Improving Bioscience Research Reporting:The ARRIVE Guidelines for Reporting Animal Research

In the last decade the number of bioscience journals has increased enormously, with many filling specialised niches reflecting new disciplines and technologies. The emergence of open-access journals has revolutionised the publication process, maximising the availability of research data. Nevertheless, a wealth of evidence shows that across many areas, the reporting of biomedical research is often inadequate, leading to the view that even if the science is sound, in many cases the publications themselves are not “fit for purpose”, meaning that incomplete reporting of relevant information effectively renders many publications of limited value as instruments to inform policy or clinical and scientific practice [1–21]. A recent review of clinical research showed that there is considerable cumulative waste of financial resources at all stages of the research process, including as a result of publications that are unusable due to poor reporting [22]. It is unlikely that this issue is confined to clinical research [2–14,16–20]

Development of a quality assessment tool for systematic reviews of observational studies (QATSO) of HIV prevalence in men having sex with men and associated risk behaviours

<p>Abstract</p> <p>Background</p> <p>Systematic reviews based on the critical appraisal of observational and analytic studies on HIV prevalence and risk factors for HIV transmission among men having sex with men are very useful for health care decisions and planning. Such appraisal is particularly difficult, however, as the quality assessment tools available for use with observational and analytic studies are poorly established.</p> <p>Methods</p> <p>We reviewed the existing quality assessment tools for systematic reviews of observational studies and developed a concise quality assessment checklist to help standardise decisions regarding the quality of studies, with careful consideration of issues such as external and internal validity.</p> <p>Results</p> <p>A pilot version of the checklist was developed based on epidemiological principles, reviews of study designs, and existing checklists for the assessment of observational studies. The Quality Assessment Tool for Systematic Reviews of Observational Studies (QATSO) Score consists of five items: External validity (1 item), reporting (2 items), bias (1 item) and confounding factors (1 item). Expert opinions were sought and it was tested on manuscripts that fulfil the inclusion criteria of a systematic review. Like all assessment scales, QATSO may oversimplify and generalise information yet it is inclusive, simple and practical to use, and allows comparability between papers.</p> <p>Conclusion</p> <p>A specific tool that allows researchers to appraise and guide study quality of observational studies is developed and can be modified for similar studies in the future.</p

Effect of treatment of gestational diabetes mellitus on pregnancy outcomes

Copyright © 2005 Massachusetts Medical Society.Background: We conducted a randomized clinical trial to determine whether treatment of women with gestational diabetes mellitus reduced the risk of perinatal complications. Methods: We randomly assigned women between 24 and 34 weeks’ gestation who had gestational diabetes to receive dietary advice, blood glucose monitoring, and insulin therapy as needed (the intervention group) or routine care. Primary outcomes included serious perinatal complications (defined as death, shoulder dystocia, bone fracture, and nerve palsy), admission to the neonatal nursery, jaundice requiring phototherapy, induction of labor, cesarean birth, and maternal anxiety, depression, and health status. Results: The rate of serious perinatal complications was significantly lower among the infants of the 490 women in the intervention group than among the infants of the 510 women in the routine-care group (1 percent vs. 4 percent; relative risk adjusted for maternal age, race or ethnic group, and parity, 0.33; 95 percent confidence interval, 0.14 to 0.75; P=0.01). However, more infants of women in the intervention group were admitted to the neonatal nursery (71 percent vs. 61 percent; adjusted relative risk, 1.13; 95 percent confidence interval, 1.03 to 1.23; P=0.01). Women in the intervention group had a higher rate of induction of labor than the women in the routine-care group (39 percent vs. 29 percent; adjusted relative risk, 1.36; 95 percent confidence interval, 1.15 to 1.62; P<0.001), although the rates of cesarean delivery were similar (31 percent and 32 percent, respectively; adjusted relative risk, 0.97; 95 percent confidence interval, 0.81 to 1.16; P=0.73). At three months post partum, data on the women’s mood and quality of life, available for 573 women, revealed lower rates of depression and higher scores, consistent with improved health status, in the intervention group. Conclusions: Treatment of gestational diabetes reduces serious perinatal morbidity and may also improve the woman’s health-related quality of life.Caroline A. Crowther, Janet E. Hiller, John R. Moss, Andrew J. McPhee, William S. Jeffries and Jeffrey S. Robinso

