An automatic method to generate domain-specific investigator networks using PubMed abstracts

<p>Abstract</p> <p>Background</p> <p>Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts.</p> <p>Results</p> <p>We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network.</p> <p>Conclusion</p> <p>We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.</p

Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations

BACKGROUND: Meta-analysis is the systematic and quantitative synthesis of effect sizes and the exploration of their diversity across different studies. Meta-analyses are increasingly applied to synthesize data from genome-wide association (GWA) studies and from other teams that try to replicate the genetic variants that emerge from such investigations. Between-study heterogeneity is important to document and may point to interesting leads. METHODOLOGY/PRINCIPAL FINDINGS: To exemplify these issues, we used data from three GWA studies on type 2 diabetes and their replication efforts where meta-analyses of all data using fixed effects methods (not incorporating between-study heterogeneity) have already been published. We considered 11 polymorphisms that at least one of the three teams has suggested as susceptibility loci for type 2 diabetes. The I2 inconsistency metric (measuring the amount of heterogeneity not due to chance) was different from 0 (no detectable heterogeneity) for 6 of the 11 genetic variants; inconsistency was moderate to very large (I2 = 32-77%) for 5 of them. For these 5 polymorphisms, random effects calculations incorporating between-study heterogeneity revealed more conservative p-values for the summary effects compared with the fixed effects calculations. These 5 associations were perused in detail to highlight potential explanations for between-study heterogeneity. These include identification of a marker for a correlated phenotype (e.g. FTO rs8050136 being associated with type 2 diabetes through its effect on obesity); differential linkage disequilibrium across studies of the identified genetic markers with the respective culprit polymorphisms (e.g., possibly the case for CDKAL1 polymorphisms or for rs9300039 and markers in linkage disequilibrium, as shown by additional studies); and potential bias. Results were largely similar, when we treated the discovery and replication data from each GWA investigation as separate studies. SIGNIFICANCE: Between-study heterogeneity is useful to document in the synthesis of data from GWA investigations and can offer valuable insights for further clarification of gene-disease associations

Identifying null meta-analyses that are ripe for updating

BACKGROUND: As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date. METHODS: We propose new methods for determining when non-significant meta-analytic results might be overturned, based on a prediction of the number of participants required in new studies. To guide decision making, we introduce the "new participant ratio", the ratio of the actual number of participants in new studies to the predicted number required to obtain statistical significance. A simulation study was conducted to study the performance of our methods and a real meta-analysis provides further evidence. RESULTS: In our three simulation configurations, our diagnostic test for determining whether a meta-analysis is out of date had sensitivity of 55%, 62%, and 49% with corresponding specificity of 85%, 80%, and 90% respectively. CONCLUSIONS: Simulations suggest that our methods are able to detect out-of-date meta-analyses. These quick and approximate methods show promise for use by systematic review teams to help decide whether to commit the considerable resources required to update a meta-analysis. Further investigation and evaluation of the methods is required before they can be recommended for general use

Haplotypes of intron 4 of the estrogen receptor alpha gene and hip fractures: a replication study in Caucasians

<p>Abstract</p> <p>Background</p> <p>Despite their great impact, few genetic association studies have used hip fractures as an endpoint. However, the association of two polymorphisms on intron 4 of estrogen receptor alpha (<it>ESR1</it>) with hip fractures was recently reported in a Chinese population. The aim of this study was to investigate whether such association is also present in Caucasians.</p> <p>Methods</p> <p>We analyzed those two SNPs and another neighbour SNP located on the exon 4 of <it>ESR1 </it>in 787 patients with hip fractures and 953 controls from Spain.</p> <p>Results</p> <p>The allelic frequencies differed markedly from those reported in Asian populations. Nevertheless, haplotypes including the rs3020314 and rs1884051 loci in intron 4 showed a significant association with hip fractures (omnibus test p = 0.006 in the whole group and 0.00005 in women). In the sex-stratified analysis, the association was significant in females, but not in males. In women, the CA haplotype appeared to have a protective influence, being present in 6.5% of the controls, but only in 3% of patients with fractures (odds ratio 0.39; 95% confidence interval 0.26-0.59; estimated population preventive fraction 3.5%). The inclusion of the rs1801132 SNP of exon 4 further increased the statistical significance of the association (odds ratio 0.17; 95% CI 0.08-0.37; p = 0.00001). Each SNP appeared to contribute independently to the association. No genotype-related differences in gene expression were found in 42 femoral bone samples.</p> <p>Conclusions</p> <p>This study confirms the association of some polymorphisms in the region of exon 4/intron 4 of <it>ESR1 </it>and hip fractures in women. However, there are marked differences in allele frequencies between Asian and Caucasian populations.</p

