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Wallace ML, Redline S, Oryshkewych N, Hoepel SJW, Luik AI, Stone KL, Kolko RP, Chung J, Leng Y, Robbins R, Zhang Y, Barnes LL, Lim AS, Yu L, Buysse DJ. Pioneering a multi-phase framework to harmonize self-reported sleep data across cohorts. Sleep 2024; 47:zsae115. [PMID: 38752786 PMCID: PMC11381567 DOI: 10.1093/sleep/zsae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/29/2024] [Indexed: 06/15/2024] Open
Abstract
STUDY OBJECTIVES Harmonizing and aggregating data across studies enables pooled analyses that support external validation and enhance replicability and generalizability. However, the multidimensional nature of sleep poses challenges for data harmonization and aggregation. Here we describe and implement our process for harmonizing self-reported sleep data. METHODS We established a multi-phase framework to harmonize self-reported sleep data: (1) compile items, (2) group items into domains, (3) harmonize items, and (4) evaluate harmonizability. We applied this process to produce a pooled multi-cohort sample of five US cohorts plus a separate yet fully harmonized sample from Rotterdam, Netherlands. Sleep and sociodemographic data are described and compared to demonstrate the utility of harmonization and aggregation. RESULTS We collected 190 unique self-reported sleep items and grouped them into 15 conceptual domains. Using these domains as guiderails, we developed 14 harmonized items measuring aspects of satisfaction, alertness/sleepiness, timing, efficiency, duration, insomnia, and sleep apnea. External raters determined that 13 of these 14 items had moderate-to-high harmonizability. Alertness/Sleepiness items had lower harmonizability, while continuous, quantitative items (e.g. timing, total sleep time, and efficiency) had higher harmonizability. Descriptive statistics identified features that are more consistent (e.g. wake-up time and duration) and more heterogeneous (e.g. time in bed and bedtime) across samples. CONCLUSIONS Our process can guide researchers and cohort stewards toward effective sleep harmonization and provide a foundation for further methodological development in this expanding field. Broader national and international initiatives promoting common data elements across cohorts are needed to enhance future harmonization and aggregation efforts.
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Affiliation(s)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Sanne J W Hoepel
- Department of Epidemiology, Erasmus MC University Medical Centre, Rotterdam, Netherlands
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC University Medical Centre, Rotterdam, Netherlands
- Trimbos Institute - The Netherlands Institute of Mental Health and Addiction, Utrecht, Netherlands
| | - Katie L Stone
- California Pacific Medical Center, San Francisco, CA, USA
| | - Rachel P Kolko
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joon Chung
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Yue Leng
- Department of Psychiatry and Behavioral Sciences, University of California at San Francisco, San Franciso, CA, USA
| | - Rebecca Robbins
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Ying Zhang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Lisa L Barnes
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Andrew S Lim
- Department of Neurology, University of Toronto, Toronto, ON, Canada
| | - Lan Yu
- Department of Medicine, University of Pittsburgh School, Pittsburgh, PA, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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Jović M, Haeri MA, Whitehouse A, van den Berg SM. Harmonizing the CBCL and SDQ ADHD scores by using linear equating, kernel equating, item response theory and machine learning methods. Front Psychol 2024; 15:1345406. [PMID: 39049945 PMCID: PMC11267626 DOI: 10.3389/fpsyg.2024.1345406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 06/17/2024] [Indexed: 07/27/2024] Open
Abstract
Introduction A problem that applied researchers and practitioners often face is the fact that different institutions within research consortia use different scales to evaluate the same construct which makes comparison of the results and pooling challenging. In order to meaningfully pool and compare the scores, the scales should be harmonized. The aim of this paper is to use different test equating methods to harmonize the ADHD scores from Child Behavior Checklist (CBCL) and Strengths and Difficulties Questionnaire (SDQ) and to see which method leads to the result. Methods Sample consists of 1551 parent reports of children aged 10-11.5 years from Raine study on both CBCL and SDQ (common persons design). We used linear equating, kernel equating, Item Response Theory (IRT), and the following machine learning methods: regression (linear and ordinal), random forest (regression and classification) and Support Vector Machine (regression and classification). Efficacy of the methods is operationalized in terms of the root-mean-square error (RMSE) of differences between predicted and observed scores in cross-validation. Results and discussion Results showed that with single group design, it is the best to use the methods that use item level information and that treat the outcome as interval measurement level (regression approach).
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Affiliation(s)
- Miljan Jović
- Department of Learning, Data Analytics and Technology, University of Twente, Enschede, Netherlands
| | - Maryam Amir Haeri
- Department of Learning, Data Analytics and Technology, University of Twente, Enschede, Netherlands
| | - Andrew Whitehouse
- Telethon Kids Institute, University of Western Australia, Perth, WA, Australia
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Sharma V, O'Sullivan M, Cassetti O, Winning L, O'Sullivan A, Crowe M. Evaluating the harmonization potential of oral health-related questionnaires in national longitudinal birth and child cohort surveys. J Public Health Dent 2024. [PMID: 38953657 DOI: 10.1111/jphd.12632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 04/16/2024] [Accepted: 06/14/2024] [Indexed: 07/04/2024]
Abstract
BACKGROUND/OBJECTIVES Effective use of longitudinal study data is challenging because of divergences in the construct definitions and measurement approaches over time, between studies and across disciplines. One approach to overcome these challenges is data harmonization. Data harmonization is a practice used to improve variable comparability and reduce heterogeneity across studies. This study describes the process used to evaluate the harmonization potential of oral health-related variables across each survey wave. METHODS National child cohort surveys with similar themes/objectives conducted in the last two decades were selected. The Maelstrom Research Guidelines were followed for harmonization potential evaluation. RESULTS Seven nationally representative child cohort surveys were included and questionnaires examined from 50 survey waves. Questionnaires were classified into three domains and fifteen constructs and summarized by age groups. A DataSchema (a list of core variables representing the suitable version of the oral health outcomes and risk factors) was compiled comprising 42 variables. For each study wave, the potential (or not) to generate each DataSchema variable was evaluated. Of the 2100 harmonization status assessments, 543 (26%) were complete. Approximately 50% of the DataSchema variables can be generated across at least four cohort surveys while only 10% (n = 4) variables can be generated across all surveys. For each survey, the DataSchema variables that can be generated ranged between 26% and 76%. CONCLUSION Data harmonization can improve the comparability of variables both within and across surveys. For future cohort surveys, the authors advocate more consistency and standardization in survey questionnaires within and between surveys.
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Affiliation(s)
- Vinay Sharma
- Division of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland
| | - Michael O'Sullivan
- Division of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland
| | - Oscar Cassetti
- Division of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland
| | - Lewis Winning
- Division of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland
| | - Aifric O'Sullivan
- Institute of Food and Health, Science Centre, South, UCD, Dublin, Ireland
| | - Michael Crowe
- Division of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland
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Nel S, de Man J, van den Berg L, Wenhold FAM. Statistical assessment of reliability of anthropometric measurements in the multi-site South African National Dietary Intake Survey 2022. Eur J Clin Nutr 2024:10.1038/s41430-024-01449-1. [PMID: 38745053 DOI: 10.1038/s41430-024-01449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/26/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND Anthropometric data quality in large multicentre nutrition surveys is seldom adequately assessed. In preparation for the South African National Dietary Intake Survey (NDIS-2022), this study assessed site leads' and fieldworkers' intra- and inter-rater reliability for measuring weight, length/height, mid-upper arm circumference (MUAC), waist circumference (WC) and calf circumference (CC). METHODS Standardised training materials and measurement protocols were developed, and new anthropometric equipment was procured. Following two training rounds (12 site lead teams, 46 fieldworker teams), measurement reliability was assessed for both groups, using repeated measurements of volunteers similar to the survey target population. Reliability was statistically assessed using the technical error of measurement (TEM), relative TEM (%TEM), intra-class correlation coefficient (ICC) and coefficient of reliability (R). Agreement was visualised with Bland-Altman analysis. RESULTS By %TEM, the best reliability was achieved for weight (%TEM = 0.260-0.923) and length/height (%TEM = 0.434-0.855), and the poorest for MUAC by fieldworkers (%TEM = 2.592-3.199) and WC (%TEM = 2.353-2.945). Whole-sample ICC and R were excellent ( > 0.90) for all parameters except site leads' CC inter-rater reliability (ICC = 0.896, R = 0.889) and fieldworkers' inter-rater reliability for MUAC in children under two (ICC = 0.851, R = 0.881). Bland-Altman analysis revealed no significant bias except in fieldworkers' intra-rater reliability of length/height measurement in adolescents/adults ( + 0.220 (0.042, 0.400) cm). Reliability was higher for site leads vs. fieldworkers, for intra-rater vs. inter-rater assessment, and for weight and length/height vs. circumference measurements. CONCLUSION NDIS-2022 site leads and fieldworkers displayed acceptable reliability in performing anthropometric measurements, highlighting the importance of intensive training and standardised measurement protocols. Ongoing reliability assessment during data collection is recommended.
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Affiliation(s)
- Sanja Nel
- University of Pretoria, Department of Human Nutrition, Faculty of Health Sciences, Pretoria, South Africa.
- University of Pretoria Research Centre for Maternal, Fetal, Newborn & Child Health Care Strategies, Kalafong Hospital, Atteridgeville, South Africa.
- South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit, Kalafong Hospital, Atteridgeville, South Africa.
| | - Jeroen de Man
- School of Public Health, Faculty of Community and Health Sciences, University of the Western Cape, Cape Town, South Africa
- Department of Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium
| | - Louise van den Berg
- University of the Free State, Department of Nutrition and Dietetics, School of Health and Rehabilitation Sciences, Faculty of Health Sciences, Bloemfontein, South Africa
| | - Friedeburg Anna Maria Wenhold
- University of Pretoria, Department of Human Nutrition, Faculty of Health Sciences, Pretoria, South Africa
- University of Pretoria Research Centre for Maternal, Fetal, Newborn & Child Health Care Strategies, Kalafong Hospital, Atteridgeville, South Africa
- South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit, Kalafong Hospital, Atteridgeville, South Africa
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Adang LA, Sevagamoorthy A, Sherbini O, Fraser JL, Bonkowsky JL, Gavazzi F, D'Aiello R, Modesti NB, Yu E, Mutua S, Kotes E, Shults J, Vincent A, Emrick LT, Keller S, Van Haren KP, Woidill S, Barcelos I, Pizzino A, Schmidt JL, Eichler F, Fatemi A, Vanderver A. Longitudinal natural history studies based on real-world data in rare diseases: Opportunity and a novel approach. Mol Genet Metab 2024; 142:108453. [PMID: 38522179 PMCID: PMC11131438 DOI: 10.1016/j.ymgme.2024.108453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/13/2024] [Accepted: 03/16/2024] [Indexed: 03/26/2024]
Abstract
Growing interest in therapeutic development for rare diseases necessitate a systematic approach to the collection and curation of natural history data that can be applied consistently across this group of heterogenous rare diseases. In this study, we discuss the challenges facing natural history studies for leukodystrophies and detail a novel standardized approach to creating a longitudinal natural history study using existing medical records. Prospective studies are uniquely challenging for rare diseases. Delays in diagnosis and overall rarity limit the timely collection of natural history data. When feasible, prospective studies are often cross-sectional rather than longitudinal and are unlikely to capture pre- or early- symptomatic disease trajectories, limiting their utility in characterizing the full natural history of the disease. Therapeutic development in leukodystrophies is subject to these same obstacles. The Global Leukodystrophy Initiative Clinical Trials Network (GLIA-CTN) comprises of a network of research institutions across the United States, supported by a multi-center biorepository protocol, to map the longitudinal clinical course of disease across leukodystrophies. As part of GLIA-CTN, we developed Standard Operating Procedures (SOPs) that delineated all study processes related to staff training, source documentation, and data sharing. Additionally, the SOP detailed the standardized approach to data extraction including diagnosis, clinical presentation, and medical events, such as age at gastrostomy tube placement. The key variables for extraction were selected through face validity, and common electronic case report forms (eCRF) across leukodystrophies were created to collect analyzable data. To enhance the depth of the data, clinical notes are extracted into "original" and "imputed" encounters, with imputed encounter referring to a historic event (e.g., loss of ambulation 3 months prior). Retrospective Functional Assessments were assigned by child neurologists, using a blinded dual-rater approach and score discrepancies were adjudicated by a third rater. Upon completion of extraction, data source verification is performed. Data missingness was evaluated using statistics. The proposed methodology will enable us to leverage existing medical records to address the persistent gap in natural history data within this unique disease group, allow for assessment of clinical trajectory both pre- and post-formal diagnosis, and promote recruitment of larger cohorts.
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Affiliation(s)
- Laura Ann Adang
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Anjana Sevagamoorthy
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Omar Sherbini
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jamie L Fraser
- Rare Disease Institute, Children's National Medical Center, Washington, DC, USA; Leukodystrophy and Myelin Disorders Program, Children's National Medical Center, Washington, DC, USA
| | - Joshua L Bonkowsky
- Division of Pediatric Neurology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA; Center for Personalized Medicine, Primary Children's Hospital, Salt Lake City, UT, USA
| | - Francesco Gavazzi
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Russel D'Aiello
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nicholson B Modesti
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emily Yu
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sylvia Mutua
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emma Kotes
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Justine Shults
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ariel Vincent
- CHOP Research Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa T Emrick
- Division of Neurology and Developmental Neuroscience in Department Pediatrics, Baylor College Medicine and Texas Children's Hospital, Houston, TX, USA; Department of Human and Molecular Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Stephanie Keller
- Children's Healthcare of Atlanta Scottish Rite Hospital, Emory University School of Medicine, Atlanta, GA, USA
| | | | - Sarah Woidill
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Isabella Barcelos
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Amy Pizzino
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Johanna L Schmidt
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Florian Eichler
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Ali Fatemi
- Moser Center for Leukodystrophies, Kennedy Krieger Institute, Baltimore, MD, USA; Departments of Neurology & Pediatrics, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Adeline Vanderver
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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Cheng C, Messerschmidt L, Bravo I, Waldbauer M, Bhavikatti R, Schenk C, Grujic V, Model T, Kubinec R, Barceló J. A General Primer for Data Harmonization. Sci Data 2024; 11:152. [PMID: 38297013 PMCID: PMC10831085 DOI: 10.1038/s41597-024-02956-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024] Open
Affiliation(s)
- Cindy Cheng
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany.
| | - Luca Messerschmidt
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany
| | - Isaac Bravo
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany
| | - Marco Waldbauer
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany
| | | | - Caress Schenk
- School of Humanities and Social Sciences, Nazarbayev University, Kabanbay Batry Ave., 53, Astana, 010000, Kazakhstan
| | - Vanja Grujic
- Faculty of Law, University of Brasilia, Campus Universitário Darcy Ribeiro Asa Norte, Brasília, 10587, Brazil
| | - Tim Model
- Delve, 2225 3rd St, San Francisco, 94107, California, USA
| | - Robert Kubinec
- Division of Social Science, New York University Abu Dhabi, Social Science Building (A5), Abu Dhabi, 129188, United Arab Emirates
| | - Joan Barceló
- Division of Social Science, New York University Abu Dhabi, Social Science Building (A5), Abu Dhabi, 129188, United Arab Emirates
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Mallya P, Stevens LM, Zhao J, Hong C, Henao R, Economou-Zavlanos N, Wojdyla DM, Schibler T, Manchanda V, Pencina MJ, Hall JL. Facilitating Harmonization of Variables in Framingham, MESA, ARIC, and REGARDS Studies Through a Metadata Repository. Circ Cardiovasc Qual Outcomes 2023; 16:e009938. [PMID: 37850400 PMCID: PMC10841164 DOI: 10.1161/circoutcomes.123.009938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
BACKGROUND High-quality research in cardiovascular prevention, as in other fields, requires inclusion of a broad range of data sets from different sources. Integrating and harmonizing different data sources are essential to increase generalizability, sample size, and representation of understudied populations-strengthening the evidence for the scientific questions being addressed. METHODS Here, we describe an effort to build an open-access repository and interactive online portal for researchers to access the metadata and code harmonizing data from 4 well-known cohort studies-the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study, FHS (Framingham Heart Study), MESA (Multi-Ethnic Study of Atherosclerosis), and ARIC (Atherosclerosis Risk in Communities) study. We introduce a methodology and a framework used for preprocessing and harmonizing variables from multiple studies. RESULTS We provide a real-case study and step-by-step guidance to demonstrate the practical utility of our repository and interactive web page. In addition to our successful development of such an open-access repository and interactive web page, this exercise in harmonizing data from multiple cohort studies has revealed several key themes. These themes include the importance of careful preprocessing and harmonization of variables, the value of creating an open-access repository to facilitate collaboration and reproducibility, and the potential for using harmonized data to address important scientific questions and disparities in cardiovascular disease research. CONCLUSIONS By integrating and harmonizing these large-scale cohort studies, such a repository may improve the statistical power and representation of understudied cohorts, enabling development and validation of risk prediction models, identification and investigation of risk factors, and creating a platform for racial disparities research. REGISTRATION URL: https://precision.heart.org/duke-ninds.
