"Summary Page": a novel tool that reduces omitted data in research databases

<p>Abstract</p> <p>Background</p> <p>Data entry errors are common in clinical research databases. Omitted data are of particular concern because they are more common than erroneously inserted data and therefore could potentially affect research findings. However, few affordable strategies for their prevention are available.</p> <p>Methods</p> <p>We have conducted a prospective observational study of the effect of a novel tool called "<it>Summary Page</it>" on the frequency of correction of omitted data errors in a radiation oncology research database between July 2008 and March 2009. "<it>Summary Page</it>" was implemented as an optionally accessed screen in the database that visually integrates key fields in the record. We assessed the frequency of omitted data on the example of the <it>Date of Relapse </it>field. We considered the data in this field to be omitted for all records that had empty <it>Date of Relapse </it>field and evidence of relapse elsewhere in the record.</p> <p>Results</p> <p>A total of 1,156 records were updated and 200 new records were entered in the database over the study period. "<it>Summary Page</it>" was accessed for 44% of all updated records and for 69% of newly entered records. Frequency of correction of the omitted date of cancer relapse was six-fold higher in records for which "<it>Summary Page</it>" was accessed (p = 0.0003).</p> <p>Conclusions</p> <p>"<it>Summary Page</it>" was strongly associated with an increased frequency of correction of omitted data errors. Further, controlled, studies are needed to confirm this finding and elucidate its mechanism of action.</p

Sample size requirements to detect the effect of a group of genetic variants in case-control studies

<p>Abstract</p> <p>Background</p> <p>Because common diseases are caused by complex interactions among many genetic variants along with environmental risk factors, very large sample sizes are usually needed to detect such effects in case-control studies. Nevertheless, many genetic variants act in well defined biologic systems or metabolic pathways. Therefore, a reasonable first step may be to detect the effect of a group of genetic variants before assessing specific variants.</p> <p>Methods</p> <p>We present a simple method for determining approximate sample sizes required to detect the average joint effect of a group of genetic variants in a case-control study for multiplicative models.</p> <p>Results</p> <p>For a range of reasonable numbers of genetic variants, the sample size requirements for the test statistic proposed here are generally not larger than those needed for assessing marginal effects of individual variants and actually decline with increasing number of genetic variants in many situations considered in the group.</p> <p>Conclusion</p> <p>When a significant effect of the group of genetic variants is detected, subsequent multiple tests could be conducted to detect which individual genetic variants and their combinations are associated with disease risk. When testing for an effect size in a group of genetic variants, one can use our global test described in this paper, because the sample size required to detect an effect size in the group is comparatively small. Our method could be viewed as a screening tool for assessing groups of genetic variants involved in pathogenesis and etiology of common complex human diseases.</p

The Dynamics of EBV Shedding Implicate a Central Role for Epithelial Cells in Amplifying Viral Output

To develop more detailed models of EBV persistence we have studied the dynamics of virus shedding in healthy carriers. We demonstrate that EBV shedding into saliva is continuous and rapid such that the virus level is replaced in ≤2 minutes, the average time that a normal individual swallows. Thus, the mouth is not a reservoir of virus but a conduit through which a continuous flow stream of virus passes in saliva. Consequently, virus is being shed at a much higher rate than previously thought, a level too high to be accounted for by replication in B cells in Waldeyer's ring alone. Virus shedding is relatively stable over short periods (hours-days) but varies through 3.5 to 5.5 logs over longer periods, a degree of variation that also cannot be accounted for solely by replication in B cells. This variation means, contrary to what is generally believed, that the definition of high and low shedder is not so much a function of variation between individuals but within individuals over time. The dynamics of shedding describe a process governing virus production that is occurring independently ≤3 times at any moment. This process grows exponentially and is then randomly terminated. We propose that these dynamics are best explained by a model where single B cells sporadically release virus that infects anywhere from 1 to 5 epithelial cells. This infection spreads at a constant exponential rate and is terminated randomly, resulting in infected plaques of epithelial cells ranging in size from 1 to 105 cells. At any one time there are a very small number (≤3) of plaques. We suggest that the final size of these plaques is a function of the rate of infectious spread within the lymphoepithelium which may be governed by the structural complexity of the tissue but is ultimately limited by the immune response