What do we know and when do we know it?

Two essential aspects of virtual screening are considered: experimental design and performance metrics. In the design of any retrospective virtual screen, choices have to be made as to the purpose of the exercise. Is the goal to compare methods? Is the interest in a particular type of target or all targets? Are we simulating a ‘real-world’ setting, or teasing out distinguishing features of a method? What are the confidence limits for the results? What should be reported in a publication? In particular, what criteria should be used to decide between different performance metrics? Comparing the field of molecular modeling to other endeavors, such as medical statistics, criminology, or computer hardware evaluation indicates some clear directions. Taken together these suggest the modeling field has a long way to go to provide effective assessment of its approaches, either to itself or to a broader audience, but that there are no technical reasons why progress cannot be made

Retrospective harm benefit analysis of pre-clinical animal research for six treatment interventions

The harm benefit analysis (HBA) is the cornerstone of animal research regulation and is considered to be a key ethical safeguard for animals. The HBA involves weighing the anticipated benefits of animal research against its predicted harms to animals but there are doubts about how objective and accountable this process is.i. To explore the harms to animals involved in pre-clinical animal studies and to assess these against the benefits for humans accruing from these studies; ii. To test the feasibility of conducting this type of retrospective HBA.Data on harms were systematically extracted from a sample of pre-clinical animal studies whose clinical relevance had already been investigated by comparing systematic reviews of the animal studies with systematic reviews of human studies for the same interventions (antifibrinolytics for haemorrhage, bisphosphonates for osteoporosis, corticosteroids for brain injury, Tirilazad for stroke, antenatal corticosteroids for neonatal respiratory distress and thrombolytics for stroke). Clinical relevance was also explored in terms of current clinical practice. Harms were categorised for severity using an expert panel. The quality of the research and its impact were considered. Bateson's Cube was used to conduct the HBA.The most common assessment of animal harms by the expert panel was 'severe'. Reported use of analgesia was rare and some animals (including most neonates) endured significant procedures with no, or only light, anaesthesia reported. Some animals suffered iatrogenic harms. Many were kept alive for long periods post-experimentally but only 1% of studies reported post-operative care. A third of studies reported that some animals died prior to endpoints. All the studies were of poor quality. Having weighed the actual harms to animals against the actual clinical benefits accruing from these studies, and taking into account the quality of the research and its impact, less than 7% of the studies were permissible according to Bateson's Cube: only the moderate bisphosphonate studies appeared to minimise harms to animals whilst being associated with benefit for humans.This is the first time the accountability of the HBA has been systematically explored across a range of pre-clinical animal studies. The regulatory systems in place when these studies were conducted failed to safeguard animals from severe suffering or to ensure that only beneficial, scientifically rigorous research was conducted. Our findings indicate a pressing need to: i. review regulations, particularly those that permit animals to suffer severe harms; ii. reform the processes of prospectively assessing pre-clinical animal studies to make them fit for purpose; and iii. systematically evaluate the benefits of pre-clinical animal research to permit a more realistic assessment of its likely future benefits

Comparison of two independent systematic reviews of trials of recombinant human bone morphogenetic protein-2 (rhBMP-2) : The Yale Open Data Access Medtronic Project