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Affiliation(s)
- Pratheek Mallya
- American Heart Association, Dallas, TX (P.M., J.Z., V.M., J.L.H.)
| | - Laura M Stevens
- University of Colorado Anschutz Medical School, Aurora (L.M.S.)
| | - Juan Zhao
- American Heart Association, Dallas, TX (P.M., J.Z., V.M., J.L.H.)
| | - Chuan Hong
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (C.H., R.H., M.P.)
- Duke Clinical Research Institute, Durham, NC (C.H., R.H., D.W., T.S.)
| | - Ricardo Henao
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (C.H., R.H., M.P.)
- Duke Clinical Research Institute, Durham, NC (C.H., R.H., D.W., T.S.)
| | | | - Daniel M Wojdyla
- Duke Clinical Research Institute, Durham, NC (C.H., R.H., D.W., T.S.)
| | - Tony Schibler
- Duke Clinical Research Institute, Durham, NC (C.H., R.H., D.W., T.S.)
| | - Vihaan Manchanda
- American Heart Association, Dallas, TX (P.M., J.Z., V.M., J.L.H.)
| | - Michael J Pencina
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (C.H., R.H., M.P.)
| | - Jennifer L Hall
- American Heart Association, Dallas, TX (P.M., J.Z., V.M., J.L.H.)
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Ridenour TA, Cruden G, Yang Y, Bonar EE, Rodriguez A, Saavedra LM, Hussong AM, Walton MA, Deeds B, Ford JL, Knight DK, Haggerty KP, Stormshak E, Kominsky TK, Ahrens KR, Woodward D, Feng X, Fiellin LE, Wilens TE, Klein DJ, Fernandes CS. Methodological Strategies for Prospective Harmonization of Studies: Application to 10 Distinct Outcomes Studies of Preventive Interventions Targeting Opioid Misuse. PREVENTION SCIENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR PREVENTION RESEARCH 2023; 24:16-29. [PMID: 35976525 PMCID: PMC9935745 DOI: 10.1007/s11121-022-01412-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2022] [Indexed: 02/02/2023]
Abstract
The Helping to End Addiction Long-Term (HEAL) Prevention Cooperative (HPC) is rapidly developing 10 distinct evidence-based interventions for implementation in a variety of settings to prevent opioid misuse and opioid use disorder. One HPC objective is to compare intervention impacts on opioid misuse initiation, escalation, severity, and disorder and identify whether any HPC interventions are more effective than others for types of individuals. It provides a rare opportunity to prospectively harmonize measures across distinct outcomes studies. This paper describes the needs, opportunities, strategies, and processes that were used to harmonize HPC data. They are illustrated with a strategy to measure opioid use that spans the spectrum of opioid use experiences (termed involvement) and is composed of common "anchor items" ranging from initiation to symptoms of opioid use disorder. The limitations and opportunities anticipated from this approach to data harmonization are reviewed. Lastly, implications for future research cooperatives and the broader HEAL data ecosystem are discussed.
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Affiliation(s)
- Ty A Ridenour
- RTI International, 3040 E. Cornwallis Rd., PO Box 12194, 326 Cox Bldg, Research Triangle Park, 27709-2194, NC, USA.
| | | | - Yang Yang
- Texas Christian University, Fort Worth, USA
| | | | | | - Lissette M Saavedra
- RTI International, 3040 E. Cornwallis Rd., PO Box 12194, 326 Cox Bldg, Research Triangle Park, 27709-2194, NC, USA
| | | | | | - Bethany Deeds
- National Institute On Drug Abuse, North Bethesda, USA
| | | | | | - Kevin P Haggerty
- Seattle Children's Hospital & University of Washington, Seattle, USA
| | | | | | - Kym R Ahrens
- Seattle Children's Hospital & University of Washington, Seattle, USA
| | | | - Xin Feng
- The Ohio State University, Columbus, USA
| | | | | | - David J Klein
- RAND Corporation, & University of California, Los Angeles, USA
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9
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Zhao IY, Ho MH, Tyrovolas S, Deng SY, Montayre J, Molassiotis A. Constructing the concept of healthy ageing and examining its association with loneliness in older adults. BMC Geriatr 2023; 23:325. [PMID: 37231364 DOI: 10.1186/s12877-023-04019-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 05/05/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND World Health Organization (WHO) has defined healthy ageing by highlighting five functional ability domains to (meet basic needs, make decisions, be mobile, build and maintain relationships, and contribute to society), which also emphasized the importance of addressing loneliness as priorities within United Nations Decade of Healthy Ageing initiative. However, the level and determinants of healthy ageing and its association with loneliness are rarely examined. This study aimed to construct a healthy ageing index to verify the WHO healthy ageing framework, measure five domains of functional ability of older adults and examine the relationship between functional ability domains and loneliness. METHODS A total of 10,746 older adults from the 2018 China Health and Retirement Longitudinal Study (CHARLS) were included. A healthy ageing index ranging from 0 to 17 was constructed using 17 components related to functional ability domains. Univariate and multivariate logistic regression analyses were utilized to determine the association between loneliness and healthy ageing. The STROBE guidelines with the RECORD statement for observational studies using routinely collected health data were observed. RESULTS The factor analysis verified the five functional ability domains for healthy ageing. After adjusting for confounders, being mobile, building and maintaining relationships, and learning, growing and making decisions were significantly associated with lesser loneliness among participants. CONCLUSIONS The healthy ageing index of this study can be utilized and further modified with respect to large-scale research with relevant healthy ageing topics. Our findings will support healthcare professionals to provide patient-centered care when identifying their comprehensive abilities and needs.
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Affiliation(s)
- Ivy Yan Zhao
- WHOCC Centre for Community Health Services, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
- School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
| | - Mu-Hsing Ho
- School of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, P. R. China.
| | - Stefanos Tyrovolas
- WHOCC Centre for Community Health Services, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
- School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
| | - Sasha Yuanjie Deng
- School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
| | - Jed Montayre
- WHOCC Centre for Community Health Services, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
- School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
| | - Alex Molassiotis
- School of Nursing, the Hong Kong Polytechnic University, Hong Kong, SAR, P. R. China
- Office of the Vice-Chancellor, College of Arts, Humanities and Education, University of Derby, Derby, UK
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Eisenberg ME, Gower AL, Watson RJ, Rider GN, Thomas D, Russell ST. Substance Use Behaviors Among LGBTQ+ Youth of Color: Identification of the Populations Bearing the Greatest Burden in Three Large Samples. J Adolesc Health 2022; 71:317-323. [PMID: 35715349 PMCID: PMC9644400 DOI: 10.1016/j.jadohealth.2022.04.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/30/2022] [Accepted: 04/01/2022] [Indexed: 11/27/2022]
Abstract
PURPOSE Research has identified persistent disparities in alcohol, e-cigarette, and marijuana use, by sexual orientation, gender identity, and race/ethnicity. Using an intersectionality framework, the present study analyzes three large datasets to identify intersecting social positions bearing the highest burden of substance use. METHODS Data from adolescents in grades 9-12 in three samples (2019 Minnesota Student Survey, 2017-2019 California Healthy Kids Survey, and 2017 National Teen Survey) were harmonized for an analysis (N = 602,470). A Chi-squared Automatic Interaction Detection analysis compared the prevalence of four types of substance use across all combinations of four social positions (six racial/ethnic identities, five sexual orientations, three gender identities, and two sexes assigned at birth). For each substance, 10 intersectional groups with the highest prevalence of use were examined. RESULTS In the full sample, 12%-14% of participants reported past 30-day alcohol, e-cigarette, or marijuana use and 7% reported past 30-day binge drinking. Several intersecting marginalized social positions were consistently found to bear a high burden of substance use. For example, transgender and gender diverse (TGD) Latina/x/o young people, particularly those assigned male at birth, were in the high prevalence groups for alcohol use, binge drinking, and marijuana use. Black TGD or gender-questioning youth were commonly in the high prevalence groups. DISCUSSION Findings suggest that support, resources, and structural changes specifically tailored to youth with multiple marginalized identities (especially TGD) may be needed. The results argue for intersectional efforts that explicitly address racial/ethnic and cultural differences, while also integrating awareness and understanding of sexual and gender diversity.
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Affiliation(s)
- Marla E. Eisenberg
- Division of General Pediatrics and Adolescent Health, Department of Pediatrics, University of Minnesota. 717 Delaware St. SE, Minneapolis, MN, 55414, USA.,Corresponding author:
| | - Amy L. Gower
- Division of General Pediatrics and Adolescent Health, Department of Pediatrics, University of Minnesota. 717 Delaware St. SE, Minneapolis, MN, 55414, USA
| | - Ryan J. Watson
- Department of Human Development and Family Studies, University of Connecticut, 348 Mansfield Rd U1058, Storrs, CT, 06269, USA
| | - G. Nic Rider
- Institute for Sexual and Gender Health, Department of Family Medicine and Community Health, University of Minnesota Medical School, 1300 S 2nd St., Ste 180, Minneapolis, MN, 55454, USA
| | - De’Shay Thomas
- Division of General Pediatrics and Adolescent Health, Department of Pediatrics, University of Minnesota. 717 Delaware St. SE, Minneapolis, MN, 55414, USA
| | - Stephen T. Russell
- Department of Human Development and Family Sciences, University of Texas, 108 Dean Keeton St, Austin, TX, 78712, USA
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11
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Torres-Espín A, Ferguson AR. Harmonization-Information Trade-Offs for Sharing Individual Participant Data in Biomedicine. HARVARD DATA SCIENCE REVIEW 2022; 4:10.1162/99608f92.a9717b34. [PMID: 36420049 PMCID: PMC9681014 DOI: 10.1162/99608f92.a9717b34] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024] Open
Abstract
Biomedical practice is evidence-based. Peer-reviewed papers are the primary medium to present evidence and data-supported results to drive clinical practice. However, it could be argued that scientific literature does not contain data, but rather narratives about and summaries of data. Meta-analyses of published literature may produce biased conclusions due to the lack of transparency in data collection, publication bias, and inaccessibility to the data underlying a publication ('dark data'). Co-analysis of pooled data at the level of individual research participants can offer higher levels of evidence, but this requires that researchers share raw individual participant data (IPD). FAIR (findable, accessible, interoperable, and reusable) data governance principles aim to guide data lifecycle management by providing a framework for actionable data sharing. Here we discuss the implications of FAIR for data harmonization, an essential step for pooling data for IPD analysis. We describe the harmonization-information trade-off, which states that the level of granularity in harmonizing data determines the amount of information lost. Finally, we discuss a framework for managing the trade-off and the levels of harmonization. In the coming era of funder mandates for data sharing, research communities that effectively manage data harmonization will be empowered to harness big data and advanced analytics such as machine learning and artificial intelligence tools, leading to stunning new discoveries that augment our understanding of diseases and their treatments. By elevating scientific data to the status of a first-class citizen of the scientific enterprise, there is strong potential for biomedicine to transition from a narrative publication product orientation to a modern data-driven enterprise where data itself is viewed as a primary work product of biomedical research.
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Affiliation(s)
- Abel Torres-Espín
- Brain and Spinal Injury Center (BASIC), Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, United States of America
| | - Adam R Ferguson
- Brain and Spinal Injury Center (BASIC), Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, United States of America
- San Francisco Veterans Affairs Health Care System, San Francisco, California, United States of America
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12
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Banerjee S, Bishop TRP. dsSynthetic: synthetic data generation for the DataSHIELD federated analysis system. BMC Res Notes 2022; 15:230. [PMID: 35761417 PMCID: PMC9235208 DOI: 10.1186/s13104-022-06111-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 06/15/2022] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE Platforms such as DataSHIELD allow users to analyse sensitive data remotely, without having full access to the detailed data items (federated analysis). While this feature helps to overcome difficulties with data sharing, it can make it challenging to write code without full visibility of the data. One solution is to generate realistic, non-disclosive synthetic data that can be transferred to the analyst so they can perfect their code without the access limitation. When this process is complete, they can run the code on the real data. RESULTS We have created a package in DataSHIELD (dsSynthetic) which allows generation of realistic synthetic data, building on existing packages. In our paper and accompanying tutorial we demonstrate how the use of synthetic data generated with our package can help DataSHIELD users with tasks such as writing analysis scripts and harmonising data to common scales and measures.
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Affiliation(s)
- Soumya Banerjee
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Tom R P Bishop
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
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13
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Clegg A, Bandeen-Roche K, Farrin A, Forster A, Gill TM, Gladman J, Kerse N, Lindley R, McManus RJ, Melis R, Mujica-Mota R, Raina P, Rockwood K, Teh R, van der Windt D, Witham M. New horizons in evidence-based care for older people: individual participant data meta-analysis. Age Ageing 2022; 51:afac090. [PMID: 35460409 PMCID: PMC9034697 DOI: 10.1093/ageing/afac090] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/10/2022] [Indexed: 11/13/2022] Open
Abstract
Evidence-based decisions on clinical and cost-effectiveness of interventions are ideally informed by meta-analyses of intervention trial data. However, when undertaken, such meta-analyses in ageing research have typically been conducted using standard methods whereby summary (aggregate) data are extracted from published trial reports. Although meta-analysis of aggregate data can provide useful insights into the average effect of interventions within a selected trial population, it has limitations regarding robust conclusions on which subgroups of people stand to gain the greatest benefit from an intervention or are at risk of experiencing harm. Future evidence synthesis using individual participant data from ageing research trials for meta-analysis could transform understanding of the effectiveness of interventions for older people, supporting evidence-based and sustainable commissioning. A major advantage of individual participant data meta-analysis (IPDMA) is that it enables examination of characteristics that predict treatment effects, such as frailty, disability, cognitive impairment, ethnicity, gender and other wider determinants of health. Key challenges of IPDMA relate to the complexity and resources needed for obtaining, managing and preparing datasets, requiring a meticulous approach involving experienced researchers, frequently with expertise in designing and analysing clinical trials. In anticipation of future IPDMA work in ageing research, we are establishing an international Ageing Research Trialists collective, to bring together trialists with a common focus on transforming care for older people as a shared ambition across nations.
