The lack of consensus on how to define and grade adverse postoperative events has greatly hampered the evaluation of surgical procedures. A new classification of complications, initiated in 1992, was updated 5 years ago. It is based on the type of therapy needed to correct the complication. The principle of the classification was to be simple, reproducible, flexible, and applicable irrespective of the cultural background. The aim of the current study was to critically evaluate this classification from the perspective of its use in the literature, by assessing interobserver variability in grading complex complication scenarios and to correlate the classification grades with patients', nurses', and doctors’ perception. Reports from the literature using the classification system were systematically analyzed. Next, 11 scenarios illustrating difficult cases were prepared to develop a consensus on how to rank the various complications. Third, 7 centers from different continents, having routinely used the classification, independently assessed the 11 scenarios. An agreement analysis was performed to test the accuracy and reliability of the classification. Finally, the perception of the severity was tested in patients, nurses, and physicians by presenting 30 scenarios, each illustrating a specific grade of complication. We noted a dramatic increase in the use of the classification in many fields of surgery. About half of the studies used the contracted form, whereas the rest used the full range of grading. Two-thirds of the publications avoided subjective terms such as minor or major complications. The study of 11 difficult cases among various centers revealed a high degree of agreement in identifying and ranking complications (89% agreement), and enabled a better definition of unclear situations. Each grade of complications significantly correlated with the perception by patients, nurses, and physicians (P < 0.05, Kruskal-Wallis test). This 5-year evaluation provides strong evidence that the classification is valid and applicable worldwide in many fields of surgery. No modification in the general principle of classification is warranted in view of the use in ongoing publications and trials. Subjective, inaccurate, or confusing terms such as “minor or major” should be removed from the surgical literature.

To develop and validate a comprehensive complication index (CCI) that integrates all events with their respective severity. Reporting of surgical complications is inconsistent and often incomplete. Most studies fail to provide information about the severity of complications, or inform only on the most severe event, ignoring events of lesser severity. We used an established classification of complications, adopting methods from operation risk index analysis in marketing research to develop a formula that considers all complications that may occur in a patient. The weights of each grade of complication, defined as median reference values, were obtained from 472 participants, who rated 30 different complications. Validation to assess sensitivity to treatment effects and validity of the CCI was performed by 4 different approaches, based on 1299 patients. The CCI is calculated as the sum of all complications that are weighted for their severity (multiplication of the median reference values from patients and physicians). The final formula yields a continuous scale to rank the severity of any combination of complications from 0 to 100 in a single patient. The CCI was highly sensitive in detecting treatment effect differences in the context of a randomized trial (effect size detected by CCI vs conventional standardized morbidity outcomes). It also showed a negative correlation with postoperative health status (r = -0.24, P = 0.002), and high correlation with the results of patient-rated single and multiple complications on conjoint analysis (r = 0.94, P < 0.001). The CCI summarizes all postoperative complications and is more sensitive than existing morbidity endpoints. It may serve as a standardized and widely applicable primary endpoint in surgical trials and other interventional fields of medicine. The CCI can be readily computed on the basis of tabulated complications according to the Clavien-Dindo classification (available at www.assessurgery.com).

To assess the impact of postoperative complications on full in-hospital costs per case. Rising expenses for complex medical procedures combined with constrained resources represent a major challenge. The severity of postoperative complications reflects surgical outcomes. The magnitude of the cost created by negative outcomes is unclear. Morbidity of 1200 consecutive patients undergoing major surgery from 2005 to 2008 in a tertiary, high-volume center was assessed by a validated, complication score system. Full in-hospital costs were collected for each patient. Statistical analysis was performed using a multivariate linear regression model adjusted for potential confounders. This study population included 393 complex liver/bile duct surgeries, 110 major pancreas operations, 389 colon resections, and 308 Roux-en-Y gastric bypasses. The overall 30-day mortality rate was 1.8%, whereas morbidity was 53.8%. Patients with an uneventful course had mean costs per case of US$ 27,946 (SD US$ 15,106). Costs increased dramatically with the severity of postoperative complications and reached the mean costs of US$ 159,345 (SD US$ 151,191) for grade IV complications. This increase in costs, up to 5 times the cost of a similar operation without complications, was observed for all types of investigated procedures, although the magnitude of the increase varied, with the highest costs in patients undergoing pancreas surgery. This study demonstrates the dramatic impact of postoperative complications on full in-hospital costs per case and that complications are the strongest indicator of costs. Furthermore, the study highlights a relevant savings capacity for major surgical procedures, and supports all efforts to lower negative events in the postoperative course.

