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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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Bhattacharjee T, Kiwuwa-Muyingo S, Kanjala C, Maoyi ML, Amadi D, Ochola M, Kadengye D, Gregory A, Kiragga A, Taylor A, Greenfield J, Slaymaker E, Todd J. INSPIRE datahub: a pan-African integrated suite of services for harmonising longitudinal population health data using OHDSI tools. Front Digit Health 2024; 6:1329630. [PMID: 38347885 PMCID: PMC10859396 DOI: 10.3389/fdgth.2024.1329630] [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: 10/31/2023] [Accepted: 01/15/2024] [Indexed: 02/15/2024] Open
Abstract
Introduction Population health data integration remains a critical challenge in low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making. This paper proposes a pan-African, Findable, Accessible, Interoperable, and Reusable (FAIR) research architecture and infrastructure named the INSPIRE datahub. This cloud-based Platform-as-a-Service (PaaS) and on-premises setup aims to enhance the discovery, integration, and analysis of clinical, population-based surveys, and other health data sources. Methods The INSPIRE datahub, part of the Implementation Network for Sharing Population Information from Research Entities (INSPIRE), employs the Observational Health Data Sciences and Informatics (OHDSI) open-source stack of tools and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to harmonise data from African longitudinal population studies. Operating on Microsoft Azure and Amazon Web Services cloud platforms, and on on-premises servers, the architecture offers adaptability and scalability for other cloud providers and technology infrastructure. The OHDSI-based tools enable a comprehensive suite of services for data pipeline development, profiling, mapping, extraction, transformation, loading, documentation, anonymization, and analysis. Results The INSPIRE datahub's "On-ramp" services facilitate the integration of data and metadata from diverse sources into the OMOP CDM. The datahub supports the implementation of OMOP CDM across data producers, harmonizing source data semantically with standard vocabularies and structurally conforming to OMOP table structures. Leveraging OHDSI tools, the datahub performs quality assessment and analysis of the transformed data. It ensures FAIR data by establishing metadata flows, capturing provenance throughout the ETL processes, and providing accessible metadata for potential users. The ETL provenance is documented in a machine- and human-readable Implementation Guide (IG), enhancing transparency and usability. Conclusion The pan-African INSPIRE datahub presents a scalable and systematic solution for integrating health data in LMICs. By adhering to FAIR principles and leveraging established standards like OMOP CDM, this architecture addresses the current gap in generating evidence to support policy and decision-making for improving the well-being of LMIC populations. The federated research network provisions allow data producers to maintain control over their data, fostering collaboration while respecting data privacy and security concerns. A use-case demonstrated the pipeline using OHDSI and other open-source tools.
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Affiliation(s)
- Tathagata Bhattacharjee
- Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom
| | | | - Chifundo Kanjala
- Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom
- UNICEF (Malawi), Lilongwe, Malawi
| | - Molulaqhooa L. Maoyi
- South African Population Research Infrastructure Network (SAPRIN), South African Medical Research Council, Durban, South Africa
| | - David Amadi
- Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom
| | - Michael Ochola
- African Population and Health Research Center (APHRC), Nairobi, Kenya
| | - Damazo Kadengye
- African Population and Health Research Center (APHRC), Nairobi, Kenya
- Department of Economics and Statistics, Kabale University, Kabale, Uganda
| | - Arofan Gregory
- Committee on Data of the International Science Council (CODATA), Paris, France
| | - Agnes Kiragga
- African Population and Health Research Center (APHRC), Nairobi, Kenya
| | - Amelia Taylor
- Malawi University of Business and Applied Sciences, Blantyre, Malawi
| | - Jay Greenfield
- Department of Economics and Statistics, Kabale University, Kabale, Uganda
| | - Emma Slaymaker
- Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom
| | - Jim Todd
- Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom
| | - INSPIRE Network
- Implementation Network for Sharing Population Information from Research Entities (INSPIRE Network), Nairobi, Kenya