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Affiliation(s)
- Andrew Clegg
- Academic Unit for Ageing & Stroke Research, University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Karen Bandeen-Roche
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Amanda Farrin
- Leeds Institute for Clinical Trials Research, University of Leeds, Leeds, UK
| | - Anne Forster
- Academic Unit for Ageing & Stroke Research, University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Thomas M Gill
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | | | - Ngaire Kerse
- Department of General Practice and Primary Health Care, University of Auckland School of Population Health, Auckland, New Zealand
| | - Richard Lindley
- Sydney Medical School, University of Sydney, Sydney, Australia
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Ruben Mujica-Mota
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Parminder Raina
- Department of Health Evidence and Impact & McMaster Institute for Research on Aging, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Kenneth Rockwood
- Division of Geriatric Medicine, Dalhousie University, Halifax, Canada
| | - Ruth Teh
- Department of General Practice and Primary Health Care, University of Auckland School of Population Health, Auckland, New Zealand
| | | | - Miles Witham
- AGE Research Group, Newcastle University, Newcastle, UK
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14
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Harmonized Phenotypes for Anxiety, Depression, and Attention-Deficit Hyperactivity Disorder (ADHD). JOURNAL OF PSYCHOPATHOLOGY AND BEHAVIORAL ASSESSMENT 2022. [DOI: 10.1007/s10862-021-09925-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
AbstractIn multi-cohort consortia, the problem often arises that a phenotype is measured using different questionnaires. This study aimed to harmonize scores based on the Child Behaviour Check List (CBCL) and the Strength and Difficulties Questionnaire (SDQ) for anxiety/depression and ADHD. To link the scales, we used parent reports on 1330 children aged 10–11.5 years from the Raine study on both SDQ and CBCL. Harmonization was done based on Item Response Theory. We started from existing CBCL and SDQ scales related to anxiety/depression and ADHD (theoretical approach). Next, we conducted a data-driven approach using factor analysis to validate the theoretical approach. Both approaches yielded similar scales, validating the combination of existing scales. In addition, we studied the impact of harmonized (IRT-based) scores on the statistical power of the results in meta-analytic gene-finding studies. The results showed that the IRT-based harmonized scores increased the statistical power of the results compared to sum scores, even with an equal sample size. These findings can help future researchers to harmonize data from different samples and/or different questionnaires that measure anxiety, depression, and ADHD, in order to obtain the larger sample sizes, to compare research results across subpopulations or to increase generalizability, the validity or statistical power of research results. We recommend using our item parameters to estimate harmonized scores that represent commensurate phenotypes across cohorts, and we explained in detail how other researchers can use our results to harmonize data in their studies.
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15
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Pezoulas VC, Goules A, Kalatzis F, Chatzis L, Kourou KD, Venetsanopoulou A, Exarchos TP, Gandolfo S, Votis K, Zampeli E, Burmeister J, May T, Marcelino Pérez M, Lishchuk I, Chondrogiannis T, Andronikou V, Varvarigou T, Filipovic N, Tsiknakis M, Baldini C, Bombardieri M, Bootsma H, Bowman SJ, Soyfoo MS, Parisis D, Delporte C, Devauchelle-Pensec V, Pers JO, Dörner T, Bartoloni E, Gerli R, Giacomelli R, Jonsson R, Ng WF, Priori R, Ramos-Casals M, Sivils K, Skopouli F, Torsten W, A. G. van Roon J, Xavier M, De Vita S, Tzioufas AG, Fotiadis DI. Addressing the clinical unmet needs in primary Sjögren's Syndrome through the sharing, harmonization and federated analysis of 21 European cohorts. Comput Struct Biotechnol J 2022; 20:471-484. [PMID: 35070169 PMCID: PMC8760551 DOI: 10.1016/j.csbj.2022.01.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/30/2021] [Accepted: 01/01/2022] [Indexed: 12/26/2022] Open
Abstract
For many decades, the clinical unmet needs of primary Sjögren's Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-art data analytics services to address the pSS clinical unmet needs, including the development of lymphoma classification models and the identification of biomarkers for lymphomagenesis. The users of the platform have been able to successfully interlink, curate, and harmonize 21 regional, national, and international European cohorts of 7,551 pSS patients with respect to the ethical and legal issues for data sharing. Federated AI algorithms were trained across the harmonized databases, with reduced execution time complexity, yielding robust lymphoma classification models with 85% accuracy, 81.25% sensitivity, 85.4% specificity along with 5 biomarkers for lymphoma development. To our knowledge, this is the first GDPR compliant platform that provides federated AI services to address the pSS clinical unmet needs.
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Affiliation(s)
- Vasileios C. Pezoulas
- Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
| | - Andreas Goules
- Dept. of Pathophysiology, School of Medicine, University of Athens, Athens, Greece
| | - Fanis Kalatzis
- Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
| | - Luke Chatzis
- Dept. of Pathophysiology, School of Medicine, University of Athens, Athens, Greece
| | - Konstantina D. Kourou
- Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
| | - Aliki Venetsanopoulou
- Dept. of Pathophysiology, School of Medicine, University of Athens, Athens, Greece
- University Hospital of Ioannina, Ioannina, Greece
| | - Themis P. Exarchos
- Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
- Dept. of Informatics, Ionian University, Corfu, Greece
| | - Saviana Gandolfo
- Clinic of Rheumatology, Dept. of Medical and Biological Sciences, Udine University, Udine, Italy
| | | | - Evi Zampeli
- Institute for Systemic Autoimmune and Neurological Diseases, Athens, Greece
| | - Jan Burmeister
- Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany
| | - Thorsten May
- Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany
| | | | - Iryna Lishchuk
- Institute of Legal Informatics, Leibniz Universität Hannover, Hannover, Germany
| | - Thymios Chondrogiannis
- Institute of Communication and Computer Systems, School of Electrical and Computer Engineering, National and Technical University of Athens, Athens, Greece
| | - Vassiliki Andronikou
- Institute of Communication and Computer Systems, School of Electrical and Computer Engineering, National and Technical University of Athens, Athens, Greece
| | - Theodora Varvarigou
- Institute of Communication and Computer Systems, School of Electrical and Computer Engineering, National and Technical University of Athens, Athens, Greece
| | - Nenad Filipovic
- Bioengineering Research and Development Center, Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia
| | - Manolis Tsiknakis
- Biomedical Informatics and eHealth Laboratory, Dept. of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Greece
| | - Chiara Baldini
- Dept. of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michele Bombardieri
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts’ Health NHS Trust, London, United Kingdom
| | - Hendrika Bootsma
- Dept. of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Simon J. Bowman
- Rheumatology Dept., University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | | | - Dorian Parisis
- Laboratory of Pathophysiological Biochemistry and Nutrition, Université Libre de Bruxelles, Brussels, Belgium
| | - Christine Delporte
- Laboratory of Pathophysiological Biochemistry and Nutrition, Université Libre de Bruxelles, Brussels, Belgium
| | | | - Jacques-Olivier Pers
- Univ Brest, Inserm, CHU de Brest, UMR1227, Lymphocytes B et Autoimmunité, Brest, France
| | - Thomas Dörner
- Dept. of Rheumatology and Clinical Immunology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Elena Bartoloni
- Rheumatology Unit, Dept. of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Roberto Gerli
- Rheumatology Unit, Dept. of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Roberto Giacomelli
- Division of Rheumatology, Dept. of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Roland Jonsson
- Dept. of Clinical Science, University of Bergen, Bergen, Norway
| | - Wan-Fai Ng
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Roberta Priori
- Dept. of Internal Medicine and Medical Specialties, Rheumatology Clinic, Sapienza University of Rome, Rome, Italy
| | - Manuel Ramos-Casals
- Laboratory of Autoimmune Diseases Josep Font, IDIBAPS-CELLEX, Barcelona, Spain
| | | | - Fotini Skopouli
- Institute for Systemic Autoimmune and Neurological Diseases, Athens, Greece
- Dept. of Internal Medicine and Clinical Immunology, Euroclinic Hospital, Athens, Greece
| | - Witte Torsten
- Dept. of Rheumatology and Immunology, Hanover Medical School, Hanover, Germany
| | - Joel A. G. van Roon
- Dept. of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Mariette Xavier
- Dept. of Rheumatology, Hôpital Bicêtre, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Salvatore De Vita
- Clinic of Rheumatology, Dept. of Medical and Biological Sciences, Udine University, Udine, Italy
| | | | - Dimitrios I. Fotiadis
- Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
- Dept. of Biomedical Research, FORTH-IMBB, Ioannina, Greece
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16
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Bamber D, Collins HE, Powell C, Gonçalves GC, Johnson S, Manktelow B, Ornelas JP, Lopes JC, Rocha A, Draper ES. Development of a data classification system for preterm birth cohort studies: the RECAP Preterm project. BMC Med Res Methodol 2022; 22:8. [PMID: 34996382 PMCID: PMC8742427 DOI: 10.1186/s12874-021-01494-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 12/06/2021] [Indexed: 11/17/2022] Open
Abstract
Background The small sample sizes available within many very preterm (VPT) longitudinal birth cohort studies mean that it is often necessary to combine and harmonise data from individual studies to increase statistical power, especially for studying rare outcomes. Curating and mapping data is a vital first step in the process of data harmonisation. To facilitate data mapping and harmonisation across VPT birth cohort studies, we developed a custom classification system as part of the Research on European Children and Adults born Preterm (RECAP Preterm) project in order to increase the scope and generalisability of research and the evaluation of outcomes across the lifespan for individuals born VPT. Methods The multidisciplinary consortium of expert clinicians and researchers who made up the RECAP Preterm project participated in a four-phase consultation process via email questionnaire to develop a topic-specific classification system. Descriptive analyses were calculated after each questionnaire round to provide pre- and post- ratings to assess levels of agreement with the classification system as it developed. Amendments and refinements were made to the classification system after each round. Results Expert input from 23 clinicians and researchers from the RECAP Preterm project aided development of the classification system’s topic content, refining it from 10 modules, 48 themes and 197 domains to 14 modules, 93 themes and 345 domains. Supplementary classifications for target, source, mode and instrument were also developed to capture additional variable-level information. Over 22,000 individual data variables relating to VPT birth outcomes have been mapped to the classification system to date to facilitate data harmonisation. This will continue to increase as retrospective data items are mapped and harmonised variables are created. Conclusions This bespoke preterm birth classification system is a fundamental component of the RECAP Preterm project’s web-based interactive platform. It is freely available for use worldwide by those interested in research into the long term impact of VPT birth. It can also be used to inform the development of future cohort studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-021-01494-5.
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Affiliation(s)
- Deborah Bamber
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Helen E Collins
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Charlotte Powell
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Gonçalo Campos Gonçalves
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
| | - Samantha Johnson
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Bradley Manktelow
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - José Pedro Ornelas
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
| | - João Correia Lopes
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal.,Faculdade de Engenharia da Universidade do Porto, Porto, Portugal
| | - Artur Rocha
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
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17
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Vaccarino AL, Beaton D, Black SE, Blier P, Farzan F, Finger E, Foster JA, Freedman M, Frey BN, Gilbert Evans S, Ho K, Javadi M, Kennedy SH, Lam RW, Lang AE, Lasalandra B, Latour S, Masellis M, Milev RV, Müller DJ, Munoz DP, Parikh SV, Placenza F, Rotzinger S, Soares CN, Sparks A, Strother SC, Swartz RH, Tan B, Tartaglia MC, Taylor VH, Theriault E, Turecki G, Uher R, Zinman L, Evans KR. Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders. Front Psychiatry 2022; 13:816465. [PMID: 35197877 PMCID: PMC8859302 DOI: 10.3389/fpsyt.2022.816465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 01/12/2022] [Indexed: 11/24/2022] Open
Abstract
The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).
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Affiliation(s)
| | - Derek Beaton
- Data Science and Advanced Analytics, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Dr. Sandra Black Centre for Brain Resilience and Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Pierre Blier
- Mood Disorders Research Unit, University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
| | - Farnak Farzan
- School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Morris Freedman
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, ON, Canada
| | | | - Keith Ho
- Department of Psychiatry, University Health Network, Toronto, ON, Canada
| | | | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J. Safra Program in Parkinson's Disease, University Health Network, Toronto, ON, Canada
| | | | | | - Mario Masellis
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Roumen V Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Sagar V Parikh
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Franca Placenza
- Department of Psychiatry, University Health Network, Toronto, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University Health Network, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Claudio N Soares
- Department of Psychiatry, Queen's University, Kingston, ON, Canada
| | | | - Stephen C Strother
- Indoc Research, Toronto, ON, Canada.,Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Research Program, Dr. Sandra Black Centre for Brain Resilience and Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto, Toronto, ON, Canada
| | - Valerie H Taylor
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Gustavo Turecki
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Lorne Zinman
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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18
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Adhikari K, Patten SB, Patel AB, Premji S, Tough S, Letourneau N, Giesbrecht G, Metcalfe A. Data harmonization and data pooling from cohort studies: a practical approach for data management. Int J Popul Data Sci 2021; 6:1680. [PMID: 34888420 PMCID: PMC8631396 DOI: 10.23889/ijpds.v6i1.1680] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Data pooling from pre-existing datasets can be useful to increase study sample size and statistical power in order to answer a research question. However, individual datasets may contain variables that measure the same construct differently, posing challenges for data pooling. Variable harmonization, an approach that can generate comparable datasets from heterogeneous sources, can address this issue in some circumstances. As an illustrative example, this paper describes the data harmonization strategies that helped generate comparable datasets across two Canadian pregnancy cohort studies: All Our Families; and the Alberta Pregnancy Outcomes and Nutrition. Variables were harmonized considering multiple features across the datasets: the construct measured; question asked/response options; the measurement scale used; the frequency of measurement; timing of measurement, and the data structure. Completely matching, partially matching, and completely un-matching variables across the datasets were determined based on these features. Variables that were an exact match were pooled as is. Partially matching variables were harmonized or processed under a common format across the datasets considering the frequency of measurement, the timing of measurement, the measurement scale used, and response options. Variables that were completely unmatching could not be harmonized into a single variable. The variable harmonization strategies that were used to generate comparable cohort datasets for data pooling are applicable to other data sources. Future studies may employ or evaluate these strategies, which permit researchers to answer novel research questions in a statistically efficient, timely, and cost-efficient manner that could not be achieved using a single data source.
