the past decade but still varies across cohorts. This study developed a preoperative risk score, on the basis significant clinical and laboratory variables, to predict 90-day mortality after hepatectomy.

METHODS

All patients who underwent hepatectomy between 2011 and 2016 were included. Univariable and multivariable analyses were performed to identify the predictors of postoperative mortality and a risk score was derived and validated.

RESULTS

The overall 90-day mortality rate in the derivation cohort (n = 1269 patients) was 4.0% (N = 51). Increasing patient age (P < 0.001), extent of resection (P = 0.001), diabetes mellitus (P = 0.006), and low preoperative sodium (P = 0.012) were predictors of the increased 90-day mortality in the multivariable analysis. The risk model developed based on these factors had an AUROC of 0.778 (P < 0.001) and remained significant in a validation cohort of 788 patients (AUROC: 0.703, P < 0.001).

CONCLUSION

The proposed preoperative risk score to predict 90-day mortality after liver resection could be useful for appropriate counseling, optimization, and risk-adjusted assessment of surgical outcomes.

Developing and validating a center-specific preoperative prediction calculator for risk of outcomes following major hepatectomy procedures

BACKGROUND

The American College of Surgeons NSQIP^® Surgical Risk Calculator (SRC) was developed to estimate postoperative outcomes. Our goal was to develop and validate an institution-specific risk calculator for patients undergoing major hepatectomy at Carolinas Medical Center (CMC).

METHODS

Outcomes generated by the SRC were recorded for 139 major hepatectomies performed at CMC (2008-2016). Novel predictive models for seven postoperative outcomes were constructed and probabilities calculated. Brier score and area under the curve (AUC) were employed to assess accuracy. Internal validation was performed using bootstrap logistic regression. Logistic regression models were constructed using bivariate and multivariate analyses.

RESULTS

Brier scores showed no significant difference in the predictive ability of the SRC and CMC model. Significant differences in the discriminative ability of the models were identified at the individual level. Both models closely predicted 30-day mortality (SRC AUC: 0.867; CMC AUC: 0.815). The CMC model was a stronger predictor of individual postoperative risk for six of seven outcomes (SRC AUC: 0.531-0.867; CMC AUC: 0.753-0.970).

CONCLUSION

Institution-specific models provide superior outcome predictions of perioperative risk for patients undergoing major hepatectomy. If properly developed and validated, institution-specific models can be used to deliver more accurate, patient-specific care.

Post-operative delayed elevation of ALT correlates with early death in patients with HBV-related hepatocellular carcinoma and Post-hepatectomy Liver Failure

BACKGROUND

Post-hepatectomy Liver Failure (PHLF) remains the primary cause of perioperative death. The kinetics of transaminase levels are usually measured as markers of hepatocellular injury following partial hepatectomy, but their correlation with PHLF and post-operative mortality is unclear. The aim of study was to compare the post-operative transaminase kinetics with short term survival in those patients that developed PHLF.

METHODS

A retrospective review of patients with HBV-related HCC and who developed PHLF was performed. Logistic regression analysis was conducted to analyze risk factors for postoperative delayed elevation of ALT (PDE-ALT) PHLF and lethal PHLF.

RESULT

Of the 69 patients who developed PHLF 36 (52%) died. In those patients who died the mean ± SD ALT and AST rose from day (POD) 1-3 and continued to fluctuate with highly abnormal levels beyond day 3 with a mean ± SD peak ALT level beyond POD 3 of 1851 ± 1644 U/L (p < 0.001).

CONCLUSIONS

The kinetics of the post-operative transaminases were significantly correlated with perioperative mortality in those patients who developed PHLF. PDE-ALT indicates an increased risk of death in HBV-related HCC patients with PHLF.

Central hepatectomy versus major hepatectomy for patients with centrally located hepatocellular carcinoma: A meta-analysis

BACKGROUND

Both central hepatectomy (CH) and major hepatectomy (MH) are suggested surgical treatments for patients with centrally located hepatocellular carcinoma (CL-HCC). However, no consensus has been reached regarding which method is superior for managing these patients. This meta-analysis was conducted to compare the short- and long-term outcomes of CH and MH in patients with CL-HCC.

METHODS

An electronic search for studies published in all years up to July 2017 in PubMed (Medline), EMBASE, Cochrane Library and Web of Science was performed. The short-term outcome was the incidence of postoperative complications, and the long-term outcomes included 1-, 3- and 5-year overall survival (OS) and corresponding disease-free survival (DFS), mortality and morbidity. The results were presented as Risk Ratios (RRs) or weighted mean differences with 95% confidence intervals.