Spatially and Financially Explicit Population Viability Analysis of Maculinea alcon in The Netherlands

Background The conservation of species structured in metapopulations involves an important dilemma of resource allocation: should investments be directed at restoring/enlarging habitat patches or increasing connectivity. This is still an open question for Maculinea species despite they are among the best studied and emblematic butterfly species, because none of the population dynamics models developed so far included dispersal. Methodology/Principal Findings We developed the first spatially and financially explicit Population Viability Analysis model for Maculinea alcon, using field data from The Netherlands. Implemented using the RAMAS/GIS platform, the model incorporated both local (contest density dependence, environmental and demographic stochasticities), and regional population dynamics (dispersal rates between habitat patches). We selected four habitat patch networks, contrasting in several basic features (number of habitat patches, their quality, connectivity, and occupancy rate) to test how these features are affecting the ability to enhance population viability of four basic management options, designed to incur the same costs: habitat enlargement, habitat quality improvement, creation of new stepping stone habitat patches, and reintroduction of captive-reared butterflies. The PVA model was validated by the close match between its predictions and independent field observations on the patch occupancy pattern. The four patch networks differed in their sensitivity to model parameters, as well as in the ranking of management options. Overall, the best cost-effective option was enlargement of existing habitat patches, followed by either habitat quality improvement or creation of stepping stones depending on the network features. Reintroduction was predicted to generally be inefficient, except in one specific patch network. Conclusions/Significance Our results underline the importance of spatial and regional aspects (dispersal and connectivity) in determining the impact of conservation actions, even for a species previously considered as sedentary. They also illustrate that failure to account for the cost of management scenarios can lead to very different conclusions

Camouflage Effects of Various Colour-Marking Morphs against Different Microhabitat Backgrounds in a Polymorphic Pygmy Grasshopper Tetrix japonica

Colour-marking polymorphism is widely distributed among cryptic species. To account for the adaptive significance of such polymorphisms, several hypotheses have been proposed to date. Although these hypotheses argue over the degree of camouflage effects of marking morphs (and the interactions between morphs and their microhabitat backgrounds), as far as we know, most empirical evidence has been provided under unnatural conditions (i.e., using artificial prey).Tetrix japonica, a pygmy grasshopper, is highly polymorphic in colour-markings and occurs in both sand and grass microhabitats. Even within a microhabitat, T. japonica is highly polymorphic. Using humans as dummy predators and printed photographs in which various morphs of grasshoppers were placed against different backgrounds, we addressed three questions to test the neutral, background heterogeneity, and differential crypsis hypotheses in four marking-type morphs: 1) do the morphs differ in the degree of crypsis in each microhabitat, 2) are different morphs most cryptic in specific backgrounds of the microhabitats, and 3) does the morph frequency reflect the degree of crypsis?The degree of camouflage differed among the four morphs; therefore, the neutral hypothesis was rejected. Furthermore, the order of camouflage advantage among morphs differed depending on the two types of backgrounds (sand and grass), although the grass background consistently provided greater camouflage effects. Thus, based on our results, we could not reject the background heterogeneity hypothesis. Under field conditions, the more cryptic morphs comprised a minority of the population. Overall, our results demonstrate that the different morphs were not equivalent in the degree of crypsis, but the degree of camouflage of the morphs was not consistent with the morph frequency. These findings suggest that trade-offs exist between the camouflage benefit of body colouration and other fitness components, providing a better understanding of the adaptive significance of colour-markings and presumably supporting the differential crypsis hypothesis

Cryptic multiple hypotheses testing in linear models: overestimated effect sizes and the winner's curse