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Affiliation(s)
- Kamala Adhikari
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
| | - Scott B Patten
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
| | - Alka B Patel
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
- Applied Research and Evaluation- Primary Health Care, Alberta Health Services, Calgary, Canada
| | - Shahirose Premji
- School of Nursing, Faculty of Health, York University, Calgary, Canada
| | - Suzanne Tough
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
- Department of Pediatrics, University of Calgary, Calgary, Canada
| | - Nicole Letourneau
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
- Department of Pediatrics, University of Calgary, Calgary, Canada
- Faculty of Nursing University of Calgary, Calgary, Canada
- Deprtment of Psychiatry, University of Calgary, Calgary, Canada
| | - Gerald Giesbrecht
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
- Department of Pediatrics, University of Calgary, Calgary, Canada
| | - Amy Metcalfe
- Department of Community Health Sciences, University of Calgary, Calgary, Canada
- Department of Obstetrics and Gynecology, University of Calgary, Calgary, Canada
- Department of Medicine, University of Calgary, Calgary, Canada
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19
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Sanchez-Niubo A, Forero CG, Wu YT, Giné-Vázquez I, Prina M, De La Fuente J, Daskalopoulou C, Critselis E, De La Torre-Luque A, Panagiotakos D, Arndt H, Ayuso-Mateos JL, Bayes-Marin I, Bickenbach J, Bobak M, Caballero FF, Chatterji S, Egea-Cortés L, García-Esquinas E, Leonardi M, Koskinen S, Koupil I, Mellor-Marsá B, Olaya B, Pająk A, Prince M, Raggi A, Rodríguez-Artalejo F, Sanderson W, Scherbov S, Tamosiunas A, Tobias-Adamczyk B, Tyrovolas S, Haro JM. Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium. Int J Epidemiol 2021; 50:880-892. [PMID: 33274372 PMCID: PMC8271194 DOI: 10.1093/ije/dyaa236] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/23/2020] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Research efforts to measure the concept of healthy ageing have been diverse and limited to specific populations. This diversity limits the potential to compare healthy ageing across countries and/or populations. In this study, we developed a novel measurement scale of healthy ageing using worldwide cohorts. METHODS In the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) project, data from 16 international cohorts were harmonized. Using ATHLOS data, an item response theory (IRT) model was used to develop a scale with 41 items related to health and functioning. Measurement heterogeneity due to intra-dataset specificities was detected, applying differential item functioning via a logistic regression framework. The model accounted for specificities in model parameters by introducing cohort-specific parameters that rescaled scores to the main scale, using an equating procedure. Final scores were estimated for all individuals and converted to T-scores with a mean of 50 and a standard deviation of 10. RESULTS A common scale was created for 343 915 individuals above 18 years of age from 16 studies. The scale showed solid evidence of concurrent validity regarding various sociodemographic, life and health factors, and convergent validity with healthy life expectancy (r = 0.81) and gross domestic product (r = 0.58). Survival curves showed that the scale could also be predictive of mortality. CONCLUSIONS The ATHLOS scale, due to its reliability and global representativeness, has the potential to contribute to worldwide research on healthy ageing.
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Affiliation(s)
- Albert Sanchez-Niubo
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
| | - Carlos G Forero
- Department of Medicine, International University of Catalunya, Barcelona, Spain
| | - Yu-Tzu Wu
- Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Iago Giné-Vázquez
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
| | - Matthew Prina
- Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Global Health Institute, King's College London, London, UK
| | - Javier De La Fuente
- Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Investigación Sanitaria Princesa (IIS Princesa), Hospital Universitario de La Princesa, Madrid, Spain
| | - Christina Daskalopoulou
- Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Elena Critselis
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University, Athens, Greece
| | - Alejandro De La Torre-Luque
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain.,Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Investigación Sanitaria Princesa (IIS Princesa), Hospital Universitario de La Princesa, Madrid, Spain
| | - Demosthenes Panagiotakos
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University, Athens, Greece
| | | | - José Luis Ayuso-Mateos
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain.,Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Investigación Sanitaria Princesa (IIS Princesa), Hospital Universitario de La Princesa, Madrid, Spain
| | - Ivet Bayes-Marin
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
| | - Jerome Bickenbach
- Swiss Paraplegic Research, Guido A. Zäch Institute (GZI), Nottwil, Switzerland.,Department of Health Sciences & Health Policy, University of Lucerne, Lucerne, Switzerland
| | - Martin Bobak
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Francisco Félix Caballero
- Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid/Idipaz, Madrid, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, CIBERESP, Madrid, Spain
| | - Somnath Chatterji
- Information, Evidence and Research, World Health Organization, Geneva, Switzerland
| | - Laia Egea-Cortés
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
| | - Esther García-Esquinas
- Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid/Idipaz, Madrid, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, CIBERESP, Madrid, Spain
| | - Matilde Leonardi
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Seppo Koskinen
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Ilona Koupil
- Department of Public Health Sciences, Stockholm University, Stockholm, Sweden.,Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Blanca Mellor-Marsá
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Sanitary Research Institute, Hospital Clínico San Carlos, Madrid, Spain
| | - Beatriz Olaya
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
| | - Andrzej Pająk
- Department of Epidemiology and Population Studies, Jagiellonian University Medical College, Krakow, Poland
| | - Martin Prince
- Global Health Institute, King's College London, London, UK.,Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Alberto Raggi
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Fernando Rodríguez-Artalejo
- Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid/Idipaz, Madrid, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, CIBERESP, Madrid, Spain
| | - Warren Sanderson
- Wittgenstein Centre for Demography and Global Human Capital, International Institute for Applied Systems Analysis, Laxenburg, Austria.,Department of Economics, Stony Brook University, Stony Brook, NY, USA
| | - Sergei Scherbov
- Wittgenstein Centre for Demography and Global Human Capital, International Institute for Applied Systems Analysis, Laxenburg, Austria.,Austrian Academy of Science, Vienna Institute of Demography, Vienna, Austria.,International Laboratory of Demography and Human Capital, Russian Presidential Academy of National Economy and Public Administration, Moscow, Russian Federation
| | - Abdonas Tamosiunas
- Department of Population Studies Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Beata Tobias-Adamczyk
- Department of Medical Sociology, Jagiellonian University Medical College, Krakow, Poland.,Department of Epidemiology, Jagiellonian University Medical College, Krakow, Poland
| | - Stefanos Tyrovolas
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
| | - Josep Maria Haro
- Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.,Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
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20
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Ginsburg GS, Cavallari LH, Chakraborty H, Cooper-DeHoff RM, Dexter PR, Eadon MT, Ferket BS, Horowitz CR, Johnson JA, Kannry J, Kucher N, Madden EB, Orlando LA, Parker W, Peterson J, Pratt VM, Rakhra-Burris TK, Ramos MA, Skaar TC, Sperber N, Steen-Burrell KA, Van Driest SL, Voora D, Wiisanen K, Winterstein AG, Volpi S. Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network. Genet Med 2021; 23:1185-1191. [PMID: 33782552 PMCID: PMC8263480 DOI: 10.1038/s41436-021-01118-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.
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Affiliation(s)
- Geoffrey S Ginsburg
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA.
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | | | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Paul R Dexter
- School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Michael T Eadon
- Division of Clinical Pharmacology, Indiana University, Indianapolis, IN, USA
| | - Bart S Ferket
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Carol R Horowitz
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Joseph Kannry
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Natalie Kucher
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Ebony B Madden
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Lori A Orlando
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA
| | - Wanda Parker
- Duke Clinical Research Institute, Duke University, Durham, NC, USA
| | - Josh Peterson
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Victoria M Pratt
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | | | - Michelle A Ramos
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Indiana University, Indianapolis, IN, USA
| | - Nina Sperber
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA.,Department of Population Health Sciences, Duke Margolis Center for Health Policy, Durham VA Health Services Research & Development Service, Duke Center for Applied Genomics & Precision Medicine, Durham, NC, USA
| | | | - Sara L Van Driest
- Department of Pediatrics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Deepak Voora
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Almut G Winterstein
- Department of Pharmaceutical Outcomes and Policy, Center for Drug Evaluation and Safety, University of Florida, Gainesville, FL, USA
| | - Simona Volpi
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
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21
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Royal CDM, Babyak M, Shah N, Srivatsa S, Stewart KA, Tanabe P, Wonkam A, Asnani M. Sickle cell disease is a global prototype for integrative research and healthcare. ADVANCED GENETICS (HOBOKEN, N.J.) 2021; 2:e10037. [PMID: 36618444 PMCID: PMC9744540 DOI: 10.1002/ggn2.10037] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 12/28/2020] [Accepted: 12/29/2020] [Indexed: 02/06/2023]
Abstract
Differences in health outcomes and treatment responses within and between global populations have been well documented. There is growing recognition of the need to move beyond simple inventories and descriptions of these differences and our linear explanations for them, and gain a better understanding of the multifaceted systems and networks underlying them in order to develop more precise and effective remedies. Typical targets for such integrative research have been common multifactorial diseases. We propose sickle cell disease, one of the most common monogenic diseases, as an ideal candidate for elucidating the complexity of the influences of endogenous and exogenous factors on disease pathophysiology, phenotypic diversity, and variations in responses to treatments at both the individual and population levels. We provide data-informed representations of diverse contributors to sickle cell disease complications that could guide innovative efforts to advance scientific knowledge, clinical practice, and policy formulation related to the disease; help improve outcomes for people worldwide with sickle cell disease; and inform approaches to studying and addressing other diseases.
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Affiliation(s)
- Charmaine D. M. Royal
- Department of African & African American StudiesDuke UniversityDurhamNorth CarolinaUSA
- Duke Global Health InstituteDuke UniversityDurhamNorth CarolinaUSA
- Center on Genomics, Race, Identity, DifferenceDuke UniversityDurhamNorth CarolinaUSA
| | - Michael Babyak
- Department of Psychiatry and Behavioral SciencesDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Nirmish Shah
- Department of MedicineDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Shantanu Srivatsa
- Center on Genomics, Race, Identity, DifferenceDuke UniversityDurhamNorth CarolinaUSA
| | | | - Paula Tanabe
- Department of MedicineDuke University School of MedicineDurhamNorth CarolinaUSA
- Duke University School of NursingDurhamNorth CarolinaUSA
| | - Ambroise Wonkam
- Division of Human Genetics, Department of Medicine, Faculty of Health SciencesUniversity of Cape TownCape TownSouth Africa
- Faculty of Medicine and Biomedical SciencesUniversity of Yaoundé 1YaoundéCameroon
| | - Monika Asnani
- Caribbean Institute for Health Research ‐ Sickle Cell UnitThe University of the West IndiesKingstonJamaica
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22
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Patti MA, Newschaffer C, Eliot M, Hamra GB, Chen A, Croen LA, Fallin MD, Hertz-Picciotto I, Kalloo G, Khoury JC, Lanphear BP, Lyall K, Yolton K, Braun JM. Gestational Exposure to Phthalates and Social Responsiveness Scores in Children Using Quantile Regression: The EARLI and HOME Studies. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:1254. [PMID: 33573264 PMCID: PMC7908417 DOI: 10.3390/ijerph18031254] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/18/2021] [Accepted: 01/22/2021] [Indexed: 12/24/2022]
Abstract
Linear regression is often used to estimate associations between chemical exposures and neurodevelopment at the mean of the outcome. However, the potential effect of chemicals may be greater among individuals at the 'tails' of outcome distributions. Here, we investigated distributional effects on the associations between gestational phthalate exposure and child Autism Spectrum Disorder (ASD)-related behaviors using quantile regression. We harmonized data from the Early Autism Risk Longitudinal Investigation (EARLI) (n = 140) Study, an enriched-risk cohort of mothers who had a child with ASD, and the Health Outcomes and Measures of the Environment (HOME) Study (n = 276), a general population cohort. We measured concentrations of 9 phthalate metabolites in urine samples collected twice during pregnancy. Caregivers reported children's ASD-related behaviors using the Social Responsiveness Scale (SRS) at age 3-8 years; higher scores indicate more ASD-related behaviors. In EARLI, associations between phthalate concentrations and SRS scores were predominately inverse or null across SRS score quantiles. In HOME, positive associations of mono-n-butyl phthalate, monobenzyl phthalate, mono-isobutyl phthalate, and di-2-ethylhexyl phthalate concentrations with SRS scores increased in strength from the median to 95th percentile of SRS scores. These results suggest associations between phthalate concentrations and SRS scores may be stronger in individuals with higher SRS scores.
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Affiliation(s)
- Marisa A. Patti
- Department of Epidemiology, Brown University, Providence, RI 02903, USA; (M.E.); (J.M.B.)
| | - Craig Newschaffer
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA 19104, USA; (C.N.); (K.L.)
- College of Health & Human Development, Pennsylvania State University, State College, PA 16801, USA
| | - Melissa Eliot
- Department of Epidemiology, Brown University, Providence, RI 02903, USA; (M.E.); (J.M.B.)
| | - Ghassan B. Hamra
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21205, USA;
| | - Aimin Chen
- Department of Biostatistics Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Lisa A. Croen
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA;
| | - M. Daniele Fallin
- Department of Mental Health, Johns Hopkins University, Baltimore, MD 21205, USA;
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, University of California, Davis, CA 95616, USA;
| | | | - Jane C. Khoury
- Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45267, USA;
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA;
| | - Bruce P. Lanphear
- Faculty of Health Sciences, Simon Fraser University, Vancouver, BC, Canada;
| | - Kristen Lyall
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA 19104, USA; (C.N.); (K.L.)
| | - Kimberly Yolton
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA;
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45267, USA
| | - Joseph M. Braun
- Department of Epidemiology, Brown University, Providence, RI 02903, USA; (M.E.); (J.M.B.)
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23
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Centralizing environmental datasets to support (inter)national chronic disease research: Values, challenges, and recommendations. Environ Epidemiol 2021; 5:e129. [PMID: 33778361 PMCID: PMC7939427 DOI: 10.1097/ee9.0000000000000129] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 12/23/2020] [Indexed: 11/22/2022] Open
Abstract
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.
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24
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Patti MA, Li N, Eliot M, Newschaffer C, Yolton K, Khoury J, Chen A, Lanphear BP, Lyall K, Hertz-Picciotto I, Fallin MD, Croen LA, Braun JM. Association between self-reported caffeine intake during pregnancy and social responsiveness scores in childhood: The EARLI and HOME studies. PLoS One 2021; 16:e0245079. [PMID: 33449933 PMCID: PMC7810310 DOI: 10.1371/journal.pone.0245079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 12/21/2020] [Indexed: 01/08/2023] Open
Abstract
Maternal nutrition during gestation has been investigated for its role in child neurodevelopment. However, little is known about the potential impact of gestational caffeine exposure on child autistic behaviors. Here, we assess the relation between maternal caffeine intake during pregnancy and children's behavioral traits related to Autism Spectrum Disorder (ASD). We harmonized data from two pregnancy cohorts, Early Autism Risk Longitudinal Investigation (EARLI) (n = 120), an enriched-risk cohort of mothers who previously had a child with ASD, from Pennsylvania, Maryland, and Northern California (2009-2012), and the Health Outcomes and Measures of the Environment (HOME) Study (n = 269), a general population cohort from Cincinnati, Ohio (2003-2006). Mothers self-reported caffeine intake twice during pregnancy. Caregivers reported child behavioral traits related to ASD using the Social Responsiveness Scale (SRS) when children were aged 3-8 years. Higher scores indicate more ASD-related behaviors. We estimated covariate-adjusted differences in continuous SRS T-scores per interquartile range increase in caffeine intake. Self-reported caffeine intake during pregnancy was positively associated with SRS T-scores among children in EARLI (β: 2.0; 95% CI -0.1, 4.0), but to a lesser extent in HOME (β: 0.6; 95% CI -0.5, 1.6). In HOME, pre-pregnancy body mass index (BMI) modified the association between caffeine intake and SRS T-scores, where more positive associations were observed among women with higher BMIs. Our findings suggest gestational caffeine intake may represent a marker of vulnerability to childhood ASD-related behaviors. Additional studies are warranted to extend these findings.