RESULTS

Four retrospective studies containing 465 patients with CL-HCC were included (248 in the CH group and 217 in the MH group). The results suggested no significant differences in the 1-, 3- and 5-year DFS, 1, 3 and 5-year OS, total morbidity or mortality between these groups. Nevertheless, the patients in the CH group presented a lower prevalence of vascular invasion (RR 0.70, 95% CI 0.52-0.93, P = 0.020) than did the MH group. In addition, CH led to a higher incidence of biliary fistula, while MH showed a higher incidence of postoperative liver failure.

CONCLUSION

This study demonstrated that the long-term outcomes of the patients with CL-HCC in these two groups were not significantly different. For short-term outcomes, CH resulted in a lower rate of postoperative liver failure, while MH resulted in a lower incidence of biliary fistula. Nonetheless, compared with MH, CH provided CL-HCC patients with greater future remnant liver volume without an increased risk of early intra-hepatic recurrence. More multi-centre, randomized controlled trials comparing the therapeutic efficacy of CH and MH are urgently warranted.

Mortality and morbidity after hepatic resection in patients undergoing hemodialysis: analysis of a national inpatient database in Japan

BACKGROUND

Whether patients undergoing hemodialysis have greater risks of mortality and morbidity after hepatic resection remains unclear.

METHODS

We used the Diagnosis Procedure Combination database, a national inpatient database in Japan, to identify patients who underwent hepatic resection from July 2010 to March 2014. Propensity scorematching analysis was performed to compare morbidity and mortality between patients with and without hemodialysis.

RESULTS

Of 53,651 eligible patients, 498 (0.93%) underwent hemodialysis. Propensity score-matching analysis indicated greater in-hospital mortality in patients with than without hemodialysis (8.6% vs 2.0%; P < .001). Patients undergoing hemodialysis had more postoperative major complications than did patients not undergoing hemodialysis (18.1% vs 7.4%; P < .001). In the subgroup analyses for in-hospital mortality, the odds ratio of hemodialysis was 2.36 (95% confidence interval, 0.78-6.59; P = .067) in limited resection, 4.61 (95% confidence interval, 1.90-11.2; P < .001) in segmentectomy or sectoriectomy, and 5.58 (95% confidence interval, 3.40-14.9; P < .001) in bisectoriectomy or trisectoriectomy. In the age subgroup analyses, the odds ratio of hemodialysis was 4.38 (95% confidence interval, 2.66-7.21; P < .001) in patients aged <80 years and 7.20 (95% confidence interval, 1.55-36.7; P = .0011) in those aged ≥80 years.

CONCLUSION

Patients undergoing hemodialysis had a substantially increased risk of mortality and morbidity after hepatic resection. Surgical indications for major hepatectomy in patients undergoing hemodialysis who are ≥80 years of age may be limited and require careful scrutiny.

Risk prediction model for major complication after hepatectomy for malignant tumour - A validated scoring system from a university center

OBJECTIVE

To derive and validate a scoring system for major complication after hepatectomy.

BACKGROUND

Complications after hepatectomy significantly compromise survival outcomes, method to predict such risk is lacking. A reliable scoring system is therefore awaited.

METHODS

Consecutive adult patients receiving hepatectomy for primary or secondary liver malignancy from 1995 to 2014 were recruited. After randomization, patients were allocated to derivation and validation group respectively. A scoring system predicting occurrence of major complication was developed.

RESULTS

There were 2613 patients eligible for the study. The overall complication rate for the series was 10%. Impaired performance status (p = 0.014), presence of pre-existing medical illness (p = 0.008), elevated ALP (p = 0.005), urea (p < 0.001), and hypoalbuminemia (p = 0.008), and major hepatectomy (p < 0.001) were found to be independently associated major complications. A score was assigned to each of these factors according to their respective odd ratio. A total score of 0-17 was calculated for all patients. This score was shown to discriminate well with complication rate in both derivation and validation group (c-statistic: 0.71, p < 0.001 and 0.74, p < 0.001 respectively). The complication rate for low (score 0-5), moderate (score 6-10) and high (score 10 or above) risk group were respectively 5%, 16% and 28%. This risk stratification model was tested and confirmed in the validation group using Chi-square goodness-of-fit test (p = 0.864).

CONCLUSION

A validated risk stratification model provides an accurate and easy-to-use reference tool for patients and clinicians during the informed consent process.

