Transforming epidemiology for 21st century medicine and public health

Sharing Medical Big Data While Preserving Patient Confidentiality in Innovative Medicines Initiative: A Summary and Case Report from BigData@Heart

Sharing individual patient data (IPD) is a simple concept but complex to achieve due to data privacy and data security concerns, underdeveloped guidelines, and legal barriers. Sharing IPD is additionally difficult in big data-driven collaborations such as Bigdata@Heart in the Innovative Medicines Initiative, due to competing interests between diverse consortium members. One project within BigData@Heart, case study 1, needed to pool data from seven heterogeneous data sets: five randomized controlled trials from three different industry partners, and two disease registries. Sharing IPD was not considered feasible due to legal requirements and the sensitive medical nature of these data. In addition, harmonizing the data sets for a federated data analysis was difficult due to capacity constraints and the heterogeneity of the data sets. An alternative option was to share summary statistics through contingency tables. Here it is demonstrated that this method along with anonymization methods to ensure patient anonymity had minimal loss of information. Although sharing IPD should continue to be encouraged and strived for, our approach achieved a good balance between data transparency while protecting patient privacy. It also allowed a successful collaboration between industry and academia.

Moving Toward Findable, Accessible, Interoperable, Reusable Practices in Epidemiologic Research

Data sharing is essential for reproducibility of epidemiologic research, replication of findings, pooled analyses in consortia efforts, and maximizing study value to address multiple research questions. However, barriers related to confidentiality, costs, and incentives often limit the extent and speed of data sharing. Epidemiological practices that follow Findable, Accessible, Interoperable, Reusable (FAIR) principles can address these barriers by making data resources findable with the necessary metadata, accessible to authorized users, and interoperable with other data, to optimize the reuse of resources with appropriate credit to its creators. We provide an overview of these principles and describe approaches for implementation in epidemiology. Increasing degrees of FAIRness can be achieved by moving data and code from on-site locations to remote, accessible ("Cloud") data servers, using machine-readable and nonproprietary files, and developing open-source code. Adoption of these practices will improve daily work and collaborative analyses and facilitate compliance with data sharing policies from funders and scientific journals. Achieving a high degree of FAIRness will require funding, training, organizational support, recognition, and incentives for sharing research resources, both data and code. However, these costs are outweighed by the benefits of making research more reproducible, impactful, and equitable by facilitating the reuse of precious research resources by the scientific community.

Digital Connectedness in the Jackson Heart Study: Cross-sectional Study

Background

Although new approaches for data collection, such as mobile technology and teleresearch, have demonstrated new opportunities for the conduct of more timely and less costly surveys in community-based studies, literature on the feasibility of conducing cardiovascular disease research using mobile health (mHealth) platforms among middle-aged and older African Americans has been limited.

Objective

The purpose of this study was to contribute to the knowledge regarding the penetrance of internet and mobile technologies, such as cellphones or smartphones in existing large cohort studies of cardiovascular disease.

Methods

A digital connectedness survey was conducted in the Jackson Heart Study (JHS), a Mississippi-based African American cohort study, as part of the annual follow-up calls with participants from July 2017 to February 2019.

Results

Of the 4024 participants contacted, 2564 (63.7%) completed the survey. Among survey respondents, 2262 (88.2%) reported use of internet or cellphone, and 1593 (62.1%) had a smartphone. Compared to nonusers (n=302), internet or cellphone users (n=2262) were younger (mean age 80.1, SD 8.0 vs 68.2, SD 11.3 years), more likely to be affluent (n=778, 40.1% vs n=39, 15.4%), and had greater than high school education (n=1636, 72.5% vs n=85, 28.1%). Internet or cellphone users were less likely to have cardiovascular disease history compared to nonusers (136/2262, 6.6% vs 41/302, 15.8%). The prevalence of current smoking and average BMI were similar between internet or cellphone users and nonusers. Among internet or cellphone users, 1316 (58.3%) reported use of email, 504 (22.3%) reported use of apps to track or manage health, and 1269 (56.1%) expressed interest in using JHS-developed apps.

Conclusions

Our findings suggest that it is feasible to use mHealth technologies to collect survey data among African Americans already enrolled in a longitudinal study. Our findings also highlight the need for more efforts to reduce the age and education divide in access and use of internet and smartphones for tracking health and research in African American communities.

Centralizing environmental datasets to support (inter)national chronic disease research: Values, challenges, and recommendations

Whereas environmental data are increasingly available, it is often not clear how or if datasets are available for health research. Exposure metrics are typically developed for specific research initiatives using disparate exposure assessment methods and no mechanisms are put in place for centralizing, archiving, or distributing environmental datasets. In parallel, potentially vast amounts of environmental data are emerging due to new technologies such as high resolution imagery and machine learning.

Funding of Hispanic/Latino Health-Related Research by the National Institutes of Health: An Analysis of the Portfolio of Research Program Grants on Six Health Topic Areas

