Project description:The Genetic Association Information Network (GAIN) Data Access Committee was established in June 2007 to provide prompt and fair access to data from six genome-wide association studies through the database of Genotypes and Phenotypes (dbGaP). Of 945 project requests received through 2011, 749 (79%) have been approved; median receipt-to-approval time decreased from 14 days in 2007 to 8 days in 2011. Over half (54%) of the proposed research uses were for GAIN-specific phenotypes; other uses were for method development (26%) and adding controls to other studies (17%). Eight data-management incidents, defined as compromises of any of the data-use conditions, occurred among nine approved users; most were procedural violations, and none violated participant confidentiality. Over 5 years of experience with GAIN data access has demonstrated substantial use of GAIN data by investigators from academic, nonprofit, and for-profit institutions with relatively few and contained policy violations. The availability of GAIN data has allowed for advances in both the understanding of the genetic underpinnings of mental-health disorders, diabetes, and psoriasis and the development and refinement of statistical methods for identifying genetic and environmental factors related to complex common diseases.
Project description:<h4>Background</h4>Ascertainment of cases and disease classification is an acknowledged problem for epidemiological research into haematological malignancies.<h4>Methods</h4>The Haematological Malignancy Research Network comprises an ongoing population-based patient cohort. All diagnoses (paediatric and adult) across two UK Cancer Networks (population 3.6 million, >2000 diagnoses annually, socio-demographically representative of the UK) are made by an integrated haematopathology laboratory. Diagnostics, prognostics, and treatment are recorded to clinical trial standards, and socio-demographic measures are routinely obtained.<h4>Results</h4>A total of 10,729 haematological malignancies (myeloid=2706, lymphoid=8023) were diagnosed over the 5 years, that is, from 2004 to 2009. Descriptive data (age, sex, and deprivation), sex-specific age-standardised (European population) rates, and estimated UK frequencies are presented for 24 sub-types. The age of patients ranged from 4 weeks to 99 years (median 70.6 years), and the male rate was more than double the female rate for several myeloid and lymphoid sub-types, this difference being evident in both children and adults. No relationship with deprivation was detected.<h4>Conclusion</h4>Accurate population-based data on haematological malignancies can be collected to the standard required to deliver reproducible results that can be extrapolated to national populations. Our analyses emphasise the importance of gender and age as disease determinants, and suggest that aetiological investigations that focus on socio-economic factors are unlikely to be rewarding.
Project description:Development assistance for health (DAH) is an important part of financing healthcare in low- and middle-income countries. We estimated the gross disbursement of DAH of the 29 Development Assistance Committee (DAC) member countries of the Organisation for Economic Co-operation and Development (OECD) for 2011-2019; and clarified its flows, including aid type, channel, target region, and target health focus area. Data from the OECD iLibrary were used. The DAH definition was based on the OECD sector classification. For core funding to non-health-specific multilateral agencies, we estimated DAH and its flows based on the OECD methodology for calculating imputed multilateral official development assistance (ODA). The total amount of DAH for all countries combined was 18.5 billion USD in 2019, at 17.4 USD per capita, with the 2011-2019 average of 19.7 billion USD. The average share of DAH in ODA for the 29 countries was about 7.9% in 2019. Between 2011 and 2019, most DAC countries allocated approximately 60% of their DAH to primary health care, with the remaining 40% allocated to health system strengthening. We expect that the estimates of this study will help DAC member countries strategize future DAH wisely, efficiently, and effectively while ensuring transparency.
Project description:Based on the profile of genetic alterations occurring in tumor samples from selected diffuse large B-cell lymphoma (DLBCL) patients, 2 recent whole-exome sequencing studies proposed partially overlapping classification systems. Using clustering techniques applied to targeted sequencing data derived from a large unselected population-based patient cohort with full clinical follow-up (n = 928), we investigated whether molecular subtypes can be robustly identified using methods potentially applicable in routine clinical practice. DNA extracted from DLBCL tumors diagnosed in patients residing in a catchment population of ∼4 million (14 centers) were sequenced with a targeted 293-gene hematological-malignancy panel. Bernoulli mixture-model clustering was applied and the resulting subtypes analyzed in relation to their clinical characteristics and outcomes. Five molecular subtypes were resolved, termed MYD88, BCL2, SOCS1/SGK1, TET2/SGK1, and NOTCH2, along with an unclassified group. The subtypes characterized by genetic alterations of BCL2, NOTCH2, and MYD88 recapitulated recent studies showing good, intermediate, and poor prognosis, respectively. The SOCS1/SGK1 subtype showed biological overlap with primary mediastinal B-cell lymphoma and conferred excellent prognosis. Although not identified as a distinct cluster, NOTCH1 mutation was associated with poor prognosis. The impact of TP53 mutation varied with genomic subtypes, conferring no effect in the NOTCH2 subtype and poor prognosis in the MYD88 subtype. Our findings confirm the existence of molecular subtypes of DLBCL, providing evidence that genomic tests have prognostic significance in non-selected DLBCL patients. The identification of both good and poor risk subtypes in patients treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) clearly show the clinical value of the approach, confirming the need for a consensus classification.