Primary Malignancy is an Independent Determinant of Morbidity and Mortality after Liver Resection

Although outcomes after liver resection have improved, there remains considerable perioperative morbidity and mortality with these procedures. Studies suggest a primary liver cancer diagnosis is associated with poorer outcomes, but the extent to which this is attributable to a higher degree of hepatic dysfunction is unclear. To better delineate this, we performed a matched pair analysis of primary versus metastatic malignancies using a national database. The American College of Surgeons National Surgical Quality Improvement Program (2005–2013) was analyzed to select elective liver resections. Diagnoses were sorted as follows: 1) primary liver cancers and 2) metastatic neoplasms. A literature review identified factors known to impact hepatectomy outcomes; these variables were evaluated by a univariate analysis. The most predictive factors were used to create similar groups from each diagnosis category via propensity matching. Multivariate regression was used to validate results in the wider study population. Outcomes were compared using chi-squared test and Fisher exact test. Matched groups of 4838 patients were similar by all variables, including indicators of liver function. A number of major complications were significantly more prevalent with a primary diagnosis; overall major morbidity rates in the metastatic and primary groups were 29.3 versus 41.6 per cent, respectively. The mortality rate for primary neoplasms was 4.6 per cent (vs 1.6%); this represents a risk of death nearly three-times greater (95% confidence interval = 2.20–3.81, P < 0.0001) in cancers of hepatic origin. Hepatectomy carries substantially higher perioperative risk when performed for primary liver cancers, independent of hepatic function and resection extent. This knowledge will help to improve treatment planning, patient education, and resource allocation in oncologic liver resection.

Acute renal injury after partial hepatectomy

Currently, partial hepatectomy is the treatment of choice for a wide variety of liver and biliary conditions. Among the possible complications of partial hepatectomy, acute kidney injury (AKI) should be considered as an important cause of increased morbidity and postoperative mortality. Difficulties in the data analysis related to postoperative AKI after liver resections are mainly due to the multiplicity of factors to be considered in the surgical patients, moreover, there is no consensus of the exact definition of AKI after liver resection in the literature, which hampers comparison and analysis of the scarce data published on the subject. Despite this multiplicity of risk factors for postoperative AKI after partial hepatectomy, there are main factors that clearly contribute to its occurrence. First factor relates to large blood losses with renal hypoperfusion during the operation, second factor relates to the occurrence of post-hepatectomy liver failure with consequent distributive circulatory changes and hepatorenal syndrome. Eventually, patients can have more than one factor contributing to post-operative AKI, and frequently these combinations of acute insults can be aggravated by sepsis or exposure to nephrotoxic drugs.

The utility of the MELD score in predicting mortality following liver resection for metastasis

BACKGROUND

The MELD score has been demonstrated to be predictive of hepatectomy outcomes in mixed patient samples of primary and secondary liver cancers. Because MELD is a measure of hepatic dysfunction, prior conclusions may rely on the high prevalence of cirrhosis observed with primary lesions. This study aims to evaluate MELD score as a predictor of mortality and develop a risk prediction model for patients specifically undergoing hepatic metastasectomy.

METHODS

ACS-NSQIP 2005-2013 was analyzed to select patients who had undergone liver resections for metastases. A receiver operating characteristic (ROC) analysis determined the MELD score most associated with 30-day mortality. A literature review identified variables that impact hepatectomy outcomes. Significant factors were included in a multivariable analysis (MVA). A risk calculator was derived from the final multivariable model.

RESULTS

Among the 14,919 patients assessed, the mortality rate was 2.7%, and the median MELD was 7.3 (range = 34.4). A MELD of 7.24 was identified by ROC (sensitivity = 81%, specificity = 51%, c-statistic = 0.71). Of all patients above this threshold, 4.4% died at 30 days vs. 1.1% in the group ≤7.24. This faction represented 50.1% of the population but accounted for 80.3% of all deaths (p < 0.001). The MVA revealed mortality to be increased 2.6-times (OR = 2.55, 95%CI 1.69-3.84, p < 0.001). A risk calculator was successfully developed and validated.

CONCLUSIONS

MELD>7.24 is an important predictor of death following hepatectomy for metastasis and may prompt a detailed assessment with the provided risk calculator. Attention to MELD in the preoperative setting will improve treatment planning and patient education prior to oncologic liver resection.

Adjusted Age-Adjusted Charlson Comorbidity Index Score as a Risk Measure of Perioperative Mortality before Cancer Surgery

Background

Identification of patients at risk of death from cancer surgery should aid in preoperative preparation. The purpose of this study is to assess and adjust the age-adjusted Charlson comorbidity index (ACCI) to identify cancer patients with increased risk of perioperative mortality.

