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Dong X, Huang J, Yi Y, Zhang L, Li T, Chen Y. Factors Associated with the Uptake of Genetic Testing for Cancer Risks: A Pathway Analysis Using the Health Information National Trends Survey Data. Life (Basel) 2022; 12:2024. [PMID: 36556389 PMCID: PMC9786267 DOI: 10.3390/life12122024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 11/24/2022] [Accepted: 12/01/2022] [Indexed: 12/11/2022] Open
Abstract
Our study aimed to identify pathways from the source of information to the uptake of cancer genetic testing, with consideration of intermediate variables including perceptional, attitudinal and psychosocial factors. We used the Health Information National Trends Survey (2020 database) and constructed a structural equation model for pathway analysis (using SPSS version 24). Variables for socio-demographic, lifestyle and health information were also collected and used for confounding adjustment. A total of 2941 participants were analyzed (68.5%, non-Hispanic white; 59.7%, females; 58 years, median age; and 142 (4.8%) had undertaken genetic testing for cancer risk previously). Our pathway analysis found that only information from particular sources (i.e., healthcare providers and genetic counsellors) had positive and significant effects on people’s perceptions of cancer regarding its prevention, detection and treatment (standardized β range, 0.15−0.31, all p-values < 0.01). Following the paths, these perceptional variables (cancer prevention, detection and treatment) showed considerable positive impacts on the uptake of genetic testing (standardized β (95% CIs): 0.25 (0.20, 0.30), 0.28 (0.23, 0.33) and 0.12 (0.06, 0.17), respectively). Pathways involving attitudinal and psychosocial factors showed much smaller or insignificant effects on the uptake of genetic testing. Our study brings several novel perspectives to the behavior model and may underpin certain issues regarding cancer risk genetic testing.
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Affiliation(s)
- Xiangning Dong
- Department of Biological Sciences, School of Science, Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
| | - Jingxian Huang
- Department of Biological Sciences, School of Science, Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
| | - Yanze Yi
- Department of Biological Sciences, School of Science, Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
| | - Lanwei Zhang
- Department of Biological Sciences, School of Science, Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
| | - Tenglong Li
- Wisdom Lake Academy of Pharmacy, Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
| | - Ying Chen
- Wisdom Lake Academy of Pharmacy, Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
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2
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Zhao J, Guan Y, McBride CM. A systematic review of theory-informed strategies used in interventions fostering family genetic risk communication. PATIENT EDUCATION AND COUNSELING 2022; 105:1953-1962. [PMID: 35304074 PMCID: PMC9203975 DOI: 10.1016/j.pec.2022.03.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/08/2022] [Accepted: 03/09/2022] [Indexed: 05/17/2023]
Abstract
BACKGROUND Inherited risk is a family issue. Identifying family members who carry a pathogenic genetic variant that increases risk of cancers and other chronic diseases can be lifesaving for those affected. OBJECTIVE The research questions are: (1) which family communication frameworks have been applied, (2) how do intervention strategies employed map to these theories, and (3) to what extent were families receptive to these strategies and communication increased? METHODS Manuscripts published between January 2010 and August 2020 were searched in three databases: PubMed, PsycINFO, and Web of Science. RESULTS Nine intervention trials were identified. All interventions were evaluated in clinical genetic counseling contexts using at least one individual-level strategy (e.g. increase knowledge). Only three focused on dyadic conversations such as preparing for relatives' information needs. CONCLUSIONS This systematic review posed the question whether theoretically based approaches have been applied to foster family genetic risk communication. Greater attention needs to be paid to the utilization of dyadic level and family system level theories to guide intervention developments. PRACTICAL IMPLICATIONS We conclude by calling for accelerating and broadening the development of interventions to enable family communication about inherited risk that are theory-based, incorporate family-systems thinking, and are conducted outside of specialty clinic settings.
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Affiliation(s)
- Jingsong Zhao
- Department of Behavioral, Social and Health Education Sciences, Emory University, GA, USA.
| | - Yue Guan
- Department of Behavioral, Social and Health Education Sciences, Emory University, GA, USA
| | - Colleen M McBride
- Department of Behavioral, Social and Health Education Sciences, Emory University, GA, USA
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Lyon V, LeRouge C, Fruhling A, Thompson M. Home testing for COVID-19 and other virus outbreaks: The complex system of translating to communities. Health Syst (Basingstoke) 2021; 10:298-317. [PMID: 34745591 PMCID: PMC8567871 DOI: 10.1080/20476965.2021.1952905] [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: 04/09/2020] [Accepted: 06/25/2021] [Indexed: 10/20/2022] Open
Abstract
Home testing is an emerging innovation that can enable nations and health care systems to safely and efficiently test large numbers of patients to manage COVID-19 and other viral outbreaks. In this position paper, we explore the process of moving home testing across the translational continuum from labs to households, and ultimately into practice and communities for optimal public health impact. We focus on the four translational science drivers to accelerate the implementation of systems-wide home testing programmes 1) collaboration and team science, 2) technology, 3) multilevel interventions, and 4) knowledge integration. We use the Socio Ecological Model (SEM) as a framework to illustrate our vision for the ideal future state of a comprehensive system of stakeholders utilising tech-enabled home testing for COVID-19 and other virus outbreaks, and we suggest SEM as a tool to address key translational readiness and response questions.
