Methods to decrease blood loss during liver resection

  • Protocol
  • Intervention

Authors


Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the comparative benefits (decreased mortality and morbidity; improved quality of life) and harms (intervention-related adverse events) of interventions that aim to decrease blood loss during elective liver resection.

Background

Description of the condition

Liver resection refers to partial removal of the liver. On average, 1800 liver resections are carried out in the UK (HES 2011) and 11,000 in the USA (Asiyanbola 2008) every year. In the Western world, the main indication for liver resection is colorectal liver metastases. Colorectal cancer is the third most common cancer in the world. Approximately 1.2 million people develop colorectal cancer each year (IARC 2010), and 50% to 60% of these people will experience liver metastasis (CLM) (Garden 2006). Liver resection, the only curative option for people with colorectal liver metastasis, is indicated in 20% to 30% of patients in whom the metastasis is confined to the liver (Garden 2006). Five-year survival for patients with colorectal liver metastases who undergo liver resection is around 40% (Garden 2006).

The second most common reason for liver resection is hepatocellular carcinoma. Hepatocellular carcinoma is one of the most common cancers, with a worldwide annual incidence of 750,000 people (IARC 2010). Most hepatocellular carcinomas develop in cirrhotic livers (Llovet 2005). Liver resection and liver transplantation are the main curative treatments (Llovet 2005; Taefi 2013). Of people who present with hepatocellular carcinoma, about 5% are suitable for liver resection (Chen 2006). Survival after surgery depends on the stage of cancer and the severity of the underlying chronic liver disease. Patients with early-stage disease (cancers smaller than 5 cm) have a five-year survival of around 50%, whereas those with more advanced disease have a five-year survival of around 30% (Chen 2006). Screening programmes in theory should lead to a diagnosis at an earlier stage, when surgery is feasible and is associated with better outcomes.

Liver resection may also be performed for benign liver tumours (Belghiti 1993). The liver is subdivided into eight Couinaud segments (Couinaud 1999), which can be removed individually or by right hemi-hepatectomy (Couinaud segments 5 to 8), left hemi-hepatectomy (segments 2 to 4), right trisectionectomy (segments 4 to 8), or left trisectionectomy (segments 2 to 5 and 8 ± 1) (Strasberg 2000). Although every liver resection is considered major surgery, only resection of three or more segments is considered a major liver resection (Belghiti 1993).

Blood loss during liver resection is an important factor affecting complications and mortality in people undergoing liver resection (Shimada 1998; Yoshimura 2004; Ibrahim 2006). Variable estimates of blood loss, ranging from 200 mL to 2 litres, have been reported (Gurusamy 2009a). Excessive blood loss during surgery or in the immediate postoperative period may result in death of the patient. During liver resection, the liver parenchyma is transected at the plane of resection. The blood vessels and the bile duct branches in the plane of resection (raw surface) are then sealed by different methods to prevent blood or bile leakage.

Description of the intervention

Various interventions have been attempted to decrease blood loss during liver resection. These interventions include temporary occlusion of the blood vessels that supply the liver (Gurusamy 2009a); different methods of liver transection (the way that the liver parenchyma is divided), such as the clamp-crush method, the cavitron ultrasonic surgical aspirator, or the radiofrequency dissecting sealer (Gurusamy 2009b); different methods of management of raw surface of the liver (the way that the resection plane of the remnant liver is managed), such as use of fibrin sealant, argon beamer, or electrocautery and suture material (Frilling 2005); different cardiopulmonary interventions to decrease blood loss, such as low central venous pressure, hypoventilation, or haemodilution (Gurusamy 2009c); and different pharmacological interventions such as aprotinin, tranexamic acid, or recombinant factor VIIa to decrease blood loss (Gurusamy 2009d).

Interventions selected to decrease blood loss can be used alone or in various combinations. Usually surgeons at different centres follow their own protocol for decreasing blood loss. The finger-fracture and clamp-crush techniques do not involve specialist equipment (Gurusamy 2009b). The minimum and standard method of managing raw surface involves electrocautery and suture material. Currently, no cardiopulmonary or pharmacological intervention is considered as part of the standard procedure of liver resection. Altogether, the ultimate goal of these interventions is to decrease the morbidity and mortality related to blood loss.

