Locating sex-specific evidence on clinical questions in MEDLINE: a search filter for use on OvidSP™

<p>Abstract</p> <p>Background</p> <p>Many recently published clinical studies report sex-specific data. This information may help to improve clinical decision-making for both sexes, but it is not easily accessible in MEDLINE. The aim of this project was to develop and validate a search filter that would facilitate the retrieval of studies reporting high quality sex-specific data on clinical questions.</p> <p>Methods</p> <p>A filter was developed by screening titles, abstracts and Medical Subject Headings (MeSH) in a set of 80 high quality and relevant papers, 75 of which were identified through a review of clinical guidelines and five through other means. The filter, for use on OvidSP™, consists of nine command lines for searching free text words in the title, abstract and MeSH of a paper. It was able to identify 74/80 (92.5%) of the articles from which it was derived. The filter was evaluated in a set of 622 recently published original studies on Alzheimer's disease and on asthma. It was validated against a reference of 98 studies from this set, which provided high quality, clinically relevant, sex-specific evidence. Recall and precision were used as performance measures.</p> <p>Results</p> <p>The filter demonstrated 81/98 (83%) recall and 81/125 (65%) precision in retrieving relevant articles on Alzheimer's disease and on asthma. In comparison, only 30/98 (31%) recall would have been achieved if sex-specific MeSH terms only had been used.</p> <p>Conclusion</p> <p>This sex-specific search filter performs well in retrieving relevant papers, while its precision rate is good. It performs better than a search with sex-specific MeSH. The filter can be useful to anyone seeking sex-specific clinical evidence (e.g., guideline organizations, researchers, medical educators, clinicians).</p

A Unifying Framework for Evaluating the Predictive Power of Genetic Variants Based on the Level of Heritability Explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait

FLT3 mutation incidence and timing of origin in a population case series of pediatric leukemia

<p>Abstract</p> <p>Background</p> <p>Mutations in <it>FLT3 </it>result in activated tyrosine kinase activity, cell growth stimulation, and a poor prognosis among various subtypes of leukemia. The causes and timing of the mutations are not currently known. We evaluated the prevalence and timing of origin of <it>FLT3 </it>mutations in a population series of childhood leukemia patients from Northern California.</p> <p>Methods</p> <p>We screened and sequenced <it>FLT3 </it>mutations (point mutations and internal tandem duplications, ITDs) among 517 childhood leukemia patients, and assessed whether these mutations occurred before or after birth using sensitive "backtracking" methods.</p> <p>Results</p> <p>We determined a mutation prevalence of 9 of 73 acute myeloid leukemias (AMLs, 12%) and 9 of 441 acute lymphocytic leukemias (ALLs, 2%). Among AMLs, <it>FLT3 </it>mutations were more common in older patients, and among ALLs, <it>FLT3 </it>mutations were more common in patients with high hyperdiploidy (3.7%) than those without this cytogenetic feature (1.4%). Five <it>FLT3 </it>ITDs, one deletion mutation, and 3 point mutations were assessed for their presence in neonatal Guthrie spots using sensitive real-time PCR techniques, and no patients were found to harbor <it>FLT3 </it>mutations at birth.</p> <p>Conclusions</p> <p><it>FLT3 </it>mutations were not common in our population-based patient series in California, and patients who harbor <it>FLT3 </it>mutations most likely acquire them after they are born.</p

Evaluating the Sensitivity of Mycobacterium tuberculosis to Biotin Deprivation Using Regulated Gene Expression

In the search for new drug targets, we evaluated the biotin synthetic pathway of Mycobacterium tuberculosis (Mtb) and constructed an Mtb mutant lacking the biotin biosynthetic enzyme 7,8-diaminopelargonic acid synthase, BioA. In biotin-free synthetic media, ΔbioA did not produce wild-type levels of biotinylated proteins, and therefore did not grow and lost viability. ΔbioA was also unable to establish infection in mice. Conditionally-regulated knockdown strains of Mtb similarly exhibited impaired bacterial growth and viability in vitro and in mice, irrespective of the timing of transcriptional silencing. Biochemical studies further showed that BioA activity has to be reduced by approximately 99% to prevent growth. These studies thus establish that de novo biotin synthesis is essential for Mtb to establish and maintain a chronic infection in a murine model of TB. Moreover, these studies provide an experimental strategy to systematically rank the in vivo value of potential drug targets in Mtb and other pathogens

My first employee: an empirical investigation

The challenge for solo entrepreneurs to add their first employee is arguably the single biggest growth event facing any growing firm. To understand how this event affects performance, and the antecedents of hiring, we analyse Danish matched employer-employee data. Those who hire enjoy superior sales outcomes in subsequent years, while the dispersion in profits increases. Furthermore, those that hire enjoy faster sales growth in the previous year, suggesting that sales growth precedes the first hire. Finally, we show that founders with a stronger profile in terms of education and previous income are more likely to increase profits, while the characteristics of the employee are less important. The latter finding is important from a job creation perspective, in light of the suggested sorting of more marginalized employees into new and established firms

Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde

Entrepreneurial Behavior as Learning Processes in a Transgenerational Entrepreneurial Family

Within the extant body of literature, little is known as to how transgenerational entrepreneurial families develop entrepreneurial mind-sets in order to create value across generations. Accordingly, this chapter aims to explore the role of the family ownership group in entrepreneurial behavior by examining the entrepreneurial learning process in a transgenerational entrepreneurial family. In achieving this aim, the 4I organizational learning framework by Crossan et al. (An organizational learning framework: From intuition to institution. Academy of Management Review 24 (3): 522-537, 1999) is adapted as a theoretical lens. The empirical evidence that draws upon evidence from a detailed longitudinal case study illustrates the interjectory influence of the family ownership group within this process, suggesting that entrepreneurial learning in a transgenerational family firm is embedded at the family group level and reproduced and co-created as a result of resilient entrepreneurial behavior

Economy and Divorces: Their Impact Over Time on the Self-Employment Rates in Spain

The paper used time-series data and examined the effect of economic and social variables on the male and female self-employment rates in Spain. We also employed cointegration analysis (with and without) structural breaks. We thus find strong evidence that long run relationships exist among the variables. More precisely, we find that the unemployment rates and the ratio of self-employment to employees’ earnings have a positive effect on self-employment, whereas, economic development and divorce rates have a negative effect. Importantly, we find that the economic variables have equal or stronger long run impact on females than males, with both groups reacting to changes in family circumstances. Finally, we show that the short run family circumstances are better predictors of self-employment choices rather than economic factors, with self-employment being a means of adjustment to new personal circumstances and economic needs