Improved curve fits to summary survival data: application to economic evaluation of health technologies

addresses: Peninsula College of Medicine and Dentistry, Veysey Building, Salmon Pool Lane, Exeter, EX2 4SG, UK. [email protected]: PMCID: PMC3198983types: Journal Article; Research Support, Non-U.S. Gov't© 2011 Hoyle and Henley; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Mean costs and quality-adjusted-life-years are central to the cost-effectiveness of health technologies. They are often calculated from time to event curves such as for overall survival and progression-free survival. Ideally, estimates should be obtained from fitting an appropriate parametric model to individual patient data. However, such data are usually not available to independent researchers. Instead, it is common to fit curves to summary Kaplan-Meier graphs, either by regression or by least squares. Here, a more accurate method of fitting survival curves to summary survival data is described

Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

Choosing the target difference ('effect size') for a randomised controlled trial - DELTA(2) guidance protocol

BACKGROUND: A key step in the design of a randomised controlled trial (RCT) is the estimation of the number of participants needed. By far the most common approach is to specify a target difference and then estimate the corresponding sample size; this sample size is chosen to provide reassurance that the trial will have high statistical power to detect such a difference between the randomised groups (at the planned statistical significance level). The sample size has many implications for the conduct of the study, as well as carrying scientific and ethical aspects to its choice. Despite the critical role of the target difference for the primary outcome in the design of an RCT, the manner in which it is determined has received little attention. This article reports the protocol of the Difference ELicitation in TriAls (DELTA(2)) project, which will produce guidance on the specification and reporting of the target difference for the primary outcome in a sample size calculation for RCTs. METHODS/DESIGN: The DELTA(2) project has five components: systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2); a Delphi study (stage 3); a 2-day consensus meeting bringing together researchers, funders and patient representatives, as well as one-off engagement sessions at relevant stakeholder meetings (stage 4); and the preparation and dissemination of a guidance document (stage 5). DISCUSSION: Specification of the target difference for the primary outcome is a key component of the design of an RCT. There is a need for better guidance for researchers and funders regarding specification and reporting of this aspect of trial design. The aim of this project is to produce consensus based guidance for researchers and funders

Reliability and Initial Validation of the Ulcerative Colitis Endoscopic Index of Severity

Background & AimsWe studied the reliability of the previously described Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and validated it with an independent cohort of investigators.MethodsWe created a new library of 57 videos of flexible sigmoidoscopy and stratified them based on disease severity. Twenty-five investigators were each randomly assigned to assess 28 videos (which included 4 duplicates to assess intraobserver reliability). Investigators were blinded to clinical details except for 2 of 4 duplicated videos (to assess the impact of knowledge of symptoms on assessment). Three descriptors (“vascular pattern”, “bleeding”, and “erosions and ulcers”) comprising the UCEIS were scored with a visual analogue scale (VAS) to assess overall severity. Intrainvestigator and interinvestigator agreement was characterized by κ statistical analysis; reliability ratios were used to compare VAS and UCEIS scores.ResultsThere was a high level of correlation between UCEIS scores and overall assessment of severity (correlation coefficient, 0.93). Internal consistency (Cronbach α analysis) was 0.86. Intrainvestigator and interinvestigator reliability ratios for UCEIS scores were 0.96 and 0.88, respectively. Intrainvestigator agreement in determination of the UCEIS score was good (κ = 0.72), with individual descriptors ranging from a κ of 0.47 (for bleeding) to 0.87 (for vascular pattern). Interinvestigator agreement in determination of UCEIS scores was moderate (κ = 0.50), with descriptors ranging from a κ of 0.48 (for bleeding) to 0.54 (for vascular pattern). Intrainvestigator variability in determining UCEIS scores did not change appreciably when a video was presented with clinical details.ConclusionsThe UCEIS and its components show satisfactory intrainvestigator and interinvestigator reliability. Among investigators, the UCEIS accounted for a median of 86% of the variability in evaluation of overall severity on the VAS when assessing the endoscopic severity of UC and was unaffected by knowledge of clinical details