Hispanics/Latinos are expected to constitute 25% of the U.S. population by 2060. Differences in the prevalence of health risk factors, chronic diseases, and access to and utilization of health-care services between Hispanics/Latinos and other populations in the U.S. have been documented. This study aimed to describe and analyze the landscape of Research Program Grants (RPGs) funded by the National Institutes of Health (NIH) between 2008 and 2015 involving Hispanic/Latino health research in six health condition areas-asthma, cancer, dementia, diabetes, liver/gallbladder disease, and obesity-and to identify opportunities for continued research in these areas. Using an NIH internal search engine, we identified new and renewal Hispanic/Latino health RPGs searching for specific Hispanic/Latino identifiers in the Title, Abstract, and Specific Aims. We used descriptive statistics to examine the distribution of funded RPGs by NIH disease-based classification codes for the six health condition areas of interest, and other selected characteristics. The most prominent clusters of research subtopics were identified within each health condition area, and performance sites were mapped at the city level. Within the selected time frame, 3,221 Hispanic/Latino health-related unique RPGs were funded (constituting 4.4% of all funded RPGs), and of those 625 RPGs were eligible for review and coding in the present study. Cancer and obesity were the most commonly studied health condition areas (72%), while studies on mechanisms of disease-biological and non-biological-(72.6%), behavioral research (42.1%) and epidemiological studies (38.1%) were the most common types of research. Most of the primary performance sites were in California, Texas, the northeastern U.S., and Illinois. The predominance of mechanistic, behavioral, and epidemiological studies in our analysis poses opportunities to evaluate knowledge gained and their clinical application, explore new research questions, or to update some methods or instruments. The findings of the present study suggest opportunities to expand research in understudied mechanisms of disease that could explain differences in prevalence of conditions like diabetes and cancer among different heritage groups. In addition, our findings suggest that the impact of interventions or policies designed to reduce health disparities, innovative multi-level interventions, implementation and dissemination studies, the role of health information technology on health outcomes, and the intersectionality of individual, sociocultural, geographic, and other factors on health outcomes, among others, are understudied approaches, which could potentially advance research in Hispanic/Latino health and contribute to the achievement of better health outcomes in this diverse population.

Demand for Health Information on COVID-19 among Vietnamese

Due to the rapid spread of coronavirus, Vietnam introduced its first national partial lockdown on April 1st, 2020. The public relied on online sources, whether through official websites or phone-based applications, to acquire up-to-date health information, provide accurate instructions, and limit misinformation. This study aims to provide insight regarding the current level of awareness of the pandemic, and to identify associated factors in Vietnamese participants to recommend necessary interventions. A cross-sectional study was conducted using a web-based survey during the first week of the lockdown period. There were 341 observations collected using a snowball sampling technique. A Tobit multivariable regression model was used to identify factors associated with the demand for each category of health information. The most requested information was the latest updated news on the epidemic, followed by information about disease symptoms and updated news on the outbreak. The prevalence of diverse socioeconomic, demographic, and ethnic factors in Vietnam requires consideration of the specific health information needs of unique groups. Identifying group-specific demands would be helpful to provide proper information to fulfill each population group’s needs.

The Population Health OutcomEs aNd Information EXchange (PHOENIX) Program - A Transformative Approach to Reduce the Burden of Chronic Disease

This concept article introduces a transformative vision to reduce the population burden of chronic disease by focusing on data integration, analytics, implementation and community engagement. Known as PHOENIX (The Population Health OutcomEs aNd Information EXchange), the approach leverages a state level health information exchange and multiple other resources to facilitate the integration of clinical and social determinants of health data with a goal of achieving true population health monitoring and management. After reviewing historical context, we describe how multilevel and multimodal data can be used to facilitate core public health services, before discussing the controversies and challenges that lie ahead.

Dietary preferences and diabetic risk in China: A large-scale nationwide Internet data-based study

BACKGROUND

Unhealthy diet is one of the important risk factors of diabetes, which is one of the major public health problems in China. The Internet tools provide large-scale passively collected data that show people's dietary preferences and their relationship with diabetes risk.

METHODS

212 341 708 individuals' dietary preference labels were created based on Internet data from online search and shopping software. Metabolic data obtained from the 2010 China Noncommunicable Disease Surveillance, which had 98 658 participants, was used to estimate the relation between dietary preferences geographical distribution and diabetes risk.

RESULTS

Chinese dietary preferences had different geographical distribution, which is related to the local climate and consumption level. Fried food preference proportion distribution was significantly positively correlated with diabetes prevalence, hypertension prevalence and body mass index (BMI). Similarly, grilled food preference proportion distribution had significantly positive correlation with the prevalence of diabetes and hypertension. In contrast, spicy food preference proportion distribution was negatively correlated with diabetes prevalence. Sweet food preference proportion distribution was positively related to diabetes prevalence. Using dietary preferences data to predict regional prevalence of diabetes, hypertension and BMI, the average values of error (95% CI) between the three paired predicted and observed values were 9.8% (6.9%-12.7%), 7.5% (5.0%-10.0%) and 1.6% (1.2%-2.0%), respectively.

CONCLUSIONS

Fried food, grilled food, and sweet food preferences were positively related to diabetes risk whereas spicy food preference was negatively correlated with diabetes risk. Dietary preferences based on passively collected Internet data could be used to predict regional prevalence of diabetes, hypertension, and BMI and showed good value for public health monitoring.

Field Application of Digital Technologies for Health Assessment in the 10,000 Families Study

BACKGROUND

We field tested new-to-market portable, digital applications to assess hearing, pulmonary, and cognitive function to determine the feasibility of implementing these applications across a range of age groups in the pilot phase of the 10,000 Families Study (10KFS), a new Minnesota family-based prospective cohort study.

METHODS

We followed manufacturer recommended protocols for audiometry (SHOEBOX Inc), spirometry (NuvoAir), and the digital clock drawing test (dCDT; Digital Cognition Technologies Inc).

RESULTS

These digital devices were low cost and readily implemented in a 2.5-hour health fair visit with minimal training (2-3 hours) of study staff. To date, we have performed these measurements on 197 eligible 10KFS participants during an in-person clinic visit. A total of 37 children (age 4-17 years), 107 adults (18-64 years), and 53 seniors (≥65 years) were eligible to undergo hearing and pulmonary assessments. Children were less likely to successfully complete the hearing test (76%) compared with adults (86%) and seniors (89%). However, successful completion of the pulmonary assessment was high across all groups: 100% of children and seniors and 98% of adults. The dCDT was performed among those over the age of 40, and completion rates were 92% for those aged 41-64 and 94% for those ≥65 years.

CONCLUSIONS

Our field testing indicates these digital applications are easy and cost-effective to implement in epidemiologic studies.

IMPACT

Digital applications provide exciting opportunities to collect data in population studies. Issues related to data privacy, data access, and reproducibility of measurements need to be addressed before deploying digital applications in epidemiologic studies.See all articles in this CEBP Focus section, "Modernizing Population Science."

Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study

BACKGROUND

Large-scale cancer epidemiology cohorts (CEC) have successfully collected, analyzed, and shared patient-reported data for years. CECs increasingly need to make their data more findable, accessible, interoperable, and reusable, or FAIR. How CECs should approach this transformation is unclear.

METHODS

The California Teachers Study (CTS) is an observational CEC of 133,477 participants followed since 1995-1996. In 2014, we began updating our data storage, management, analysis, and sharing strategy. With the San Diego Supercomputer Center, we deployed a new infrastructure based on a data warehouse to integrate and manage data and a secure and shared workspace with documentation, software, and analytic tools that facilitate collaboration and accelerate analyses.

RESULTS

Our new CTS infrastructure includes a data warehouse and data marts, which are focused subsets from the data warehouse designed for efficiency. The secure CTS workspace utilizes a remote desktop service that operates within a Health Insurance Portability and Accountability Act (HIPAA)- and Federal Information Security Management Act (FISMA)-compliant platform. Our infrastructure offers broad access to CTS data, includes statistical analysis and data visualization software and tools, flexibly manages other key data activities (e.g., cleaning, updates, and data sharing), and will continue to evolve to advance FAIR principles.

CONCLUSIONS

Our scalable infrastructure provides the security, authorization, data model, metadata, and analytic tools needed to manage, share, and analyze CTS data in ways that are consistent with the NCI's Cancer Research Data Commons Framework.

IMPACT

The CTS's implementation of new infrastructure in an ongoing CEC demonstrates how population sciences can explore and embrace new cloud-based and analytics infrastructure to accelerate cancer research and translation.See all articles in this CEBP Focus section, "Modernizing Population Science."

Bridging the epidemiology-policy divide: A consequential and evidence-based framework to optimize population health

Epidemiology is the scientific cornerstone of public health. Its traditional role has been to test scientific hypotheses on causal relationships of exposures with health outcomes, the results of which should in turn be synthesized and lead to evidence-based recommendations and the formation of policy. However, the messy truth is that the path from epidemiology to policy is frequently not a perfectly rational, linear one, and the choices of which scientific hypotheses are pursued and the ways in which they are tested, evaluated, and translated into policies do not occur systematically. One avenue for bridging this divide is widespread adoption and implementation of a consequential, evidence-based framework-whereby we can systematically facilitate the translation of epidemiology into policies and interventions to optimize population health. This paper describes the roadmap for a seven-step, outcomes-based consequential approach, that includes priority-setting of problems at both the federal and regional/state levels, and that proposes to strengthen alignment of public and private research funding and journals with these priorities. Over the long term, implementing this framework should help to bridge the divide between epidemiology and policy and optimize the use of increasingly constrained resources to reduce disease burden and promote the nation's health.

Training the Twenty-First Century Cancer Epidemiologist

To assess and advance training of twenty-first century cancer epidemiologists, the National Cancer Institute (NCI) sought to obtain a snapshot of the cancer epidemiology training landscape by conducting a survey across academic institutions and cancer centers, focusing on four key training areas driving current cancer epidemiology research ("drivers"): (1) collaboration, (2) novel methods/technologies, (3) multilevel analysis, and (4) knowledge integration. Complementary to the survey, we conducted a portfolio analysis of active NCI-funded training grants. In the present report, we provide our findings from this effort and contribute to the on-going conversation regarding the training of next-generation cancer epidemiologists. Analyses and insights gained from conversations with leaders/educators across 24 academic institutions/cancer centers and the portfolio analysis of training grants echoed contemporaneous conversation that cancer epidemiology training must adapt to meet the needs of the changing research environment. Currently, with the exception of novel methods/technologies, cancer epidemiology trainees receive the majority of their training in collaboration, multilevel approaches, and knowledge integration/translation either informally, ad hoc, or not at all; exposure to these identified drivers varied considerably by institution, mentor, and other external as well as internal factors.

Comparison of On-Site Versus Remote Mobile Device Support in the Framingham Heart Study Using the Health eHeart Study for Digital Follow-up: Randomized Pilot Study Set Within an Observational Study Design

Background

New electronic cohort (e-Cohort) study designs provide resource-effective methods for collecting participant data. It is unclear if implementing an e-Cohort study without direct, in-person participant contact can achieve successful participation rates.

Objective

The objective of this study was to compare 2 distinct enrollment methods for setting up mobile health (mHealth) devices and to assess the ongoing adherence to device use in an e-Cohort pilot study.

Methods

We coenrolled participants from the Framingham Heart Study (FHS) into the FHS–Health eHeart (HeH) pilot study, a digital cohort with infrastructure for collecting mHealth data. FHS participants who had an email address and smartphone were randomized to our FHS-HeH pilot study into 1 of 2 study arms: remote versus on-site support. We oversampled older adults (age ≥65 years), with a target of enrolling 20% of our sample as older adults. In the remote arm, participants received an email containing a link to enrollment website and, upon enrollment, were sent 4 smartphone-connectable sensor devices. Participants in the on-site arm were invited to visit an in-person FHS facility and were provided in-person support for enrollment and connecting the devices. Device data were tracked for at least 5 months.

Results

Compared with the individuals who declined, individuals who consented to our pilot study (on-site, n=101; remote, n=93) were more likely to be women, highly educated, and younger. In the on-site arm, the connection and initial use of devices was ≥20% higher than the remote arm (mean percent difference was 25% [95% CI 17-35] for activity monitor, 22% [95% CI 12-32] for blood pressure cuff, 20% [95% CI 10-30] for scale, and 43% [95% CI 30-55] for electrocardiogram), with device connection rates in the on-site arm of 99%, 95%, 95%, and 84%. Once connected, continued device use over the 5-month study period was similar between the study arms.

Conclusions

Our pilot study demonstrated that the deployment of mobile devices among middle-aged and older adults in the context of an on-site clinic visit was associated with higher initial rates of device use as compared with offering only remote support. Once connected, the device use was similar in both groups.