How the interventions might work

Temporarily occluding the blood vessels that supply the liver may reduce the blood in cut vessels. Different methods of liver transection are used to remove the liver parenchyma, so that damage to the blood vessels is minimized. This might result in clear visualisation of the blood vessels, which can be clamped and then divided. Different methods of management of raw surface attempt to seal the blood vessels on the resection plane, preventing blood loss. Cardiopulmonary interventions decrease the quantity of red cells lost in different ways. Pharmacological interventions attempt to alter clotting mechanisms to prevent blood loss.

Why it is important to do this review

Liver resection is a major surgical procedure with significant mortality (estimated at 4%) and morbidity (estimated at 40%) (Reissfelder 2011). Interventions that decrease blood loss may improve outcomes of liver resection. Each category of interventions has been systematically reviewed previously (Gurusamy 2009a; Gurusamy 2009b). H owever, to our knowledge, no review has been conducted to assess and synthesise the comparative effectiveness of all available interventions and treatment strategies that aim to decrease blood loss and associated morbidity and mortality. This systematic review is intended as a useful guide for patients and healthcare providers as they seek to understand the role of different interventions in decreasing blood loss and blood transfusion requirements in people undergoing elective liver resection.

Objectives

To assess the comparative benefits (decreased mortality and morbidity; improved quality of life) and harms (intervention-related adverse events) of interventions that aim to decrease blood loss during elective liver resection.

Methods

Criteria for considering studies for this review

Types of studies

We will consider only randomised clinical trials for this overview. We will exclude studies of other design.

Types of participants

We will include randomised clinical trials in which participants underwent elective liver resection using vascular occlusion, irrespective of the method of vascular occlusion or the nature of the background liver (ie, normal or cirrhotic). We will exclude randomised clinical trials in which participants underwent liver resection combined with other major surgical procedures (eg, one-stage liver and bowel resection for synchronous metastases from colorectal tumours).

Types of interventions

We will include in this review randomised clinical trials that assessed one or more of the following interventions.

  1. Vascular occlusion.

  2. Methods of liver parenchymal transection.

  3. Methods of management of raw surface (resection plane) of liver.

The surgeon (and hence the trialists) may use a particular combination of each of the above. For example, one surgeon may perform liver resection using intermittent vascular occlusion, clamp-crush technique as the method of liver parenchymal transection, and a fibrin sealant on the raw surface; while another surgeon may perform liver resection without using any method of vascular occlusion, with the cavitron ultrasonic surgical aspirator as the method of liver parenchymal transection, and without any fibrin sealant on the raw surface. Each combination will be assessed as a treatment strategy, that is, a combination of several interventions. The purpose of this review is to identify the overall treatment effect of a treatment strategy rather than the contribution of each component intervention towards the overall effect.

Commonly used surgical techniques under each of the above categories are listed in Table 1, Table 2, and Table 3. In practice, any intervention in Table 1 can be used in combination with an intervention from Table 2 or Table 3. Any intervention in Table 2 can be used in combination with an intervention from Table 3.

Table 1. Different methods of vascular occlusion
No vascular occlusion
Portal triad clamping (continuous) (occlusion of inflow alone)
Portal triad clamping (intermittent) (occlusion of inflow alone)
Hepatic vascular exclusion (occlusion of inflow and outflow)
Selective vascular occlusion (occlusion of inflow to the hemi-liver that is being resected)
Selective hepatic artery occlusion (occlusion of hepatic artery supplying the hemi-liver that is being resected)
Selective portal vein occlusion (occlusion of portal vein supplying the hemi-liver that is being resected)
Selective hepatic vascular exclusion (occlusion of inflow to the hemi-liver and outflow from the hemi-liver that is being resected)
Table 2. Different methods of parenchymal transection
Finger-fracture method
Clamp-crush method
Cavitron ultrasonic surgical aspirator (CUSA)
Sharp dissection
Radiofrequency dissecting sealer
Ultrasonic shears
Table 3. Different methods of dealing with raw surface
Suturing for large and medium vessels and ducts and performing electrocauterisation of small vessels and ducts
Suturing for large vessels and performing ultrasonic shears for medium-sized and small vessels and ducts
Suturing and argon beam coagulator
Suturing and fibrin sealant

Types of outcome measures

We will assess the comparative effectiveness of available treatment strategies that aimed to decrease blood loss during liver resection for the following outcomes.