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Affiliation(s)
- Victoria Lyon
- Department of Family Medicine, Primary Care Innovation Lab, University of Washington, Seattle, Washington, USA
| | - Cynthia LeRouge
- Department of Family Medicine, Primary Care Innovation Lab, University of Washington, Seattle, Washington, USA
- Department of Information Systems & Business Analytics, Florida International University, Miami, FL, USA
| | - Ann Fruhling
- School of Interdisciplinary Informatics, University of Nebraska, Omaha, NE, USA
| | - Matthew Thompson
- Department of Family Medicine, Primary Care Innovation Lab, University of Washington, Seattle, Washington, USA
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Allen CG, Peterson S, Khoury MJ, Brody LC, McBride CM. A scoping review of social and behavioral science research to translate genomic discoveries into population health impact. Transl Behav Med 2021; 11:901-911. [PMID: 32902617 PMCID: PMC8240657 DOI: 10.1093/tbm/ibaa076] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Since the completion of the Human Genome Project, progress toward translating genomic research discoveries to address population health issues has been limited. Several meetings of social and behavioral scientists have outlined priority research areas where advancement of translational research could increase population health benefits of genomic discoveries. In this review, we track the pace of progress, study size and design, and focus of genomics translational research from 2012 to 2018 and its concordance with five social and behavioral science recommended priorities. We conducted a review of the literature following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Guidelines for Scoping Reviews. Steps involved completing a search in five databases and a hand search of bibliographies of relevant literature. Our search (from 2012 to 2018) yielded 4,538 unique studies; 117 were included in the final analyses. Two coders extracted data including items from the PICOTS framework. Analysis included descriptive statistics to help identify trends in pace, study size and design, and translational priority area. Among the 117 studies included in our final sample, nearly half focused on genomics applications that have evidence to support translation or implementation into practice (Centers for Disease Control and Prevention Tier 1 applications). Common study designs were cross-sectional (40.2%) and qualitative (24.8%), with average sample sizes of 716 across all studies. Most often, studies addressed public understanding of genetics and genomics (33.3%), risk communication (29.1%), and intervention development and testing of interventions to promote behavior change (19.7%). The number of studies that address social and behavioral science priority areas is extremely limited and the pace of this research continues to lag behind basic science advances. Much of the research identified in this review is descriptive and related to public understanding, risk communication, and intervention development and testing of interventions to promote behavior change. The field has been slow to develop and evaluate public health-friendly interventions and test implementation approaches that could enable health benefits and equitable access to genomic discoveries. As the completion of the human genome approaches its 20th anniversary, full engagement of transdisciplinary efforts to address translation challenges will be required to close this gap.
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Affiliation(s)
- Caitlin G Allen
- Behavioral, Social and Health Education Sciences Department, Emory University, Atlanta, GA, USA
| | - Shenita Peterson
- Woodruff Health Science Center Library, Emory University, Atlanta, GA, USA
| | - Muin J Khoury
- Office of Genomics and Precision Public Health, Office of Science, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Lawrence C Brody
- Gene and Environment Interaction Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Colleen M McBride
- Behavioral, Social and Health Education Sciences Department, Emory University, Atlanta, GA, USA
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Daly MB. Navigating the Intersection between Genomic Research and Clinical Practice. Cancer Prev Res (Phila) 2021; 13:219-222. [PMID: 32132115 DOI: 10.1158/1940-6207.capr-19-0267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 07/29/2019] [Accepted: 08/23/2019] [Indexed: 12/11/2022]
Abstract
The Risk Assessment Program (RAP) at Fox Chase Cancer Center (Philadelphia, PA) is a multi-generational prospective cohort, enhanced for personal and family history of cancer, consisting of over 10,000 individuals for whom data on personal and family history of cancer, risk factors, genetic and genomic data, health behaviors, and biospecimens are available. The RAP has a broad research agenda including the characterization of genes with known or potential relevance to cancer, gene-gene and gene-environment interactions, and their contribution to clinically useful risk assessment and risk reduction strategies. Increasingly, this body of research is identifying genetic changes which may have clinical significance for RAP research participants, leading us to confront the issue of whether to return genetic results emerging from research laboratories. This review will describe some of the important fundamental points that must be debated as we develop a paradigm for return of research results. The key issues to address as the scientific community moves toward adopting a policy of return of research results include the best criteria for determining which results to offer, the consent document components necessary to ensure that the participant makes a truly informed decision about receiving their results, and associated logistical and cost challenges.See all articles in this Special Collection Honoring Paul F. Engstrom, MD, Champion of Cancer Prevention.
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Affiliation(s)
- Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania.
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6
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An implementation science primer for psycho-oncology: translating robust evidence into practice. ACTA ACUST UNITED AC 2019. [DOI: 10.1097/or9.0000000000000014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Molster CM, Bowman FL, Bilkey GA, Cho AS, Burns BL, Nowak KJ, Dawkins HJS. The Evolution of Public Health Genomics: Exploring Its Past, Present, and Future. Front Public Health 2018; 6:247. [PMID: 30234091 PMCID: PMC6131666 DOI: 10.3389/fpubh.2018.00247] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 08/15/2018] [Indexed: 12/12/2022] Open
Abstract
Public health genomics has evolved to responsibly integrate advancements in genomics into the fields of personalized medicine and public health. Appropriate, effective and sustainable integration of genomics into healthcare requires an organized approach. This paper outlines the history that led to the emergence of public health genomics as a distinguishable field. In addition, a range of activities are described that illustrate how genomics can be incorporated into public health practice. Finally, it presents the evolution of public health genomics into the new era of "precision public health."