Background: It is uncertain whether the replication of systematic reviews, particularly those with the same objectives and resources, would employ similar methods and/or arrive at identical findings. We compared the results and conclusions of two concurrent systematic reviews undertaken by two independent research teams provided with the same objectives, resources, and individual participant-level data. Methods: Two centers in the USA and UK were each provided with participant-level data on 17 multi-site clinical trials of recombinant human bone morphogenetic protein-2 (rhBMP-2). The teams were blinded to each other's methods and findings until after publication. We conducted a retrospective structured comparison of the results of the two systematic reviews. The main outcome measures included (1) trial inclusion criteria; (2) statistical methods; (3) summary efficacy and risk estimates; and (4) conclusions. Results: The two research teams' meta-analyses inclusion criteria were broadly similar but differed slightly in trial inclusion and research methodology. They obtained similar results in summary estimates of most clinical outcomes and adverse events. Center A incorporated all trials into summary estimates of efficacy and harms, while Center B concentrated on analyses stratified by surgical approach. Center A found a statistically significant, but small, benefit whereas Center B reported no advantage. In the analysis of harms, neither showed an increased cancer risk at 48 months, although Center B reported a significant increase at 24 months. Conclusions reflected these differences in summary estimates of benefit balanced with small but potentially important risk of harm. Conclusions: Two independent groups given the same research objectives, data, resources, funding, and time produced broad general agreement but differed in several areas. These differences, the importance of which is debatable, indicate the value of the availability of data to allow for more than a single approach and a single interpretation of the data. Systematic review registration: PROSPERO CRD42012002040and CRD42012001907

An NIH intramural percubator as a model of academic-industry partnerships: from the beginning of life through the valley of death

In 2009 the NIH publicly announced five strategic goals for the institutes that included the critical need to translate research discoveries into public benefit at an accelerated pace, with a commitment to find novel ways to engage academic investigators in the process. The emphasis on moving scientific advancements from the laboratory to the clinic is an opportune time to discuss how the NIH intramural program in Bethesda, the largest biomedical research center in the world, can participate in this endeavor. Proposed here for consideration is a percolator-incubator program, a 'percubator' designed to enable NIH intramural investigators to develop new medical interventions as quickly and efficiently as possible

Abstracts in high profile journals often fail to report harm

<p>Abstract</p> <p>Background</p> <p>To describe how frequently harm is reported in the abstract of high impact factor medical journals.</p> <p>Methods</p> <p><it>Design and population</it>: We carried out a blinded structured review of a random sample of 363 Randomised Controlled Trials (RCTs) carried out on human beings, and published in high impact factor medical journals in 2003. <it>Main endpoint</it>: 1) Proportion of articles reporting harm in the abstract; and 2) Proportion of articles that reported harm in the abstract when harm was reported in the main body of the article. <it>Analysis</it>: Corrected Prevalence Ratio (cPR) and its exact confidence interval were calculated. Non-conditional logistic regression was used.</p> <p>Results</p> <p>363 articles and 407 possible comparisons were studied. Overall, harm was reported in 135 abstracts [37.2% (CI95%:32.2 to 42.4)]. Harm was reported in the main text of 243 articles [66.9% (CI95%: 61.8 to 71.8)] and was statistically significant in 54 articles [14.9% (CI95%: 11.4 to 19.0)]. Among the 243 articles that mentioned harm in the text, 130 articles [53.5% (CI95% 47.0 to 59.9)] reported harm in the abstract; a figure that rose to 75.9% (CI95%: 62.4 to 86.5) when the harm reported in the text was statistically significant. Harm in the abstract was more likely to be reported when statistically significant harm was reported in the main body of the article [cPR = 1.70 (CI95% 1.47 to 1.92)] and when drug companies (not public institutions) funded the RCTs [cPR = 1.29 (CI95% 1.03 to 1.67)].</p> <p>Conclusion</p> <p>Abstracts published in high impact factor medical journals underreport harm, even when harm is reported in the main body of the article.</p