233 research outputs found

    Assessment and Implication of Prognostic Imbalance in Randomized Controlled Trials with a Binary Outcome – A Simulation Study

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    Chance imbalance in baseline prognosis of a randomized controlled trial can lead to over or underestimation of treatment effects, particularly in trials with small sample sizes. Our study aimed to (1) evaluate the probability of imbalance in a binary prognostic factor (PF) between two treatment arms, (2) investigate the impact of prognostic imbalance on the estimation of a treatment effect, and (3) examine the effect of sample size (n) in relation to the first two objectives.We simulated data from parallel-group trials evaluating a binary outcome by varying the risk of the outcome, effect of the treatment, power and prevalence of the PF, and n. Logistic regression models with and without adjustment for the PF were compared in terms of bias, standard error, coverage of confidence interval and statistical power.For a PF with a prevalence of 0.5, the probability of a difference in the frequency of the PFβ‰₯5% reaches 0.42 with 125/arm. Ignoring a strong PF (relative riskβ€Š=β€Š5) leads to underestimating the strength of a moderate treatment effect, and the underestimate is independent of n when n is >50/arm. Adjusting for such PF increases statistical power. If the PF is weak (RRβ€Š=β€Š2), adjustment makes little difference in statistical inference. Conditional on a 5% imbalance of a powerful PF, adjustment reduces the likelihood of large bias. If an absolute measure of imbalance β‰₯5% is deemed important, including 1000 patients/arm provides sufficient protection against such an imbalance. Two thousand patients/arm may provide an adequate control against large random deviations in treatment effect estimation in the presence of a powerful PF.The probability of prognostic imbalance in small trials can be substantial. Covariate adjustment improves estimation accuracy and statistical power, and hence should be performed when strong PFs are observed

    Reporting on covariate adjustment in randomised controlled trials before and after revision of the 2001 CONSORT statement: a literature review

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    <p>Abstract</p> <p>Objectives</p> <p>To evaluate the use and reporting of adjusted analysis in randomised controlled trials (RCTs) and compare the quality of reporting before and after the revision of the CONSORT Statement in 2001.</p> <p>Design</p> <p>Comparison of two cross sectional samples of published articles.</p> <p>Data Sources</p> <p>Journal articles indexed on PubMed in December 2000 and December 2006.</p> <p>Study Selection</p> <p>Parallel group RCTs with a full publication carried out in humans and published in English</p> <p>Main outcome measures</p> <p>Proportion of articles reported adjusted analysis; use of adjusted analysis; the reason for adjustment; the method of adjustment and the reporting of adjusted analysis results in the main text and abstract.</p> <p>Results</p> <p>In both cohorts, 25% of studies reported adjusted analysis (84/355 in 2000 vs 113/422 in 2006). Compared with articles reporting only unadjusted analyses, articles that reported adjusted analyses were more likely to specify primary outcomes, involve multiple centers, perform stratified randomization, be published in general medical journals, and recruit larger sample sizes. In both years a minority of articles explained why and how covariates were selected for adjustment (20% to 30%). Almost all articles specified the statistical methods used for adjustment (99% in 2000 vs 100% in 2006) but only 5% and 10%, respectively, reported both adjusted and unadjusted results as recommended in the CONSORT guidelines.</p> <p>Conclusion</p> <p>There was no evidence of change in the reporting of adjusted analysis results five years after the revision of the CONSORT Statement and only a few articles adhered fully to the CONSORT recommendations.</p

    A comparison of methods to adjust for continuous covariates in the analysis of randomised trials

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    BACKGROUND: Although covariate adjustment in the analysis of randomised trials can be beneficial, adjustment for continuous covariates is complicated by the fact that the association between covariate and outcome must be specified. Misspecification of this association can lead to reduced power, and potentially incorrect conclusions regarding treatment efficacy. METHODS: We compared several methods of adjustment to determine which is best when the association between covariate and outcome is unknown. We assessed (a) dichotomisation or categorisation; (b) assuming a linear association with outcome; (c) using fractional polynomials with one (FP1) or two (FP2) polynomial terms; and (d) using restricted cubic splines with 3 or 5 knots. We evaluated each method using simulation and through a re-analysis of trial datasets. RESULTS: Methods which kept covariates as continuous typically had higher power than methods which used categorisation. Dichotomisation, categorisation, and assuming a linear association all led to large reductions in power when the true association was non-linear. FP2 models and restricted cubic splines with 3 or 5 knots performed best overall. CONCLUSIONS: For the analysis of randomised trials we recommend (1) adjusting for continuous covariates even if their association with outcome is unknown; (2) keeping covariates as continuous; and (3) using fractional polynomials with two polynomial terms or restricted cubic splines with 3 to 5 knots when a linear association is in doubt

    The Na(+)–H(+ )exchanger-1 induces cytoskeletal changes involving reciprocal RhoA and Rac1 signaling, resulting in motility and invasion in MDA-MB-435 cells