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Affiliation(s)
- Caron M. Molster
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
| | - Faye L. Bowman
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
| | - Gemma A. Bilkey
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
- Office of the Chief Health Officer, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
| | - Angela S. Cho
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
| | - Belinda L. Burns
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
| | - Kristen J. Nowak
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
- School of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Western Australia, Crawley, WA, Australia
- Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia
| | - Hugh J. S. Dawkins
- Office of Population Health Genomics, Public and Aboriginal Health Division, Western Australian Department of Health, East Perth, WA, Australia
- School of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Western Australia, Crawley, WA, Australia
- Sir Walter Murdoch School of Policy and International Affairs, Murdoch University, Murdoch, WA, Australia
- School of Public Health, Curtin University of Technology, Bentley, WA, Australia
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Hiatt RA. New Directions in Cancer Control and Population Sciences. Cancer Epidemiol Biomarkers Prev 2018; 26:1165-1169. [PMID: 28765336 DOI: 10.1158/1055-9965.epi-16-1022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 01/03/2017] [Accepted: 03/09/2017] [Indexed: 11/16/2022] Open
Abstract
Cancer control science has been evolving since it first became a focus for cancer research and program activities a century ago. The evolution of the field has responded to historical megatrends along the way that keep it relevant to the cancer-related needs of society. This commentary describes some of the key trends and developments now influencing cancer control and population sciences that reflect societal change and new tools and concepts in modern biomedical science. New directions include the impact of climate change, health care delivery research, the growth of population health science, data science, precision medicine, data sharing, implementation science, and new technologies, including social media and new geospatial methodologies. Cancer Epidemiol Biomarkers Prev; 26(8); 1165-9. ©2017 AACR.
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Affiliation(s)
- Robert A Hiatt
- University of California, San Francisco, San Francisco, California.
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9
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¿CÓMO PUEDO MODIFICAR MI RIESGO A DESARROLLAR CÁNCER, CUANDO SOY PORTADOR DE UNA MUTACIÓN? REVISTA MÉDICA CLÍNICA LAS CONDES 2017. [DOI: 10.1016/j.rmclc.2017.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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10
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Trends in National Institutes of Health-Funded Congenital Heart Disease Research from 2005 to 2015. Pediatr Cardiol 2017; 38:974-980. [PMID: 28349207 PMCID: PMC5745797 DOI: 10.1007/s00246-017-1605-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 03/18/2017] [Indexed: 10/19/2022]
Abstract
In an era of ongoing need for research to enable evidence-based care for the expanding population with congenital heart disease (CHD), economic fluctuations have impacted research funding. We characterize trends in NIH-funded CHD research from 2005 to 2015. We searched the NIH RePORTER database from 2005 to 2015 using the terms "congenital heart" and "cardiac morphogenesis". Projects were characterized by year, institute, mechanism, costs, type and topic, and funding trends were analyzed. From 2005 to 2015, NIH funded 633 CHD research projects with total costs of $991 million. The National Heart, Lung, and Blood Institute funded 83% of CHD projects (528, $857 million). The R01 mechanism was used for 45% of projects (288, $421 million). Projects were 70% basic/early translational research, 27% clinical research, and 3% both. Cardiac developmental biology was the most common topic (52%), followed by technology/therapy development (15%), and diagnosis/management (12%). The total number of CHD projects ranged from 153 to 221 per year (30-58 new projects/year), and costs per year ranged from $58 to $116 million. The number of projects and total costs increased until 2012, but decreased again thereafter. CHD research did not experience as much erosion as overall NIH purchasing power; in constant dollars, CHD research funding levels in 2015 were $12 million higher than those in 2005. The NIH supported a diverse portfolio of CHD projects from 2005 to 2015. Support of CHD research projects trended upward until 2012, but declined thereafter due to fiscal austerity measures.
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Trifiletti DM, Sturz VN, Showalter TN, Lobo JM. Towards decision-making using individualized risk estimates for personalized medicine: A systematic review of genomic classifiers of solid tumors. PLoS One 2017; 12:e0176388. [PMID: 28486497 PMCID: PMC5423583 DOI: 10.1371/journal.pone.0176388] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 04/10/2017] [Indexed: 12/16/2022] Open
Abstract
Recent advances in the understanding of the genetic underpinnings of cancer offer the promise to customize cancer treatments to the individual through the use of genomic classifiers (GCs). At present, routine clinical utilization of GCs is uncommon and their current scope and status, in a broad sense, are unknown. As part of a registered review (PROSPERO 2014:CRD42014013371), we systematically reviewed the literature evaluating the utility of commercially available GCs by searching Ovid Medline (PubMed), EMBASE, the Cochrane Database of Systematic Reviews, and CINAHL on September 2, 2014. We excluded articles involving pediatric malignancies, non-solid or non-invasive cancers, hereditary risk of cancer, non-validated GCs, and GCs involving fewer than 3 biomarkers. A total of 3,625 studies were screened, but only 37 met the pre-specified inclusion criteria. Of these, 15 studies evaluated outcomes and clinical utility of GCs through clinical trials, and the remainder through the use of mathematical models. Most studies (29 of 37) were specific to hormone-receptor positive breast cancer, whereas only 4 studies evaluated GCs in non-breast cancer (prostate, colon, and lung cancers). GCs have spurred excitement across disciplines in recent decades. While there are several GCs that have been validated, the general quality of the data are weak. Further research, including prospective validation is needed, particularly in the non-breast cancer GCs.