Primary outcomes

1. Mortality.
a) Short-term (30-day mortality or in-hospital mortality). We will use in-hospital mortality as defined in the included trials.
b) Long-term (at maximal follow-up).
2. Serious adverse events. An adverse event is defined as any untoward medical occurrence not necessarily having a causal relationship with the treatment but resulting in a dose reduction or discontinuation of treatment (ICH-GCP 1997). A serious adverse event is defined as any event that would increase mortality; is life-threatening; requires inpatient hospitalisation; or results in persistent or significant disability; or any important medical event that might have jeopardised the patient or requires intervention to prevent it. Serious adverse events correspond roughly to Grade III or above of the Clavien-Dindo classification- the only validated system for classifying postoperative complications (Dindo 2004; Clavien 2009) (Table 4). In cases where the authors did not classify the severity of adverse events, we will follow the criteria provided in Table 4 to classify the severity.
3. Quality of life as defined in the included trials.
a) Short-term (30 days, three months).
b) Long-term (maximal follow-up).

Table 4. Clavien-Dindo classification of post-operative complications
  1. Adapted from the following sources: Dindo 2004; Clavien 2009.

GradesDefinitionsExamples
IAny deviation from the normal post-operative course without the need for pharmacological treatment or surgical, endoscopic, and radiological interventionsDrugs such as antiemetics, antipyretics, analgesics, diuretics, and electrolytes; physiotherapy; wound infections opened at the bedside
IIRequiring pharmacological treatment with drugs other than those allowed for grade I complicationsBlood transfusions, total parenteral nutrition
IIIRequiring surgical, endoscopic or radiological interventionBile leak requiring endoscopic stent; reoperation for any cause; drainage of infected intra-abdominal collection
IVLife-threatening complication requiring high dependency or intensive care managementDialysis
VDeath of patient 
Suffix dIf the patient suffers from a complication at the time of discharge and needs further follow-up to fully evaluate the complication 
Secondary outcomes

4. Blood transfusion requirements.
a) Number of participants who require red cell or whole blood heterologous blood transfusion.
b) Quantity of blood transfusion (heterologous red cell or whole blood product, platelet, and fresh frozen plasma).
c) Total operative blood loss.
5. Hospital stay.
a) Length of total hospital stay (including readmissions).
b) Intensive therapy unit (ITU) stay.
6. Operating time.
7. Time needed to return to work.

Search methods for identification of studies

Electronic searches

We will search The Cochrane Hepato-Biliary Group Controlled Trials Register and the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, MEDLINE, EMBASE, and Science Citation Index Expanded (Royle 2003). We will also search the World Health Organization International Clinical Trials Registry Platform search portal, which searches various trial registers, including ISRCTN and ClinicalTrials.gov (http://apps.who.int/trialsearch/Default.aspx) to identify further trials. Because subsets of all available interventions on this topic have been reviewed comprehensively in existing Cochrane systematic reviews (Gurusamy 2009a; Gurusamy 2009b), we will also use these reviews as a way to identify trials. Preliminary search strategies with expected time spans of the searches are available in Appendix 1.

Searching other resources

We will search the references of the identified trials to identify additional trials for inclusion.

Data collection and analysis

Selection of studies

Two review authors (KSG and another review author) will independently identify the trials for inclusion. We will list the excluded studies with reasons for the exclusion. Any ongoing trials identified primarily through World Health Organization International Clinical Trials Registry Platform search portal will be listed for further follow-up. We will resolve discrepancies through discussion.