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Pan K, Bazzano LA, Betha K, Charlton BM, Chavarro JE, Cordero C, Gunderson EP, Haggerty CL, Hart JE, Jukic AM, Ley SH, Mishra GD, Mumford SL, Schisterman EF, Schliep K, Shaffer JG, Sotres-Alvarez D, Stanford JB, Wilcox AJ, Wise LA, Yeung E, Harville EW. Large-Scale Data Harmonization Across Prospective Studies. Am J Epidemiol 2023; 192:2033-2049. [PMID: 37403415 PMCID: PMC10988223 DOI: 10.1093/aje/kwad153] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 04/11/2023] [Accepted: 06/29/2023] [Indexed: 07/06/2023] Open
Abstract
The Preconception Period Analysis of Risks and Exposures Influencing Health and Development (PrePARED) Consortium creates a novel resource for addressing preconception health by merging data from numerous cohort studies. In this paper, we describe our data harmonization methods and results. Individual-level data from 12 prospective studies were pooled. The crosswalk-cataloging-harmonization procedure was used. The index pregnancy was defined as the first postbaseline pregnancy lasting more than 20 weeks. We assessed heterogeneity across studies by comparing preconception characteristics in different types of studies. The pooled data set included 114,762 women, and 25,531 (22%) reported at least 1 pregnancy of more than 20 weeks' gestation during the study period. Babies from the index pregnancies were delivered between 1976 and 2021 (median, 2008), at a mean maternal age of 29.7 (standard deviation, 4.6) years. Before the index pregnancy, 60% of women were nulligravid, 58% had a college degree or more, and 37% were overweight or obese. Other harmonized variables included race/ethnicity, household income, substance use, chronic conditions, and perinatal outcomes. Participants from pregnancy-planning studies had more education and were healthier. The prevalence of preexisting medical conditions did not vary substantially based on whether studies relied on self-reported data. Use of harmonized data presents opportunities to study uncommon preconception risk factors and pregnancy-related events. This harmonization effort laid the groundwork for future analyses and additional data harmonization.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Emily W Harville
- Correspondence to Dr. Emily W. Harville, Department of Epidemiology, Tulane School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112 (e-mail: )
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Fortier I, Wey TW, Bergeron J, Pinot de Moira A, Nybo-Andersen AM, Bishop T, Murtagh MJ, Miočević M, Swertz MA, van Enckevort E, Marcon Y, Mayrhofer MT, Ornelas JP, Sebert S, Santos AC, Rocha A, Wilson RC, Griffith LE, Burton P. Life course of retrospective harmonization initiatives: key elements to consider. J Dev Orig Health Dis 2023; 14:190-198. [PMID: 35957574 DOI: 10.1017/s2040174422000460] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.
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Affiliation(s)
- Isabel Fortier
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Tina W Wey
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Julie Bergeron
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | | | | | - Tom Bishop
- Epidemiology Unit, University of Cambridge, England, UK
| | - Madeleine J Murtagh
- School of Social and Political Sciences, University of Glasgow, Scotland, UK
| | - Milica Miočević
- Department of Psychology, McGill University, Montreal, QC, Canada
| | - Morris A Swertz
- University Medical Center Groningen, University of Groningen, Netherlands
| | - Esther van Enckevort
- Department of Genetics, University Medical Center Groningen, University of Groningen, Netherlands
| | | | | | - Jos Pedro Ornelas
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
| | | | - Ana Cristina Santos
- Department of Epidemiology, Institute of Public Health of the University of Porto, Portugal
| | - Artur Rocha
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
| | - Rebecca C Wilson
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, England, UK
| | - Lauren E Griffith
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Paul Burton
- Population Health Sciences Institute, Newcastle University, Newcastle-upon-Tyne, England, UK
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Kirsh VA, Skead K, McDonald K, Kreiger N, Little J, Menard K, McLaughlin J, Mukherjee S, Palmer LJ, Goel V, Purdue MP, Awadalla P. Cohort Profile: The Ontario Health Study (OHS). Int J Epidemiol 2022; 52:e137-e151. [PMID: 35962976 DOI: 10.1093/ije/dyac156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 07/20/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Victoria A Kirsh
- Ontario Institute for Cancer Research, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.)