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Affiliation(s)
- Daniel M. Trifiletti
- Department of Radiation Oncology, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - Vanessa N. Sturz
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - Timothy N. Showalter
- Department of Radiation Oncology, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - Jennifer M. Lobo
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, United States of America
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Hay JL, Berwick M, Zielaskowski K, White KA, Rodríguez VM, Robers E, Guest DD, Sussman A, Talamantes Y, Schwartz MR, Greb J, Bigney J, Kaphingst KA, Hunley K, Buller DB. Implementing an Internet-Delivered Skin Cancer Genetic Testing Intervention to Improve Sun Protection Behavior in a Diverse Population: Protocol for a Randomized Controlled Trial. JMIR Res Protoc 2017; 6:e52. [PMID: 28442450 PMCID: PMC5424125 DOI: 10.2196/resprot.7158] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 02/08/2017] [Accepted: 02/08/2017] [Indexed: 11/13/2022] Open
Abstract
Background Limited translational genomic research currently exists to guide the availability, comprehension, and appropriate use of personalized genomics in diverse general population subgroups. Melanoma skin cancers are preventable, curable, common in the general population, and disproportionately increasing in Hispanics. Objective Variants in the melanocortin-1 receptor (MC1R) gene are present in approximately 50% of the population, are major factors in determining sun sensitivity, and confer a 2-to-3-fold increase in melanoma risk in the general population, even in populations with darker skin. Therefore, feedback regarding MC1R risk status may raise risk awareness and protective behavior in the general population. Methods We are conducting a randomized controlled trial examining Internet presentation of the risks and benefits of personalized genomic testing for MC1R gene variants that are associated with increased melanoma risk. We will enroll a total of 885 participants (462 participants are currently enrolled), who will be randomized 6:1 to personalized genomic testing for melanoma risk versus waiting list control. Control participants will be offered testing after outcome assessments. Participants will be balanced across self-reported Hispanic versus non-Hispanic ethnicity (n=750 in personalized genomic testing for melanoma risk arm; n=135 in control arm), and will be recruited from a general population cohort in Albuquerque, New Mexico, which is subject to year-round sun exposure. Baseline surveys will be completed in-person with study staff and follow-up measures will be completed via telephone. Results Aim 1 of the trial will examine the personal utility of personalized genomic testing for melanoma risk in terms of short-term (3-month) sun protection and skin screening behaviors, family and physician communication, and melanoma threat and control beliefs (ie, putative mediators of behavior change). We will also examine potential unintended consequences of testing among those who receive average-risk personalized genomic testing for melanoma risk findings, and examine predictors of sun protection at 3 months as the outcome. These findings will be used to develop messages for groups that receive average-risk feedback. Aim 2 will compare rates of test consideration in Hispanics versus non-Hispanics, including consideration of testing pros and cons and registration of a decision to either accept or decline testing. Aim 3 will examine personalized genomic testing for melanoma risk feedback comprehension, recall, satisfaction, and cancer-related distress in those who undergo testing, and whether these outcomes differ by ethnicity (Hispanic vs non-Hispanic), or sociocultural or demographic factors. Final outcome data collection is anticipated to be complete by October 2017, at which point data analysis will commence. Conclusions This study has important implications for personalized genomics in the context of melanoma risk, and may be broadly applicable as a model for delivery of personalized genomic feedback for other health conditions.
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Affiliation(s)
- Jennifer L Hay
- Memorial Sloan Kettering Cancer Center, Department of Psychiatry & Behavioral Sciences, New York, NY, United States
| | | | - Kate Zielaskowski
- Memorial Sloan Kettering Cancer Center, Department of Psychiatry & Behavioral Sciences, New York, NY, United States
| | | | | | - Erika Robers
- University of New Mexico, Albuquerque, NM, United States
| | | | - Andrew Sussman
- University of New Mexico, Albuquerque, NM, United States
| | | | | | - Jennie Greb
- University of New Mexico, Albuquerque, NM, United States
| | - Jessica Bigney
- University of New Mexico, Albuquerque, NM, United States
| | | | - Keith Hunley
- University of New Mexico, Albuquerque, NM, United States
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Fort DG, Herr TM, Shaw PL, Gutzman KE, Starren JB. Mapping the evolving definitions of translational research. J Clin Transl Sci 2017; 1:60-66. [PMID: 28480056 PMCID: PMC5408839 DOI: 10.1017/cts.2016.10] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Revised: 08/10/2016] [Accepted: 10/11/2016] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Systematic review and analysis of definitions of translational research. MATERIALS AND METHODS The final corpus was comprised of 33 papers, each read by at least 2 reviewers. Definitions were mapped to a common set of research processes for presentation and analysis. Influence of papers and definitions was further evaluated using citation analysis and agglomerative clustering. RESULTS All definitions were mapped to common research processes, revealing most common labels for each process. Agglomerative clustering revealed 3 broad families of definitions. Citation analysis showed that the originating paper of each family has been cited ~10 times more than any other member. DISCUSSION Although there is little agreement between definitions, we were able to identify an emerging consensus 5-phase (T0-T4) definition for translational research. T1 involves processes that bring ideas from basic research through early testing in humans. T2 involves the establishment of effectiveness in humans and clinical guidelines. T3 primarily focuses on implementation and dissemination research while T4 focuses on outcomes and effectiveness in populations. T0 involves research such as genome-wide association studies which wrap back around to basic research. CONCLUSION We used systematic review and analysis to identify emerging consensus between definitions of translational research phases.
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Affiliation(s)
- Daniel G. Fort
- Department of Preventive Medicine, Feinberg School of Medicine, Division of Health and Biomedical Informatics, Northwestern University, Chicago, IL, USA
| | - Timothy M. Herr
- Department of Preventive Medicine, Feinberg School of Medicine, Division of Health and Biomedical Informatics, Northwestern University, Chicago, IL, USA
| | - Pamela L. Shaw
- Galter Health Sciences Library, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Karen E. Gutzman
- Galter Health Sciences Library, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Justin B. Starren
- Department of Preventive Medicine, Feinberg School of Medicine, Division of Health and Biomedical Informatics, Northwestern University, Chicago, IL, USA
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Building a Platform to Enable NCD Research to Address Population Health in Africa: CVD Working Group Discussion at the Sixth H3Africa Consortium Meeting in Zambia. Glob Heart 2017; 11:165-70. [PMID: 27102038 DOI: 10.1016/j.gheart.2015.11.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Accepted: 11/24/2015] [Indexed: 12/15/2022] Open
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Maas P, Barrdahl M, Joshi AD, Auer PL, Gaudet MM, Milne RL, Schumacher FR, Anderson WF, Check D, Chattopadhyay S, Baglietto L, Berg CD, Chanock SJ, Cox DG, Figueroa JD, Gail MH, Graubard BI, Haiman CA, Hankinson SE, Hoover RN, Isaacs C, Kolonel LN, Le Marchand L, Lee IM, Lindström S, Overvad K, Romieu I, Sanchez MJ, Southey MC, Stram DO, Tumino R, VanderWeele TJ, Willett WC, Zhang S, Buring JE, Canzian F, Gapstur SM, Henderson BE, Hunter DJ, Giles GG, Prentice RL, Ziegler RG, Kraft P, Garcia-Closas M, Chatterjee N. Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States. JAMA Oncol 2016; 2:1295-1302. [PMID: 27228256 PMCID: PMC5719876 DOI: 10.1001/jamaoncol.2016.1025] [Citation(s) in RCA: 234] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
IMPORTANCE An improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention. OBJECTIVE To evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors. DESIGN, SETTING, AND PARTICIPANTS Using a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality. EXPOSURES Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors. MAIN OUTCOMES AND MEASURES Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking). RESULTS The average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population. CONCLUSIONS AND RELEVANCE This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.