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Affiliation(s)
- Marisa A. Patti
- Department of Epidemiology, Brown University, Providence, Rhode Island, United States of America
| | - Nan Li
- Department of Epidemiology, Brown University, Providence, Rhode Island, United States of America
| | - Melissa Eliot
- Department of Epidemiology, Brown University, Providence, Rhode Island, United States of America
| | - Craig Newschaffer
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania, United States of America
- College of Health & Human Development, Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Kimberly Yolton
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio United States of America
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Jane Khoury
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio United States of America
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Aimin Chen
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Bruce P. Lanphear
- Department of Health Sciences, Simon Fraser University, British Columbia, Vancouver, Canada
| | - Kristen Lyall
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania, United States of America
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, University of California, Davis, California, United States of America
| | - Margaret Daniele Fallin
- Department of Mental Health, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Lisa A. Croen
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Joseph M. Braun
- Department of Epidemiology, Brown University, Providence, Rhode Island, United States of America
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25
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Mc Dowell CP, Carlin A, Capranica L, Dillon C, Harrington JM, Lakerveld J, Loyen A, Ling FCM, Brug J, MacDonncha C, Herring MP. Associations of self-reported physical activity and anxiety symptoms and status among 7,874 Irish adults across harmonised datasets: a DEDIPAC-study. BMC Public Health 2020; 20:365. [PMID: 32192475 PMCID: PMC7082967 DOI: 10.1186/s12889-020-08481-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 03/09/2020] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Anxiety is an adaptive response to an objective or perceived threat; however, when symptoms become severe and chronic it that can become a maladaptive anxiety disorder. Limited evidence suggests that physical activity may be associated with prevention against anxiety. This study uses data from The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study to investigate cross-sectional associations between physical activity and anxiety symptoms and status among Irish adults. METHODS Both datasets were harmonized (n = 7874). The short form International Physical Activity Questionnaire measured physical activity. Participants were classified as meeting World Health Organization physical activity guidelines (≥150 min weekly of moderate intensity physical activity, ≥75 min weekly of vigorous intensity physical activity, or ≥ 600 MET-minutes) or not. They were also divided into three groups based on weekly MET-minutes of moderate-to-vigorous physical activity (Low: 0-599; Moderate: 600-1199; High: ≥1200), and three groups based on weekly minutes of walking (Low: 0-209; Moderate: 210-419; High: 420+). Anxiety symptoms were measured by the Hospital Anxiety and Depression Scale with a score of ≥8 indicating anxiety. Binomial logistic regression, adjusted for relevant confounders examined physical activity-anxiety associations. RESULTS Females had higher rates of anxiety than males (28.0% vs 20.0%; p < 0.001). Following adjustment for relevant covariates, meeting physical activity guidelines was associated with 13.5% (95% CI: 2.0-23.7; p = 0.023) lower odds of anxiety. Moderate and High physical activity were associated with 13.5% (- 11.0-32.6; p = 0.254) and 13.6% (1.4-4.2; p = 0.030) lower odds of anxiety compared to Low physical activity, respectively. Moderate and High walking were associated with 2.1% (- 14.5-16.3; p = 0.789) and 5.1% (- 9.3-17.6; p = 0.467) lower odds of anxiety compared to Low walking, respectively. CONCLUSION Meeting physical activity guidelines is associated with lower odds of anxiety, but the strength of associations did not increase considerably with increased physical activity levels.
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Affiliation(s)
- Cillian P. Mc Dowell
- The Irish Longitudinal Study on Ageing (TILDA), Lincoln Gate, Trinity College Dublin, Dublin 2, Ireland
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Health Research Institute, University of Limerick, Limerick, Ireland
| | - Angela Carlin
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Centre for Exercise Medicine, Physical Activity and Health, Sport and Exercise Sciences Research Institute, Ulster University, Northern Ireland, UK
| | - Laura Capranica
- Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Rome, Italy
| | | | | | - Jeroen Lakerveld
- Department of Epidemiology and Biostatistics, Amsterdam UMC, VU University Medical Center, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
- Global Geo Health Data Center, Utrecht University, Utrecht, The Netherlands
| | - Anne Loyen
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Fiona Chun Man Ling
- Department of Sport, Exercise & Rehabilitation, Northumbria University, Newcastle upon Tyne, UK
| | - Johannes Brug
- Amsterdam School for Communication Research, University of Amsterdam, Amsterdam, the Netherlands
- National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Ciaran MacDonncha
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Health Research Institute, University of Limerick, Limerick, Ireland
| | - Matthew P. Herring
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Health Research Institute, University of Limerick, Limerick, Ireland
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Immediate Breast Reconstruction in The Netherlands and the United States: A Proof-of-Concept to Internationally Compare Quality of Care Using Cancer Registry Data. Plast Reconstr Surg 2019; 144:565e-574e. [PMID: 31568284 DOI: 10.1097/prs.0000000000006011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Studies based on large-volume databases have made significant contributions to research on breast cancer surgery. To date, no comparison between large-volume databases has been made internationally. This is the first proof-of-concept study exploring the feasibility of combining two existing operational databases of The Netherlands and the United States, focusing on breast cancer care and immediate breast reconstruction specifically.313/291 METHODS:: The National Breast Cancer Organization The Netherlands Breast Cancer Audit (NBCA) (2011 to 2015) and the U.S. Surveillance, Epidemiology, and End Results (SEER) database (2010 to 2013) were compared on structure and content. Data variables were grouped into general, treatment-specific, cancer-specific, and follow-up variables and were matched. As proof-of-concept, mastectomy and immediate breast reconstruction rates in patients diagnosed with invasive breast cancer or ductal carcinoma in situ were analyzed. RESULTS The NBCA included 115 variables and SEER included 112. The NBCA included significantly more treatment-specific variables (n = 46 versus 6), whereas the SEER database included more cancer-specific variables (n = 74 versus 26). In patients diagnosed with breast cancer or ductal carcinoma in situ, immediate breast reconstruction was performed in 19.3 percent and 24.0 percent of the breast cancer cohort and 44.0 percent and 35.3 percent of the ductal carcinoma in situ cohort in the NBCA and SEER, respectively. Immediate breast reconstruction rates increased significantly over time in both data sets. CONCLUSIONS This study provides a first overview of available registry data on breast cancer care in The Netherlands and the United States, and revealed limited data on treatment in the United States. Comparison of treatment patterns of immediate breast reconstruction showed interesting differences. The authors advocate the urgency for an international database with alignment of (treatment) variables to improve quality of breast cancer care for patients across the globe.
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Fortier I, Dragieva N, Saliba M, Craig C, Robson PJ. Harmonization of the Health and Risk Factor Questionnaire data of the Canadian Partnership for Tomorrow Project: a descriptive analysis. CMAJ Open 2019; 7:E272-E282. [PMID: 31018973 PMCID: PMC6498449 DOI: 10.9778/cmajo.20180062] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND The Canadian Partnership for Tomorrow Project is a multistudy platform integrating the British Columbia Generations Project, Alberta's Tomorrow Project, the Ontario Health Study, CARTaGENE (Quebec) and the Atlantic Partnership for Tomorrow's Health. This paper describes the process used to harmonize the Health and Risk Factor Questionnaire data and provides an overview of the key information required to properly use the core data set generated. METHODS This is a descriptive analysis of the harmonization process that was developed on the basis of the Maelstrom Research guidelines for retrospective harmonization. Core variables (DataSchema) to be generated across cohorts were defined and the potential for cohort-specific data sets to generate the DataSchema variables was assessed. Where relevant, algorithms were developed and applied to process cohort-specific data into the DataSchema format, and information to be provided to data users was documented. RESULTS The Health and Risk Factor Questionnaire DataSchema (version 2.0, October 2017) comprised 694 variables. The assessment of harmonization potential for the variables over 12 cohort-specific data sets resulted in 6799 (81.6%) of the variables being considered as harmonizable. A total of 307 017 participants were included in the harmonized data set. Through the cohort data portal, researchers can find information about the definitions of variables, harmonization potential, algorithms applied to generate harmonized variables and participant distributions. INTERPRETATION The harmonization process enabled the creation of a unique data set including data on health and risk factors from over 307 000 Canadians. These data, in combination with complementary data sets, can be used to investigate the impact of biological, environmental and behavioural factors on cancer and chronic diseases.
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Affiliation(s)
- Isabel Fortier
- Research Institute of the McGill University Health Centre (Fortier, Dragieva, Saliba); Centre hospitalier de l'Université de Montréal (CHUM) Research Centre (Craig), Montréal, Que.; CancerControl Alberta and Cancer Strategic Clinical Network (Robson), Alberta Health Services; Department of Agricultural, Food and Nutritional Science (Robson), Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alta.
| | - Nataliya Dragieva
- Research Institute of the McGill University Health Centre (Fortier, Dragieva, Saliba); Centre hospitalier de l'Université de Montréal (CHUM) Research Centre (Craig), Montréal, Que.; CancerControl Alberta and Cancer Strategic Clinical Network (Robson), Alberta Health Services; Department of Agricultural, Food and Nutritional Science (Robson), Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alta
| | - Matilda Saliba
- Research Institute of the McGill University Health Centre (Fortier, Dragieva, Saliba); Centre hospitalier de l'Université de Montréal (CHUM) Research Centre (Craig), Montréal, Que.; CancerControl Alberta and Cancer Strategic Clinical Network (Robson), Alberta Health Services; Department of Agricultural, Food and Nutritional Science (Robson), Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alta
| | - Camille Craig
- Research Institute of the McGill University Health Centre (Fortier, Dragieva, Saliba); Centre hospitalier de l'Université de Montréal (CHUM) Research Centre (Craig), Montréal, Que.; CancerControl Alberta and Cancer Strategic Clinical Network (Robson), Alberta Health Services; Department of Agricultural, Food and Nutritional Science (Robson), Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alta
| | - Paula J Robson
- Research Institute of the McGill University Health Centre (Fortier, Dragieva, Saliba); Centre hospitalier de l'Université de Montréal (CHUM) Research Centre (Craig), Montréal, Que.; CancerControl Alberta and Cancer Strategic Clinical Network (Robson), Alberta Health Services; Department of Agricultural, Food and Nutritional Science (Robson), Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alta
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Benet M, Albang R, Pinart M, Hohmann C, Tischer CG, Annesi-Maesano I, Baïz N, Bindslev-Jensen C, Lødrup Carlsen KC, Carlsen KH, Cirugeda L, Eller E, Fantini MP, Gehring U, Gerhard B, Gori D, Hallner E, Kull I, Lenzi J, McEachan R, Minina E, Momas I, Narduzzi S, Petherick ES, Porta D, Rancière F, Standl M, Torrent M, Wijga AH, Wright J, Kogevinas M, Guerra S, Sunyer J, Keil T, Bousquet J, Maier D, Anto JM, Garcia-Aymerich J. Integrating Clinical and Epidemiologic Data on Allergic Diseases Across Birth Cohorts: A Harmonization Study in the Mechanisms of the Development of Allergy Project. Am J Epidemiol 2019; 188:408-417. [PMID: 30351340 DOI: 10.1093/aje/kwy242] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 10/16/2018] [Indexed: 12/27/2022] Open
Abstract
The numbers of international collaborations among birth cohort studies designed to better understand asthma and allergies have increased in the last several years. However, differences in definitions and methods preclude direct pooling of original data on individual participants. As part of the Mechanisms of the Development of Allergy (MeDALL) Project, we harmonized data from 14 birth cohort studies (each with 3-20 follow-up periods) carried out in 9 European countries during 1990-1998 or 2003-2009. The harmonization process followed 6 steps: 1) organization of the harmonization panel; 2) identification of variables relevant to MeDALL objectives (candidate variables); 3) proposal of a definition for each candidate variable (reference definition); 4) assessment of the compatibility of each cohort variable with its reference definition (inferential equivalence) and classification of this inferential equivalence as complete, partial, or impossible; 5) convocation of a workshop to agree on the reference definitions and classifications of inferential equivalence; and 6) preparation and delivery of data through a knowledge management portal. We agreed on 137 reference definitions. The inferential equivalence of 3,551 cohort variables to their corresponding reference definitions was classified as complete, partial, and impossible for 70%, 15%, and 15% of the variables, respectively. A harmonized database was delivered to MeDALL investigators. In asthma and allergy birth cohorts, the harmonization of data for pooled analyses is feasible, and high inferential comparability may be achieved. The MeDALL harmonization approach can be used in other collaborative projects.
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Affiliation(s)
- Marta Benet
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
| | | | - Mariona Pinart
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Cynthia Hohmann
- Institute for Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christina G Tischer
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
| | - Isabella Annesi-Maesano
- Epidemiology of Allergic and Respiratory Diseases Department, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Institut National de la Santé et de la Recherche Médicale, Paris, France
- Saint-Antoine Medical School, Université Pierre et Marie Curie, Paris, France
| | - Nour Baïz
- Epidemiology of Allergic and Respiratory Diseases Department, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Institut National de la Santé et de la Recherche Médicale, Paris, France
- Saint-Antoine Medical School, Université Pierre et Marie Curie, Paris, France
| | - Carsten Bindslev-Jensen
- Odense Research Center for Anaphylaxis, Department of Dermatology and Allergy Center, Odense University Hospital, Odense, Denmark
| | - Karin C Lødrup Carlsen
- Department of Paediatric Allergy and Pulmonology, Division of Paediatric and Adolescent Medicine, Faculty of Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Kai-Hakon Carlsen
- Department of Paediatric Allergy and Pulmonology, Division of Paediatric and Adolescent Medicine, Faculty of Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Lourdes Cirugeda
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
| | - Esben Eller
- Odense Research Center for Anaphylaxis, Department of Dermatology and Allergy Center, Odense University Hospital, Odense, Denmark
| | - Maria Pia Fantini
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum–University of Bologna, Bologna, Italy
| | - Ulrike Gehring
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | | | - Davide Gori
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum–University of Bologna, Bologna, Italy
| | - Eva Hallner
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Inger Kull
- Sachs’ Children and Youth Hospital, South General Hospital Stockholm, Stockholm, Sweden
- Department of Clinical Science and Education, Karolinska Institutet, Stockholm, Sweden
| | - Jacopo Lenzi
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum–University of Bologna, Bologna, Italy
| | - Rosemary McEachan
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | | | - Isabelle Momas
- Université Paris Descartes, Sorbonne Paris Cité, EA 4064 Epidémiologie Environnementale, Paris, France
- Mairie de Paris, Direction de l’Action Sociale de l’Enfance et de la Santé, Cellule Cohorte, Paris, France
| | - Silvia Narduzzi
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Emily S Petherick
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - Daniela Porta
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Fanny Rancière
- Université Paris Descartes, Sorbonne Paris Cité, EA 4064 Epidémiologie Environnementale, Paris, France
| | - Marie Standl
- Institute of Epidemiology I, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
| | - Maties Torrent
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
- Servei de Salut de les Illes Balears, Area de Salut de Menorca, Spain
| | - Alet H Wijga
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Manolis Kogevinas
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- National School of Public Health, Athens, Greece
| | - Stefano Guerra
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
- Asthma and Airway Disease Research Center, University of Arizona, Tucson, Arizona
| | - Jordi Sunyer
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Thomas Keil
- Institute for Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jean Bousquet
- Contre les Maladies Chroniques pour un Vieillissement Actif en France, European Innovation Partnership on Active and Healthy Ageing Reference Site, Montpellier, France
- Institut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche 1168
| | | | - Josep M Anto
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Judith Garcia-Aymerich
- ISGlobal
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Consorcio Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
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29
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Sundström J, Björkelund C, Giedraitis V, Hansson PO, Högman M, Janson C, Koupil I, Kristenson M, Trolle Lagerros Y, Leppert J, Lind L, Lissner L, Johansson I, Ludvigsson JF, Nilsson PM, Olsson H, Pedersen NL, Rosenblad A, Rosengren A, Sandin S, Snäckerström T, Stenbeck M, Söderberg S, Weiderpass E, Wanhainen A, Wennberg P, Fortier I, Heller S, Storgärds M, Svennblad B. Rationale for a Swedish cohort consortium. Ups J Med Sci 2019; 124:21-28. [PMID: 30618330 PMCID: PMC6450580 DOI: 10.1080/03009734.2018.1556754] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
We herein outline the rationale for a Swedish cohort consortium, aiming to facilitate greater use of Swedish cohorts for world-class research. Coordination of all Swedish prospective population-based cohorts in a common infrastructure would enable more precise research findings and facilitate research on rare exposures and outcomes, leading to better utilization of study participants' data, better return of funders' investments, and higher benefit to patients and populations. We motivate the proposed infrastructure partly by lessons learned from a pilot study encompassing data from 21 cohorts. We envisage a standing Swedish cohort consortium that would drive development of epidemiological research methods and strengthen the Swedish as well as international epidemiological competence, community, and competitiveness.