Objectives: To design a new score on risk assessment for orthotopic liver transplantation (OLT) based on both donor and recipient parameters. Background: The balance of waiting list mortality and posttransplant outcome remains a difficult task in the era of the model for end-stage liver disease (MELD). Methods: Using the United Network for Organ Sharing database, a risk analysis was performed in adult recipients of OLT in the United States of America between 2002 and 2010 (n = 37,255). Living donor-, partial-, or combined-, and donation after cardiac death liver transplants were excluded. Next, a risk score was calculated (balance of risk score, BAR score) on the basis of logistic regression factors, and validated using our own OLT database (n = 233). Finally, the new score was compared with other prediction systems including donor risk index, survival outcome following liver transplantation, donor-age combined with MELD, and MELD score alone. Results: Six strongest predictors of posttransplant survival were identified: recipient MELD score, cold ischemia time, recipient age, donor age, previous OLT, and life support dependence prior to transplant. The new balance of risk score stratified recipients best in terms of patient survival in the United Network for Organ Sharing data, as in our European population. Conclusions: The BAR system provides a new, simple and reliable tool to detect unfavorable combinations of donor and recipient factors, and is readily available before decision making of accepting or not an organ for a specific recipient. This score may offer great potential for better justice and utility, as it revealed to be superior to recent developed other prediction scores.

To test whether the newly developed comprehensive complication index (CCI) is more sensitive than traditional endpoints for detecting between-group differences in randomized controlled trials (RCTs). A major challenge in RCTs is the choice of optimal endpoints to detect treatment effects. Mortality is no longer a sufficient marker in studies, and morbidity is often poorly defined. The CCI, integrating all complications including their severity in a linear scale ranging from 0 (no complication) to 100 (death), is a new tool, which may be more sensitive than other traditional endpoints to detect treatment effects on postoperative morbidity. The CCI was tested in 3 published RCTs from European centers evaluating pancreas, esophageal and colon resections. To compare the sensitivity of the CCI with traditional morbidity endpoints, for example, presence of any (yes/no) or only the most severe complications, all postoperative events were assessed, and the CCI calculated. Treatment effects and sample size calculations were compared using the CCI and traditional endpoints. Although RCTs failed to show between-group differences using any or most severe complications, the CCI revealed significant differences between treatment groups in 2 RCTs-after pancreas (P=0.009) and esophageal surgery (P=0.014). The CCI in the RCT on colon resections confirmed the absence of between-group differences (P=0.39). The required sample sizes in trials are up to 9 times lower for the CCI than for traditional morbidity endpoints. This study demonstrates superiority of the CCI to traditional endpoints. The CCI may serve as an appealing endpoint for future RCTs and may reduce the sample size.

Objective: Hepatocellular carcinoma (HCC) is a heterogeneous disease with poor prognosis and limited methods for predicting patient survival. The nature of the immune cells that infiltrate tumours is known to impact clinical outcome. However, the molecular events that regulate this infiltration require further understanding. Here the ability of immune genes expressed in the tumour microenvironment to predict disease progression was investigated. Methods: Using quantitative PCR, the expression of 14 immune genes in resected tumour tissues from 57 Singaporean patients was analysed. The nearest-template prediction method was used to derive and test a prognostic signature from this training cohort. The signature was then validated in an independent cohort of 98 patients from Hong Kong and Zurich. Intratumoural components expressing these critical immune genes were identified by in situ labelling. Regulation of these genes was analysed in vitro using the HCC cell line SNU-182. Results: The identified 14 immune-gene signature predicts patient survival in both the training cohort (p=0.0004 and HR=5.2) and the validation cohort (p=0.0051 and HR=2.5) irrespective of patient ethnicity and disease aetiology. Importantly, it predicts the survival of patients with early disease (stages I and II), for whom classical clinical parameters provide limited information. The lack of predictive power in late disease stages III and IV emphasises that a protective immune microenvironment has to be established early in order to impact disease progression significantly. This signature includes the chemokine genes CXCL10, CCL5 and CCL2, whose expression correlates with markers of T helper 1 (Th1), CD8⁺ T and natural killer (NK) cells. Inflammatory cytokines (tumour necrosis factor α, interferon γ) and Toll-like receptor 3 ligands stimulate intratumoural production of these chemokines which drive tumour infiltration by T and NK cells, leading to enhanced cancer cell death. Conclusion: A 14 immune-gene signature, which identifies molecular cues driving tumour infiltration by lymphocytes, accurately predicts survival of patients with HCC especially in early disease.