Methods

We identified 156,151 patients undergoing surgery for one of the ten common cancers between 2007 and 2011 in the Taiwan National Health Insurance Research Database. Half of the patients were randomly selected, and a multivariate logistic regression analysis was used to develop an adjusted-ACCI score for estimating the risk of 90-day mortality by variables from the original ACCI. The score was validated. The association between the score and perioperative mortality was analyzed.

Results

The adjusted-ACCI score yield a better discrimination on mortality after cancer surgery than the original ACCI score, with c-statics of 0.75 versus 0.71. Over 80 years of age, 70–80 years, and renal disease had the strongest impact on mortality, hazard ratios 8.40, 3.63, and 3.09 (P < 0.001), respectively. The overall 90-day mortality rates in the entire cohort varied from 0.9%, 2.9%, 7.0%, and 13.2% in four risk groups stratifying by the adjusted-ACCI score; the adjusted hazard ratio for score 4–7, 8–11, and ≥ 12 was 2.84, 6.07, and 11.17 (P < 0.001), respectively, in 90-day mortality compared to score 0–3.

Conclusions

The adjusted-ACCI score helps to identify patients with a higher risk of 90-day mortality after cancer surgery. It might be particularly helpful for preoperative evaluation of patients over 80 years of age.

Thirty-day mortality leads to underestimation of postoperative death after liver resection: A novel method to define the acute postoperative period

BACKGROUND

Postoperative mortality commonly is defined as death occurring within 30 days of surgery or during hospitalization. After resection for liver malignancies, this definition may result in underreporting, because mortality caused by postoperative complications can be delayed as the result of improved critical care. The aim of this study was to estimate statistically the acute postoperative period (APP) after partial hepatectomy and to compare mortality within this phase to standard timestamps.

METHODS

From a prospective database, 784 patients undergoing resection for primary and secondary hepatic malignancies between 2003 and 2013 were reviewed. For estimation of APP, a novel statistical method applying tests for a constant postoperative hazard was implemented. Multivariable mortality analysis was performed.

RESULTS

The APP was determined to last for 80 postoperative days (95% confidence interval 40-100 days). Within this period, 55 patients died (7.0%; 80-day mortality). In comparison, 30-day mortality (N = 32, 4.0%) and in-hospital death (N = 39, 5.0%) were relevantly less. No patient died between postoperative days 80 and 90. The causes of mortality within 30 days and from days 30-80 did not greatly differ, especially regarding posthepatectomy liver failure (44% vs 39%, P = .787). Septic complications, however, tended to cause late deaths more frequently (43% vs 25%, P = .255). Comorbidities (Charlson comorbidity index ≥ 3; P = .046), increased preoperative alanine aminotransferase activity (P = .030), and major liver resection (P = .035) were independent risk factors of 80-day mortality.

CONCLUSION

After liver resection for primary and secondary malignancies, 90-day rather than 30-day or in-hospital mortality should be used to avoid underreporting of deaths.

Preoperative hepatitis B virus DNA level is a risk factor for postoperative liver failure in patients who underwent partial hepatectomy for hepatitis B-related hepatocellular carcinoma

OBJECTIVE

Our objective was to explore the short-term effects of preoperative serum hepatitis B virus DNA level (HBV DNA) on postoperative hepatic function in patients who underwent partial hepatectomy for hepatitis B-related hepatocellular carcinoma (HCC).

METHODS

The clinical data of 1,602 patients with hepatitis B-related HCC who underwent partial hepatectomy in our department were retrospectively studied. The patients were divided into three groups according to their preoperative HBV DNA levels: group A <200 IU/mL, group B 200-20,000 IU/mL, and group C >20,000 IU/mL. The rates of postoperative complications, especially the rate of postoperative liver failure, were compared.

RESULTS

There were significant differences among the three groups in the rates of postoperative liver failure. On multivariate logistic regression analysis, a high preoperative HBV DNA level was an independent risk factor for postoperative liver failure.

CONCLUSIONS

Preoperative HBV DNA level was a significant risk factor for postoperative hepatic dysfunction.

Improving the quality of liver resection: a systematic review and critical analysis of the available prognostic models

BACKGROUND

Liver resection is considered to offer the only hope of cure for patients with liver malignancy. However, there are concerns about its safety, particularly in view of the increasing efficacy of less invasive strategies. No systematic review of prognostic research in liver resections has yet been performed.

METHODS

A systematic search identified articles published between 1999 and 2012 that performed a risk prediction analysis in patients undergoing liver resection. Studies were included if an outcome occurring within 90 days of surgery was identified, multivariable analysis performed and regression coefficients provided. The main endpoints were the outcomes and predictors chosen by the investigators, their definition, the performance and validity of the models, and the quality of the study as assessed using the QUIPS (quality in prognosis studies) tool.