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Affiliation(s)
- Paige Maas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Myrto Barrdahl
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Amit D Joshi
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Paul L Auer
- Fred Hutchinson Cancer Research Center, Seattle, Washington5School of Public Health, University of Wisconsin-Milwaukee, Milwaukee
| | - Mia M Gaudet
- Epidemiology Research Program, American Cancer Society, Atlanta Georgia
| | - Roger L Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia8Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Fredrick R Schumacher
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles
| | - William F Anderson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - David Check
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Subham Chattopadhyay
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Laura Baglietto
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia8Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Christine D Berg
- Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - David G Cox
- INSERM U1052 - Cancer Research Center of Lyon, Centre Léon Bérard, Lyon, France12Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, England
| | - Jonine D Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Mitchell H Gail
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Barry I Graubard
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles
| | - Susan E Hankinson
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst14Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Robert N Hoover
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Claudine Isaacs
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC
| | - Laurence N Kolonel
- Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu
| | | | - I-Min Lee
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Sara Lindström
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Isabelle Romieu
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Maria-Jose Sanchez
- Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.GRANADA. Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain22CIBER de Epidemiología y Salud Pública (CIBERESP), Spain
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Australia
| | - Daniel O Stram
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles
| | - Rosario Tumino
- Cancer Registry and Histopathology Unit, "Civic- M.P.Arezzo" Hospital, ASP Ragusa, Italy
| | - Tyler J VanderWeele
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts26Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Walter C Willett
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Shumin Zhang
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | | | - Susan M Gapstur
- Epidemiology Research Program, American Cancer Society, Atlanta Georgia
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles
| | - David J Hunter
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia8Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia29Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Ross L Prentice
- Fred Hutchinson Cancer Research Center, Seattle, Washington30University of Washington, School of Public Health and Community Medicine, Seattle
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Montse Garcia-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland31Breakthrough Breast Cancer Research Centre, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, England
| | - Nilanjan Chatterjee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland32Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland33Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
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Blazer KR, Nehoray B, Solomon I, Niell-Swiller M, Culver JO, Uman GC, Weitzel JN. Next-Generation Testing for Cancer Risk: Perceptions, Experiences, and Needs Among Early Adopters in Community Healthcare Settings. Genet Test Mol Biomarkers 2015; 19:657-65. [PMID: 26539620 DOI: 10.1089/gtmb.2015.0061] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Advances in next-generation sequencing (NGS) technologies are driving a shift from single-gene to multigene panel testing for clinical genetic cancer risk assessment (GCRA). This study explored perceptions, experiences, and challenges with NGS testing for GCRA among U.S. community-based clinicians. METHODS Surveys delivered at initial and 8-month time points, and 12-month tracking of cases presented in a multidisciplinary web-based case conference series, were conducted with GCRA providers who participated in a 235-member nationwide community of practice. RESULTS The proportion of respondents ordering panel tests rose from 29% at initial survey (27/94) to 44% (46/107) within 8 months. Respondents reported significantly less confidence about interpreting and counseling about NGS compared with single-gene test results (p < 0.0001 for all comparisons). The most cited reasons for not ordering NGS tests included concerns about clinical utility, interpreting and communicating results, and lack of knowledge/skills. Multigene panels were used in 204/668 cases presented during 2013, yielding 37 (18%) deleterious (7% in low/moderate-penetrance genes), 88 (43%) with ≥1 variant of uncertain significance, 77 (38%) uninformative negative, and 2 (1%) inconclusive results. CONCLUSIONS Despite concerns about utility and ability to interpret/counsel about NGS results, a rapidly increasing uptake of NGS testing among community clinicians was documented. Challenges identified in case discussions point to the need for ongoing education, practice-based support, and opportunities to partner in research that contributes to characterization of lesser known genes.
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Affiliation(s)
- Kathleen R Blazer
- 1 City of Hope, Division of Clinical Cancer Genetics , Duarte, California
| | - Bita Nehoray
- 1 City of Hope, Division of Clinical Cancer Genetics , Duarte, California
| | - Ilana Solomon
- 1 City of Hope, Division of Clinical Cancer Genetics , Duarte, California
| | | | - Julie O Culver
- 1 City of Hope, Division of Clinical Cancer Genetics , Duarte, California
| | | | - Jeffrey N Weitzel
- 1 City of Hope, Division of Clinical Cancer Genetics , Duarte, California
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Cohn EG, Husamudeen M, Larson EL, Williams JK. Increasing participation in genomic research and biobanking through community-based capacity building. J Genet Couns 2015; 24:491-502. [PMID: 25228357 PMCID: PMC4815899 DOI: 10.1007/s10897-014-9768-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2014] [Accepted: 08/27/2014] [Indexed: 10/24/2022]
Abstract
Achieving equitable minority representation in genomic biobanking is one of the most difficult challenges faced by researchers today. Capacity building--a framework for research that includes collaborations and on-going engagement--can be used to help researchers, clinicians and communities better understand the process, utility, and clinical application of genomic science. The purpose of this exploratory descriptive study was to examine factors that influence the decision to participate in genomic research, and identify essential components of capacity building with a community at risk of being under-represented in biobanks. Results of focus groups conducted in Central Harlem with 46 participants were analyzed by a collaborative team of community and academic investigators using content analysis and AtlisTi. Key themes identified were: (1) the potential contribution of biobanking to individual and community health, for example the effect of the environment on health, (2) the societal context of the science, such as DNA criminal databases and paternity testing, that may affect the decision to participate, and (3) the researchers' commitment to community health as an outcome of capacity building. These key factors can contribute to achieving equity in biobank participation, and guide genetic specialists in biobank planning and implementation.
