Cluster randomised trials in the medical literature: two bibliometric surveys

Background: Several reviews of published cluster randomised trials have reported that about half did not take clustering into account in the analysis, which was thus incorrect and potentially misleading. In this paper I ask whether cluster randomised trials are increasing in both number and quality of reporting. Methods: Computer search for papers on cluster randomised trials since 1980, hand search of trial reports published in selected volumes of the British Medical Journal over 20 years. Results: There has been a large increase in the numbers of methodological papers and of trial reports using the term 'cluster random' in recent years, with about equal numbers of each type of paper. The British Medical Journal contained more such reports than any other journal. In this journal there was a corresponding increase over time in the number of trials where subjects were randomised in clusters. In 2003 all reports showed awareness of the need to allow for clustering in the analysis. In 1993 and before clustering was ignored in most such trials. Conclusion: Cluster trials are becoming more frequent and reporting is of higher quality. Perhaps statistician pressure works

How to spot a statistical problem: advice for a non-statistical reviewer

Statistical analyses presented in general medical journals are becoming increasingly sophisticated. BMC Medicine relies on subject reviewers to indicate when a statistical review is required. We consider this policy and provide guidance on when to recommend a manuscript for statistical evaluation. Indicators for statistical review include insufficient detail in methods or results, some common statistical issues and interpretation not based on the presented evidence. Reviewers are required to ensure that the manuscript is methodologically sound and clearly written. Within that context, they are expected to provide constructive feedback and opinion on the statistical design, analysis, presentation and interpretation. If reviewers lack the appropriate background to positively confirm the appropriateness of any of the manuscript’s statistical aspects, they are encouraged to recommend it for expert statistical review

A systematic review of scabies transmission models and data to evaluate the cost-effectiveness of scabies interventions

© 2019 van der Linden et al. Background: Scabies is a common dermatological condition, affecting more than 130 million people at any time. To evaluate and/or predict the effectiveness and cost-effectiveness of scabies interventions, disease transmission modelling can be used. Objective: To review published scabies models and data to inform the design of a comprehensive scabies transmission modelling framework to evaluate the cost-effectiveness of scabies interventions. Methods: Systematic literature search in PubMed, Medline, Embase, CINAHL, and the Cochrane Library identified scabies studies published since the year 2000. Selected papers included modelling studies and studies on the life cycle of scabies mites, patient quality of life and resource use. Reference lists of reviews were used to identify any papers missed through the search strategy. Strengths and limitations of identified scabies models were evaluated and used to design a modelling framework. Potential model inputs were identified and discussed. Findings: Four scabies models were published: a Markov decision tree, two compartmental models, and an agent-based, network-dependent Monte Carlo model. None of the models specifically addressed crusted scabies, which is associated with high morbidity, mortality, and increased transmission. There is a lack of reliable, comprehensive information about scabies biology and the impact this disease has on patients and society. Discussion: Clinicians and health economists working in the field of scabies are encouraged to use the current review to inform disease transmission modelling and economic evaluations on interventions against scabies

Lizards Cooperatively Tunnel to Construct a Long-Term Home for Family Members

Constructing a home to protect offspring while they mature is common in many vertebrate groups, but has not previously been reported in lizards. Here we provide the first example of a lizard that constructs a long-term home for family members, and a rare case of lizards behaving cooperatively. The great desert skink, Liopholis kintorei from Central Australia, constructs an elaborate multi-tunnelled burrow that can be continuously occupied for up to 7 years. Multiple generations participate in construction and maintenance of burrows. Parental assignments based on DNA analysis show that immature individuals within the same burrow were mostly full siblings, even when several age cohorts were present. Parents were always captured at burrows containing their offspring, and females were only detected breeding with the same male both within- and across seasons. Consequently, the individual investments made to construct or maintain a burrow system benefit their own offspring, or siblings, over several breeding seasons

Sustainable institutionalized punishment requires elimination of second-order free-riders