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    INTRODUCTION: An increasing body of evidence shows that the tumour microenvironment is essential in driving neoplastic progression. The low serum component of this microenvironment stimulates motility/invasion in human breast cancer cells via activation of the Na(+)–H(+ )exchanger (NHE) isoform 1, but the signal transduction systems that underlie this process are still poorly understood. We undertook the present study to elucidate the role and pattern of regulation by the Rho GTPases of this serum deprivation-dependent activation of both NHE1 and subsequent invasive characteristics, such as pseudopodia and invadiopodia protrusion, directed cell motility and penetration of normal tissues. METHODS: The present study was performed in a well characterized human mammary epithelial cell line representing late stage metastatic progression, MDA-MB-435. The activity of RhoA and Rac1 was modified using their dominant negative and constitutively active mutants and the activity of NHE1, cell motility/invasion, F-actin content and cell shape were measured. RESULTS: We show for the first time that serum deprivation induces NHE1-dependent morphological and cytoskeletal changes in metastatic cells via a reciprocal interaction of RhoA and Rac1, resulting in increased chemotaxis and invasion. Deprivation changed cell shape by reducing the amount of F-actin and inducing the formation of leading edge pseudopodia. Serum deprivation inhibited RhoA activity and stimulated Rac1 activity. Rac1 and RhoA were antagonistic regulators of both basal and stimulated tumour cell NHE1 activity. The regulation of NHE1 activity by RhoA and Rac1 in both conditions was mediated by an alteration in intracellular proton affinity of the exchanger. Interestingly, the role of each of these G-proteins was reversed during serum deprivation; basal NHE1 activity was regulated positively by RhoA and negatively by Rac1, whereas RhoA negatively and Rac1 positively directed the stimulation of NHE1 during serum deprivation. Importantly, the same pattern of RhoA and Rac1 regulation found for NHE1 activity was observed in both basal and serum deprivation dependent increases in motility, invasion and actin cytoskeletal organization. CONCLUSION: Our findings suggest that the reported antagonistic roles of RhoA and Rac1 in cell motility/invasion and cytoskeletal organization may be due, in part, to their concerted action on NHE1 activity as a convergence point

    Parenting Science Gang : radical co-creation of research projects led by parents of young children

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    Background Parents are increasingly searching online for information supported by research but can find it difficult to identify results relevant to their own experiences. More troublingly, a number of studies indicate that parenting information found online often can be misleading or wrong. The goal of the Parenting Science Gang (PSG) project was to use the power of the Internet to help parents ask questions they wanted to have answered by scientific research and to feel confident in assessing research evidence. Methods By using Facebook to recruit groups and facilitate interactions, PSG was able to engage fully the target public of parents of young children in the radical co-production of scientific studies, while not creating an undue burden on time or restricting participants due to disability, financial status or location. By giving parents true partnership and control of creation of projects, PSG ensured that the chosen questions were ones that were of most relevance and interest to them. Results This paper presents a summary of eight projects, with three in more detail, designed and implemented by PSG Facebook groups in collaboration with experts. Most projects had health related themes, often prompted by dissatisfaction with treatment of parents by health professionals or by feelings of being marginalised by pregnancy and motherhood, as well as by the lack of evidence for their questions and concerns. The PSG approach meant that these frustrations were channelled into actions. All eight of the PSG groups engaged in meaningful interactions with experts and co-produced studies with the groups defining the questions of interest. Conclusions This radically user-led design meant that the PSG staff and the collaborating experts had to live with a high degree of uncertainty. Nevertheless, PSG achieved its goal of academically productive, truly co-produced projects, but as important were the positive effects it had on many of the participants, both parents and experts. At the point of writing this paper, PSG projects have led to outputs including at least eight papers published, in press or in preparation, seven conference presentations, testimony to the Infant Feeding All-Party Parliamentary Group, and with more to come

    Novel Association Strategy with Copy Number Variation for Identifying New Risk Loci of Human Diseases

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    Copy number variations (CNV) are important causal genetic variations for human disease; however, the lack of a statistical model has impeded the systematic testing of CNVs associated with disease in large-scale cohort.Here, we developed a novel integrated strategy to test CNV-association in genome-wide case-control studies. We converted the single-nucleotide polymorphism (SNP) signal to copy number states using a well-trained hidden Markov model. We mapped the susceptible CNV-loci through SNP site-specific testing to cope with the physiological complexity of CNVs. We also ensured the credibility of the associated CNVs through further window-based CNV-pattern clustering. Genome-wide data with seven diseases were used to test our strategy and, in total, we identified 36 new susceptible loci that are associated with CNVs for the seven diseases: 5 with bipolar disorder, 4 with coronary artery disease, 1 with Crohn's disease, 7 with hypertension, 9 with rheumatoid arthritis, 7 with type 1 diabetes and 3 with type 2 diabetes. Fifteen of these identified loci were validated through genotype-association and physiological function from previous studies, which provide further confidence for our results. Notably, the genes associated with bipolar disorder converged in the phosphoinositide/calcium signaling, a well-known affected pathway in bipolar disorder, which further supports that CNVs have impact on bipolar disorder.Our results demonstrated the effectiveness and robustness of our CNV-association analysis and provided an alternative avenue for discovering new associated loci of human diseases

    Drosophila Ribosomal Protein Mutants Control Tissue Growth Non-Autonomously via Effects on the Prothoracic Gland and Ecdysone

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    The ribosome is critical for all aspects of cell growth due to its essential role in protein synthesis. Paradoxically, many Ribosomal proteins (Rps) act as tumour suppressors in Drosophila and vertebrates. To examine how reductions in Rps could lead to tissue overgrowth, we took advantage of the observation that an RpS6 mutant dominantly suppresses the small rough eye phenotype in a cyclin E hypomorphic mutant (cycEJP). We demonstrated that the suppression of cycEJP by the RpS6 mutant is not a consequence of restoring CycE protein levels or activity in the eye imaginal tissue. Rather, the use of UAS-RpS6 RNAi transgenics revealed that the suppression of cycEJP is exerted via a mechanism extrinsic to the eye, whereby reduced Rp levels in the prothoracic gland decreases the activity of ecdysone, the steroid hormone, delaying developmental timing and hence allowing time for tissue and organ overgrowth. These data provide for the first time a rationale to explain the counter-intuitive organ overgrowth phenotypes observed for certain members of the Minute class of Drosophila Rp mutants. They also demonstrate how Rp mutants can affect growth and development cell non-autonomously
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