RESULTS

A total of 91 studies were included. Eleven were prospective, but only two of these were registered. Twenty-eight endpoints were identified. These focused on postoperative morbidity or mortality, but many were redundant or ill defined and other relevant patient-reported outcomes were lacking. Predictors were not standardized, were poorly defined and overlapped. Only nine studies assessed the performance of their models and seven made an internal or temporal validation, but none reported an external validation or impact analysis. The median QUIPS score was 34 out of 50, indicating a high risk for bias.

CONCLUSION

Prognostic research in liver resection is still at the developmental stage.

Preoperative risk score predicting 90-day mortality after liver resection in a population-based study

The impact of important preexisting comorbidities, such as liver and renal disease, on the outcome of liver resection remains unclear. Identification of patients at risk of mortality will aid in improving preoperative preparations. The purpose of this study is to develop and validate a population-based score based on available preoperative and predictable parameters predicting 90-day mortality after liver resection using data from a hepatitis endemic country.We identified 13,159 patients who underwent liver resection between 2002 and 2006 in the Taiwan National Health Insurance Research Database. In a randomly selected half of the total patients, multivariate logistic regression analysis was used to develop a prediction score for estimating the risk of 90-day mortality by patient demographics, preoperative liver disease and comorbidities, indication for surgery, and procedure type. The score was validated with the remaining half of the patients.Overall 90-day mortality was 3.9%. Predictive characteristics included in the model were age, preexisting cirrhosis-related complications, ischemic heart disease, heart failure, cerebrovascular disease, renal disease, malignancy, and procedure type. Four risk groups were stratified by mortality scores of 1.1%, 2.2%, 7.7%, and 15%. Preexisting renal disease and cirrhosis-related complications were the strongest predictors. The score discriminated well in both the derivation and validation sets with c-statistics of 0.75 and 0.75, respectively.This population-based score could identify patients at risk of 90-day mortality before liver resection. Preexisting renal disease and cirrhosis-related complications had the strongest influence on mortality. This score enables preoperative risk stratification, decision-making, quality assessment, and counseling for individual patients.

Development and validation of a prediction score for complications after hepatectomy in hepatitis B-related hepatocellular carcinoma patients

Objective and Background

The aim of the present study was to develop and validate a prediction score for postoperative complications by severity and guide perioperative management and patient selection in hepatitis B-related hepatocellular carcinoma patients undergoing liver resection.

Methods

A total of 1543 consecutive liver resections cases were included in the study. Randomly selected sample set of 70% of the study cohort was used to develop a score to predict complications III–V and the remaining 30% was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression analysis was used to identify risk factors and create an integer score for the predicting of complication.

Results

American Society of Anesthesiologists category, portal hypertension, major liver resection (more than 3 segments) and extrahepatic procedures were identified as independent predictors for complications III–V by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups and significantly predicted the risk of complications III–V, with a rate of 1.6%, 11.9% and 65.6% for low, moderate and high risk, respectively. Using the score, the complications risk could be predicted accurately in the validation set, without significant differences between predicted (10.4%) and observed (8.4%) risks for complications III–V (P = 0.466).

Conclusions

Based on four preoperative risk factors, we have developed and validated an integer-based risk score to predict postoperative severe complications after liver resection for hepatitis B-related hepatocellular carcinoma patients in high-volume surgical center. This score may contribute to preoperative risk stratification and clinical decision-making.

Central hepatectomy for centrally located malignant liver tumors: A systematic review

AIM: To study whether central hepatectomy (CH) can achieve similar overall patient survival and disease-free survival rates as conventional major hepatectomies or not.

METHODS: A systematic literature search was performed in MEDLINE for articles published from January 1983 to June 2013 to evaluate the evidence for and against CH in the management of central hepatic malignancies and to compare the perioperative variables and outcomes of CH to lobar/extended hemihepatectomy.

RESULTS: A total of 895 patients were included from 21 relevant studies. Most of these patients who underwent CH were a sub-cohort of larger liver resection studies. Only 4 studies directly compared Central vs hemi-/extended hepatectomies. The range of operative time for CH was reported to be 115 to 627 min and Pringle’s maneuver was used for vascular control in the majority of studies. The mean intraoperative blood loss during CH ranged from 380 to 2450 mL. The reported morbidity rates ranged from 5.1% to 61.1%, the most common surgical complication was bile leakage and the most common cause of mortality was liver failure. Mortality ranged from 0.0% to 7.1% with an overall mortality of 2.3% following CH. The 1-year overall survival (OS) for patients underwent CH for hepatocellular carcinoma ranged from 67% to 94%; with the 3-year and 5-year OS having a reported range of 44% to 66.8%, and 31.7% to 66.8% respectively.