| | - Kimberly Skead
- Ontario Institute for Cancer Research, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kelly McDonald
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Nancy Kreiger
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.).,Prevention and Cancer Control, Ontario Health, Cancer Care Ontario, Toronto, ON, Canada
| | - Julian Little
- Faculty of Medicine, School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | - Karen Menard
- Office of Institutional Research and Planning, University of Guelph, Guelph, ON, Canada
| | - John McLaughlin
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.)
| | - Sutapa Mukherjee
- Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Lyle J Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Vivek Goel
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.).,Office of the President, University of Waterloo, Waterloo, ON, Canada
| | - Mark P Purdue
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Philip Awadalla
- Ontario Institute for Cancer Research, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.).,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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Paalanen L, Tolonen H. Experiences from the harmonization of Finnish national population-based health survey data. Scand J Public Health 2021; 50:972-979. [PMID: 34706593 PMCID: PMC9578096 DOI: 10.1177/14034948211052164] [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] [Indexed: 11/15/2022]
Abstract
Aims: There are several advantages to pooling survey data from individual studies over time or across different countries. Our aim is to share our experiences on harmonizing data from 13 Finnish health examination surveys covering the years 1972–2017 and to describe the challenges related to harmonizing different variable types using two questionnaire variables – blood pressure measurement and total cholesterol assessment – as examples. Methods: Data from Finnish national population-based health surveys were harmonized as part of the research project ‘Projections of the Burden of Disease and Disability in Finland – Health Policy Prospects’, including variables from questionnaires, objective health measurements and results from the laboratory analysis of biological samples. The process presented in the Maelstrom Research guidelines for data harmonization was followed with minor adjustments. Results: The harmonization of data from objective measurements and biomarkers was reasonably straightforward, but questionnaire items proved more challenging. Some questions and response options had changed during the covered time period. This concerned, for example, questionnaire items on the availability and use of medication and diet. Conclusions: The long time period – 45 years – made harmonization more complicated. The survey questions or response options had changed for some topics due to changes in society. However, common core variables for topics that were especially relevant for the project, such as lifestyle factors and certain diseases or conditions, could be harmonized with sufficient comparability. For future surveys, the use of standardized survey methods and the proper documentation of data collection are recommended to facilitate harmonization.
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Affiliation(s)
- Laura Paalanen
- Finnish Institute for Health and Welfare (THL), Department of Public Health and Welfare, Helsinki, Finland
| | - Hanna Tolonen
- Finnish Institute for Health and Welfare (THL), Department of Public Health and Welfare, Helsinki, Finland
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7
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Zhang Z, Wang J, Kwong JC, Burnett RT, van Donkelaar A, Hystad P, Martin RV, Bai L, McLaughlin J, Chen H. Long-term exposure to air pollution and mortality in a prospective cohort: The Ontario Health Study. ENVIRONMENT INTERNATIONAL 2021; 154:106570. [PMID: 33892223 DOI: 10.1016/j.envint.2021.106570] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 03/31/2021] [Accepted: 04/08/2021] [Indexed: 05/06/2023]
Abstract
BACKGROUND Air pollution has been associated with increased mortality. However, updated evidence from cohort studies with detailed information on various risk factors is needed, especially in regions with low air pollution levels. We investigated the associations between long-term exposure to air pollution and mortality in a prospective cohort. METHODS We studied 88,615 participants aged ≥30 years from an ongoing cohort study in Ontario, Canada from 2009 to 2017. Exposure to ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) was estimated at participants' residence. Cox proportional hazard models were used to investigate the associations between air pollution and non-accidental, cardiovascular, and respiratory mortality, adjusted for a wide array of individual-level and contextual covariates. Potential effect modification by socio-demographic and behavioral factors was also examined in exploratory stratified analyses. RESULTS The fully adjusted hazard ratios (HRs) per 1 µg/m3 increment in PM2.5 were 1.037 [95% confidence interval (CI): 1.018, 1.057]¸ 1.083 (95% CI: 1.040, 1.128) and 1.109 (95% CI: 1.035, 1.187) for non-accidental, cardiovascular, and respiratory mortality, respectively. Positive associations were also found for NO2; the corresponding HRs per 1 ppb increment were 1.027 (95% CI: 1.021, 1.034), 1.032 (95% CI: 1.019, 1.046) and 1.044 (95% CI: 1.020, 1.068). We found suggestive evidence of stronger associations in physically active participants, smokers, and those with lower household income. CONCLUSIONS Long-term exposure to PM2.5 and NO2 was associated with increased risks for non-accidental, cardiovascular, and respiratory mortality, suggesting potential benefits of further improvement in air quality even in low-exposure environments.