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Affiliation(s)
- Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center (UCR), Uppsala, Sweden
- CONTACT Johan Sundström
| | - Cecilia Björkelund
- Department of Public Health and Community Medicine/Primary Health Care, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Per-Olof Hansson
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Marieann Högman
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Christer Janson
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Ilona Koupil
- Department of Public Health Sciences, Stockholm University, Stockholm, Sweden
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Margareta Kristenson
- Department of Medical and Health Sciences, Division of Community Medicine, Linköping University, Linköping, Sweden
| | - Ylva Trolle Lagerros
- Department of Medicine, Unit of Clinical Epidemiology, Karolinska Institutet, Stockholm, Sweden
- Department of Endocrinology, Metabolism and Diabetes, Karolinska University Hospital Huddinge, Huddinge, Sweden
| | - Jerzy Leppert
- Västerås Centre for Clinical Research, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Lauren Lissner
- Department of Public Health and Community Medicine/Epidemiology and Social Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Ingegerd Johansson
- Department of Odontology, School of Dentistry, Umeå University, Umeå, Sweden
| | - Jonas F. Ludvigsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Pediatrics, Örebro University Hospital, Örebro University, Örebro, Sweden
| | - Peter M. Nilsson
- Department of Clinical Sciences, Skane University Hospital, Malmö, Lund University, Lund, Sweden
| | - Håkan Olsson
- Department of Clinical Sciences, Cancer Epidemiology, Lund University, Lund, Sweden
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Andreas Rosenblad
- Västerås Centre for Clinical Research, Uppsala University, Uppsala, Sweden
| | - Annika Rosengren
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sven Sandin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Seaver Autism Center for Research and Treatment at Mount Sinai, New York, NY, USA
| | | | - Magnus Stenbeck
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Söderberg
- Department of Public Health and Clinical Medicine, and Heart Center, Umeå University, Umeå, Sweden
| | - Elisabete Weiderpass
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
- Genetic Epidemiology Group, Folkhälsan Research Center, Faculty of Medicine, Helsinki University, Helsinki, Finland
- Department of Community Medicine, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
| | - Anders Wanhainen
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Patrik Wennberg
- Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, Umeå, Sweden, and
| | - Isabel Fortier
- Research Institute of the McGill University Health Centre, Montreal, Canada
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30
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Kourou KD, Pezoulas VC, Georga EI, Exarchos TP, Tsanakas P, Tsiknakis M, Varvarigou T, De Vita S, Tzioufas A, Fotiadis DI. Cohort Harmonization and Integrative Analysis From a Biomedical Engineering Perspective. IEEE Rev Biomed Eng 2019; 12:303-318. [DOI: 10.1109/rbme.2018.2855055] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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31
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Singh A, Babyak MA, Brummett BH, Kraus WE, Siegler IC, Hauser ER, Williams RB. Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses. BMC Res Notes 2018; 11:504. [PMID: 30041705 PMCID: PMC6057001 DOI: 10.1186/s13104-018-3595-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 07/12/2018] [Indexed: 01/13/2023] Open
Abstract
Objectives Among many challenges in cardiovascular disease (CVD) risk prediction are interactions of genes with stress, race, and/or sex and developing robust estimates of these interactions. Improved power with larger sample size contributed by the accumulation of epidemiological data could be helpful, but integration of these datasets is difficult due the absence of standardized phenotypic measures. In this paper, we describe the details of our undertaking to harmonize a dozen datasets and provide a detailed account of a number of decisions made in the process. Results We harmonized candidate genetic variants and CVD-risk variables related to demography, adiposity, hypertension, lipodystrophy, hypertriglyceridemia, hyperglycemia, depressive symptom, and chronic psychosocial stress from a dozen studies. Using our synthetic stress algorithm, we constructed a synthetic chronic psychosocial stress measure in nine out of twelve studies where a formal self-rated stress measure was not available. The mega-analytic partial correlation between the stress measure and depressive symptoms while controlling for the effect of study variable in the combined dataset was significant (Rho = 0.27, p < 0.0001). This evidence of the validity and the detailed account of our data harmonization approaches demonstrated that it is possible to overcome the inconsistencies in the collection and measurement of human health risk variables. Electronic supplementary material The online version of this article (10.1186/s13104-018-3595-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Abanish Singh
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham, NC, USA. .,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA. .,Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA.
| | - Michael A Babyak
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Beverly H Brummett
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - William E Kraus
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA.,Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ilene C Siegler
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Elizabeth R Hauser
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA.,Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA
| | - Redford B Williams
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
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32
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Mc Dowell CP, Carlin A, Capranica L, Dillon C, Harrington JM, Lakerveld J, Loyen A, Ling FCM, Brug J, MacDonncha C, Herring MP. Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study. BMC Public Health 2018; 18:779. [PMID: 29960595 PMCID: PMC6026508 DOI: 10.1186/s12889-018-5702-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 06/12/2018] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Depression is a prevalent, debilitating, and often recurrent mood disorder for which successful first-line treatments remains limited. The purpose of this study was to investigate the cross-sectional associations between self-reported physical activity (PA) and depressive symptoms and status among Irish adults, using two existing datasets, The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study. METHODS The two selected databases were pooled (n = 10,122), and relevant variables were harmonized. PA was measured using the short form International Physical Activity Questionnaire. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression (CES-D) questionnaire. Participants were classified as meeting World Health Organization moderate-to-vigorous PA (MVPA) guidelines or not, and divided into tertiles based on weekly minutes of MVPA. A CES-D score of ≥16 indicated elevated depressive symptoms. Data collection were conducted in 2010-2011. RESULTS Significantly higher depressive symptoms were reported by females (7.11 ± 7.87) than males (5.74 ± 6.86; p < 0.001). Following adjustment for age, sex, BMI, and dataset, meeting the PA guidelines was associated with 44.7% (95%CI: 35.0 to 52.9; p < 0.001) lower odds of elevated depressive symptoms. Compared to the low PA tertile, the middle and high PA tertiles were associated with 25.2% (95%CI: 8.7 to 38.6; p < 0.01) and 50.8% (95%CI: 40.7 to 59.2; p < 0.001) lower odds of elevated depressive symptoms, respectively. CONCLUSION Meeting the PA guidelines is associated with lower odds of elevated depressive symptoms, and increased volumes of MVPA are associated with lower odds of elevated depressive symptoms.
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Affiliation(s)
- Cillian P. Mc Dowell
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
| | - Angela Carlin
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Centre for Exercise Medicine, Physical Activity and Health, School of Sport, Ulster University, Belfast, Northern Ireland
| | - Laura Capranica
- Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Rome, Italy
| | - Christina Dillon
- National Suicide Research Foundation, University College Cork, Cork, Ireland
| | | | - Jeroen Lakerveld
- Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Anne Loyen
- Department of Social and Occupational Health, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, the Netherlands
| | - Fiona Chun Man Ling
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Institute of Sport, Exercise and Active Living, Victoria University, Melbourne, Australia
- Department of Psychology, Faculty of Science & Technology, Bournemouth University, Bournemouth, UK
| | - Johannes Brug
- Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
- Amsterdam School for Communication Research, University of Amsterdam, Amsterdam, the Netherlands
| | - Ciaran MacDonncha
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Health Research Institute, University of Limerick, Limerick, Ireland
| | - Matthew P. Herring
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
- Health Research Institute, University of Limerick, Limerick, Ireland
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Hansen WB, Chen SH, Saldana S, Ip EH. An Algorithm for Creating Virtual Controls Using Integrated and Harmonized Longitudinal Data. Eval Health Prof 2018; 41:183-215. [PMID: 29724115 DOI: 10.1177/0163278718772882] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
We introduce a strategy for creating virtual control groups-cases generated through computer algorithms that, when aggregated, may serve as experimental comparators where live controls are difficult to recruit, such as when programs are widely disseminated and randomization is not feasible. We integrated and harmonized data from eight archived longitudinal adolescent-focused data sets spanning the decades from 1980 to 2010. Collectively, these studies examined numerous psychosocial variables and assessed past 30-day alcohol, cigarette, and marijuana use. Additional treatment and control group data from two archived randomized control trials were used to test the virtual control algorithm. Both randomized controlled trials (RCTs) assessed intentions, normative beliefs, and values as well as past 30-day alcohol, cigarette, and marijuana use. We developed an algorithm that used percentile scores from the integrated data set to create age- and gender-specific latent psychosocial scores. The algorithm matched treatment case observed psychosocial scores at pretest to create a virtual control case that figuratively "matured" based on age-related changes, holding the virtual case's percentile constant. Virtual controls matched treatment case occurrence, eliminating differential attrition as a threat to validity. Virtual case substance use was estimated from the virtual case's latent psychosocial score using logistic regression coefficients derived from analyzing the treatment group. Averaging across virtual cases created group estimates of prevalence. Two criteria were established to evaluate the adequacy of virtual control cases: (1) virtual control group pretest drug prevalence rates should match those of the treatment group and (2) virtual control group patterns of drug prevalence over time should match live controls. The algorithm successfully matched pretest prevalence for both RCTs. Increases in prevalence were observed, although there were discrepancies between live and virtual control outcomes. This study provides an initial framework for creating virtual controls using a step-by-step procedure that can now be revised and validated using other prevention trial data.
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Affiliation(s)
| | - Shyh-Huei Chen
- 2 Department of Biostatistical Sciences, Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC, USA
| | - Santiago Saldana
- 2 Department of Biostatistical Sciences, Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC, USA
| | - Edward H Ip
- 2 Department of Biostatistical Sciences, Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC, USA
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Cai Y, Hodgson S, Blangiardo M, Gulliver J, Morley D, Fecht D, Vienneau D, de Hoogh K, Key T, Hveem K, Elliott P, Hansell AL. Road traffic noise, air pollution and incident cardiovascular disease: A joint analysis of the HUNT, EPIC-Oxford and UK Biobank cohorts. ENVIRONMENT INTERNATIONAL 2018; 114:191-201. [PMID: 29518662 DOI: 10.1016/j.envint.2018.02.048] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 02/12/2018] [Accepted: 02/27/2018] [Indexed: 05/20/2023]
Abstract
BACKGROUND This study aimed to investigate the effects of long-term exposure to road traffic noise and air pollution on incident cardiovascular disease (CVD) in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. METHODS In pooled complete-case sample of the three cohorts from Norway and the United Kingdom (N = 355,732), 21,081 incident all CVD cases including 5259 ischemic heart disease (IHD) and 2871 cerebrovascular cases were ascertained between baseline (1993-2010) and end of follow-up (2008-2013) through medical record linkage. Annual mean 24-hour weighted road traffic noise (Lden) and air pollution (particulate matter with aerodynamic diameter ≤ 10 μm [PM10], ≤2.5 μm [PM2.5] and nitrogen dioxide [NO2]) exposure at baseline address was modelled using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU) and European-wide Land Use Regression models. Individual-level covariate data were harmonised and physically pooled across the three cohorts. Analysis was via Cox proportional hazard model with mutual adjustments for both noise and air pollution and potential confounders. RESULTS No significant associations were found between annual mean Lden and incident CVD, IHD or cerebrovascular disease in the overall population except that the association with incident IHD was significant among current-smokers. In the fully adjusted models including adjustment for Lden, an interquartile range (IQR) higher PM10 (4.1 μg/m3) or PM2.5 (1.4 μg/m3) was associated with a 5.8% (95%CI: 2.5%-9.3%) and 3.7% (95%CI: 0.2%-7.4%) higher risk for all incident CVD respectively. No significant associations were found between NO2 and any of the CVD outcomes. CONCLUSIONS We found suggestive evidence of a possible association between road traffic noise and incident IHD, consistent with current literature. Long-term particulate air pollution exposure, even at concentrations below current European air quality standards, was significantly associated with incident CVD.
