An investigation of the impact of using different methods for network meta-analysis: A protocol for an empirical evaluation

BACKGROUND: Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. METHODS: We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. DISCUSSION: The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies

Personalised randomised controlled trial designs—a new paradigm to define optimal treatments for carbapenem-resistant infections

Antimicrobial resistance is impacting treatment decisions for, and patient outcomes from, bacterial infections worldwide, with particular threats from infections with carbapenem-resistant Enterobacteriaceae, Acinetobacter baumanii, or Pseudomonas aeruginosa. Numerous areas of clinical uncertainty surround the treatment of these highly resistant infections, yet substantial obstacles exist to the design and conduct of treatment trials for carbapenem-resistant bacterial infections. These include the lack of a widely acceptable optimised standard of care and control regimens, varying antimicrobial susceptibilities and clinical contraindications making specific intervention regimens infeasible, and diagnostic and recruitment challenges. The current single comparator trials are not designed to answer the urgent public health question, identified as a high priority by WHO, of what are the best regimens out of the available options that will significantly reduce morbidity, costs, and mortality. This scenario has an analogy in network meta-analysis, which compares multiple treatments in an evidence synthesis to rank the best of a set of available treatments. To address these obstacles, we propose extending the network meta-analysis approach to individual randomisation of patients. We refer to this approach as a Personalised RAndomised Controlled Trial (PRACTical) design that compares multiple treatments in an evidence synthesis, to identify, overall, which is the best treatment out of a set of available treatments to recommend, or how these different treatments rank against each other. In this Personal View, we summarise the design principles of personalised randomised controlled trial designs. Specifically, of a network of different potential regimens for life-threatening carbapenem-resistant infections, each patient would be randomly assigned only to regimens considered clinically reasonable for that patient at that time, incorporating antimicrobial susceptibility, toxicity profile, pharmacometric properties, availability, and physician assessment. Analysis can use both direct and indirect comparisons across the network, analogous to network meta-analysis. This new trial design will maximise the relevance of the findings to each individual patient, and enable the top-ranked regimens from any personalised randomisation list to be identified, in terms of both efficacy and safety

Practical approaches to Bayesian sample size determination in non-inferiority trials with binary outcomes.

Bayesian analysis of a non-inferiority trial is advantageous in allowing direct probability statements to be made about the relative treatment difference rather than relying on an arbitrary and often poorly justified non-inferiority margin. When the primary analysis will be Bayesian, a Bayesian approach to sample size determination will often be appropriate for consistency with the analysis. We demonstrate three Bayesian approaches to choosing sample size for non-inferiority trials with binary outcomes and review their advantages and disadvantages. First, we present a predictive power approach for determining sample size using the probability that the trial will produce a convincing result in the final analysis. Next, we determine sample size by considering the expected posterior probability of non-inferiority in the trial. Finally, we demonstrate a precision-based approach. We apply these methods to a non-inferiority trial in antiretroviral therapy for treatment of HIV-infected children. A predictive power approach would be most accessible in practical settings, because it is analogous to the standard frequentist approach. Sample sizes are larger than with frequentist calculations unless an informative analysis prior is specified, because appropriate allowance is made for uncertainty in the assumed design parameters, ignored in frequentist calculations. An expected posterior probability approach will lead to a smaller sample size and is appropriate when the focus is on estimating posterior probability rather than on testing. A precision-based approach would be useful when sample size is restricted by limits on recruitment or costs, but it would be difficult to decide on sample size using this approach alone

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.BACKGROUND: The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. METHODS: We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. RESULTS: We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. CONCLUSIONS: Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based.CC is a recipient of a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (funding reference number—CGV 121171) and is a trainee on the Canadian Institutes of Health Research Drug Safety and Effectiveness Network team grant (funding reference number—116573). BH is funded by a New Investigator award from the Canadian Institutes of Health Research and the Drug Safety and Effectiveness Network. This research was partly supported by funding from CADTH as part of a project to develop Excel-based tools to support the conduct of health technology assessments. This research was also supported by Cornerstone Research Group

Supporting surveillance capacity for antimicrobial resistance: Laboratory capacity strengthening for drug resistant infections in low and middle income countries.