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Affiliation(s)
- Zilong Zhang
- Public Health Ontario, Toronto, ON, Canada; ICES, Toronto, ON, Canada; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - John Wang
- Public Health Ontario, Toronto, ON, Canada; ICES, Toronto, ON, Canada
| | - Jeffrey C Kwong
- Public Health Ontario, Toronto, ON, Canada; ICES, Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
| | - Richard T Burnett
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada; Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Perry Hystad
- College of Public Health and Human Studies, Oregon State University, Corvallis, OR, USA
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada; Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Harvard-Smithsonian Centre for Astrophysics, Cambridge, MA, USA
| | - Li Bai
- ICES, Toronto, ON, Canada
| | - John McLaughlin
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Hong Chen
- Public Health Ontario, Toronto, ON, Canada; ICES, Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.
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8
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Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation (PERSPECTIVE I&I). J Pers Med 2021; 11:jpm11060511. [PMID: 34199804 PMCID: PMC8226444 DOI: 10.3390/jpm11060511] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/28/2021] [Accepted: 05/31/2021] [Indexed: 12/12/2022] Open
Abstract
Early detection of breast cancer through screening reduces breast cancer mortality. The benefits of screening must also be considered within the context of potential harms (e.g., false positives, overdiagnosis). Furthermore, while breast cancer risk is highly variable within the population, most screening programs use age to determine eligibility. A risk-based approach is expected to improve the benefit-harm ratio of breast cancer screening programs. The PERSPECTIVE I&I (Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation) project seeks to improve personalized risk assessment to allow for a cost-effective, population-based approach to risk-based screening and determine best practices for implementation in Canada. This commentary describes the four inter-related activities that comprise the PERSPECTIVE I&I project. 1: Identification and validation of novel moderate to high-risk susceptibility genes. 2: Improvement, validation, and adaptation of a risk prediction web-tool for the Canadian context. 3: Development and piloting of a socio-ethical framework to support implementation of risk-based breast cancer screening. 4: Economic analysis to optimize the implementation of risk-based screening. Risk-based screening and prevention is expected to benefit all women, empowering them to work with their healthcare provider to make informed decisions about screening and prevention.
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Newell M, Ghosh S, Goruk S, Pakseresht M, Vena JE, Dummer TJB, Field CJ. A Prospective Analysis of Plasma Phospholipid Fatty Acids and Breast Cancer Risk in 2 Provinces in Canada. Curr Dev Nutr 2021; 5:nzab022. [PMID: 33889794 PMCID: PMC8049855 DOI: 10.1093/cdn/nzab022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 02/23/2021] [Accepted: 03/09/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Studies suggest that fatty acid status influences breast cancer etiology, yet the roles of individual fatty acids in breast cancer risk are unclear, specifically when central adiposity and menopausal status are considered. OBJECTIVES This study examined the associations of fatty acid status with breast cancer risk including location, menopausal status, and waist-to-hip ratio as key variables. METHODS Prediagnostic plasma phospholipid fatty acids were measured in women with breast cancer (n = 393) and age-matched controls (n = 786) from a nested case-control prospective study within Alberta's Tomorrow Project (ATP) and British Columbia Generations Project (BCGP) cohorts. Binary logistic regression models were used to evaluate associations of fatty acids and breast cancer risk with subgroup analysis for menopausal status and waist-to-hip ratio. RESULTS Women from BCGP had a higher n-3 (ɷ-3) fatty acid status compared with the ATP (6.4% ± 0.08% vs. 5.3% ± 0.06%; P < 0.001), so subsequent analysis was blocked by cohort. Overall, fatty acids had