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Affiliation(s)
- Elizabeth Gross Cohn
- Columbia University, School of Nursing, 617 W. 168 Street Room 244, New York, NY, USA,
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18
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Brownson RC, Samet JM, Chavez GF, Davies MM, Galea S, Hiatt RA, Hornung CA, Khoury MJ, Koo D, Mays VM, Remington P, Yarber L. Charting a future for epidemiologic training. Ann Epidemiol 2015; 25:458-65. [PMID: 25976024 DOI: 10.1016/j.annepidem.2015.03.002] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2015] [Accepted: 03/03/2015] [Indexed: 01/24/2023]
Abstract
PURPOSE To identify macro-level trends that are changing the needs of epidemiologic research and practice and to develop and disseminate a set of competencies and recommendations for epidemiologic training that will be responsive to these changing needs. METHODS There were three stages to the project: (1) assembling of a working group of senior epidemiologists from multiple sectors, (2) identifying relevant literature, and (3) conducting key informant interviews with 15 experienced epidemiologists. RESULTS Twelve macro trends were identified along with associated actions for the field and educational competencies. The macro trends include the following: (1) "Big Data" or informatics, (2) the changing health communication environment, (3) the Affordable Care Act or health care system reform, (4) shifting demographics, (5) globalization, (6) emerging high-throughput technologies (omics), (7) a greater focus on accountability, (8) privacy changes, (9) a greater focus on "upstream" causes of disease, (10) the emergence of translational sciences, (11) the growing centrality of team and transdisciplinary science, and (12) the evolving funding environment. CONCLUSIONS Addressing these issues through curricular change is needed to allow the field of epidemiology to more fully reach and sustain its full potential to benefit population health and remain a scientific discipline that makes critical contributions toward ensuring clinical, social, and population health.
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Affiliation(s)
- Ross C Brownson
- Prevention Research Center in St. Louis, Brown School, Washington University in St. Louis, St. Louis, MO; Division of Public Health Sciences and Alvin J. Siteman Cancer Center, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO.
| | - Jonathan M Samet
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles
| | - Gilbert F Chavez
- Center for Infectious Diseases, California Department of Public Health, Sacramento
| | - Megan M Davies
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh; Council of State and Territorial Epidemiologists, Atlanta, GA
| | - Sandro Galea
- School of Public Health, Boston University, Boston, MA
| | - Robert A Hiatt
- Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco
| | - Carlton A Hornung
- Department of Medicine, School of Medicine, University of Louisville, Louisville, KY
| | - Muin J Khoury
- Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA; Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
| | - Denise Koo
- Office of Public Health Scientific Services, Centers for Disease Control and Prevention, Atlanta, GA
| | - Vickie M Mays
- Department of Psychology, UCLA Fielding School of Public Health and UCLA BRITE Center for Science, Research and Policy, Los Angeles CA; Department of Health Policy and Management, UCLA Fielding School of Public Health and UCLA BRITE Center for Science, Research and Policy, Los Angeles CA
| | - Patrick Remington
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | - Laura Yarber
- Prevention Research Center in St. Louis, College of Public Health and Social Justice, Saint Louis University, St. Louis, MO
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Snyder SR, Mitropoulou C, Patrinos GP, Williams MS. Economic Evaluation of Pharmacogenomics: A Value-Based Approach to Pragmatic Decision Making in the Face of Complexity. Public Health Genomics 2014; 17:256-64. [DOI: 10.1159/000366177] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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20
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Bielecka ZF, Czarnecka AM, Szczylik C. Genomic Analysis as the First Step toward Personalized Treatment in Renal Cell Carcinoma. Front Oncol 2014; 4:194. [PMID: 25120953 PMCID: PMC4110478 DOI: 10.3389/fonc.2014.00194] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Accepted: 07/09/2014] [Indexed: 12/13/2022] Open
Abstract
Drug resistance mechanisms in renal cell carcinoma (RCC) still remain elusive. Although most patients initially respond to targeted therapy, acquired resistance can still develop eventually. Most of the patients suffer from intrinsic (genetic) resistance as well, suggesting that there is substantial need to broaden our knowledge in the field of RCC genetics. As molecular abnormalities occur for various reasons, ranging from single nucleotide polymorphisms to large chromosomal defects, conducting whole-genome association studies using high-throughput techniques seems inevitable. In principle, data obtained via genome-wide research should be continued and performed on a large scale for the purposes of drug development and identification of biological pathways underlying cancerogenesis. Genetic alterations are mostly unique for each histological RCC subtype. According to recently published data, RCC is a highly heterogeneous tumor. In this paper, the authors discuss the following: (1) current state-of-the-art knowledge on the potential biomarkers of RCC subtypes; (2) significant obstacles encountered in the translational research on RCC; and (3) recent molecular findings that may have a crucial impact on future therapeutic approaches.
