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      Maintenance immunosuppression for adults undergoing liver transplantation: a network meta-analysis

      1 , 1 , 2 , 3 , 2 , 3
      Cochrane Hepato-Biliary Group
      Cochrane Database of Systematic Reviews
      Wiley

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          Abstract

          As part of liver transplantation, immunosuppression (suppressing the host immunity) is given to prevent graft rejections resulting from the immune response of the body against transplanted organ or tissues from a different person whose tissue antigens are not compatible with those of the recipient. The optimal maintenance immunosuppressive regimen after liver transplantation remains uncertain. To assess the comparative benefits and harms of different maintenance immunosuppressive regimens in adults undergoing liver transplantation through a network meta‐analysis and to generate rankings of the different immunosuppressive regimens according to their safety and efficacy. We searched CENTRAL, MEDLINE, Embase, Science Citation Index Expanded, World Health Organization International Clinical Trials Registry Platform, and trials registers until October 2016 to identify randomised clinical trials on immunosuppression for liver transplantation. We included only randomised clinical trials (irrespective of language, blinding, or publication status) in adult participants undergoing liver transplantation (or liver retransplantation) for any reason. We excluded trials in which participants had undergone multivisceral transplantation or participants with established graft rejections. We considered any of the various maintenance immunosuppressive regimens compared with each other. We performed a network meta‐analysis with OpenBUGS using Bayesian methods and calculated the odds ratio, rate ratio, and hazard ratio (HR) with 95% credible intervals (CrI) based on an available‐case analysis, according to National Institute of Health and Care Excellence Decision Support Unit guidance. We included a total of 26 trials (3842 participants) in the review, and 23 trials (3693 participants) were included in one or more outcomes in the review. The vast majority of the participants underwent primary liver transplantation. All of the trials were at high risk of bias, and all of the evidence was of low or very low quality. In addition, because of sparse data involving trials at high risk of bias, it is not possible to entirely rely on the results of the network meta‐analysis. The trials included mainly participants undergoing primary liver transplantation of varied aetiologies. The follow‐up in the trials ranged from 3 to 144 months. The most common maintenance immunosuppression used as a control was tacrolimus. There was no evidence of difference in mortality (21 trials; 3492 participants) or graft loss (15 trials; 2961 participants) at maximal follow‐up between the different maintenance immunosuppressive regimens based on the network meta‐analysis. In the direct comparison, based on a single trial including 222 participants, tacrolimus plus sirolimus had increased mortality (HR 2.76, 95% CrI 1.30 to 6.69) and graft loss (HR 2.34, 95% CrI 1.28 to 4.61) at maximal follow‐up compared with tacrolimus. There was no evidence of differences in the proportion of people with serious adverse events (1 trial; 719 participants), proportion of people with any adverse events (2 trials; 940 participants), renal impairment (8 trials; 2233 participants), chronic kidney disease (1 trial; 100 participants), graft rejections (any) (16 trials; 2726 participants), and graft rejections requiring treatment (5 trials; 1025 participants) between the different immunosuppressive regimens. The network meta‐analysis showed that the number of adverse events was lower with cyclosporine A than with many other immunosuppressive regimens (12 trials; 1748 participants), and the risk of retransplantation (13 trials; 1994 participants) was higher with cyclosporine A than with tacrolimus (HR 3.08, 95% CrI 1.13 to 9.90). None of the trials reported number of serious adverse events, health‐related quality of life, or costs. Funding: 14 trials were funded by pharmaceutical companies who would benefit from the results of the trial; two trials were funded by parties who had no vested interest in the results of the trial; and 10 trials did not report the source of funding. Based on low‐quality evidence from a single small trial from direct comparison, tacrolimus plus sirolimus increases mortality and graft loss at maximal follow‐up compared with tacrolimus. Based on very low‐quality evidence from network meta‐analysis, we found no evidence of difference between different immunosuppressive regimens. We found very low‐quality evidence from network meta‐analysis and low‐quality evidence from direct comparison that cyclosporine A causes more retransplantation compared with tacrolimus. Future randomised clinical trials should be adequately powered; performed in people who are generally seen in the clinic rather than in highly selected participants; employ blinding; avoid postrandomisation dropouts or planned cross‐overs; and use clinically important outcomes such as mortality, graft loss, renal impairment, chronic kidney disease, and retransplantation. Such trials should use tacrolimus as one of the control groups. Moreover, such trials ought to be designed in such a way as to ensure low risk of bias and low risks of random errors. Background Liver transplantation is the main treatment option for people with severe advanced liver disease. When organs or tissues are transplanted from one person (organ donor) to another (organ recipient), the body of the organ recipient identifies the donor organ (or graft) as a foreign body and mounts a response against it in a way similar to the natural body defence mechanism against infections (immune response). This can lead to graft rejection and graft loss resulting in death of the organ recipient. Various medical interventions are used either alone or in combination (immunosuppressive regimen) to prevent graft rejections. The combination of interventions used in the first few months after liver transplantation (induction immunosuppressive regimen) often differs from the combination used for the rest of the patient's life (maintenance immunosuppression). It is unclear which immunosuppressive regimen after liver transplantation is the best. We sought to identify the best maintenance immunosuppressive regimen by searching for existing studies on the topic. We included all randomised clinical trials reported until October 2016. We included only trials of participants who had previously undergone liver transplantation. We excluded trials of participants who had undergone multi‐organ transplantation (e.g. liver and kidney transplantations) or participants with established graft rejections. Apart from using standard Cochrane methods, which allow comparison of only two interventions at a time (direct comparison), we also employed advanced methods that allow comparison of the many different interventions individually compared in the trials (network meta‐analysis). Study characteristics We identified 26 randomised clinical trials with a total of 3842 participants. Of these, 23 randomised clinical trials (3693 participants) provided information for one or more outcomes. The trials mainly included participants undergoing liver transplantation for the first time, for various reasons. Funding: 14 trials were funded by pharmaceutical companies who would benefit from the results of the trial; two trials were funded by parties who had no vested interest in the results of the trial; and 10 trials did not report the source of funding. Quality of evidence The overall quality of the evidence was low or very low, and all of the trials were at high risk of bias, which means it is possible that the conclusions made could overestimate the benefits or underestimate the harms of a given intervention because of the way the trials were conducted. In addition, because of insufficient information, the results of network meta‐analysis are not entirely reliable. Key results Several medical drugs were compared in the trials. We found no evidence of difference in the risk of death or graft loss between the different immunosuppressive regimens based on the network meta‐analysis. In the direct comparison, based on a single trial including 222 participants, the risk of death and graft loss was higher with tacrolimus plus sirolimus than with tacrolimus alone. There was no evidence of differences between the various immunosuppressive regimens in percentage of people who developed serious adverse events, percentage of people who developed any adverse events, risk of poor kidney function requiring dialysis or kidney transplantation (kidney dysfunction), prolonged kidney disease, graft rejections requiring treatment, and any graft rejections. The number of adverse events was lower with cyclosporine A than with many other immunosuppressive regimens. The risk of retransplantation was higher with cyclosporine A than with tacrolimus. None of the trials reported number of serious adverse events, health‐related quality of life, or costs. There is significant uncertainty as to the optimal maintenance immunosuppressive regimen after liver transplantation; further well‐designed randomised clinical trials are required. Future trials should be performed in people who are generally seen in the clinic rather than in highly selected participants and report clinically important outcomes such as death, graft loss, kidney dysfunction, long‐term kidney disease, and retransplantation. Such trials should use tacrolimus as one of the control groups. Moreover, such trials ought to be designed in such a way as to ensure low risk of bias and low risks of random errors.