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Affiliation(s)
- Yutong Cai
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; MRC-PHE Centre for Environment and Health, Department of Analytical, Environmental and Forensic Sciences, School of Population Health and Environmental Sciences, King's College London, London, United Kingdom.
| | - Susan Hodgson
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Marta Blangiardo
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - John Gulliver
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - David Morley
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Daniela Fecht
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Danielle Vienneau
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Tim Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Kristian Hveem
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Directorate of Public Health and Primary Care, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Anna L Hansell
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Directorate of Public Health and Primary Care, Imperial College Healthcare NHS Trust, London, United Kingdom
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Cai Y, Hansell AL, Blangiardo M, Burton PR, de Hoogh K, Doiron D, Fortier I, Gulliver J, Hveem K, Mbatchou S, Morley DW, Stolk RP, Zijlema WL, Elliott P, Hodgson S. Long-term exposure to road traffic noise, ambient air pollution, and cardiovascular risk factors in the HUNT and lifelines cohorts. Eur Heart J 2018; 38:2290-2296. [PMID: 28575405 DOI: 10.1093/eurheartj/ehx263] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 04/28/2017] [Indexed: 01/27/2023] Open
Abstract
Aims Blood biochemistry may provide information on associations between road traffic noise, air pollution, and cardiovascular disease risk. We evaluated this in two large European cohorts (HUNT3, Lifelines). Methods and results Road traffic noise exposure was modelled for 2009 using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU). Annual ambient air pollution (PM10, NO2) at residence was estimated for 2007 using a Land Use Regression model. The statistical platform DataSHIELD was used to pool data from 144 082 participants aged ≥20 years to enable individual-level analysis. Generalized linear models were fitted to assess cross-sectional associations between pollutants and high-sensitivity C-reactive protein (hsCRP), blood lipids and for (Lifelines only) fasting blood glucose, for samples taken during recruitment in 2006-2013. Pooling both cohorts, an inter-quartile range (IQR) higher day-time noise (5.1 dB(A)) was associated with 1.1% [95% confidence interval (95% CI: 0.02-2.2%)] higher hsCRP, 0.7% (95% CI: 0.3-1.1%) higher triglycerides, and 0.5% (95% CI: 0.3-0.7%) higher high-density lipoprotein (HDL); only the association with HDL was robust to adjustment for air pollution. An IQR higher PM10 (2.0 µg/m3) or NO2 (7.4 µg/m3) was associated with higher triglycerides (1.9%, 95% CI: 1.5-2.4% and 2.2%, 95% CI: 1.6-2.7%), independent of adjustment for noise. Additionally for NO2, a significant association with hsCRP (1.9%, 95% CI: 0.5-3.3%) was seen. In Lifelines, an IQR higher noise (4.2 dB(A)) and PM10 (2.4 µg/m3) was associated with 0.2% (95% CI: 0.1-0.3%) and 0.6% (95% CI: 0.4-0.7%) higher fasting glucose respectively, with both remaining robust to adjustment for air/noise pollution. Conclusion Long-term exposures to road traffic noise and ambient air pollution were associated with blood biochemistry, providing a possible link between road traffic noise/air pollution and cardio-metabolic disease risk.
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Affiliation(s)
- Yutong Cai
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK
| | - Anna L Hansell
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK.,Directorate of Public Health and Primary Care, Imperial College Healthcare NHS Trust, London, UK
| | - Marta Blangiardo
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK
| | - Paul R Burton
- Data to Knowledge (D2K) Research Group, University of Bristol, Oakfield Grove, Bristol BS8 2BN, UK.,Maelstrom Research Program, Public Population Project in Genomics and Society (P G), 740 Dr Penfield Avenue, Suite 5104, H3A 0G1, Montreal, Canada
| | | | - Kees de Hoogh
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK.,Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland.,University of Basel, Petersplatz 1, 4003 Basel, Switzerland
| | - Dany Doiron
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland.,University of Basel, Petersplatz 1, 4003 Basel, Switzerland.,Child Health and Human Development Program, Research Institute of the McGill University Health Centre, McGill University, 2155 Guy St, H3H 2L9 Montreal, Canada
| | - Isabel Fortier
- Maelstrom Research Program, Public Population Project in Genomics and Society (P G), 740 Dr Penfield Avenue, Suite 5104, H3A 0G1, Montreal, Canada.,Child Health and Human Development Program, Research Institute of the McGill University Health Centre, McGill University, 2155 Guy St, H3H 2L9 Montreal, Canada
| | - John Gulliver
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK
| | - Kristian Hveem
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Forskningsvegen 2, 7600 Levanger, Trondheim, Norway
| | - Stéphane Mbatchou
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, McGill University, 2155 Guy St, H3H 2L9 Montreal, Canada
| | - David W Morley
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK
| | - Ronald P Stolk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands
| | - Wilma L Zijlema
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands.,Barcelona Institute for Global Health (ISGlobal), Centre for Research in Environmental Epidemiology (CREAL), Doctor Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Doctor Aiguader 88, 08003 Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Melchor Fernández Almagro, 3-5, 28029 Madrid, Spain
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK
| | - Susan Hodgson
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PG, London, UK
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Manders P, Peters TM, Siezen AE, van Rooij IA, Snijder R, Swinkels DW, Zielhuis GA. A Stepwise Procedure to Define a Data Collection Framework for a Clinical Biobank. Biopreserv Biobank 2018; 16:138-147. [DOI: 10.1089/bio.2017.0084] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Peggy Manders
- Radboud Biobank, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tessa M.A. Peters
- Radboud Biobank, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ariaan E. Siezen
- Radboud Biobank, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Iris A.L.M. van Rooij
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Dorine W. Swinkels
- Radboud Biobank, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Gerhard A. Zielhuis
- Radboud Biobank, Radboud University Medical Center, Nijmegen, the Netherlands
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
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Genetic variation associated with the occurrence and progression of neurological disorders. Neurotoxicology 2017; 61:243-264. [DOI: 10.1016/j.neuro.2016.09.018] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 09/23/2016] [Indexed: 02/08/2023]
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Bally M, Dendukuri N, Rich B, Nadeau L, Helin-Salmivaara A, Garbe E, Brophy JM. Risk of acute myocardial infarction with NSAIDs in real world use: bayesian meta-analysis of individual patient data. BMJ 2017; 357:j1909. [PMID: 28487435 PMCID: PMC5423546 DOI: 10.1136/bmj.j1909] [Citation(s) in RCA: 272] [Impact Index Per Article: 38.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Objective To characterise the determinants, time course, and risks of acute myocardial infarction associated with use of oral non-steroidal anti-inflammatory drugs (NSAIDs).Design Systematic review followed by a one stage bayesian individual patient data meta-analysis.Data sources Studies from Canadian and European healthcare databases.Review methods Eligible studies were sourced from computerised drug prescription or medical databases, conducted in the general or an elderly population, documented acute myocardial infarction as specific outcome, studied selective cyclo-oxygenase-2 inhibitors (including rofecoxib) and traditional NSAIDs, compared risk of acute myocardial infarction in NSAID users with non-users, allowed for time dependent analyses, and minimised effects of confounding and misclassification bias. Exposure and outcomes Drug exposure was modelled as an indicator variable incorporating the specific NSAID, its recency, duration of use, and dose. The outcome measures were the summary adjusted odds ratios of first acute myocardial infarction after study entry for each category of NSAID use at index date (date of acute myocardial infarction for cases, matched date for controls) versus non-use in the preceding year and the posterior probability of acute myocardial infarction.Results A cohort of 446 763 individuals including 61 460 with acute myocardial infarction was acquired. Taking any dose of NSAIDs for one week, one month, or more than a month was associated with an increased risk of myocardial infarction. With use for one to seven days the probability of increased myocardial infarction risk (posterior probability of odds ratio >1.0) was 92% for celecoxib, 97% for ibuprofen, and 99% for diclofenac, naproxen, and rofecoxib. The corresponding odds ratios (95% credible intervals) were 1.24 (0.91 to 1.82) for celecoxib, 1.48 (1.00 to 2.26) for ibuprofen, 1.50 (1.06 to 2.04) for diclofenac, 1.53 (1.07 to 2.33) for naproxen, and 1.58 (1.07 to 2.17) for rofecoxib. Greater risk of myocardial infarction was documented for higher dose of NSAIDs. With use for longer than one month, risks did not appear to exceed those associated with shorter durations.Conclusions All NSAIDs, including naproxen, were found to be associated with an increased risk of acute myocardial infarction. Risk of myocardial infarction with celecoxib was comparable to that of traditional NSAIDS and was lower than for rofecoxib. Risk was greatest during the first month of NSAID use and with higher doses.
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Affiliation(s)
- Michèle Bally
- Department of Pharmacy and Research Centre, Centre hospitalier de l'Université de Montréal, Montreal, H2X 1N4, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
| | - Nandini Dendukuri
- Technology Assessment Unit of the McGill University Health Centre, Montreal, Canada
- Division of Clinical Epidemiology, McGill University Health Centre-Research Institute, Montreal, Canada
| | - Benjamin Rich
- Division of Clinical Epidemiology, McGill University Health Centre-Research Institute, Montreal, Canada
| | - Lyne Nadeau
- Division of Clinical Epidemiology, McGill University Health Centre-Research Institute, Montreal, Canada
| | | | - Edeltraut Garbe
- Department of Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology-BIPS, Bremen, Germany
| | - James M Brophy
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
- Division of Clinical Epidemiology, McGill University Health Centre-Research Institute, Montreal, Canada
- Department of Medicine, McGill University, Montreal, Canada
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Lorenz MW, Abdi NA, Scheckenbach F, Pflug A, Bülbül A, Catapano AL, Agewall S, Ezhov M, Bots ML, Kiechl S, Orth A. Automatic identification of variables in epidemiological datasets using logic regression. BMC Med Inform Decis Mak 2017; 17:40. [PMID: 28407816 PMCID: PMC5390441 DOI: 10.1186/s12911-017-0429-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 03/23/2017] [Indexed: 12/11/2022] Open
Abstract
Background For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0429-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Matthias W Lorenz
- Department of Neurology, University Clinic Frankfurt, Schleusenweg 2-16, D-60528, Frankfurt/Main, Germany.
| | - Negin Ashtiani Abdi
- Faculty of Computer Science and Engineering, Frankfurt University of Applied Sciences, Frankfurt/Main, Germany
| | - Frank Scheckenbach
- Department of Neurology, University Clinic Frankfurt, Schleusenweg 2-16, D-60528, Frankfurt/Main, Germany
| | - Anja Pflug
- Department of Neurology, University Clinic Frankfurt, Schleusenweg 2-16, D-60528, Frankfurt/Main, Germany
| | - Alpaslan Bülbül
- Department of Neurology, University Clinic Frankfurt, Schleusenweg 2-16, D-60528, Frankfurt/Main, Germany
| | - Alberico L Catapano
- IRCSS Multimedica, Milan, Italy.,Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Stefan Agewall
- Institute of Clinical Sciences, University of Oslo, Oslo, Norway.,Department of Cardiology, Oslo University Hospital Ullevål, Oslo, Norway
| | - Marat Ezhov
- Atherosclerosis Department, Cardiology Research Center, Moscow, Russia
| | - Michiel L Bots
- University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Epidemiology and Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Stefan Kiechl
- Department of Neurology, Medical University Innsbruck, Innsbruck, Austria
| | - Andreas Orth
- Faculty of Computer Science and Engineering, Frankfurt University of Applied Sciences, Frankfurt/Main, Germany
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Fortier I, Raina P, Van den Heuvel ER, Griffith LE, Craig C, Saliba M, Doiron D, Stolk RP, Knoppers BM, Ferretti V, Granda P, Burton P. Maelstrom Research guidelines for rigorous retrospective data harmonization. Int J Epidemiol 2017; 46:103-105. [PMID: 27272186 PMCID: PMC5407152 DOI: 10.1093/ije/dyw075] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/16/2016] [Indexed: 12/26/2022] Open
Abstract
Background It is widely accepted and acknowledged that data harmonization is crucial: in its absence, the co-analysis of major tranches of high quality extant data is liable to inefficiency or error. However, despite its widespread practice, no formalized/systematic guidelines exist to ensure high quality retrospective data harmonization. Methods To better understand real-world harmonization practices and facilitate development of formal guidelines, three interrelated initiatives were undertaken between 2006 and 2015. They included a phone survey with 34 major international research initiatives, a series of workshops with experts, and case studies applying the proposed guidelines. Results A wide range of projects use retrospective harmonization to support their research activities but even when appropriate approaches are used, the terminologies, procedures, technologies and methods adopted vary markedly. The generic guidelines outlined in this article delineate the essentials required and describe an interdependent step-by-step approach to harmonization: 0) define the research question, objectives and protocol; 1) assemble pre-existing knowledge and select studies; 2) define targeted variables and evaluate harmonization potential; 3) process data; 4) estimate quality of the harmonized dataset(s) generated; and 5) disseminate and preserve final harmonization products. Conclusions This manuscript provides guidelines aiming to encourage rigorous and effective approaches to harmonization which are comprehensively and transparently documented and straightforward to interpret and implement. This can be seen as a key step towards implementing guiding principles analogous to those that are well recognised as being essential in securing the foundational underpinning of systematic reviews and the meta-analysis of clinical trials.
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Affiliation(s)
- Isabel Fortier
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Parminder Raina
- McMaster University, Department of Clinical Epidemiology and Biostatistics, Hamilton, ON, Canada
| | - Edwin R Van den Heuvel
- Eindhoven University of Technology, Department of Mathematics and Computer Science, Eindhoven, The Netherlands
| | - Lauren E Griffith
- McMaster University, Department of Clinical Epidemiology and Biostatistics, Hamilton, ON, Canada
| | - Camille Craig
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Matilda Saliba
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Dany Doiron
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Ronald P Stolk
- University Medical Center Groningen, Department of Epidemiology, Groningen, Groningen, The Netherlands
| | - Bartha M Knoppers
- McGill University, Centre of Genomics and Policy, Montreal, Montrreal, QC, Canada
| | - Vincent Ferretti
- Ontario Institute for Cancer Research, MaRS Centre, Toronto, ON, Canada
| | - Peter Granda
- University of Michigan, Inter-university Consortium for Political and Social Research (ICPSR), Ann Arbor, MI, USA
| | - Paul Burton
- University of Bristol, D2K Research Group, School of Social and Community Medicine, Bristol, UK
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Cai Y, Zijlema WL, Doiron D, Blangiardo M, Burton PR, Fortier I, Gaye A, Gulliver J, de Hoogh K, Hveem K, Mbatchou S, Morley DW, Stolk RP, Elliott P, Hansell AL, Hodgson S. Ambient air pollution, traffic noise and adult asthma prevalence: a BioSHaRE approach. Eur Respir J 2017; 49:1502127. [PMID: 27824608 DOI: 10.1183/13993003.02127-2015] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Accepted: 09/01/2016] [Indexed: 11/05/2022]
Abstract
We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006-2013 (HUNT3, Lifelines and UK Biobank).Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM10) and nitrogen dioxide (NO2)) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a "compute to the data" approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence.PM10 or NO2 higher by 10 µg·m-3 was associated with 12.8% (95% CI 9.5-16.3%) and 1.9% (95% CI 1.1-2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence.This study suggests that long-term ambient PM10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation.
