NIDDK data repository: a central collection of clinical trial data

Dug: a semantic search engine leveraging peer-reviewed knowledge to query biomedical data repositories

MOTIVATION

As the number of public data resources continues to proliferate, identifying relevant datasets across heterogenous repositories is becoming critical to answering scientific questions. To help researchers navigate this data landscape, we developed Dug: a semantic search tool for biomedical datasets utilizing evidence-based relationships from curated knowledge graphs to find relevant datasets and explain why those results are returned.

RESULTS

Developed through the National Heart, Lung and Blood Institute's (NHLBI) BioData Catalyst ecosystem, Dug has indexed more than 15 911 study variables from public datasets. On a manually curated search dataset, Dug's total recall (total relevant results/total results) of 0.79 outperformed default Elasticsearch's total recall of 0.76. When using synonyms or related concepts as search queries, Dug (0.36) far outperformed Elasticsearch (0.14) in terms of total recall with no significant loss in the precision of its top results.

AVAILABILITY AND IMPLEMENTATION

Dug is freely available at https://github.com/helxplatform/dug. An example Dug deployment is also available for use at https://search.biodatacatalyst.renci.org/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evaluating Community-Based Translational Interventions Using Historical Controls: Propensity Score vs. Disease Risk Score Approach

Many community-based translations of evidence-based interventions are designed as one-arm studies due to ethical and other considerations. Evaluating the impacts of such programs is challenging. Here, we examine the effectiveness of the lifestyle intervention implemented by the Special Diabetes Program for Indians Diabetes Prevention (SDPI-DP) demonstration project, a translational lifestyle intervention among American Indian and Alaska Native communities. Data from the landmark Diabetes Prevention Program placebo group was used as a historical control. We compared the use of propensity score (PS) and disease risk score (DRS) matching to adjust for potential confounder imbalance between groups. The unadjusted hazard ratio (HR) for diabetes risk was 0.35 for SDPI-DP lifestyle intervention vs. control. However, when relevant diabetes risk factors were considered, the adjusted HR estimates were attenuated toward 1, ranging from 0.56 (95% CI 0.44-0.71) to 0.69 (95% CI 0.56-0.96). The differences in estimated HRs using the PS and DRS approaches were relatively small but DRS matching resulted in more participants being matched and smaller standard errors of effect estimates. Carefully employed, publicly available randomized clinical trial data can be used as a historical control to evaluate the intervention effectiveness of one-arm community translational initiatives. It is critical to use a proper statistical method to balance the distributions of potential confounders between comparison groups in this kind of evaluations.

Analytic Considerations for Repeated Measures of eGFR in Cohort Studies of CKD

Repeated measures of various biomarkers provide opportunities for us to enhance understanding of many important clinical aspects of CKD, including patterns of disease progression, rates of kidney function decline under different risk factors, and the degree of heterogeneity in disease manifestations across patients. However, because of unique features, such as correlations across visits and time dependency, these data must be appropriately handled using longitudinal data analysis methods. We provide a general overview of the characteristics of data collected in cohort studies and compare appropriate statistical methods for the analysis of longitudinal exposures and outcomes. We use examples from the Chronic Renal Insufficiency Cohort Study to illustrate these methods. More specifically, we model longitudinal kidney outcomes over annual clinical visits and assess the association with both baseline and longitudinal risk factors.

UK publicly funded Clinical Trials Units supported a controlled access approach to share individual participant data but highlighted concerns

OBJECTIVES

Evaluate current data sharing activities of UK publicly funded Clinical Trial Units (CTUs) and identify good practices and barriers.

STUDY DESIGN AND SETTING

Web-based survey of Directors of 45 UK Clinical Research Collaboration (UKCRC)-registered CTUs.

RESULTS

Twenty-three (51%) CTUs responded: Five (22%) of these had an established data sharing policy and eight (35%) specifically requested consent to use patient data beyond the scope of the original trial. Fifteen (65%) CTUs had received requests for data, and seven (30%) had made external requests for data in the previous 12 months. CTUs supported the need for increased data sharing activities although concerns were raised about patient identification, misuse of data, and financial burden. Custodianship of clinical trial data and requirements for a CTU to align its policy to their parent institutes were also raised. No CTUs supported the use of an open access model for data sharing.

CONCLUSION

There is support within the publicly funded UKCRC-registered CTUs for data sharing, but many perceived barriers remain. CTUs are currently using a variety of approaches and procedures for sharing data. This survey has informed further work, including development of guidance for publicly funded CTUs, to promote good practice and facilitate data sharing.

Baseline characteristics predict risk of progression and response to combined medical therapy for benign prostatic hyperplasia (BPH)

OBJECTIVE

To better risk stratify patients, using baseline characteristics, to help optimise decision-making for men with moderate-to-severe lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH) through a secondary analysis of the Medical Therapy of Prostatic Symptoms (MTOPS) trial.