CONCLUSION: Based on current literature, CH is a promising option for anatomical parenchymal-preserving procedure in patients with centrally located liver malignancies; it appears to be safe and comparable in both perioperative, early and long term outcomes when compared to patients undergoing hemi-/extended hepatectomy. More prospective studies are awaited to further define its role.

A risk calculator for short-term morbidity and mortality after hip fracture surgery

OBJECTIVE

Hip fractures are a common source of morbidity and mortality among the elderly. Although multiple prior studies have identified risk factors for poor outcomes, few studies have presented a validated risk stratification calculator.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program database was used to identify 4331 patients undergoing surgery for hip fracture between 2005 and 2010. Patient demographics, comorbidities, laboratory values, and operative characteristics were compared in a univariate analysis, and a multivariate logistic regression analysis was then used to identify independent predictors of 30-day morbidity and mortality. Weighted values were assigned to each independent risk factor and used to create predictive models of 30-day morbidity, minor complication risk, major complication risk, and total complication risk. The models were internally validated with randomly partitioned 80%/20% cohort groups.

RESULTS

Thirty-day mortality was 5.9% and morbidity was 30.0%. Patient age, especially age greater than 80 years [mortality: odds ratio (OR): 2.41, 95% confidence interval (CI): 1.17-4.99); morbidity: OR: 1.43, 95% CI: 1.05-1.94], and male gender (mortality: OR: 2.28, 95% CI: 1.61-3.22; morbidity: OR: 1.26, 95% CI: 1.03-1.54) were associated with both increased mortality and morbidity. An increased American Society of Anesthesia class had the highest negative impact on total complication incidence in the scoring models. Additionally, complete functional dependence, active malignancy, patient race, cardiopulmonary disease, laboratory derangements, prolonged operating time, and open versus percutaneous surgery independently influenced outcomes. Risk scores, based on weighted models, which included the aforementioned variables, predicted mortality (P < 0.001, C index: 0.702) and morbidity (P < 0.001, C index: 0.670) after hip fracture surgery.

CONCLUSIONS

In this study, we have developed an internally validated method for risk stratifying patients undergoing hip fracture surgery, and this model is predictive of both 30-day morbidity and mortality. Our model could be useful for identifying high-risk individuals, for obtaining informed consent, and for risk-adjusted comparisons of outcomes between institutions.

LEVEL OF EVIDENCE

Prognostic level II. See instructions for authors for a complete description of levels of evidence.

Risk assessment in patients undergoing liver resection

BACKGROUND

Liver resection is still a risky procedure with high morbidity and mortality. It is significant to predict the morbidity and mortality with some models after liver resection.

DATA SOURCES

The MEDLINE/PubMed, Web of Science, Google Scholar, and Cochrane Library databases were searched using the terms "hepatectomy" and "risk assessment" for relevant studies before August 2012. Papers published in English were included.

RESULTS

Thirty-four original papers were included finally. Some models, such as MELD, APACHE II, E-PASS, or POSSUM, widely used in other populations, are useful to predict the morbidity and mortality after liver resection. Some special models for liver resection are used to predict outcomes after liver resection, such as mortality, liver dysfunction, transfusion, or acute renal failure. However, there is no good scoring system to predict or classify surgical complications because of shortage of internal or external validation.

CONCLUSION

It is important to validate the models for the major complications after liver resection with further internal or external databases.

Relationship between hospital volume and operative mortality for liver resection: Data from the Japanese Diagnosis Procedure Combination database

AIM

  The present study aimed to conduct a nationwide investigation on the relationship between hospital volume and outcomes following liver resection in Japan. We also discuss health policy implications of the results.

METHODS

  Using the Japanese Diagnosis Procedure Combination database, we identified 18 046 patients who underwent hepatic resection between July and December 2007-2009. Patients were subdivided into hospital-volume quartiles: very low- (<18/year), low- (18-35), high- (36-70) and very high-volume groups (>70). Multivariate logistic regression analysis for in-hospital mortality within 30 days of surgery was performed to analyze adjusted effects of various factors.