Fitting generalised linear models (GLMs) with more than one predictor has become the standard method of analysis in evolutionary and behavioural research. Often, GLMs are used for exploratory data analysis, where one starts with a complex full model including interaction terms and then simplifies by removing non-significant terms. While this approach can be useful, it is problematic if significant effects are interpreted as if they arose from a single a priori hypothesis test. This is because model selection involves cryptic multiple hypothesis testing, a fact that has only rarely been acknowledged or quantified. We show that the probability of finding at least one ‘significant’ effect is high, even if all null hypotheses are true (e.g. 40% when starting with four predictors and their two-way interactions). This probability is close to theoretical expectations when the sample size (N) is large relative to the number of predictors including interactions (k). In contrast, type I error rates strongly exceed even those expectations when model simplification is applied to models that are over-fitted before simplification (low N/k ratio). The increase in false-positive results arises primarily from an overestimation of effect sizes among significant predictors, leading to upward-biased effect sizes that often cannot be reproduced in follow-up studies (‘the winner's curse’). Despite having their own problems, full model tests and P value adjustments can be used as a guide to how frequently type I errors arise by sampling variation alone. We favour the presentation of full models, since they best reflect the range of predictors investigated and ensure a balanced representation also of non-significant results

Adaptive Strategy for the Statistical Analysis of Connectomes

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores

Zollinger-Ellison syndrome associated with neurofibromatosis type 1: a case report

BACKGROUND: Neurofibromatosis type 1 is an autosomal dominant neurocutaneous disorder with characteristic features of skin and central nervous system involvement. Gastrointestinal involvement is rare, but the risk of malignancy development is considerable. Zollinger-Ellison syndrome is caused by gastrin-secreting tumors called gastrinomas. Correct diagnosis is often difficult, and curative treatment can only be achieved surgically. CASE PRESENTATION: A 41-year-old female affected by neurofibromatosis type 1 presented with a history of recurrent epigastric soreness, diarrhea, and relapsing chronic duodenal ulcer. Her serum fasting gastrin level was over 1000 pg/mL. An abdominal CT scan revealed a 3 × 2-cm, well-enhanced mass adjacent to the duodenal loop. She was not associated with multiple endocrine neoplasia type 1. Operative resection was performed and gastrinoma was diagnosed by immunohistochemical staining. The serum gastrin level decreased to 99.1 pg/mL after surgery, and symptoms and endoscopic findings completely resolved without recurrences. CONCLUSION: Gastrinoma is difficult to detect even in the general population, and hence symptoms such as recurrent idiopathic peptic ulcer and diarrhea in neurofibromatosis type 1 patients should be accounted for as possibly contributing to Zollinger-Ellison syndrome

Effects of chronic ascariasis and trichuriasis on cytokine production and gene expression in human blood: a cross-sectional study.

Background Chronic soil-transmitted helminth (STH) infections are associated with effects on systemic immune responses that could be caused by alterations in immune homeostasis. To investigate this, we measured the impact in children of STH infections on cytokine responses and gene expression in unstimulated blood. Methodology/Principal Findings Sixty children were classified as having chronic, light, or no STH infections. Peripheral blood mononuclear cells were cultured in medium for 5 days to measure cytokine accumulation. RNA was isolated from peripheral blood and gene expression analysed using microarrays. Different infection groups were compared for the purpose of analysis: STH infection (combined chronic and light vs. uninfected groups) and chronic STH infection (chronic vs. combined light and uninfected groups). The chronic STH infection effect was associated with elevated production of GM-CSF (P = 0.007), IL-2 (P = 0.03), IL-5 (P = 0.01), and IL-10 (P = 0.01). Data reduction suggested that chronic infections were primarily associated with an immune phenotype characterized by elevated IL-5 and IL-10, typical of a modified Th2-like response. Chronic STH infections were associated with the up-regulation of genes associated with immune homeostasis (IDO, P = 0.03; CCL23, P = 0.008, HRK, P = 0.005), down-regulation of microRNA hsa-let-7d (P = 0.01) and differential regulation of several genes associated with granulocyte-mediated inflammation (IL-8, down-regulated, P = 0.0002; RNASE2, up-regulated, P = 0.009; RNASE3, up-regulated, p = 0.03). Conclusions/Significance Chronic STH infections were associated with a cytokine response indicative of a modified Th2 response. There was evidence that STH infections were associated with a pattern of gene expression suggestive of the induction of homeostatic mechanisms, the differential expression of several inflammatory genes and the down-regulation of microRNA has-let-7d. Effects on immune homeostasis and the development of a modified Th2 immune response during chronic STH infections could explain the systemic immunologic effects that have been associated with these infections such as impaired immune responses to vaccines and the suppression of inflammatory diseases