Although empirical and theoretical studies affirm that punishment can elevate collaborative efforts, its emergence and stability remain elusive. By peer-punishment the sanctioning is something an individual elects to do depending on the strategies in its neighborhood. The consequences of unsustainable efforts are therefore local. By pool-punishment, on the other hand, where resources for sanctioning are committed in advance and at large, the notion of sustainability has greater significance. In a population with free-riders, punishers must be strong in numbers to keep the "punishment pool" from emptying. Failure to do so renders the concept of institutionalized sanctioning futile. We show that pool-punishment in structured populations is sustainable, but only if second-order free-riders are sanctioned as well, and to a such degree that they cannot prevail. A discontinuous phase transition leads to an outbreak of sustainability when punishers subvert second-order free-riders in the competition against defectors.Comment: 7 two-column pages, 3 figures; accepted for publication in Scientific Report

Comparisons against baseline within randomised groups are often used and can be highly misleading

<p>Abstract</p> <p>Background</p> <p>In randomised trials, rather than comparing randomised groups directly some researchers carry out a significance test comparing a baseline with a final measurement separately in each group.</p> <p>Methods</p> <p>We give several examples where this has been done. We use simulation to demonstrate that the procedure is invalid and also show this algebraically.</p> <p>Results</p> <p>This approach is biased and invalid, producing conclusions which are, potentially, highly misleading. The actual alpha level of this procedure can be as high as 0.50 for two groups and 0.75 for three.</p> <p>Conclusions</p> <p>Randomised groups should be compared directly by two-sample methods and separate tests against baseline are highly misleading.</p

Evolution of opinions on social networks in the presence of competing committed groups

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions $A$ and $B$, and constituting fractions $p_A$ and $p_B$ of the total population respectively, are present in the network. We show for stylized social networks (including Erd\H{o}s-R\'enyi random graphs and Barab\'asi-Albert scale-free networks) that the phase diagram of this system in parameter space $(p_A,p_B)$ consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.Comment: 23 pages: 15 pages + 7 figures (main text), 8 pages + 1 figure + 1 table (supplementary info

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

A risk profile for identifying community-dwelling elderly with a highrisk of recurrent falling: results of a 3-year prospective study

Introduction: The aim of the prospective study reported here was to develop a risk profile that can be used to identify community-dwelling elderly at a high risk of recurrent falling. Materials and methods: The study was designed as a 3-year prospective cohort study. A total of 1365 community-dwelling persons, aged 65 years and older, of the population-based Longitudinal Aging Study Amsterdam participated in the study. During an interview in 1995/1996, physical, cognitive, emotional and social aspects of functioning were assessed. A follow-up on the number of falls and fractures was conducted during a 3-year period using fall calendars that participants filled out weekly. Recurrent fallers were identified as those who fell at least twice within a 6-month period during the 3-year follow-up. Results: The incidence of recurrent falls at the 3-year follow-up point was 24.9% in women and 24.4% in men. Of the respondents, 5.5% reported a total of 87 fractures that resulted from a fall, including 20 hip fractures, 21 wrist fractures and seven humerus fractures. Recurrent fallers were more prone to have a fall-related fracture than those who were not defined as recurrent fallers (11.9% vs. 3.4%; OR: 3.8; 95% CI: 2.3-6.1). Backward logistic regression analysis identified the following predictors in the risk profile for recurrent falling: two or more previous falls, dizziness, functional limitations, weak grip strength, low body weight, fear of falling, the presence of dogs/cats in the household, a high educational level, drinking 18 or more alcoholic consumptions per week and two interaction terms (high educationx18 or more alcohol consumptions per week and two or more previous falls x fear of falling) (AUC=0.71). Discussion: At a cut-off point of 5 on the total risk score (range 0-30), the model predicted recurrent falling with a sensitivity of 59% and a specificity of 71%. At a cut-off point of 10, the sensitivity and specificity were 31% and 92%, respectively. A risk profile including nine predictors that can easily be assessed seems to be a useful tool for the identification of community-dwelling elderly with a high risk of recurrent falling. © International Osteoporosis Foundation and National Osteoporosis Foundation 2006