Sole-source business models for genetic testing can create private databases containing information vital to interpreting the clinical significance of human genetic variations. But incomplete access to those databases threatens to impede the clinical interpretation of genomic medicine. National health systems and insurers, regulators, researchers, providers and patients all have a strong interest in ensuring broad access to information about the clinical significance of variants discovered through genetic testing. They can create incentives for sharing data and interpretive algorithms in several ways, including: promoting voluntary sharing; requiring laboratories to share as a condition of payment for or regulatory approval of laboratory services; establishing - and compelling participation in - resources that capture the information needed to interpret the data independent of company policies; and paying for sharing and interpretation in addition to paying for the test itself. US policies have failed to address the data-sharing issue. The entry of new and established firms into the European genetic testing market presents an opportunity to correct this failure.European Journal of Human Genetics advance online publication, 14 November 2012; doi:10.1038/ejhg.2012.217.
BACKGROUND: Accurate interpretation of HIV drug resistance (HIVDR) testing is challenging, yet important for patient care. We compared genotyping interpretation, based on the Stanford University HIV Drug Resistance Database (Stanford HIVdb), and virtual phenotyping, based on the Janssen Diagnostics BVBA’s vircoTYPETM HIV-1, and investigated their level of agreement in antiretroviral (ARV) naive patients in Asia, where non-B subtypes predominate. METHODS: Sequences from 1301 ARV-naive patients enrolled in the TREAT Asia Studies to Evaluate Resistance – Monitoring Study (TASER-M) were analysed by both interpreting systems. Interpretations from both Stanford HIVdb and vircoTYPETM HIV-1 were initially grouped into 2 levels: susceptible and non-susceptible. Discrepancy was defined as a discordant result between the susceptible and non-susceptible interpretations from the two systems for the same ARV. Further analysis was performed when interpretations from both systems were categorised into 3 levels: susceptible, intermediate and resistant; whereby discrepancies could be categorised as major discrepancies and minor discrepancies. Major discrepancy was defined as having a susceptible result from one system and resistant from the other. Minor discrepancy corresponded to having an intermediate interpretation in one system, with a susceptible or resistant result in the other. The level of agreement was analysed using the prevalence adjusted bias adjusted kappa (PABAK). RESULTS: Overall, the agreement was high, with each ARV being in “almost perfect agreement”, using Landis and Koch’s categorisation. Highest discordance was observed for efavirenz (75/1301, 5.8 %), all arising from susceptible Stanford HIVdb versus non-susceptible vircoTYPETM HIV-1 predictions. Protease Inhibitors had highest level of concordance with PABAKs all above 0.99, followed by Nucleoside Reverse Transcriptase Inhibitors with PABAKs above 0.97 and non-NRTIs with the lowest PABAK of 0.88. The 68/75 patients with discordant efavirenz results harboured the V179D/E mutations compared to 7/1226 with no efavirenz discrepancy (p-value <0.001). In the 3-level comparison, all but one of the discrepancies was minor. CONCLUSIONS: The two systems agreed well with lowest concordance observed for efavirenz. When interpreting HIVDR, especially in non-B subtypes, clinical correlation is crucial, in particular when efavirenz resistance is interpreted based on V179D/E.
It is common to present multiple adjusted effect estimates from a single model in a single table. For example, a table might show odds ratios for one or more exposures and also for several confounders from a single logistic regression. This can lead to mistaken interpretations of these estimates. We use causal diagrams to display the sources of the problems. Presentation of exposure and confounder effect estimates from a single model may lead to several interpretative difficulties, inviting confusion of direct-effect estimates with total-effect estimates for covariates in the model. These effect estimates may also be confounded even though the effect estimate for the main exposure is not confounded. Interpretation of these effect estimates is further complicated by heterogeneity (variation, modification) of the exposure effect measure across covariate levels. We offer suggestions to limit potential misunderstandings when multiple effect estimates are presented, including precise distinction between total and direct effect measures from a single model, and use of multiple models tailored to yield total-effect estimates for covariates.
The effects of clinical-trial funding on the interpretation of trial results are poorly understood. We examined how such support affects physicians' reactions to trials with a high, medium, or low level of methodologic rigor.