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          Most cited references319

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          This article is the first of a series providing guidance for use of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system of rating quality of evidence and grading strength of recommendations in systematic reviews, health technology assessments (HTAs), and clinical practice guidelines addressing alternative management options. The GRADE process begins with asking an explicit question, including specification of all important outcomes. After the evidence is collected and summarized, GRADE provides explicit criteria for rating the quality of evidence that include study design, risk of bias, imprecision, inconsistency, indirectness, and magnitude of effect. Recommendations are characterized as strong or weak (alternative terms conditional or discretionary) according to the quality of the supporting evidence and the balance between desirable and undesirable consequences of the alternative management options. GRADE suggests summarizing evidence in succinct, transparent, and informative summary of findings tables that show the quality of evidence and the magnitude of relative and absolute effects for each important outcome and/or as evidence profiles that provide, in addition, detailed information about the reason for the quality of evidence rating. Subsequent articles in this series will address GRADE's approach to formulating questions, assessing quality of evidence, and developing recommendations. Copyright © 2011 Elsevier Inc. All rights reserved.
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            SPIRIT 2013 statement: defining standard protocol items for clinical trials.

            The protocol of a clinical trial serves as the foundation for study planning, conduct, reporting, and appraisal. However, trial protocols and existing protocol guidelines vary greatly in content and quality. This article describes the systematic development and scope of SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013, a guideline for the minimum content of a clinical trial protocol.The 33-item SPIRIT checklist applies to protocols for all clinical trials and focuses on content rather than format. The checklist recommends a full description of what is planned; it does not prescribe how to design or conduct a trial. By providing guidance for key content, the SPIRIT recommendations aim to facilitate the drafting of high-quality protocols. Adherence to SPIRIT would also enhance the transparency and completeness of trial protocols for the benefit of investigators, trial participants, patients, sponsors, funders, research ethics committees or institutional review boards, peer reviewers, journals, trial registries, policymakers, regulators, and other key stakeholders.
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              Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

              Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                146518
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                October 2017
                March 31 2017
                : 2017
                : 10
                Affiliations
                [1 ]Reina Sofía University Hospital, IMIBIC, CIBERehd; Hepatology and Liver Transplantation; Avenida Menéndez Pidal s/n Córdoba Spain 14004
                [2 ]Royal Free Hospital and the UCL Institute of Liver and Digestive Health; Sheila Sherlock Liver Centre; Pond Street London UK NW3 2QG
                [3 ]Royal Free Campus, UCL Medical School; Department of Surgery; Pond Street London UK NW3 2QG
                Article
                10.1002/14651858.CD011639.pub2
                6464256
                28362060
                48dd219f-09d9-419b-b58e-9a8db8ea28b0
                © 2017
                History

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