Data extraction and management

Both review authors will independently extract the following data.

  1. Year and language of publication.

  2. Country in which the participants were recruited.

  3. Year(s) in which the trial was conducted.

  4. Inclusion and exclusion criteria.

  5. Participant characteristics such as age, sex, underlying disease, comorbidity, number and proportion of participants with cirrhosis, and number and proportion of participants undergoing major versus minor liver resection.

  6. Details of the intervention and treatment strategy that aimed to decrease blood loss and blood transfusion requirements (eg, surgical technique, procedure and cointervention, concurrent surgery and medications).

  7. Outcomes (described previously).

  8. Follow-up time points.

  9. Risk of bias (described later).

We will seek unclear or missing information by contacting the authors of the individual trials. If there is any doubt whether trials share the same participants - completely or partially (by identifying common authors and centres) - we will contact the authors of the trials to clarify whether the trial report was duplicated. We will resolve any differences in opinion through discussion.

Assessment of risk of bias in included studies

We will follow the guidance given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011) and those described in the Cochrane Hepato-Biliary Group Module (Gluud 2013) to assess the risk of bias in included studies. Specifically, we will assess the risk of bias in included trials for the following domains (Schulz 1995; Moher 1998; Kjaergard 2001; Wood 2008; Lundh 2012; Savovic 2012; Savovic 2012a).

Allocation sequence generation 
  1. Low risk of bias: Sequence generation was achieved using computer random number generation or a random number table. Drawing lots, tossing a coin, shuffling cards, and throwing dice are adequate if performed by an independent adjudicator.

  2. Uncertain risk of bias: The trial is described as randomised, but the method of sequence generation is not specified.

  3. High risk of bias: The sequence generation method is not, or may not be, random. Quasi-randomised studies (those using dates, names, or admittance numbers to allocate participants) are inadequate and will be excluded for the assessment of benefits but not for assessing harms.

Allocation concealment
  1. Low risk of bias: Allocation was controlled by a central and independent randomisation unit, sequentially numbered, opaque and sealed envelopes, or something similar, so that intervention allocations could not have been foreseen in advance of, or during, enrolment.

  2. Uncertain risk of bias: The trial was described as randomised, but the method used to conceal the allocation was not described, so that intervention allocations may have been foreseen in advance of, or during, enrolment.

  3. High risk of bias: If the allocation sequence was known to the investigators who assigned participants, or the study was quasi-randomised. Quasi-randomised studies will be excluded for assessment of benefits but not for assessment of harms.

Blinding of participants and personnel
  1. Low risk of bias: Blinding was performed adequately, or the outcome measurement is not likely to be influenced by lack of blinding.

  2. Uncertain risk of bias: Information is insufficient to allow assessment of whether the type of blinding used is likely to induce bias on the estimate of effect.

  3. High risk of bias: No blinding or incomplete blinding and the outcome or the outcome measurement are likely to be influenced by lack of blinding.

Blinding of outcome assessors
  1. Low risk of bias: Blinding was performed adequately, or the outcome measurement is not likely to be influenced by lack of blinding.

  2. Uncertain risk of bias: Information is insufficient to allow assessment of whether the type of blinding used is likely to induce bias on the estimate of effect.

  3. High risk of bias: No blinding or incomplete blinding and the outcome or the outcome measurement are likely to be influenced by lack of blinding.

Incomplete outcome data
  1. Low risk of bias: The underlying reasons for missing data are unlikely to make treatment effects depart from plausible values, or proper methods have been employed to handle missing data.

  2. Uncertain risk of bias: Information is insufficient to allow assessment of whether the missing data mechanism in combination with the method used to handle missing data is likely to induce bias on the estimate of effect.

  3. High risk of bias: The crude estimate of effects (eg, complete case estimate) will clearly be biased because of the underlying reasons for missing data, and the methods used to handle missing data are unsatisfactory.

Selective outcome reporting
  1. Low risk of bias: Predefined or clinically relevant and reasonably expected outcomes are reported.

