Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review

Background: Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. Methods: We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. Results: For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Conclusions: Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses

Safety and Clinical Outcome of Thrombolysis in Ischaemic Stroke Using a Perfusion CT Mismatch between 3 and 6 Hours

It may be possible to thrombolyse ischaemic stroke (IS) patients up to 6 h by using penumbral imaging. We investigated whether a perfusion CT (CTP) mismatch can help to select patients for thrombolysis up to 6 h.A cohort of 254 thrombolysed IS patients was studied. 174 (69%) were thrombolysed at 0-3 h by using non-contrast CT (NCCT), and 80 (31%) at 3-6 h (35 at 3-4.5 h and 45 at 4.5-6 h) by using CTP mismatch criteria. Symptomatic intracerebral haemorrhage (SICH), the mortality and the modified Rankin Score (mRS) were assessed at 3 months. Independent determinants of outcome in patients thrombolysed between 3 and 6 h were identified.The baseline characteristics were comparable in the two groups. There were no differences in SICH (3% v 4%, p = 0.71), any ICH (7% v 9%, p = 0.61), or mortality (16% v 9%, p = 0.15) or mRS 0-2 at 3 months (55% v 54%, p = 0.96) between patients thrombolysed at 0-3 h (NCCT only) or at 3-6 h (CTP mismatch). There were no significant differences in outcome between patients thrombolysed at 3-4.5 h or 4.5-6 h. The NIHSS score was the only independent determinant of a mRS of 0-2 at 3 months (OR 0.89, 95% CI 0.82-0.97, p = 0.007) in patients treated using CTP mismatch criteria beyond 3 h.The use of a CTP mismatch model may help to guide thrombolysis decisions up to 6 h after IS onset

Prediction of potential drug targets based on simple sequence properties

<p>Abstract</p> <p>Background</p> <p>During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets.</p> <p>Results</p> <p>Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research.</p> <p>Conclusion</p> <p>We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.</p

Clinical use of Whole Genome Sequencing for Mycobacterium tuberculosis

Drug resistant tuberculosis (TB) remains a major challenge to global health and to healthcare in the UK. In 2014, England recorded 6520 cases of TB of which 1.4% were multi-drug resistant (MDR-TB). Extensively drug resistant TB (XDR-TB) occurs at a much lower rate, but the impact on the patient and hospital is severe. Current diagnostic methods such as drug susceptibility testing and targeted molecular tests are slow to return or examine only a limited number of target regions respectively. Faster, more comprehensive diagnostics will enable earlier use of the most appropriate drug regimen thus improving patient outcome and reducing overall healthcare costs. Whole genome sequencing has been shown to provide a rapid and comprehensive view of the genotype of the organism and thus enable reliable prediction of the drug susceptibility phenotype within a clinically relevant time frame. In addition it provides the highest resolution when investigating transmission events in possible outbreak scenarios. However, robust software and database tools need to be developed for the full potential to be realized in this specialized area of medicine

Quantitative Analysis of the Effect of Cancer Invasiveness and Collagen Concentration on 3D Matrix Remodeling

Extracellular matrix (ECM) remodeling is a key component of cell migration and tumor metastasis, and has been associated with cancer progression. Despite the importance of matrix remodeling, systematic and quantitative studies on the process have largely been lacking. Furthermore, it remains unclear if the disrupted tensional homeostasis characteristic of malignancy is due to initially altered ECM and tissue properties, or to the alteration of the tissue by tumor cells. To explore these questions, we studied matrix remodeling by two different prostate cancer cell lines in a three-dimensional collagen system. Over one week, we monitored structural changes in gels of varying collagen content using confocal reflection microscopy and quantitative image analysis, tracking metrics of fibril fraction, pore size, and fiber length and diameter. Gels that were seeded with no cells (control), LNCaP cells, and DU-145 cells were quantitatively compared. Gels with higher collagen content initially had smaller pore sizes and higher fibril fractions, as expected. However, over time, LNCaP- and DU-145-populated matrices showed different structural properties compared both to each other and to the control gels, with LNCaP cells appearing to favor microenvironments with lower collagen fiber fractions and larger pores than DU-145 cells. We posit that the DU-145 cells' preference for denser matrices is due to their higher invasiveness and proteolytic capabilities. Inhibition of matrix proteases resulted in reduced fibril fractions for high concentration gels seeded with either cell type, supporting our hypothesis. Our novel quantitative results probe the dynamics of gel remodeling in three dimensions and suggest that prostate cancer cells remodel their ECM in a synergistic manner that is dependent on both initial matrix properties as well as their invasiveness