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Affiliation(s)
- Zofia Felicja Bielecka
- Department of Oncology with the Laboratory of Molecular Oncology, Military Institute of Medicine , Warsaw , Poland ; Postgraduate School of Molecular Medicine, Medical University of Warsaw , Warsaw , Poland
| | - Anna Małgorzata Czarnecka
- Department of Oncology with the Laboratory of Molecular Oncology, Military Institute of Medicine , Warsaw , Poland
| | - Cezary Szczylik
- Department of Oncology with the Laboratory of Molecular Oncology, Military Institute of Medicine , Warsaw , Poland
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21
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Jbilou J, Halilem N, Blouin-Bougie J, Amara N, Landry R, Simard J. Medical genetic counseling for breast cancer in primary care: a synthesis of major determinants of physicians' practices in primary care settings. Public Health Genomics 2014; 17:190-208. [PMID: 24993835 DOI: 10.1159/000362358] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2013] [Accepted: 03/20/2014] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES This paper aims to identify relevant potential predictors of medical genetic counseling for breast cancer (MGC-BC) in primary care and to develop a comprehensive questionnaire to study MGC-BC. METHODS A scoping review was conducted to identify the predictors of MGC-BC among primary care physicians. Relevant articles were identified in selected databases (PubMed, Embase, CINAHL, ISI Web of Science, PsycINFO, and Cochrane CENTRAL) and 4 selected relevant electronic journals. RESULTS An inductive analysis of the 193 quantitatively tested variables, conducted by 3 researchers, showed that 6 conceptual categories of determinants, namely (1) demographic, (2) organizational, (3) experiential, (4) professional, (5) psychological, and (6) cognitive, influence MGC-BC practices. CONCLUSION There is a scarcity of literature addressing the medical behavior determinants of MGC-BC. Future research is needed to identify effective strategies put into action to support the integration of MGC-BC in primary care medical practices and routines. However, our results shed light on 2 levels of actions that could improve genetic counseling services in primary care: (1) medical training and educational efforts emphasizing family history collection (individual level), and (2) clarification of roles and responsibilities in ordering and referral practices in genetic counseling and genetic testing for better healthcare management (organizational level).
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Affiliation(s)
- Jalila Jbilou
- Centre de formation médicale du Nouveau-Brunswick, Université de Moncton, Moncton, N.B., Canada
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22
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Bartlett G, Rahimzadeh V, Longo C, Orlando LA, Dawes M, Lachaine J, Bochud M, Paccaud F, Bergman H, Crimi L, Issa AM. The future of genomic testing in primary care: the changing face of personalized medicine. Per Med 2014; 11:477-486. [PMID: 29758776 DOI: 10.2217/pme.14.36] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Primary care is recognized worldwide as a key component for improving health outcomes in the population. At the same time, healthcare systems are rapidly changing with increasing expectations from technological advances. Genomics is a major driver in changing how medicine is being practiced; however, the importance for primary care has been under-appreciated. Strategically implementing genomics in a way that accounts for the unique characteristics of the primary care context is essential. In this perspective, we present important areas that we believe are critical in consideration of both the future of genomic medicine and primary healthcare delivery.
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Affiliation(s)
- Gillian Bartlett
- Department of Family Medicine, McGill University, 5858 Cote-des-Neiges, Suite 300, Montreal, Quebec, H3S 1Z1, Canada
| | - Vaso Rahimzadeh
- Department of Family Medicine, McGill University, 5858 Cote-des-Neiges, Suite 300, Montreal, Quebec, H3S 1Z1, Canada
| | - Cristina Longo
- Department of Family Medicine, McGill University, 5858 Cote-des-Neiges, Suite 300, Montreal, Quebec, H3S 1Z1, Canada
| | - Lori A Orlando
- Department of Medicine & Center for Personalized & Precision Medicine, Duke University, Wallace Clinic, Room 204, 3475 Erwin Rd, Duke Box 3022, Durham, NC 27705, USA
| | - Martin Dawes
- Department of Family Practice, University of British Columbia, David Strangway Building Third floor, 5950 University Blvd, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Jean Lachaine
- Faculté de Pharmacie, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada
| | - Murielle Bochud
- University Institute of Social & Preventive Medicine, Lausanne University Hospital, Route de la Corniche 10, 1010 Lausanne, Switzerland
| | - Fred Paccaud
- University Institute of Social & Preventive Medicine, Lausanne University Hospital, Route de la Corniche 10, 1010 Lausanne, Switzerland
| | - Howard Bergman
- Department of Family Medicine, McGill University, 5858 Cote-des-Neiges, Suite 300, Montreal, Quebec, H3S 1Z1, Canada
| | - Laura Crimi
- Department of Family Medicine, McGill University, 5858 Cote-des-Neiges, Suite 300, Montreal, Quebec, H3S 1Z1, Canada
| | - Amalia M Issa
- Program in Personalized Medicine & Targeted Therapeutics & the Department of Health Policy & Public Health, University of the Sciences, 600 South 43rd Street, Philadelphia, PA 19104, USA
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Stakeholder consultation insights on the future of genomics at the clinical-public health interface. Transl Res 2014; 163:466-77. [PMID: 24434657 DOI: 10.1016/j.trsl.2013.12.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2013] [Revised: 12/18/2013] [Accepted: 12/19/2013] [Indexed: 02/03/2023]
Abstract
In summer 2011, the Centers for Disease Control and Prevention Office of Public Health Genomics conducted a stakeholder consultation, administered by the University of Michigan Center for Public Health and Community Genomics, and Genetic Alliance, to recommend priorities for public health genomics from 2012 through 2017. Sixty-two responses from health professionals, administrators, and members of the public were pooled with 2 sets of key informant interviews and 3 discussion groups. NVivo 9 and manual methods were used to organize themes. This review offers an interim analysis of progress with respect to the final recommendations, which demonstrated a strong interest in moving genomic discoveries toward implementation and comparative effectiveness (T3/T4) translational research. A translational research continuum exists with familial breast and ovarian cancer at one end and prostate cancer at the other. Cascade screening for inherited arrhythmia syndromes and hypercholesterolemia lags stakeholder recommendations in the United States but not in Europe; implementation of health service-based screening for Lynch syndrome, and integration into electronic health information systems, is on pace with the recommended timeline. A number of options exist to address deficits in the funding of translational research, particularly for oncogenomic gene expression profiling. The goal of personalized risk assessment necessitates both research progress (eg, in whole genome sequencing, as well as provider education in the differentiation of low- vs high-risk status. The public health approach supports an emphasis on genetic test validation while endorsing clinical translation research inclusion of an environmental and population-based perspective.