Development of antimicrobial resistance (AMR) threatens our ability to treat common and life threatening infections. Identifying the emergence of AMR requires strengthening of surveillance for AMR, particularly in low and middle-income countries (LMICs) where the burden of infection is highest and health systems are least able to respond. This work aimed, through a combination of desk-based investigation, discussion with colleagues worldwide, and visits to three contrasting countries (Ethiopia, Malawi and Vietnam), to map and compare existing models and surveillance systems for AMR, to examine what worked and what did not work. Current capacity for AMR surveillance varies in LMICs, but and systems in development are focussed on laboratory surveillance. This approach limits understanding of AMR and the extent to which laboratory results can inform local, national and international public health policy. An integrated model, combining clinical, laboratory and demographic surveillance in sentinel sites is more informative and costs for clinical and demographic surveillance are proportionally much lower. The speed and extent to which AMR surveillance can be strengthened depends on the functioning of the health system, and the resources available. Where there is existing laboratory capacity, it may be possible to develop 5-20 sentinel sites with a long term view of establishing comprehensive surveillance; but where health systems are weaker and laboratory infrastructure less developed, available expertise and resources may limit this to 1-2 sentinel sites. Prioritising core functions, such as automated blood cultures, reduces investment at each site. Expertise to support AMR surveillance in LMICs may come from a variety of international, or national, institutions. It is important that these organisations collaborate to support the health systems on which AMR surveillance is built, as well as improving technical capacity specifically relating to AMR surveillance. Strong collaborations, and leadership, drive successful AMR surveillance systems across countries and contexts

2-Arylamino-6-ethynylpurines are cysteine-targeting irreversible inhibitors of Nek2 kinase

Renewed interest in covalent inhibitors of enzymes implicated in disease states has afforded several agents targeted at protein kinases of relevance to cancers. We now report the design, synthesis and biological evaluation of 6-ethynylpurines that act as covalent inhibitors of Nek2 by capturing a cysteine residue (Cys22) close to the catalytic domain of this protein kinase. Examination of the crystal structure of the non-covalent inhibitor 3-((6-cyclohexylmethoxy-7H-purin-2-yl)amino)benzamide in complex with Nek2 indicated that replacing the alkoxy with an ethynyl group places the terminus of the alkyne close to Cys22 and in a position compatible with the stereoelectronic requirements of a Michael addition. A series of 6-ethynylpurines was prepared and a structure activity relationship (SAR) established for inhibition of Nek2. 6-Ethynyl-N-phenyl-7H-purin-2-amine [IC50 0.15 μM (Nek2)] and 4-((6-ethynyl-7H-purin-2-yl)amino)benzenesulfonamide (IC50 0.14 μM) were selected for determination of the mode of inhibition of Nek2, which was shown to be time-dependent, not reversed by addition of ATP and negated by site directed mutagenesis of Cys22 to alanine. Replacement of the ethynyl group by ethyl or cyano abrogated activity. Variation of substituents on the N-phenyl moiety for 6-ethynylpurines gave further SAR data for Nek2 inhibition. The data showed little correlation of activity with the nature of the substituent, indicating that after sufficient initial competitive binding to Nek2 subsequent covalent modification of Cys22 occurs in all cases. A typical activity profile was that for 2-(3-((6-ethynyl-9H-purin-2-yl)amino)phenyl)acetamide [IC50 0.06 μM (Nek2); GI50 (SKBR3) 2.2 μM] which exhibited >5–10-fold selectivity for Nek2 over other kinases; it also showed > 50% growth inhibition at 10 μM concentration against selected breast and leukaemia cell lines. X-ray crystallographic analysis confirmed that binding of the compound to the Nek2 ATP-binding site resulted in covalent modification of Cys22. Further studies confirmed that 2-(3-((6-ethynyl-9H-purin-2-yl)amino)phenyl)acetamide has the attributes of a drug-like compound with good aqueous solubility, no inhibition of hERG at 25 μM and a good stability profile in human liver microsomes. It is concluded that 6-ethynylpurines are promising agents for cancer treatment by virtue of their selective inhibition of Nek2