Child Health CheckPoint: cohort summary and methodology of a physical health and biospecimen module for the Longitudinal Study of Australian Children

OBJECTIVES

'Growing Up in Australia: The Longitudinal Study of Australian Children' (LSAC) is Australia's only nationally representative children's longitudinal study, focusing on social, economic, physical and cultural impacts on health, learning, social and cognitive development. LSAC's first decade collected wide-ranging repeated psychosocial and administrative data; here, we describe the Child Health CheckPoint, LSAC's dedicated biophysical module.

DESIGN, SETTING AND PARTICIPANTS

LSAC recruited a cross-sequential sample of 5107 infants aged 0-1 year and a sample of 4983 children aged 4-5 years in 2004, since completing seven biennial visits. CheckPoint was a cross-sectional wave that travelled Australia in 2015-2016 to reach LSAC's younger cohort at ages 11-12 years between LSAC waves 6 and 7. Parent-child pairs participated in comprehensive assessments at 15 Assessment Centres nationwide or, if unable to attend, a shorter home visit.

MEASURES

CheckPoint's intergenerational, multidimensional measures were prioritised to show meaningful variation within normal ranges and capture non-communicable disease (NCD) phenotype precursors. These included anthropometry, physical activity, fitness, time use, vision, hearing, and cardiovascular, respiratory and bone health. Biospecimens included blood, saliva, buccal swabs (also from second parent), urine, hair and toenails. The epidemiology and parent-child concordance of many measures are described in separate papers.

RESULTS

1874 (54% of eligible) parent-child pairs and 1051 second parents participated. Participants' geographical distribution mirrored the broader Australian population; however, mean socioeconomic position and parental education were higher and fewer reported non-English-speaking or Indigenous backgrounds. Application of survey weights partially mitigates that the achieved sample is less population representative than previous waves of LSAC due to non-random attrition. Completeness was uniformly high for phenotypic data (>92% of eligible), biospecimens (74%-97%) and consent (genetic analyses 98%, accessing neonatal blood spots 97%, sharing 96%).

CONCLUSIONS

CheckPoint enriches LSAC to study how NCDs develop at the molecular and phenotypic levels before overt disease emerges, and clarify the underlying dimensionality of health in childhood and mid-adulthood.

Design and Preliminary Findings From a New Electronic Cohort Embedded in the Framingham Heart Study

Background

New models of scalable population-based data collection that integrate digital and mobile health (mHealth) data are necessary.

Objective

The aim of this study was to describe a cardiovascular digital and mHealth electronic cohort (e-cohort) embedded in a traditional longitudinal cohort study, the Framingham Heart Study (FHS).

Methods

We invited eligible and consenting FHS Generation 3 and Omni participants to download the electronic Framingham Heart Study (eFHS) app onto their mobile phones and co-deployed a digital blood pressure (BP) cuff. Thereafter, participants were also offered a smartwatch (Apple Watch). Participants are invited to complete surveys through the eFHS app, to perform weekly BP measurements, and to wear the smartwatch daily.

Results

Up to July 2017, we enrolled 790 eFHS participants, representing 76% (790/1044) of potentially eligible FHS participants. eFHS participants were, on average, 53±8 years of age and 57% were women. A total of 85% (675/790) of eFHS participants completed all of the baseline survey and 59% (470/790) completed the 3-month survey. A total of 42% (241/573) and 76% (306/405) of eFHS participants adhered to weekly digital BP and heart rate (HR) uploads, respectively, over 12 weeks.

Conclusions

We have designed an e-cohort focused on identifying novel cardiovascular disease risk factors using a new smartphone app, a digital BP cuff, and a smartwatch. Despite minimal training and support, preliminary findings over a 3-month follow-up period show that uptake is high and adherence to periodic app-based surveys, weekly digital BP assessments, and smartwatch HR measures is acceptable.

New Directions in Cancer Control and Population Sciences

Cancer control science has been evolving since it first became a focus for cancer research and program activities a century ago. The evolution of the field has responded to historical megatrends along the way that keep it relevant to the cancer-related needs of society. This commentary describes some of the key trends and developments now influencing cancer control and population sciences that reflect societal change and new tools and concepts in modern biomedical science. New directions include the impact of climate change, health care delivery research, the growth of population health science, data science, precision medicine, data sharing, implementation science, and new technologies, including social media and new geospatial methodologies. Cancer Epidemiol Biomarkers Prev; 26(8); 1165-9. ©2017 AACR.

Knowledge integration in One Health policy formulation, implementation and evaluation

The One Health concept covers the interrelationship between human, animal and environmental health and requires multistakeholder collaboration across many cultural, disciplinary, institutional and sectoral boundaries. Yet, the implementation of the One Health approach appears hampered by shortcomings in the global framework for health governance. Knowledge integration approaches, at all stages of policy development, could help to address these shortcomings. The identification of key objectives, the resolving of trade-offs and the creation of a common vision and a common direction can be supported by multicriteria analyses. Evidence-based decision-making and transformation of observations into narratives detailing how situations emerge and might unfold in the future can be achieved by systems thinking. Finally, transdisciplinary approaches can be used both to improve the effectiveness of existing systems and to develop novel networks for collective action. To strengthen One Health governance, we propose that knowledge integration becomes a key feature of all stages in the development of related policies. We suggest several ways in which such integration could be promoted.

Linking Data From Health Surveys and Electronic Health Records: A Demonstration Project in Two Chicago Health Center Clinics

Introduction

Monitoring and understanding population health requires conducting health-related surveys and surveillance. The objective of our study was to assess whether data from self-administered surveys could be collected electronically from patients in urban, primary-care, safety-net clinics and subsequently linked and compared with the same patients’ electronic health records (EHRs).

Methods

Data from self-administered surveys were collected electronically from a convenience sample of 527 patients at 2 Chicago health centers from September through November, 2014. Survey data were linked to EHRs.