PATIENTS AND METHODS

After review of the literature, we identified potential baseline risk factors for BPH progression. Using bivariate tests in a secondary analysis of MTOPS data, we determined which variables retained prognostic significance. We then used these factors in Cox proportional hazard modelling to: i) more comprehensively risk stratify the study population based on pre-treatment parameters and ii) to determine which risk strata stood to benefit most from medical intervention.

RESULTS

In all, 3047 men were followed in MTOPS for a mean of 4.5 years. We found varying risks of progression across quartiles. Baseline BPH Impact Index score, post-void residual urine volume, serum prostate-specific antigen (PSA) level, age, American Urological Association Symptom Index score, and maximum urinary flow rate were found to significantly correlate with overall BPH progression in multivariable analysis.

CONCLUSIONS

Using baseline factors permits estimation of individual patient risk for clinical progression and the benefits of medical therapy. A novel clinical decision tool based on these analyses will allow clinicians to weigh patient-specific benefits against possible risks of adverse effects for a given patient.

'What's in the NIDDK CDR?'--public query tools for the NIDDK central data repository

The National Institute of Diabetes and Digestive Disease (NIDDK) Central Data Repository (CDR) is a web-enabled resource available to researchers and the general public. The CDR warehouses clinical data and study documentation from NIDDK funded research, including such landmark studies as The Diabetes Control and Complications Trial (DCCT, 1983–93) and the Epidemiology of Diabetes Interventions and Complications (EDIC, 1994–present) follow-up study which has been ongoing for more than 20 years. The CDR also houses data from over 7 million biospecimens representing 2 million subjects. To help users explore the vast amount of data stored in the NIDDK CDR, we developed a suite of search mechanisms called the public query tools (PQTs). Five individual tools are available to search data from multiple perspectives: study search, basic search, ontology search, variable summary and sample by condition. PQT enables users to search for information across studies. Users can search for data such as number of subjects, types of biospecimens and disease outcome variables without prior knowledge of the individual studies. This suite of tools will increase the use and maximize the value of the NIDDK data and biospecimen repositories as important resources for the research community.

Database URL:https://www.niddkrepository.org/niddk/home.do

IT Infrastructure Components for Biobanking

OBJECTIVE

Within translational research projects in the recent years large biobanks have been established, mostly supported by homegrown, proprietary software solutions. No general requirements for biobanking IT infrastructures have been published yet. This paper presents an exemplary biobanking IT architecture, a requirements specification for a biorepository management tool and exemplary illustrations of three major types of requirements.

METHODS

We have pursued a comprehensive literature review for biobanking IT solutions and established an interdisciplinary expert panel for creating the requirements specification. The exemplary illustrations were derived from a requirements analysis within two university hospitals.

RESULTS

The requirements specification comprises a catalog with more than 130 detailed requirements grouped into 3 major categories and 20 subcategories. Special attention is given to multitenancy capabilities in order to support the project-specific definition of varying research and bio-banking contexts, the definition of workflows to track sample processing, sample transportation and sample storage and the automated integration of preanalytic handling and storage robots.

CONCLUSION

IT support for biobanking projects can be based on a federated architectural framework comprising primary data sources for clinical annotations, a pseudonymization service, a clinical data warehouse with a flexible and user-friendly query interface and a biorepository management system. Flexibility and scalability of all such components are vital since large medical facilities such as university hospitals will have to support biobanking for varying monocentric and multicentric research scenarios and multiple medical clients.

Weight loss of black, white, and Hispanic men and women in the Diabetes Prevention Program

OBJECTIVE

To provide the specific weight loss outcomes for African-American, Hispanic, and white men and women in the lifestyle and metformin treatment arms of the Diabetes Prevention Program (DPP) by race-gender group to facilitate researchers translating similar interventions to minority populations, as well as provide realistic weight loss expectations for clinicians.

METHODS AND PROCEDURES

Secondary analyses of weight loss of 2,921 overweight participants (22% black; 17% Hispanic; 61% white; and 68% women) with impaired glucose tolerance randomized in the DPP to intensive lifestyle modification, metformin or placebo. Data over a 30-month period are examined for comparability across treatment arms by race and gender.

RESULTS

Within lifestyle treatment, all race-gender groups lost comparable amounts of weight with the exception of black women who exhibited significantly smaller weight losses (P < 0.01). For example, at 12 months, weight losses for white men (-8.4%), white women (-8.1%), Hispanic men (-7.8%), Hispanic women (-7.1%), and black men (-7.1%) were similar and significantly higher than black women (-4.5%). In contrast, within metformin treatment, all race-gender groups including black women lost similar amounts of weight. Race-gender specific mean weight loss data are provided by treatment arm for each follow-up period.

DISCUSSION

Diminished weight losses were apparent among black women in comparison with other race-gender groups in a lifestyle intervention but not metformin, underscoring the critical nature of examining sociocultural and environmental contributors to successful lifestyle intervention for black women.