RESULTS

  Patients in the very high-volume group had a higher Charlson Comorbidity Index (P < 0.001) than those in the very low-volume group. Very low-volume hospitals were significantly less likely to perform extended lobectomy than very high-volume hospitals (5.4% vs 17.6%, P < 0.001). Crude in-hospital mortality within 30 days of surgery was 1.1% (0.6%, 0.8%, 1.9% and 3.0% for limited resection, segmentectomy, lobectomy and extended lobectomy, respectively). With reference to the very low-volume group, risk-adjusted odds ratios (95% confidence intervals) of low-, high- and very high-volume groups for overall mortality were 0.70 (0.48-1.02; P = 0.060), 0.52 (0.34-0.81; P = 0.004) and 0.16 (0.09-0.30; P < 0.001), respectively.

CONCLUSION

  There is a linear trend between higher hospital volume and lower in-hospital mortality of liver resection in Japan, particularly for lobectomy and extended lobectomy. Based on these results, regionalization of lobectomy and extended lobectomy in high-volume centers could be effective for reducing postoperative mortality.

Hepatocellular Carcinomas and Primary Liver Tumors as Predictive Factors for Postoperative Mortality after Liver Resection: A Meta-Analysis of More than 35,000 Hepatic Resections

Liver resection is considered the therapeutic gold standard for primary and metastatic liver neoplasms. The reduction of postoperative complications and mortality has resulted in a more aggressive approach to hepatic malignancies. For the most part, results of liver surgery have been published by highly experienced institutions, but the observations of highly specialized units results may not reflect the current status of hepatic surgery, underestimating mortality and complications. The objective of this study is to evaluate morbidity and mortality as a result of liver resection for primary and metastatic lesions, analyzing a large number of studies with a meta-analytic process taking into account the overdispersion of data. An extensive literature search has been conducted, and 148 papers published between January 2000 and April 2008, including a total of 36,629 patients from both high-volume and low volume institutions, were included in the meta-analysis. A beta binomial model was used to provide a robust estimate of the summary event rate by pooling overdispersion binomial data from different studies. Overall morbidity and mortality after liver surgery were 29.32 per cent and 3.15 per cent, respectively. Significantly higher postoperative mortality was observed after liver resection for hepatocellular carcinomas and primary hepatic tumors. The application of a beta binomial model to correct for overdispersion of liver surgery data showed significantly higher postoperative mortality rates in patients with hepatocellular carcinomas or primary hepatic tumors after liver resection.

External validation of a pre-operative nomogram predicting peri-operative mortality risk after liver resections for malignancy

AIM

A pre-operative nomogram using a population-based database to predict peri-operative mortality risk after liver resections for malignancy has recently been developed. The aim of the present study was to perform an external validation of the nomogram using data from a high volume institution.

METHODS

The National Inpatient Sample (NIS) database (2000-2004) was used initially to construct the nomogram. The dataset for external validation was obtained from a high volume centre specializing in hepatobiliary surgery. Validation was performed using calibration plots and concordance index.

RESULTS

A total of 794 patients who underwent liver resection from the years 2000-2010 at the external institute were included in the validation set with an observed mortality rate of 1.6%. The mean total points for this sample of patients was 124.9 [standard error (SE) 1.8, range 0-383] which translates to a nomogram predicted mortality rate of 1.5%, similar to the actual observed overall mortality rate. The nomogram concordance index was 0.65 [95% confidence interval (CI) 0.46-0.82] and calibration plots stratified by quartiles revealed good agreement between the predicted and observed mortality rates.

CONCLUSIONS

The present study provides an external validation of the pre-operative nomogram to predict the risk of peri-operative mortality after liver resection for malignancy.

Risk stratification for distal pancreatectomy utilizing ACS-NSQIP: preoperative factors predict morbidity and mortality

BACKGROUND

Evaluation of risk factors for adverse outcomes following distal pancreatectomy (DP) has been limited to data collected from retrospective, primarily single-institution studies. Using a large, multi-institutional prospectively collected dataset, we sought to define the incidence of complications after DP, identify the preoperative and operative risk factors for the development of complications, and develop a risk score that can be utilized preoperatively.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program participant use file was utilized to identify patients who underwent DP from 2005 to 2008 by Current Procedural Terminology codes. Multivariate logistic regression analysis was performed to identify variables associated with 30-day morbidity and mortality. A scoring system was developed to allow for preoperative risk stratification.