Results

A total of 251 (47.6%) patients who completed the survey consented to having their responses linked to their EHRs. Consenting participants were older, more likely to report fair or poor health, and took longer to complete the survey than those who did not consent. For 8 of 18 categorical variables, overall percentage of agreement between survey data and EHR data exceeded 80% (sex, race/ethnicity, pneumococcal vaccination, self-reported body mass index [BMI], diabetes, high blood pressure, medication for high blood pressure, and hyperlipidemia), and of these, the level of agreement was good or excellent (κ ≥0.64) except for pneumococcal vaccination (κ = 0.40) and hyperlipidemia (κ = 0.47). Of 7 continuous variables, agreement was substantial for age and weight (concordance coefficients ≥0.95); however, with the exception of calculated survey BMI and EHR–BMI (concordance coefficient = 0.88), all other continuous variables had poor agreement.

Conclusions

Self-administered and web-based surveys can be completed in urban, primary-care, safety-net clinics and linked to EHRs. Linking survey and EHR data can enhance public health surveillance by validating self-reported data, completing gaps in patient data, and extending sample sizes obtained through current methods. This approach will require promoting and sustaining patient involvement.

Repeat: a framework to assess empirical reproducibility in biomedical research

BACKGROUND

The reproducibility of research is essential to rigorous science, yet significant concerns of the reliability and verifiability of biomedical research have been recently highlighted. Ongoing efforts across several domains of science and policy are working to clarify the fundamental characteristics of reproducibility and to enhance the transparency and accessibility of research.

METHODS

The aim of the proceeding work is to develop an assessment tool operationalizing key concepts of research transparency in the biomedical domain, specifically for secondary biomedical data research using electronic health record data. The tool (RepeAT) was developed through a multi-phase process that involved coding and extracting recommendations and practices for improving reproducibility from publications and reports across the biomedical and statistical sciences, field testing the instrument, and refining variables.

RESULTS

RepeAT includes 119 unique variables grouped into five categories (research design and aim, database and data collection methods, data mining and data cleaning, data analysis, data sharing and documentation). Preliminary results in manually processing 40 scientific manuscripts indicate components of the proposed framework with strong inter-rater reliability, as well as directions for further research and refinement of RepeAT.

CONCLUSIONS

The use of RepeAT may allow the biomedical community to have a better understanding of the current practices of research transparency and accessibility among principal investigators. Common adoption of RepeAT may improve reporting of research practices and the availability of research outputs. Additionally, use of RepeAT will facilitate comparisons of research transparency and accessibility across domains and institutions.

State of the evidence 2017: an update on the connection between breast cancer and the environment

BACKGROUND

In this review, we examine the continually expanding and increasingly compelling data linking radiation and various chemicals in our environment to the current high incidence of breast cancer. Singly and in combination, these toxicants may have contributed significantly to the increasing rates of breast cancer observed over the past several decades. Exposures early in development from gestation through adolescence and early adulthood are particularly of concern as they re-shape the program of genetic, epigenetic and physiological processes in the developing mammary system, leading to an increased risk for developing breast cancer. In the 8 years since we last published a comprehensive review of the relevant literature, hundreds of new papers have appeared supporting this link, and in this update, the evidence on this topic is more extensive and of better quality than that previously available.

CONCLUSION

Increasing evidence from epidemiological studies, as well as a better understanding of mechanisms linking toxicants with development of breast cancer, all reinforce the conclusion that exposures to these substances - many of which are found in common, everyday products and byproducts - may lead to increased risk of developing breast cancer. Moving forward, attention to methodological limitations, especially in relevant epidemiological and animal models, will need to be addressed to allow clearer and more direct connections to be evaluated.

Incorporating Data Citation in a Biomedical Repository: An Implementation Use Case

Research data is a dynamic and evolving entity and the ability to cite such data depends on recreating the same datasets utilized in the original research. Despite the availability of several existing technologies, most data repositories lack the necessary setup to recreate a point-in-time snapshot of data, let alone long-term sustainability of dynamic data without restoring an entire database. Through this project, we adopted a subset of the Research Data Alliance data citation working group recommendations to establish a robust informatics system supporting dynamic data and its use for reproducible research within our evolving clinical data repository. We implemented key recommendations: data versioning, times-stamping, query storing, query time-stamping, query PID, and data citation in one data repository, implemented entirely at the database level, and were able to successfully reproduce a previous dataset as it existed at a specific point-in-time using only the PID as provided in a citation.

New frontiers for environmental epidemiology in a changing world

BACKGROUND

In the next 25years, transformative changes, in particular the rapid pace of technological development and data availability, will require environmental epidemiologists to prioritize what should (rather than could) be done to most effectively improve population health.

OBJECTIVES

In this essay, we map out key driving forces that will shape environmental epidemiology in the next 25years. We also identify how the field should adapt to best take advantage of coming opportunities and prepare for challenges.

DISCUSSION

Future environmental epidemiologists will face a world shaped by longer lifespans but also larger burdens of chronic health conditions; shifting populations by region and into urban areas; and global environmental change. Rapidly evolving technologies, particularly in sensors and OMICs, will present opportunities for the field. How should it respond? We argue, the field best adapts to a changing world by focusing on healthy aging; evidence gaps, especially in susceptible populations and low-income countries; and by developing approaches to better handle complexity and more formalized analysis.

CONCLUSIONS

Environmental epidemiology informing disease prevention will continue to be valuable. However, the field must adapt to remain relevant. In particular, the field must ensure that public health importance drives research questions, while seizing the opportunities presented by new technologies. Environmental epidemiologists of the future will require different, refined skills to work effectively across disciplines, ask the right questions, and implement appropriate study designs in a data-rich world.

Phylodynamic applications in 21st century global infectious disease research

BACKGROUND

Phylodynamics, the study of the interaction between epidemiological and pathogen evolutionary processes within and among populations, was originally defined in the context of rapidly evolving viruses and used to characterize transmission dynamics. The concept of phylodynamics has evolved since the early 21st century, extending its reach to slower-evolving pathogens, including bacteria and fungi, and to the identification of influential factors in disease spread and pathogen population dynamics.