inconsistent associations with risk. In the ATP among premenopausal women, total long-chain n-3 fatty acids (ORQ4vsQ1 = 1.78; 95% CI: 0.58, 5.43; P-trend = 0.007, P-interaction = 0.07) were positively associated with breast cancer risk, whereas in BCGP, DHA (ORQ4vsQ1 = 0.66; 95% CI: 0.28, 1.53; P-trend = 0.03, P-interaction = 0.05) and total long-chain n-3 fatty acids (ORQ4vsQ1 = 0.66; 95% CI: 0.28, 1.54; P-trend = 0.03) were associated with decreased cancer risk when the waist-to-hip ratio was <0.85. CONCLUSIONS Our findings suggest that regional variations in fatty acid status influence breast cancer risk, resulting in positive associations of total long-chain n-3 fatty acids in premenopausal ATP women and negative associations of these fatty acids in BCGP women with a waist-to-hip ratio below guidelines. This study highlights the complexity and difficulty in using fatty acid status to predict breast cancer risk in diverse populations without the consideration of other risk factors.
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Affiliation(s)
- Marnie Newell
- Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, Canada
| | - Sunita Ghosh
- Department of Medical Oncology, University of Alberta, Edmonton, Canada
| | - Susan Goruk
- Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, Canada
| | - Mohammedreza Pakseresht
- Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, Canada
| | - Jennifer E Vena
- Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, Canada
- Alberta's Tomorrow Project, CancerCare Alberta, Alberta Health Services, Calgary, Canada
| | - Trevor J B Dummer
- School of Population and Public Health, University of British Columbia, Vancouver, Canada
- Cancer Control Research, BC Cancer, Vancouver, Canada
| | - Catherine J Field
- Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, Canada
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Salter A, Stahmann A, Ellenberger D, Fneish F, Rodgers WJ, Middleton R, Nicholas R, Marrie RA. Data harmonization for collaborative research among MS registries: A case study in employment. Mult Scler 2020; 27:281-289. [PMID: 32163003 DOI: 10.1177/1352458520910499] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To assess the feasibility of collaboration and retrospective data harmonization among three multiple sclerosis (MS) registries by investigating employment status. METHODS We used the Maelstrom guidelines to facilitate retrospective harmonization of data from three MS registries, including the NARCOMS (North American Research Committee on MS) Registry, German MS Register (GMSR), and United Kingdom MS (UK-MS) Register. A protocol was developed based on the guidelines, and summary-level data were used to combine results. Employment status and a limited set of factors associated with employment (age, sex, education, and disability level) were harmonized. A meta-analytic approach was used to pool estimates using a weighted average of logistic regression estimates and their variances in a random effects model. RESULTS Employment status, age, sex, education, and disability were mapped. The overall employment rate was 57% (11,143 employed out of 19,562 persons with MS) with the GMSR having the highest proportion of participants employed (66.2%), followed by the UK-MS (55.2%) and NARCOMS (43.0%) registries. As disability level increased, the odds of not being employed increased. CONCLUSION Harmonization across registries was feasible. The Maelstrom guidelines provide a valuable roadmap for conducting high-quality harmonization projects. The pooling of data sources has the potential to be an important mechanism for conducting research in MS.
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Affiliation(s)
- A Salter
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | - A Stahmann
- MS Forschungs- und Projektentwicklungs-gGmbH, German MS Register, Hannover, Germany
| | - D Ellenberger
- MS Forschungs- und Projektentwicklungs-gGmbH, German MS Register, Hannover, Germany
| | - F Fneish
- MS Forschungs- und Projektentwicklungs-gGmbH, German MS Register, Hannover, Germany
| | - W J Rodgers
- Swansea University Medical School, Swansea, UK
| | - R Middleton
- Swansea University Medical School, Swansea, UK
| | | | - R A Marrie
- Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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