  2. Uncertain risk of bias: Not all predefined or clinically relevant and reasonably expected outcomes are reported, or they are not reported fully, or it is unclear whether data on these outcomes were recorded.

  3. High risk of bias: One or more clinically relevant and reasonably expected outcomes were not reported; data on these outcomes were likely to have been recorded.

Vested interest bias
  1. Low risk of bias: The trial is conducted by a party with no vested interests (ie, a party benefitting from the results of the trial) in the outcome of the trial.

  2. Uncertain risk of bias: It is not clear if the trial is conducted by a party with vested interest in the outcome of the trial.

  3. High risk of bias: The trial is conducted by a party with vested interests in the outcome of the trial (such as a drug manufacturer).

We will consider a trial at low risk of bias if the trial is assessed as at low risk of bias for all domains. We will consider a trial at low risk of bias for an outcome if the trial is assessed as at low risk of bias for all study level domains, as well as for outcome-specific domains (eg, blinding, incomplete outcome data). Otherwise, trials with uncertain risk of bias or with high risk of bias regarding one or more domains will be considered trials with high risk of bias.

Measures of treatment effect

For dichotomous variables (short-term mortality, serious adverse events, participants requiring blood transfusion), we will calculate the risk ratio (RR) with 95% confidence interval (CI). Risk ratio calculations do not include trials in which no events occurred in either group, whereas risk difference calculations do. We will report the risk difference if the results using this association measure were different from the risk ratio. For continuous variables, such as blood loss, hospital stay, operating time, and time needed to return to work, we will calculate the mean difference (MD) with 95% CI. We will use standardised mean difference (SMD) with 95% CI for quality of life if different scales were used (but we will not combine the quality of life at different time points) and for the quantity of blood transfused (some authors report this in litres transfused, while others report this as number of units transfused). For count data, such as overall number of serious adverse events, we will report the rate ratio (RaR) with 95% CI. For time-to-event data, such as long-term survival, we will use hazard ratio (HR) with 95% CI.

We will also present the 'Summary of findings' table using GRADEpro (http://ims.cochrane.org/revman/other-resources/gradepro).

Unit of analysis issues

The unit of analysis will be the patients according to the intervention group to which they are randomly assigned.

Dealing with missing data

We will perform an intention-to-treat analysis (Newell 1992) whenever possible. Otherwise, we will use data that are available to us (eg, a trial may report only per-protocol analysis results). As such 'per protocol' analyses may be biased, we will also conduct best-worst case scenario and worst-best case scenario analyses as sensitivity analyses.

For continuous outcomes, we will impute the standard deviation from P values according to guidance given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011). If the data are likely to be normally distributed, we will use the median for meta-analysis when the mean is not available. If it is not possible to calculate the standard deviation from the P value or the CIs, we will impute the standard deviation using the largest standard deviation in other trials for that outcome. This form of imputation may decrease the weight of the study for calculation of mean differences and may bias the effect estimate to no effect for calculation of standardised mean differences (Higgins 2011).

Assessment of heterogeneity

We will assess clinical and methodological heterogeneity by carefully examining the characteristics and design of included trials. Major sources of clinical heterogeneity include cirrhotic compared to non-cirrhotic livers and major compared to minor liver resections. In addition, we anticipate considerable heterogeneity in the way the intervention is performed. For example, intermittent portal triad clamping may be performed with different time periods of occlusion and non-occlusion. In addition, different doses of fibrin sealant may be used. Different study design and risk of bias may contribute to methodological heterogeneity.

We will quantify statistically heterogeneity using Q statistics and the related Chi2 test and P value (significance level at 0.10), as well as the I2 value (Higgins 2002). If substantial heterogeneity is identified - clinical, methodological, or statistical - we will explore and address heterogeneity in a subgroup analysis (see section on Subgroup analysis and investigation of heterogeneity).