RESULTS

The phylodynamic approach has now become a fundamental building block for the development of comparative phylogenetic tools capable of incorporating epidemiological surveillance data with molecular sequences into a single statistical framework. These innovative tools have greatly enhanced scientific investigations of the temporal and geographical origins, evolutionary history, and ecological risk factors associated with the growth and spread of viruses such as human immunodeficiency virus (HIV), Zika, and dengue and bacteria such as Methicillin-resistant Staphylococcus aureus.

CONCLUSIONS

Capitalizing on an extensive review of the literature, we discuss the evolution of the field of infectious disease epidemiology and recent accomplishments, highlighting the advancements in phylodynamics, as well as the challenges and limitations currently facing researchers studying emerging pathogen epidemics across the globe.

Efficient design of clinical trials and epidemiological research: is it possible?

Randomized clinical trials and large-scale, cohort studies continue to have a critical role in generating evidence in cardiovascular medicine; however, the increasing concern is that ballooning costs threaten the clinical trial enterprise. In this Perspectives article, we discuss the changing landscape of clinical research, and clinical trials in particular, focusing on reasons for the increasing costs and inefficiencies. These reasons include excessively complex design, overly restrictive inclusion and exclusion criteria, burdensome regulations, excessive source-data verification, and concerns about the effect of clinical research conduct on workflow. Thought leaders have called on the clinical research community to consider alternative, transformative business models, including those models that focus on simplicity and leveraging of digital resources. We present some examples of innovative approaches by which some investigators have successfully conducted large-scale, clinical trials at relatively low cost. These examples include randomized registry trials, cluster-randomized trials, adaptive trials, and trials that are fully embedded within digital clinical care or administrative platforms.

Transdisciplinary approaches enhance the production of translational knowledge

The primary goal of translational research is to generate and apply knowledge that can improve human health. Although research conducted within the confines of a single discipline has helped us to achieve this goal in many settings, this unidisciplinary approach may not be optimal when disease causation is complex and health decisions are pressing. To address these issues, we suggest that transdisciplinary approaches can facilitate the progress of translational research, and we review publications that demonstrate what these approaches can look like. These examples serve to (1) demonstrate why transdisciplinary research is useful, and (2) stimulate a conversation about how it can be further promoted. While we note that open-minded communication is a prerequisite for germinating any transdisciplinary work and that epidemiologists can play a key role in promoting it, we do not propose a rigid protocol for conducting transdisciplinary research, as one really does not exist. These achievements were developed in settings where typical disciplinary and institutional barriers were surmountable, but they were not accomplished with a single predetermined plan. The benefits of cross-disciplinary communication are hard to predict a priori and a detailed research protocol or process may impede the realization of novel and important insights. Overall, these examples demonstrate that enhanced cross-disciplinary information exchange can serve as a starting point that helps researchers frame better questions, integrate more relevant evidence, and advance translational knowledge more effectively. Specifically, we discuss examples where transdisciplinary approaches are helping us to better explore, assess, and intervene to improve human health.

Geospatial Approaches to Cancer Control and Population Sciences

Cancer incidence and mortality display strong geographic patterns worldwide and in the United States (1, 2). The environment where individuals live, work, and play is increasingly being recognized as important across the cancer control continuum, including the risk of cancer development, detection, diagnosis, treatment, mortality, and survivorship (3-5). At the same time, emergent technological capacity in geographic information systems (GIS) and mapping, along with increasing sophistication in applied spatial methods, has resulted in a growing research community developing and applying geospatial approaches in health research (5). Through collaborative, transdisciplinary efforts, and continued data collection efforts, there is great potential to apply these emerging geospatial approaches to various aspects of cancer prevention and control to inform etiology and target interventions and implementation of efficacious risk-reducing strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 472-5. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Trends in published meta-analyses in cancer research, 2008-2013

In order to capture trends in the contribution of epidemiology to cancer research, we describe an online meta-analysis database resource for cancer clinical and population research and illustrate trends and descriptive detail of cancer meta-analyses from 2008 through 2013. A total of 4,686 cancer meta-analyses met our inclusion criteria. During this 6-year period, a fivefold increase was observed in the yearly number of meta-analyses. Fifty-six percent of meta-analyses concerned observational studies, mostly of cancer risk, more than half of which were genetic studies. The major cancer sites were breast, colorectal, and digestive. This online database for Cancer Genomics and Epidemiology Navigator will be continuously updated to allow investigators to quickly navigate the meta-analyses emerging from cancer epidemiology studies and cancer clinical trials.

The Cancer Epidemiology Descriptive Cohort Database: A Tool to Support Population-Based Interdisciplinary Research

BACKGROUND

We report on the establishment of a web-based Cancer Epidemiology Descriptive Cohort Database (CEDCD). The CEDCD's goals are to enhance awareness of resources, facilitate interdisciplinary research collaborations, and support existing cohorts for the study of cancer-related outcomes.

METHODS

Comprehensive descriptive data were collected from large cohorts established to study cancer as primary outcome using a newly developed questionnaire. These included an inventory of baseline and follow-up data, biospecimens, genomics, policies, and protocols. Additional descriptive data extracted from publicly available sources were also collected. This information was entered in a searchable and publicly accessible database. We summarized the descriptive data across cohorts and reported the characteristics of this resource.

RESULTS

As of December 2015, the CEDCD includes data from 46 cohorts representing more than 6.5 million individuals (29% ethnic/racial minorities). Overall, 78% of the cohorts have collected blood at least once, 57% at multiple time points, and 46% collected tissue samples. Genotyping has been performed by 67% of the cohorts, while 46% have performed whole-genome or exome sequencing in subsets of enrolled individuals. Information on medical conditions other than cancer has been collected in more than 50% of the cohorts. More than 600,000 incident cancer cases and more than 40,000 prevalent cases are reported, with 24 cancer sites represented.