Estimating the Worldwide Extent of Illegal Fishing

Illegal and unreported fishing contributes to overexploitation of fish stocks and is a hindrance to the recovery of fish populations and ecosystems. This study is the first to undertake a world-wide analysis of illegal and unreported fishing. Reviewing the situation in 54 countries and on the high seas, we estimate that lower and upper estimates of the total value of current illegal and unreported fishing losses worldwide are between $10 bn and$23.5 bn annually, representing between 11 and 26 million tonnes. Our data are of sufficient resolution to detect regional differences in the level and trend of illegal fishing over the last 20 years, and we can report a significant correlation between governance and the level of illegal fishing. Developing countries are most at risk from illegal fishing, with total estimated catches in West Africa being 40% higher than reported catches. Such levels of exploitation severely hamper the sustainable management of marine ecosystems. Although there have been some successes in reducing the level of illegal fishing in some areas, these developments are relatively recent and follow growing international focus on the problem. This paper provides the baseline against which successful action to curb illegal fishing can be judged

The Persisting Burden of Intracerebral Haemorrhage: Can Effective Treatments Be Found?

Colin Josephson, Rustam Al-Shahi Salman, and colleagues discuss the effectiveness of treatments for intracerebral haemorrhage

Prior mucosal exposure to heterologous cells alters the pathogenesis of cell-associated mucosal feline immunodeficiency virus challenge

<p>Abstract</p> <p>Background</p> <p>Several lines of research suggest that exposure to cellular material can alter the susceptibility to infection by HIV-1. Because sexual contact often includes exposure to cellular material, we hypothesized that repeated mucosal exposure to heterologous cells would induce an immune response that would alter the susceptibility to mucosal infection. Using the feline immunodeficiency virus (FIV) model of HIV-1 mucosal transmission, the cervicovaginal mucosa was exposed once weekly for 12 weeks to 5,000 heterologous cells or media (control) and then cats were vaginally challenged with cell-associated or cell-free FIV.</p> <p>Results</p> <p>Exposure to heterologous cells decreased the percentage of lymphocytes in the mucosal and systemic lymph nodes (LN) expressing L-selectin as well as the percentage of CD4+ CD25+ T cells. These shifts were associated with enhanced ex-vivo proliferative responses to heterologous cells. Following mucosal challenge with cell-associated, but not cell-free, FIV, proviral burden was reduced by 64% in cats previously exposed to heterologous cells as compared to media exposed controls.</p> <p>Conclusions</p> <p>The pathogenesis and/or the threshold for mucosal infection by infected cells (but not cell-free virus) can be modulated by mucosal exposure to uninfected heterologous cells.</p

Multiple network properties overcome random connectivity to enable stereotypic sensory responses

Connections between neuronal populations may be genetically hardwired or random. In the insect olfactory system, projection neurons of the antennal lobe connect randomly to Kenyon cells of the mushroom body. Consequently, while the odor responses of the projection neurons are stereotyped across individuals, the responses of the Kenyon cells are variable. Surprisingly, downstream of Kenyon cells, mushroom body output neurons show stereotypy in their responses. We found that the stereotypy is enabled by the convergence of inputs from many Kenyon cells onto an output neuron, and does not require learning. The stereotypy emerges in the total response of the Kenyon cell population using multiple odor-specific features of the projection neuron responses, benefits from the nonlinearity in the transfer function, depends on the convergence:randomness ratio, and is constrained by sparseness. Together, our results reveal the fundamental mechanisms and constraints with which convergence enables stereotypy in sensory responses despite random connectivity