Assessment of reporting biases

We will use visual asymmetry on a funnel plot to explore reporting bias in case at least ten trials are included for direct comparison (Egger 1997; Macaskill 2001). In the presence of heterogeneity that can be explained by subgroup analysis, we will perform the funnel plot for each subgroup in the presence of the adequate number of trials. We will perform the linear regression approach described by Egger 1997 to determine the funnel plot asymmetry. Selective reporting will be considered evidence of reporting bias.

Data synthesis

We will apply classifications described in Table 1, Table 2, and Table 3 to categorize different methods of vascular occlusion and parenchymal transection, as well as methods used to manage raw surface of the liver. Each category in the table is broadly defined to encompass a relatively homogeneous group of interventions, although we anticipate that variations will be noted in the way each method is carried out. For example, intermittent portal triad clamping may be performed with different time periods of occlusion and non-occlusion. Regardless of the time intervals, we will categorise them under intermittent portal triad clamping. Likewise, we will not distinguish different maximum periods for continuous vascular occlusion (Clavien 1996; Chouker 2004) and will not determine whether the suprahepatic inferior vena cava or the hepatic veins were occluded for outflow obstruction. These practice variations might be a source of heterogeneity; however, evidence is insufficient to suggest that these variations may affect the outcome.

In liver resection, a surgeon typically uses one item from Table 1, one item from Table 2, and one item from Table 3. Together, one can consider this combination of one method from each table as a treatment strategy, or in terms of network meta-analysis, each unique treatment strategy can be defined as a 'node'. Because of the large number of possible treatment strategies (8 methods of vascular occlusion × 6 methods of parenchymal transection × 4 methods of treatment of raw surface, that is, 192 potential treatment strategies or nodes), we will construct the network graph once the trials are identified. We do not expect that all 192 nodes are represented in the trials available in the literature. If the data are sparse, we will categorise the treatments into fewer categories by having only three methods of vascular occlusion (no vascular occlusion, continuous vascular occlusion, or intermittent vascular occlusion) and by having only two methods of treatment of raw surface (fibrin sealant used or no fibrin sealant used). This will reduce the categories to 36 treatment strategies or nodes (3 methods of vascular occlusion × 6 methods of parenchymal transection × 2 methods of treatment of raw surface).

We do not anticipate that every node will be represented. Some methods are more commonly practiced than others. From Table 1, no vascular occlusion, intermittent portal triad clamping, and continuous portal triad clamping are more often used than other techniques (Gurusamy 2009a). From Table 2, clamp-crush method and cavitron ultrasonic surgical aspirator are more commonly applied (Gurusamy 2009b). The clamp-crush method and the finger-fracture method do not require any special equipment, but the remaining methods do require special equipment. From Table 3, common methods of managing raw surface include suturing for large and medium vessels and ducts and performing electrocauterisation of small vessels and ducts (Gurusamy 2009b).

Direct comparison

We will perform pair-wise meta-analyses using Review Mananger 5 (RevMan 2011) in accordance with recommendations of The Cochrane Collaboration (Higgins 2011) and those described in the Cochrane Hepato-Biliary Group Module (Gluud 2013). We will use both random-effects models (DerSimonian 1986) and a fixed-effect model (DeMets 1987) for the meta-analyses. In case of discrepancy between the two models, we will report results of both; otherwise, we will report results of the random effects model. We will use the generic inverse method to combine the hazard ratios for time-to-event outcome data.

Network meta-analysis

We will conduct network meta-analyses to compare multiple interventions simultaneously for all primary outcomes and one secondary outcome on blood transfusion requirements. Network meta-analysis combines direct evidence within trials and indirect evidence across trials (Mills 2012).

We will fit the Bayesian random-effects network meta-analysis model using the Markov chain Monte Carlo method in WinBUGS 1.4. We will model the treatment contrast (eg, odds ratio for binary outcome, mean difference for continuous outcomes) for any two interventions ('functional parameters') as a function of comparisons between each individual intervention and an arbitrarily selected reference group ('basic parameters') (Lu 2004). We will convert odds ratio to risk ratio within the Bayesian framework (Dias 2011). We will assess whether direct evidence and indirect evidence are consistent qualitatively and quantitatively. If inconsistency is likely because of variations in participants and in design characteristics, we will also fit an inconsistency model that uses the design-by-treatment approach proposed by Whites and Higgins (Higgins 2012; White 2012). Under the inconsistency model, we will calculate the global test of inconsistency and will identify areas in the network where substantial inconsistency may be present. We will consider clinical and methodological diversities between trials and, when appropriate, will limit network meta-analysis to a more compatible subset of trials. We will interpret the information conservatively in the presence of inconsistency.