RESULTS

In 2,322 patients who underwent DP, overall 30-day complication and mortality were 28.1% and 1.2%, respectively. Serious complication occurred in 22.2%, and the most common complications included sepsis (8.7%), surgical site infection (5.9%), and pneumonia (4.7%). On multivariate analysis, preoperative variables associated with morbidity included male gender, high BMI, smoking, steroid use, neurologic disease, preoperative SIRS/sepsis, hypoalbuminemia, elevated creatinine, and abnormal platelet count. Preoperative variables associated with 30-day mortality included esophageal varices, neurologic disease, dependent functional status, recent weight loss, elevated alkaline phosphatase, and elevated blood urea nitrogen. Operative variables associated with both morbidity and mortality included high intraoperative transfusion requirement (≥3 U) and prolonged operation time (>360 min). Weighted risk scores were created based on the preoperatively determined factors that predicted both morbidity (p < 0.001) and mortality (p < 0.001) after DP.

DISCUSSION

The rate of serious complication after DP is 22%. The DP-specific preoperative risk scoring system described in this paper may be utilized for patient counseling and informed consent discussions, identifying high-risk patients who would benefit from disease optimization, and risk adjustment when comparing outcomes between institutions.

Colorectal liver metastases

BACKGROUND

Despite major advances in therapies for liver metastases, colorectal cancer remains one of the commonest causes of cancer-related deaths in the UK.

SOURCES OF DATA

The international literature on the management of colorectal liver metastases (CLM) was reviewed.

AREAS OF AGREEMENT

Due to a combination of highly active systemic agents and low perioperative mortality achieved by high-volume centres, a growing number of patients are being offered liver resection with curative intent. Patients with bilobar and/or extrahepatic disease who would previously have received palliative treatment only, are undergoing major surgery with good results. This review focuses on preoperative evaluation, surgical planning and the role of adjuvant therapies in the management of patients with CLM.

AREAS OF CONTROVERSY

Can ablative therapies match the outcomes of surgical resection? How can even more patients be rendered resectable?

GROWING POINTS

The use of other therapies, such as radiofrequency ablation and selective internal radiation therapy.

AREAS TIMELY FOR DEVELOPING RESEARCH

New chemotherapy regimens for neo-adjuvant therapy and the development of new modalities of liver tumour ablation.

Pre-operative nomogram to predict risk of peri-operative mortality following liver resections for malignancy

INTRODUCTION

The majority of liver resections for malignancy are performed in older patient with major co-morbidities. There is currently no pre-operative, patient-specific method to determine the likely peri-operative mortality for each individual patient. The aim of this study was to develop a pre-operative nomogram based on the presence of co-morbidities to predict risk of peri-operative mortality following liver resections for malignancy.

METHODS

The Nationwide Inpatient Sample database was queried to identify adult patients that underwent liver resection for malignancy. The pre-operative co-morbidities, identified as predictors were used and a nomogram was created with multivariate regression using Taylor expansion method in SAS software, surveylogistic procedure. Training set (years 2000-2004) was utilized to develop the model and validation set (year 2005) was utilized to validate this model.

RESULTS

A total of 3,947 and 972 patients were included in training and validation sets, respectively. The overall actual-observed peri-operative mortality rates for training and validation sets were 4.1% and 3.2%, respectively. The decile-based calibration plots for the training set revealed good agreement between the observed probabilities and nomogram-predicted probabilities. Similarly, the quartile-based calibration plot for the validation set revealed good agreement between the observed and predicted probabilities. The accuracy of the nomogram was further reinforced by a good concordance index of 0.80 with a 95% confidence interval of 0.72 and 0.87.

CONCLUSIONS

This pre-operative nomogram may be utilized to predict the risk of peri-operative mortality following liver resection for malignancy.

Predicting major complications after laparoscopic cholecystectomy: a simple risk score

INTRODUCTION

Reported morbidity varies widely for laparoscopic cholecystectomy (LC). A reliable method to determine complication risk may be useful to optimize care. We developed an integer-based risk score to determine the likelihood of major complications following LC.

METHODS

Using the Nationwide Inpatient Sample 1998-2006, patient discharges for LC were identified. Using previously validated methods, major complications were assessed. Preoperative covariates including patient demographics, disease characteristics, and hospital factors were used in logistic regression/bootstrap analyses to generate an integer score predicting postoperative complication rates. A randomly selected 80% was used to create the risk score, with validation in the remaining 20%.

RESULTS

Patient discharges (561,923) were identified with an overall complication rate of 6.5%. Predictive characteristics included: age, sex, Charlson comorbidity score, biliary tract inflammation, hospital teaching status, and admission type. Integer values were assigned and used to calculate an additive score. Three groups stratifying risk were assembled, with a fourfold gradient for complications ranging from 3.2% to 13.5%. The score discriminated well in both derivation and validation sets (c-statistic of 0.7).

CONCLUSION

An integer-based risk score can be used to predict complications following LC and may assist in preoperative risk stratification and patient counseling.