The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.
Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support. The Human Behaviour-Change Project (HBCP) will use Artificial Intelligence and Machine Learning to (i) develop and evaluate a ‘Knowledge System’ that automatically extracts, synthesises and interprets findings from BCI evaluation reports to generate new insights about behaviour change and improve prediction of intervention effectiveness and (ii) allow users, such as practitioners, policy makers and researchers, to easily and efficiently query the system to get answers to variants of the question ‘What works, compared with what, how well, with what exposure, with what behaviours (for how long), for whom, in what settings and why?’.
Microwaves in the cold war: the Moscow embassy study and its interpretation. Review of a retrospective cohort study.
- Environmental health : a global access science source
- Published almost 8 years ago
BACKGROUND: From 1953 to 1976, beams of microwaves of 2.5 to 4.0 GHz were aimed at the US embassy building in Moscow. An extensive study investigated the health of embassy staff and their families, comparing Moscow embassy staff with staff in other Eastern European US embassies. The resulting large report has never been published in peer reviewed literature. METHODS: The original report and other published comments or extracts from the report were reviewed. RESULTS: The extensive study reports on mortality and morbidity, recorded on medical records and by regular examinations, and on self-reported symptoms. Exposure levels were low, but similar or greater than present-day exposures to radiofrequencies sources such as cell phone base stations. The conclusions were that no adverse health effects of the radiation were shown. The study validity depends on the assumption that staff at the other embassies were not exposed to similar radiofrequencies. This has been questioned, and other interpretations of the data have been presented. CONCLUSIONS: The conclusions of the original report are supported. Contrary conclusions given in some other reports are due to misinterpretation of the results.
Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used ‘functional connectivity fingerprints’ to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.
Objective: To assess the application of TeleCyP for real-time fine-needle aspiration interpretation (RFI) necessary for case management and specimen triage. Study Design: Twenty-two endobronchial ultrasound (EBUS)-guided mediastinal and pulmonary cases were included in the learning phase to determine the time and efficiency of TeleCyP. Slides were scanned by a cytopathology fellow in real time, and high-speed transmitted images over a secure network were interpreted by a cytopathologist while maintaining audio communication. In the validation phase, an additional 38 pancreas cases from endoscopic ultrasound (EUS) were evaluated recapitulating the RFI scenario from the learning phase. The cytopathologist was blinded to the results of the diagnosis in both phases. Results: The time to provide assessment of specimen adequacy and a preliminary diagnosis was 53 s in the learning phase and 49 s in the validation phase. There was 100% correlation between RFI and TeleCyP assessment for specimen adequacy. TeleCyP particularly posed challenges in providing definitive interpretation on EUS-fine-needle aspiration of some of the pancreatic solid masses (11%, 4/36). Conclusion: TeleCyP can serve as a powerful alternative, time-efficient strategy to provide RFI, and for specimen triaging which is critical for personalized medicine and patient management.
- International journal of sports physiology and performance
- Published almost 5 years ago
Recent studies have brought new insights into the evaluation of power-force-velocity profiles in both ballistic push-offs (e.g. jumps) and sprint movements. These are major physical components of performance in many sports, and the methods we developed and validated are based on data that are now rather simple to obtain in field conditions (e.g. body mass, jump height, sprint times or velocity). The promising aspect of these approaches is that they allow for a more individualized and accurate evaluation, monitoring, and training practices; the success of which are highly dependent on the correct collection, generation and interpretation of athletes' mechanical outputs. We therefore wanted to provide a practical vade mecum to sports practitioners interested in implementing these power-force-velocity profiling approaches. After providing a summary of theoretical and practical definitions for the main variables, we have first detailed how vertical profiling can be used to manage ballistic push-off performance with emphasis on the concept of optimal force-velocity profile and the associated force-velocity imbalance. Further, we have discussed these same concepts with regards to horizontal profiling in the management of sprinting performance. These sections have been illustrated by typical examples from our own practice. Finally, we have provided a practical and operational synthesis, and outlined future challenges that will help in further developing these approaches.