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Affiliation(s)
- Yutong Cai
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Wilma L Zijlema
- Dept of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Dany Doiron
- Research Institute of the McGill University Health Centre and Dept of Medicine, McGill University, Montreal, QC, Canada
| | - Marta Blangiardo
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Paul R Burton
- Data to Knowledge (D2K) Research Group, University of Bristol, Bristol, UK
- Public Population Project in Genomics and Society (P3G), Montreal, QC, Canada
| | - Isabel Fortier
- Research Institute of the McGill University Health Centre and Dept of Medicine, McGill University, Montreal, QC, Canada
| | - Amadou Gaye
- Metabolic, Cardiovascular and Inflammatory Disease Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - John Gulliver
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Kees de Hoogh
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Kristian Hveem
- Dept of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
| | - Stéphane Mbatchou
- Research Institute of the McGill University Health Centre and Dept of Medicine, McGill University, Montreal, QC, Canada
| | - David W Morley
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Ronald P Stolk
- Dept of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Anna L Hansell
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Directorate of Public Health and Primary Care, Imperial College Healthcare NHS Trust, London, UK
| | - Susan Hodgson
- MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
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42
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Palumbo P, Klenk J, Cattelani L, Bandinelli S, Ferrucci L, Rapp K, Chiari L, Rothenbacher D. Predictive Performance of a Fall Risk Assessment Tool for Community-Dwelling Older People (FRAT-up) in 4 European Cohorts. J Am Med Dir Assoc 2016; 17:1106-1113. [PMID: 27594522 PMCID: PMC6136246 DOI: 10.1016/j.jamda.2016.07.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 07/21/2016] [Indexed: 12/23/2022]
Abstract
BACKGROUND AND OBJECTIVE The fall risk assessment tool (FRAT-up) is a tool for predicting falls in community-dwelling older people based on a meta-analysis of fall risk factors. Based on the fall risk factor profile, this tool calculates the individual risk of falling over the next year. The objective of this study is to evaluate the performance of FRAT-up in predicting future falls in multiple cohorts. METHODS Information about fall risk factors in 4 European cohorts of older people [Activity and Function in the Elderly (ActiFE), Germany; English Longitudinal Study of Aging (ELSA), England; Invecchiare nel Chianti (InCHIANTI), Italy; Irish Longitudinal Study on Aging (TILDA), Ireland] was used to calculate the FRAT-up risk score in individual participants. Information about falls that occurred after the assessment of the risk factors was collected from subsequent longitudinal follow-ups. We compared the performance of FRAT-up against those of other prediction models specifically fitted in each cohort by calculation of the area under the receiver operating characteristic curve (AUC). RESULTS The AUC attained by FRAT-up is 0.562 [95% confidence interval (CI) 0.530-0.594] for ActiFE, 0.699 (95% CI 0.680-0.718) for ELSA, 0.636 (95% CI 0.594-0.681) for InCHIANTI, and 0.685 (95% CI 0.660-0.709) for TILDA. Mean FRAT-up AUC as estimated from meta-analysis is 0.646 (95% CI 0.584-0.708), with substantial heterogeneity between studies. In each cohort, FRAT-up discriminant ability is surpassed, at most, by the cohort-specific risk model fitted on that same cohort. CONCLUSIONS We conclude that FRAT-up is a valid approach to estimate risk of falls in populations of community-dwelling older people. However, further studies should be performed to better understand the reasons for the observed heterogeneity across studies and to refine a tool that performs homogeneously with higher accuracy measures across different populations.
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Affiliation(s)
- Pierpaolo Palumbo
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi"-DEI, University of Bologna, Bologna, Italy.
| | - Jochen Klenk
- Department of Geriatrics and Clinic of Geriatric Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany; Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Luca Cattelani
- Department of Computer Science and Engineering-DISI, University of Bologna, Bologna, Italy
| | | | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, MD
| | - Kilian Rapp
- Department of Geriatrics and Clinic of Geriatric Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Lorenzo Chiari
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi"-DEI, University of Bologna, Bologna, Italy; Health Sciences and Technologies Interdepartmental Center for Industrial Research, University of Bologna, Bologna, Italy
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Griffith LE, van den Heuvel E, Raina P, Fortier I, Sohel N, Hofer SM, Payette H, Wolfson C, Belleville S, Kenny M, Doiron D. Comparison of Standardization Methods for the Harmonization of Phenotype Data: An Application to Cognitive Measures. Am J Epidemiol 2016; 184:770-778. [PMID: 27769990 DOI: 10.1093/aje/kww098] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 09/07/2016] [Indexed: 12/15/2022] Open
Abstract
Standardization procedures are commonly used to combine phenotype data that were measured using different instruments, but there is little information on how the choice of standardization method influences pooled estimates and heterogeneity. Heterogeneity is of key importance in meta-analyses of observational studies because it affects the statistical models used and the decision of whether or not it is appropriate to calculate a pooled estimate of effect. Using 2-stage individual participant data analyses, we compared 2 common methods of standardization, T-scores and category-centered scores, to create combinable memory scores using cross-sectional data from 3 Canadian population-based studies (the Canadian Study on Health and Aging (1991-1992), the Canadian Community Health Survey on Healthy Aging (2008-2009), and the Quebec Longitudinal Study on Nutrition and Aging (2004-2005)). A simulation was then conducted to assess the influence of varying the following items across population-based studies: 1) effect size, 2) distribution of confounders, and 3) the relationship between confounders and the outcome. We found that pooled estimates based on the unadjusted category-centered scores tended to be larger than those based on the T-scores, although the differences were negligible when adjusted scores were used, and that most individual participant data meta-analyses identified significant heterogeneity. The results of the simulation suggested that in terms of heterogeneity, the method of standardization played a smaller role than did different effect sizes across populations and differential confounding of the outcome measure across studies. Although there was general consistency between the 2 types of standardization methods, the simulations identified a number of sources of heterogeneity, some of which are not the usual sources considered by researchers.
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Zijlema W, Cai Y, Doiron D, Mbatchou S, Fortier I, Gulliver J, de Hoogh K, Morley D, Hodgson S, Elliott P, Key T, Kongsgard H, Hveem K, Gaye A, Burton P, Hansell A, Stolk R, Rosmalen J. Road traffic noise, blood pressure and heart rate: Pooled analyses of harmonized data from 88,336 participants. ENVIRONMENTAL RESEARCH 2016; 151:804-813. [PMID: 27692672 DOI: 10.1016/j.envres.2016.09.014] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 09/06/2016] [Accepted: 09/16/2016] [Indexed: 06/06/2023]
Abstract
INTRODUCTION Exposure to road traffic noise may increase blood pressure and heart rate. It is unclear to what extent exposure to air pollution may influence this relationship. We investigated associations between noise, blood pressure and heart rate, with harmonized data from three European cohorts, while taking into account exposure to air pollution. METHODS Road traffic noise exposure was assessed using a European noise model based on the Common Noise Assessment Methods in Europe framework (CNOSSOS-EU). Exposure to air pollution was estimated using a European-wide land use regression model. Blood pressure and heart rate were obtained by trained clinical professionals. Pooled cross-sectional analyses of harmonized data were conducted at the individual level and with random-effects meta-analyses. RESULTS We analyzed data from 88,336 participants, across the three participating cohorts (mean age 47.0 (±13.9) years). Each 10dB(A) increase in noise was associated with a 0.93 (95% CI 0.76;1.11) bpm increase in heart rate, but with a decrease in blood pressure of 0.01 (95% CI -0.24;0.23) mmHg for systolic and 0.38 (95% CI -0.53; -0.24) mmHg for diastolic blood pressure. Adjustments for PM10 or NO2 attenuated the associations, but remained significant for DBP and HR. Results for BP differed by cohort, with negative associations with noise in LifeLines, no significant associations in EPIC-Oxford, and positive associations with noise >60dB(A) in HUNT3. CONCLUSIONS Our study suggests that road traffic noise may be related to increased heart rate. No consistent evidence for a relation between noise and blood pressure was found.
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Affiliation(s)
- Wilma Zijlema
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands; ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Yutong Cai
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Dany Doiron
- Research Institute of the McGill University Health Centre (RI-MUHC), Montréal, Québec, Canada; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Stéphane Mbatchou
- Research Institute of the McGill University Health Centre (RI-MUHC), Montréal, Québec, Canada
| | - Isabel Fortier
- Research Institute of the McGill University Health Centre (RI-MUHC), Montréal, Québec, Canada
| | - John Gulliver
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Kees de Hoogh
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - David Morley
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Susan Hodgson
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Timothy Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Havard Kongsgard
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Amadou Gaye
- National Human Genome Research Institute, Metabolic, Cardiovascular and Inflammatory Disease Genomics Branch, Bethesda, USA
| | - Paul Burton
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Anna Hansell
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra (UPF), Barcelona, Spain; Imperial College Healthcare NHS Trust, London, UK
| | - Ronald Stolk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Judith Rosmalen
- University of Groningen, University Medical Center Groningen, Departments of Psychiatry and Internal Medicine, Groningen, The Netherlands
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Tassé AM. A Comparative Analysis of the Legal and Bioethical Frameworks Governing the Secondary Use of Data for Research Purposes. Biopreserv Biobank 2016; 14:207-16. [DOI: 10.1089/bio.2015.0121] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Anne-Marie Tassé
- Public Population Project in Genomics and Society, McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada
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Murtagh MJ, Turner A, Minion JT, Fay M, Burton PR. International Data Sharing in Practice: New Technologies Meet Old Governance. Biopreserv Biobank 2016; 14:231-40. [PMID: 27200470 DOI: 10.1089/bio.2016.0002] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The social structures that govern data/sample release aim to safeguard the confidentiality and privacy of cohort research participants (without whom there would be no data or samples) and enable the realization of societal benefit through optimizing the scientific use of those cohorts. Within collaborations involving multiple cohorts and biobanks, however, the local, national, and supranational institutional and legal guidelines for research (which produce a multiplicity of data access governance structures and guidelines) risk impeding the very science that is the raison d'etre of these consortia. We present an ethnographic study, which examined the epistemic and nonepistemic values driving decisions about data access and their consequences in the context of the pilot of an integrated approach to co-analysis of data. We demonstrate how the potential analytic flexibility offered by this approach was lost under contemporary data access governance. We identify three dominant values: protecting the research participant, protecting the study, and protecting the researcher. These values were both supported by and juxtaposed against a "public good" argument, and each was used as a rationale to both promote and inhibit sharing of data. While protection of the research participants was central to access permissions, decisions were also attentive to the desire of researchers to see their efforts in building population biobanks and cohorts realized in the form of scientific outputs. We conclude that systems for governing and enabling data access in large consortia need to (1) protect disclosure of research participant information or identity, (2) ensure the specific expectations of research participants are met, (3) embody systems of review that are transparent and not compromised by the specific interests of one particular group of stakeholders, and (4) facilitate data access procedures that are timely and efficient. Practical solutions are urgently needed. New approaches to data access governance should be trialed (and formally evaluated) with input from and discussion with stakeholders.
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Affiliation(s)
- Madeleine J Murtagh
- Data to Knowledge Research Group, School of Social and Community Medicine, University of Bristol , Bristol, United Kingdom
| | - Andrew Turner
- Data to Knowledge Research Group, School of Social and Community Medicine, University of Bristol , Bristol, United Kingdom
| | - Joel T Minion
- Data to Knowledge Research Group, School of Social and Community Medicine, University of Bristol , Bristol, United Kingdom
| | - Michaela Fay
- Data to Knowledge Research Group, School of Social and Community Medicine, University of Bristol , Bristol, United Kingdom
| | - Paul R Burton
- Data to Knowledge Research Group, School of Social and Community Medicine, University of Bristol , Bristol, United Kingdom
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47
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Affiliation(s)
- James M. Roberts
- From the Departments of Obstetrics, Gynecology, and Reproductive Sciences, Epidemiology and Clinical and Translational Research, Magee-Womens Research Institute, University of Pittsburgh, PA (J.M.R.); Centre for Research Ethics and Bioethics, Department of Public Health, Uppsala University, Uppsala, Sweden (D.M.); Centre for Biomedicine EURAC, Bolzano, Italy (D.M.); University of Texas School of Public Health, Houston (R.B.N.); and Division of Women’s Health, Women’s Health Academic Centre, King’s
| | - Deborah Mascalzoni
- From the Departments of Obstetrics, Gynecology, and Reproductive Sciences, Epidemiology and Clinical and Translational Research, Magee-Womens Research Institute, University of Pittsburgh, PA (J.M.R.); Centre for Research Ethics and Bioethics, Department of Public Health, Uppsala University, Uppsala, Sweden (D.M.); Centre for Biomedicine EURAC, Bolzano, Italy (D.M.); University of Texas School of Public Health, Houston (R.B.N.); and Division of Women’s Health, Women’s Health Academic Centre, King’s
| | - Roberta B. Ness
- From the Departments of Obstetrics, Gynecology, and Reproductive Sciences, Epidemiology and Clinical and Translational Research, Magee-Womens Research Institute, University of Pittsburgh, PA (J.M.R.); Centre for Research Ethics and Bioethics, Department of Public Health, Uppsala University, Uppsala, Sweden (D.M.); Centre for Biomedicine EURAC, Bolzano, Italy (D.M.); University of Texas School of Public Health, Houston (R.B.N.); and Division of Women’s Health, Women’s Health Academic Centre, King’s
| | - Lucilla Poston
- From the Departments of Obstetrics, Gynecology, and Reproductive Sciences, Epidemiology and Clinical and Translational Research, Magee-Womens Research Institute, University of Pittsburgh, PA (J.M.R.); Centre for Research Ethics and Bioethics, Department of Public Health, Uppsala University, Uppsala, Sweden (D.M.); Centre for Biomedicine EURAC, Bolzano, Italy (D.M.); University of Texas School of Public Health, Houston (R.B.N.); and Division of Women’s Health, Women’s Health Academic Centre, King’s
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Forgetta V, Richards JB. Software Application Profiles: useful and novel software for epidemiological data analysis. Int J Epidemiol 2016; 45:309-10. [DOI: 10.1093/ije/dyw064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
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Pang C, van Enckevort D, de Haan M, Kelpin F, Jetten J, Hendriksen D, de Boer T, Charbon B, Winder E, van der Velde KJ, Doiron D, Fortier I, Hillege H, Swertz MA. MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks. Bioinformatics 2016; 32:2176-83. [PMID: 27153686 PMCID: PMC4937195 DOI: 10.1093/bioinformatics/btw155] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 03/15/2016] [Indexed: 12/20/2022] Open
Abstract
Motivation: While the size and number of biobanks, patient registries and other data collections are increasing, biomedical researchers still often need to pool data for statistical power, a task that requires time-intensive retrospective integration. Results: To address this challenge, we developed MOLGENIS/connect, a semi-automatic system to find, match and pool data from different sources. The system shortlists relevant source attributes from thousands of candidates using ontology-based query expansion to overcome variations in terminology. Then it generates algorithms that transform source attributes to a common target DataSchema. These include unit conversion, categorical value matching and complex conversion patterns (e.g. calculation of BMI). In comparison to human-experts, MOLGENIS/connect was able to auto-generate 27% of the algorithms perfectly, with an additional 46% needing only minor editing, representing a reduction in the human effort and expertise needed to pool data. Availability and Implementation: Source code, binaries and documentation are available as open-source under LGPLv3 from http://github.com/molgenis/molgenis and www.molgenis.org/connect. Contact: m.a.swertz@rug.nl Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Chao Pang
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - David van Enckevort
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Mark de Haan
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Fleur Kelpin
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Jonathan Jetten
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Dennis Hendriksen
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Tommy de Boer
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Bart Charbon
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Erwin Winder
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - K Joeri van der Velde
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands
| | - Dany Doiron
- Research Institute of the McGill University Health Centre and Department of Medicine, McGill University, Montreal, Canada
| | - Isabel Fortier
- Research Institute of the McGill University Health Centre and Department of Medicine, McGill University, Montreal, Canada
| | - Hans Hillege
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Morris A Swertz
- Department of Genetics, University Medical Center Groningen, Genomics Coordination Center, University of Groningen, Groningen, The Netherlands Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Zijlema W, Wolf K, Emeny R, Ladwig K, Peters A, Kongsgård H, Hveem K, Kvaløy K, Yli-Tuomi T, Partonen T, Lanki T, Eeftens M, de Hoogh K, Brunekreef B, Stolk R, Rosmalen J. The association of air pollution and depressed mood in 70,928 individuals from four European cohorts. Int J Hyg Environ Health 2016; 219:212-9. [DOI: 10.1016/j.ijheh.2015.11.006] [Citation(s) in RCA: 95] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Revised: 11/02/2015] [Accepted: 11/23/2015] [Indexed: 12/18/2022]
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