We will report estimates of treatment effects and associated 95% credible intervals in a table. We will also estimate the probability that each intervention ranks at one of the possible positions and will present the results in a graph.

We will first calculate all pair-wise meta-analysis estimates; we will then compare them with indirect comparison estimates (Bucher 1997).

Sample size calculations

To control for the risk of random errors, we will interpret the information with caution when the accrued sample size in the meta-analysis was less than the required sample size (required information size). The required information size for the outcome measure of perioperative mortality is 20,116 participants based on a perioperative mortality proportion of 3.5% in the control group (Finch 2007), a relative risk reduction of 20% in the experimental group, type I error of 5%, and type II error of 20%. Network analyses may be more prone to the risk of random errors than direct comparisons (Del Re 2013). Accordingly, a greater sample size is required in indirect comparisons than direct comparisons (Thorlund 2012). The power and precision in indirect comparisons depends upon various factors such as the number of participants included under each comparison and the heterogeneity between the trials (Thorlund 2012). If there was no heterogeneity across the trials, the sample size in indirect comparisons would be equivalent to the sample size in direct comparisons. The effective indirect sample size can be calculated using the number of participants included in each direct comparison (Thorlund 2012). For example, a sample size of 2500 participants in the direct comparison A versus C (nAC) and a sample size of 7500 participants in the direct comparison B versus C (nBC) results in an effective indirect sample size of 1,876 participants. However, in the presence of heterogeneity within the comparisons, the sample size required is higher. In the above scenario, for an I2 for each of the comparisons A versus C (IAC 2) and B versus C (IBC 2) of 25%, the effective indirect sample size is 1,407 participants. For an I2 for each of the comparisons A versus C and B versus C of 50%, the effective indirect sample size is 938 participants (Thorlund 2012). We will calculate the effective indirect sample size using the following generic formula (Thorlund 2012):

((nAC x (1 - IAC 2)) x (nBC x (1-IBC 2))/((nAC x (1 - IAC 2)) + (nBC x (1-IBC 2)).

Subgroup analysis and investigation of heterogeneity

We will perform the following subgroup analyses (for direct comparison and network meta-analysis) when at least one trial is included in each subgroup.

  1. Trials with low risk of bias compared to trials with high risk of bias.

  2. Cirrhotic compared to non-cirrhotic livers.

  3. Major liver resections compared to minor liver resections.

We will use the Chi2 test for subgroup differences to identify subgroup differences. A P value < 0.05 will be considered statistically significant for direct comparison. We will also use meta-regression to assess the impact of cirrhotic versus non-cirrhotic livers and major versus minor liver resections on effect estimates in the presence of at least 10 trials with this information.

Sensitivity analysis

Reporting of the severity of adverse events may be inadequate or incomplete. For example, minor bile leaks are considered mild adverse events, and major bile leaks are considered serious adverse events. In cases where the severity cannot be determined, we will exclude those events from the main analysis. We will perform a sensitivity analysis to include those events and will treat them as severe adverse events in the sensitivity analysis.

Acknowledgements

We thank the Cochrane Comparing of Multiple Interventions Methods Group and the Cochrane Hepato-Biliary Group for their support and advice.

Peer Reviewers: Christopher Schmid, USA; Kristian Thorlund, Canada.
Contact Editor: Christian Gluud, Denmark.