CONCLUSIONS

The CEDCD assembles detailed descriptive information on a large number of cancer cohorts in a searchable database.

IMPACT

Information from the CEDCD may assist the interdisciplinary research community by facilitating identification of well-established population resources and large-scale collaborative and integrative research. Cancer Epidemiol Biomarkers Prev; 25(10); 1392-401. ©2016 AACR.

Participants' Accounts on Their Decision to Join a Cohort Study With an Attached Biobank: A Qualitative Content Analysis Study Within Two German Studies

Reliable participation and sustained retention rates are crucial in longitudinal studies involving human subjects and biomaterials. Understanding the decision to enroll is an essential step to develop adequate strategies promoting long-term participation. Semi-structured interviews were implemented with newly recruited and long-term participants randomly drawn from two ongoing longitudinal studies with a biobank component in Germany. Iterative qualitative content analysis was applied to the transcribed interviews. Participants (n = 31) expressed their decision to enroll or remain in the study as the result of the complex interplay of individual factors, institutional cues, study-related features, and societal dynamics. Different forms of trust were identified as central within the elements used to explain participation and could be compared to Dibben, Morris, and Lean's dynamic model of interpersonal trust. Given these high levels of trust, an investigation of the morality of the trustful relationship at stake between participants and research(ers) is warranted.

Research Needs for Understanding the Biology of Overdiagnosis in Cancer Screening

Many cancers offer an extended window of opportunity for early detection and therapeutic intervention that could lead to a reduction in cause-specific mortality. The pursuit of early detection in screening settings has resulted in decreased incidence and mortality for some cancers (e.g., colon and cervical cancers), and increased incidence with only modest or no effect on cause-specific mortality in others (e.g., breast and prostate). Whereas highly sensitive screening technologies are better at detecting a number of suspected "cancers" that are indolent and likely to remain clinically unimportant in the lifetime of a patient, defined as overdiagnosis, they often miss cancers that are aggressive and tend to present clinically between screenings, known as interval cancers. Unrecognized overdiagnosis leads to overtreatment with its attendant (often long-lasting) side effects, anxiety, and substantial financial harm. Existing methods often cannot differentiate indolent lesions from aggressive ones or understand the dynamics of neoplastic progression. To correctly identify the population that would benefit the most from screening and identify the lesions that would benefit most from treatment, the evolving genomic and molecular profiles of individual cancers during the clinical course of progression or indolence must be investigated, while taking into account an individual's genetic susceptibility, clinical and environmental risk factors, and the tumor microenvironment. Practical challenges lie not only in the lack of access to tissue specimens that are appropriate for the study of natural history, but also in the absence of targeted research strategies. This commentary summarizes the recommendations from a diverse group of scientists with expertise in basic biology, translational research, clinical research, statistics, and epidemiology and public health professionals convened to discuss research directions. J. Cell. Physiol. 231: 1870-1875, 2016. © 2015 Wiley Periodicals, Inc.

Comparative Effectiveness Research: A Roadmap for Physical Activity and Lifestyle

PURPOSE

Comparative effectiveness research (CER) is designed to support informed decision making at both the individual, population, and policy levels. The American College of Sports Medicine and partners convened a conference with the focus of building an agenda for CER within the context of physical activity and nonpharmacological lifestyle approaches in the prevention and treatment of chronic disease. This report summarizes the conference content and consensus recommendations that culminated in a CER roadmap for physical activity and lifestyle approaches to reducing the risk of chronic disease.

METHODS

This conference focused on presentations and discussion around the following topic areas: 1) defining CER, 2) identifying the current funding climate to support CER, 3) summarizing methods for conducting CER, and 4) identifying CER opportunities for physical activity.

RESULTS

This conference resulted in consensus recommendations to adopt a CER roadmap for physical activity and lifestyle approaches to reducing the risk of chronic disease. In general, this roadmap provides a systematic framework by which CER for physical activity can move from a planning phase to a phase of engagement in CER related to lifestyle factors with particular emphasis on physical activity to a societal change phase that results in changes in policy, practice, and health.

CONCLUSIONS

It is recommended that physical activity researchers and health care providers use the roadmap developed from this conference as a method to systematically engage in and apply CER to the promotion of physical activity as a key lifestyle behavior that can be effective at making an impact on a variety of health-related outcomes.

Digital Connectedness in the Framingham Heart Study

Background

New avenues of data collection such as eHealth and mobile technology have the potential to revolutionize the way large populations can be assessed and managed outside of standard research and clinical settings.

Methods and Results

A digital connectedness survey was administered within the Framingham Heart Study from 2014 to 2015. The exposure was usage of the Internet, email, cell phones, and smartphones in relation to demographic and cardiovascular disease risk factors; all results were adjusted for age and sex. Among 8096 living study participants, 6503 (80.3%) completed the digital survey. Among survey responders, 5678 (87.4%) reported regular Internet use. Participants reporting regular Internet use were younger (aged 59.1 versus 76.5 years, P<0.0001), were more likely to be employed (70.3% versus 23.7%, P=0.002), and had more favorable cardiovascular disease risk factors than those who did not use the Internet (all P≤0.05). Overall, 5946 (92.1%) responders reported using cell phones. Among cell phone users, 3907 (67.8%) had smartphones. Smartphone users were younger (aged 55.4 versus 68.5 years, P<0.0001), more likely to be employed (81.1% versus 43.9%, P<0.0001) and to have a college education, and less likely to have hypertension (27.9% versus 55.7%, P=0.0002) than those who did not use smartphones.

Conclusions

Digital connectedness varies substantially by age; connected persons tend to be younger and better educated and to have more favorable cardiovascular disease risk factor profiles. Less than two‐thirds of study participants who completed the survey had a smartphone. The generalizability of studies focused on digitally connected persons may have limitations.

Toward a Modern Science of Obesity at Washington University: How We Do It and What is the Payoff?