Structure-guided design of purine-based probes for selective Nek2 inhibition

Nek2 (NIMA-related kinase 2) is a cell cycle-dependent serine/threonine protein kinase that regulates centrosome separation at the onset of mitosis. Overexpression of Nek2 is common in human cancers and suppression can restrict tumor cell growth and promote apoptosis. Nek2 inhibition with small molecules, therefore, offers the prospect of a new therapy for cancer. To achieve this goal, a better understanding of the requirements for selective-inhibition of Nek2 is required. 6-Alkoxypurines were identified as ATP-competitive inhibitors of Nek2 and CDK2. Comparison with CDK2-inhibitor structures indicated that judicious modification of the 6-alkoxy and 2-arylamino substituents could achieve discrimination between Nek2 and CDK2. In this study, a library of 6-cyclohexylmethoxy-2-arylaminopurines bearing carboxamide, sulfonamide and urea substituents on the 2-arylamino ring was synthesized. Few of these compounds were selective for Nek2 over CDK2, with the best result being obtained for 3-((6-(cyclohexylmethoxy)-9H-purin-2-yl)amino)-N,N-dimethylbenzamide (CDK2 IC50 = 7.0 μM; Nek2 IC50 = 0.62 μM) with >10-fold selectivity. Deletion of the 6-substituent abrogated activity against both Nek2 and CDK2. Nine compounds containing an (E)-dialkylaminovinyl substituent at C-6, all showed selectivity for Nek2, e.g. (E)-6-(2-(azepan-1-yl)vinyl)-N-phenyl-9H-purin-2-amine (CDK2 IC50 = 2.70 μM; Nek2 IC50 = 0.27 μM). Structural biology of selected compounds enabled a partial rationalization of the observed structure activity relationships and mechanism of Nek2 activation. This showed that carboxamide 11 is the first reported inhibitor of Nek2 in the DFG-in conformation

RNAseq Analyses Identify Tumor Necrosis Factor-Mediated Inflammation as a Major Abnormality in ALS Spinal Cord

ALS is a rapidly progressive, devastating neurodegenerative illness of adults that produces disabling weakness and spasticity arising from death of lower and upper motor neurons. No meaningful therapies exist to slow ALS progression, and molecular insights into pathogenesis and progression are sorely needed. In that context, we used high-depth, next generation RNA sequencing (RNAseq, Illumina) to define gene network abnormalities in RNA samples depleted of rRNA and isolated from cervical spinal cord sections of 7 ALS and 8 CTL samples. We aligned \u3e50 million 2X150 bp paired-end sequences/sample to the hg19 human genome and applied three different algorithms (Cuffdiff2, DEseq2, EdgeR) for identification of differentially expressed genes (DEG’s). Ingenuity Pathways Analysis (IPA) and Weighted Gene Co-expression Network Analysis (WGCNA) identified inflammatory processes as significantly elevated in our ALS samples, with tumor necrosis factor (TNF) found to be a major pathway regulator (IPA) and TNFα-induced protein 2 (TNFAIP2) as a major network “hub” gene (WGCNA). Using the oPOSSUM algorithm, we analyzed transcription factors (TF) controlling expression of the nine DEG/hub genes in the ALS samples and identified TF’s involved in inflammation (NFkB, REL, NFkB1) and macrophage function (NR1H2::RXRA heterodimer). Transient expression in human iPSC-derived motor neurons of TNFAIP2 (also a DEG identified by all three algorithms) reduced cell viability and induced caspase 3/7 activation. Using high-density RNAseq, multiple algorithms for DEG identification, and an unsupervised gene co-expression network approach, we identified significant elevation of inflammatory processes in ALS spinal cord with TNF as a major regulatory molecule. Overexpression of the DEG TNFAIP2 in human motor neurons, the population most vulnerable to die in ALS, increased cell death and caspase 3/7 activation. We propose that therapies targeted to reduce inflammatory TNFα signaling may be helpful in ALS patients

Sequential inverse dysregulation of the RNA helicases DDX3X and DDX3Y facilitates MYC-driven lymphomagenesis

Summary DDX3X is a ubiquitously expressed RNA helicase involved in multiple stages of RNA biogenesis. DDX3X is frequently mutated in Burkitt lymphoma, but the functional basis for this is unknown. Here, we show that loss-of-function DDX3X mutations are also enriched in MYC-translocated diffuse large B cell lymphoma and reveal functional cooperation between mutant DDX3X and MYC. DDX3X promotes the translation of mRNA encoding components of the core translational machinery, thereby driving global protein synthesis. Loss-of-function DDX3X mutations moderate MYC-driven global protein synthesis, thereby buffering MYC-induced proteotoxic stress during early lymphomagenesis. Established lymphoma cells restore full protein synthetic capacity by aberrant expression of DDX3Y, a Y chromosome homolog, the expression of which is normally restricted to the testis. These findings show that DDX3X loss of function can buffer MYC-driven proteotoxic stress and highlight the capacity of male B cell lymphomas to then compensate for this loss by ectopic DDX3Y expression