Appendices

Appendix 1. Search strategies

DatabaseTime spanSearch strategy
The Cochrane Hepato-Biliary Group Controlled Trials Register and Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (Wiley)Latest issue

1. Blood loss OR bleeding OR hemorrhage OR haemorrhage OR hemorrhages OR haemorrhages OR hemostasis OR haemostasis OR transfusion
2. MeSH descriptor Hemorrhage explode all trees
3. MeSH descriptor Blood Transfusion explode all trees
4. (#1 OR #2 OR #3)
5. Liver OR hepatic OR hepato*
6. MeSH descriptor Liver explode all trees
7. (5 OR 6)
8. Resection OR resections OR segmentectomy OR segmentectomies
9. (7 AND 8)
10. Hepatectomy OR hepatectomies

11. MeSH descriptor Hepatectomy explode all trees

12. (9 OR 10 OR 11)
13. (4 AND 12)

MEDLINE (PubMed)January 1947 to the date of search(Blood loss OR bleeding OR hemorrhage OR haemorrhage OR hemorrhages OR haemorrhages OR hemostasis OR haemostasis OR transfusion OR "Hemorrhage" [MeSH] OR "Blood Transfusion" [MeSH]) AND (((liver OR hepatic OR hepato* OR "liver" [MeSH]) AND (resection OR resections OR segmentectomy OR segmentectomies)) OR hepatectomy OR hepatectomies OR "hepatectomy" [MeSH]) AND ((randomized controlled trial [pt] OR controlled clinical trial [pt] OR randomized [tiab] OR placebo [tiab] OR drug therapy [sh] OR randomly [tiab] OR trial [tiab] OR groups [tiab]) NOT (animals [mh] NOT humans [mh]))
EMBASE (OvidSP)Janurary 1974 to the date of search

1. (Blood loss or bleeding or hemorrhage or haemorrhage or hemorrhages or haemorrhages or hemostasis or haemostasis or transfusion).af 
2. Exp bleeding/or exp blood transfusion/ 
3 .1 or 2
4. (Liver or hepatic or hepato*).af
5. (Resection or resections or segmentectomy or segmentectomies).af
6. 4 and 5
7. (Hepatectomy or hepatectomies).af
8. Exp Liver Resection/
9. 6 or 7 or 8
10. 3 and 9
11. Exp crossover-procedure/or exp double-blind procedure/or exp randomized controlled trial/or single-blind procedure/ 

12. (Random* OR factorial* OR crossover* OR cross over* OR cross-over* OR placebo* OR double* adj blind* OR single* adj blind* OR assign* OR allocat* OR volunteer*).af

13. 11 OR 12

14. 10 AND 13

Science Citation Index Expanded (http://portal.isiknowledge.com/portal.cgi?DestApp=WOS&Func=Frame)January 1945 to the date of search1. TS=(Blood loss OR bleeding OR hemorrhage OR haemorrhage OR hemorrhages OR haemorrhages OR hemostasis OR haemostasis OR transfusion)
2. TS=((liver OR hepatic OR hepato*) AND (resection OR resections OR segmentectomy OR segmentectomies) OR hepatectomy OR hepatectomies)
3. TS=(random* OR rct* OR crossover OR masked OR blind* OR placebo* OR meta-analysis OR systematic review* OR meta-analys*)
4. 1 AND 2 AND 3
World Health Organization International Clinical Trials Registry Platform Search Portal (http://apps.who.int/trialsearch/Default.aspx)Date of search will be given at review stageLiver resection OR hepatectomy

Contributions of authors

Kurinchi S Gurusamy drafted the protocol, which was carefully reviewed and revised by Tianjing Li. Tianjing Li also wrote the sections related to network meta-analysis. The protocol was developed after discussion with Lorne A Becker and Brian R Davidson. All review authors agreed on this version before publication.

Declarations of interest

Review authors perform research related to decreasing blood loss in liver resection. This includes clinical studies.

Sources of support

Internal sources

  • University College London, UK.

External sources

  • National Institute for Health Research, UK.

    National Institute for Health Research, the health research wing of the UK Government Department of Health funds K Gurusamy to complete this review.

Notes

Considerable overlap is evident in the background and methods sections of this review and those of several other reviews written by the same group of authors.

Ancillary