In our Cancer Prevention Program at Washington University in Saint Louis (WUSTL), we have made extraordinary efforts to create the kind of cancer prevention and control program that is both translational and transdisciplinary in nature, to accelerate the march from basic discoveries to population change. Here we present an overview of our obesity-related research currently ongoing in our Center, paying particular attention to both the translational- transdisciplinary process and to community-based participatory research. We end with our future directions for improving obesity-related cancer outcomes research. Cancer Prev Res; 9(7); 503-8. ©2016 AACR.

A novel web informatics approach for automated surveillance of cancer mortality trends

Cancer surveillance data are collected every year in the United States via the National Program of Cancer Registries (NPCR) and the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute (NCI). General trends are closely monitored to measure the nation's progress against cancer. The objective of this study was to apply a novel web informatics approach for enabling fully automated monitoring of cancer mortality trends. The approach involves automated collection and text mining of online obituaries to derive the age distribution, geospatial, and temporal trends of cancer deaths in the US. Using breast and lung cancer as examples, we mined 23,850 cancer-related and 413,024 general online obituaries spanning the timeframe 2008-2012. There was high correlation between the web-derived mortality trends and the official surveillance statistics reported by NCI with respect to the age distribution (ρ=0.981 for breast; ρ=0.994 for lung), the geospatial distribution (ρ=0.939 for breast; ρ=0.881 for lung), and the annual rates of cancer deaths (ρ=0.661 for breast; ρ=0.839 for lung). Additional experiments investigated the effect of sample size on the consistency of the web-based findings. Overall, our study findings support web informatics as a promising, cost-effective way to dynamically monitor spatiotemporal cancer mortality trends.

Tackling NCD in LMIC: Achievements and Lessons Learned From the NHLBI-UnitedHealth Global Health Centers of Excellence Program

Effectively tackling the growing noncommunicable disease (NCD) burden in low- and middle-income countries (LMIC) is a major challenge. To address research needs in this setting for NCDs, in 2009, National Heart, Lung, and Blood Institute (NHLBI) and UnitedHealth Group (UHG) engaged in a public-private partnership that supported a network of 11 LMIC-based research centers and created the NHLBI-UnitedHealth Global Health Centers of Excellence (COE) Program. The Program's overall goal was to contribute to reducing the cardiovascular and lung disease burdens by catalyzing in-country research institutions to develop a global network of biomedical research centers. Key elements of the Program included team science and collaborative approaches, developing research and training platforms for future investigators, and creating a data commons. This Program embraced a strategic approach for tackling NCDs in LMICs and will provide capacity for locally driven research efforts that can identify and address priority health issues in specific countries' settings.

Commentary: Epidemiology in the era of big data

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called "three V's": variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field's future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future.

Characterising the epigenome as a key component of the fetal exposome in evaluating in utero exposures and childhood cancer risk

Recent advances in laboratory sciences hold a promise for a 'leap forward' in understanding the aetiology of complex human diseases, notably cancer, potentially providing an evidence base for prevention. For example, remarkable advances in epigenomics have an important impact on our understanding of biological phenomena and importance of environmental stressors in complex diseases. Environmental and lifestyle factors are thought to be implicated in the development of a wide range of human cancers by eliciting changes in the epigenome. These changes, thus, represent attractive targets for biomarker discovery intended for the improvement of exposure and risk assessment, diagnosis and prognosis and provision of short-term outcomes in intervention studies. The epigenome can be viewed as an interface between the genome and the environment; therefore, aberrant epigenetic events associated with environmental exposures are likely to play an important role in the onset and progression of different human diseases. The advent of powerful technologies for analysing epigenetic patterns in both cancer tissues and normal cells holds promise that the next few years will be fundamental for the identification of critical cancer- and exposure-associated epigenetic changes and for their evaluation as new generation of biomarkers. Here, we discuss new opportunities in the current age of 'omics' technologies for studies with prospective design and associated biospecimens that represent exciting potential for characterising the epigenome as a key component of the fetal exposome and for understanding causal pathways and robust predictors of cancer risk and associated environmental determinants during in utero life. Such studies should improve our knowledge concerning the aetiology of childhood cancer and identify both novel biomarkers and clues to causation, thus, providing an evidence base for cancer prevention.

Representativeness of breast cancer cases in an integrated health care delivery system

BACKGROUND

Integrated health care delivery systems, with their comprehensive and integrated electronic medical records (EMR), are well-poised to conduct research that leverages the detailed clinical data within the EMRs. However, information regarding the representativeness of these clinical populations is limited, and thus the generalizability of research findings is uncertain.

METHODS

Using data from the population-based California Cancer Registry, we compared age-adjusted distributions of patient and neighborhood characteristics for three groups of breast cancer patients: 1) those diagnosed within Kaiser Permanente Northern California (KPNC), 2) non-KPNC patients from NCI-designated cancer centers, and 3) those from all other hospitals.

RESULTS

KPNC patients represented 32 % (N = 36,109); cancer center patients represented 7 % (N = 7805); and all other hospitals represented 61 % (N = 68,330) of the total breast cancer patients from this geographic area during 1996-2009. Compared with cases from all other hospitals, KPNC had slightly fewer non-Hispanic Whites (70.6 % versus 74.4 %) but more Blacks (8.1 % versus 5.0 %), slightly more patients in the 50-69 age range and fewer in the younger and older age groups, a slightly lower proportion of in situ but higher proportion of stage I disease (41.6 % versus 38.9 %), were slightly less likely to reside in the lowest (4.2 % versus 6.5 %) and highest (36.2 % versus 39.0 %) socioeconomic status neighborhoods, and more likely to live in suburban metropolitan areas and neighborhoods with more racial/ethnic minorities. Cancer center patients differed substantially from patients from KPNC and all other hospitals on all characteristics assessed. All differences were statistically significant (p < .001).

CONCLUSIONS

Although much of clinical research discoveries are based in academic medical centers, patients from large, integrated medical centers are likely more representative of the underlying population, providing support for the generalizability of cancer research based on electronic data from these centers.