Project description:The review of human participant research by Research Ethics Committees (RECs) or Institutional Review Boards (IRBs) is a complex multi-faceted process that cannot be reduced to an algorithm. However, this does not give RECs/ IRBs permission to be inconsistent in their specific requirements to researchers or in their final opinions. In England the Health Research Authority (HRA) coordinates 67 committees, and has adopted a consistency improvement plan including a process called "Shared Ethical Debate" (ShED) where multiple committees review the same project. Committee reviews are compared for consistency by analysing the resulting minutes.We present a description of the ShED process. We report an analysis of minutes created by research ethics committees participating in two ShED exercises, and compare them to minutes produced in a published "mystery shopper" exercise. We propose a consistency score by defining top themes for each exercise, and calculating the ratio between top themes and total themes identified by each committee for each ShED exercise.Our analysis highlights qualitative differences between the ShED 19, ShED 20 and "mystery shopper" exercises. The quantitative measure of consistency showed only one committee across the three exercises with more than half its total themes as top themes (ratio of 0.6). The average consistency scores for the three exercises were 0.23 (ShED19), 0.35 (ShED20) and 0.32 (mystery shopper). There is a statistically significant difference between the ShED 19 exercise, and the ShED 20 and mystery shopper exercises.ShED exercises are effective in identifying inconsistency between ethics committees and we describe a scoring method that could be used to quantify this. However, whilst a level of inconsistency is probably inevitable in research ethics committee reviews, studies must move beyond the ShED methodology to understand why inconsistency occurs, and what an acceptable level of inconsistency might be.
Project description:The database of Genotypes and Phenotypes (dbGaP) Data Browser (https://www.ncbi.nlm.nih.gov/gap/ddb/) was developed in response to requests from the scientific community for a resource that enable view-only access to summary-level information and individual-level genotype and sequence data associated with phenotypic features maintained in the controlled-access tier of dbGaP. Until now, the dbGaP controlled-access environment required investigators to submit a data access request, wait for Data Access Committee review, download each data set and locally examine them for potentially relevant information. Existing unrestricted-access genomic data browsing resources (e.g. http://evs.gs.washington.edu/EVS/, http://exac.broadinstitute.org/) provide only summary statistics or aggregate allele frequencies. The dbGaP Data Browser serves as a third solution, providing researchers with view-only access to a compilation of individual-level data from general research use (GRU) studies through a simplified controlled-access process. The National Institutes of Health (NIH) will continue to improve the Browser in response to user feedback and believes that this tool may decrease unnecessary download requests, while still facilitating responsible genomic data-sharing.
Project description:<b>Background</b>: Official development assistance (ODA) is one of the most important means for donor countries to foster diplomatic relations with low- and middle-income countries and contribute to the welfare of the international community.<b>Objective</b>: This study estimated the sectoral allocation of gross disbursements of ODA of the 29 Development Assistance Committee (DAC) member countries of the Organisation for Economic Co-operation and Development (OECD) for the duration of 2011 to 2018, by aid type (bilateral, multilateral, and both aids).<b>Methods</b>: Data from the OECD iLibrary were used. The sector definition was based on the OECD sector classification. For core funding to multilateral agencies that do not specialize in each aid sector, we estimated ODA and its flows based on the OECD methodology for calculating imputed multilateral ODA.<b>Results</b>: For all 29 countries, during the period of 2014-2018 where data were available for all the countries, the sector with the highest average annual ODA contribution was health at 20.34 billion USD (13.21%), followed by humanitarian aid at 18.04 billion (11.72%). Humanitarian aid has increased in the sectoral share rankings in both bilateral and multilateral aid, and the sectoral share for refugees in donor countries has increased in bilateral aid. While the 29 countries show relatively similar trends for sectoral shares, some countries and sectors display unique trends. For instance, infrastructure and energy sectors in bilateral aid of Japan are particularly high accounts for 48.48% of the total bilateral ODA of the country in 2018.<b>Conclusions</b>: This paper evaluated ODA trends by major donors of DAC countries in the pre-COVID-19 pandemic periods. We hope that our estimates will contribute to the review of the strategic decision-making and the effective implementation of future ODA policy discussions in the DAC countries while ensuring transparency.
Project description:BACKGROUND:Translational researchers need robust IT solutions to access a range of data types, varying from public data sets to pseudonymised patient information with restricted access, provided on a case by case basis. The reason for this complication is that managing access policies to sensitive human data must consider issues of data confidentiality, identifiability, extent of consent, and data usage agreements. All these ethical, social and legal aspects must be incorporated into a differential management of restricted access to sensitive data. METHODS:In this paper we present a pilot system that uses several common open source software components in a novel combination to coordinate access to heterogeneous biomedical data repositories containing open data (open access) as well as sensitive data (restricted access) in the domain of biobanking and biosample research. Our approach is based on a digital identity federation and software to manage resource access entitlements. RESULTS:Open source software components were assembled and configured in such a way that they allow for different ways of restricted access according to the protection needs of the data. We have tested the resulting pilot infrastructure and assessed its performance, feasibility and reproducibility. CONCLUSIONS:Common open source software components are sufficient to allow for the creation of a secure system for differential access to sensitive data. The implementation of this system is exemplary for researchers facing similar requirements for restricted access data. Here we report experience and lessons learnt of our pilot implementation, which may be useful for similar use cases. Furthermore, we discuss possible extensions for more complex scenarios.