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24
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Hiraki S, Rinella ES, Schnabel F, Oratz R, Ostrer H. Cancer risk assessment using genetic panel testing: considerations for clinical application. J Genet Couns 2014; 23:604-17. [PMID: 24599651 DOI: 10.1007/s10897-014-9695-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Accepted: 01/28/2014] [Indexed: 02/07/2023]
Abstract
With the completion of the Human Genome Project and the development of high throughput technologies, such as next-generation sequencing, the use of multiplex genetic testing, in which multiple genes are sequenced simultaneously to test for one or more conditions, is growing rapidly. Reflecting underlying heterogeneity where a broad range of genes confer risks for one or more cancers, the development of genetic cancer panels to assess these risks represents just one example of how multiplex testing is being applied clinically. There are a number of issues and challenges to consider when conducting genetic testing for cancer risk assessment, and these issues become exceedingly more complex when moving from the traditional single-gene approach to panel testing. Here, we address the practical considerations for clinical use of panel testing for breast, ovarian, and colon cancers, including the benefits, limitations and challenges, genetic counseling issues, and management guidelines.
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Affiliation(s)
- Susan Hiraki
- Department of Pathology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Ullmann 819, Bronx, NY, 10046, USA,
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25
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Graves KD, Hay JL, O'Neill SC. The promise of using personalized genomic information to promote behavior change: is the debate over, or just beginning? Per Med 2014; 11:173-185. [PMID: 29751381 DOI: 10.2217/pme.13.110] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Over recent years, significant debate has centered on whether and how communication of personalized genomic risk information can positively influence health behavior change. Several thoughtful commentaries have cautioned that efforts to incorporate genomic risk feedback to motivate health behavior change have had little success. As a field, we should consider the reasons for this limited success and be strategic in the next steps for this line of research. In this article, we consider several reasons that prior research that integrates personalized genomic information has had relative degrees of success in changing or maintaining health behaviors. We suggest ways forward and outline the possibilities presented by emerging technologies and novel approaches in translational genomic research.
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Affiliation(s)
- Kristi D Graves
- Department of Oncology, Jess & Mildred Fisher Center for Familial Cancer Research, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Jennifer L Hay
- Department of Psychiatry & Behavioral Sciences, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Suzanne C O'Neill
- Department of Oncology, Jess & Mildred Fisher Center for Familial Cancer Research, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
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Ioannidis JPA, Greenland S, Hlatky MA, Khoury MJ, Macleod MR, Moher D, Schulz KF, Tibshirani R. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 2014; 383:166-75. [PMID: 24411645 PMCID: PMC4697939 DOI: 10.1016/s0140-6736(13)62227-8] [Citation(s) in RCA: 945] [Impact Index Per Article: 94.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Correctable weaknesses in the design, conduct, and analysis of biomedical and public health research studies can produce misleading results and waste valuable resources. Small effects can be difficult to distinguish from bias introduced by study design and analyses. An absence of detailed written protocols and poor documentation of research is common. Information obtained might not be useful or important, and statistical precision or power is often too low or used in a misleading way. Insufficient consideration might be given to both previous and continuing studies. Arbitrary choice of analyses and an overemphasis on random extremes might affect the reported findings. Several problems relate to the research workforce, including failure to involve experienced statisticians and methodologists, failure to train clinical researchers and laboratory scientists in research methods and design, and the involvement of stakeholders with conflicts of interest. Inadequate emphasis is placed on recording of research decisions and on reproducibility of research. Finally, reward systems incentivise quantity more than quality, and novelty more than reliability. We propose potential solutions for these problems, including improvements in protocols and documentation, consideration of evidence from studies in progress, standardisation of research efforts, optimisation and training of an experienced and non-conflicted scientific workforce, and reconsideration of scientific reward systems.
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Affiliation(s)
- John P A Ioannidis
- Stanford Prevention Research Center, Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA; Division of Epidemiology, School of Medicine, Stanford University, Stanford, CA, USA; Department of Statistics, School of Humanities and Sciences, Stanford University, Stanford, CA, USA; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.
| | - Sander Greenland
- Department of Epidemiology and Department of Statistics, UCLA School of Public Health, Los Angeles, CA, USA
| | - Mark A Hlatky
- Division of Cardiovascular Medicine, Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA; Division of Health Services Research, Stanford University, Stanford, CA, USA
| | - Muin J Khoury
- Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemiology and Genomics Research Program, National Cancer Institute, Rockville, MD, USA
| | - Malcolm R Macleod
- Department of Clinical Neurosciences, University of Edinburgh School of Medicine, Edinburgh, UK
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada; Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Kenneth F Schulz
- FHI 360, Durham, NC, USA; Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Robert Tibshirani
- Department of Health Research and Policy, Stanford University, Stanford, CA, USA; Department of Statistics, School of Humanities and Sciences, Stanford University, Stanford, CA, USA
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Waters EA, Kincaid C, Kaufman AR, Stock ML, Peterson LM, Muscanell NL, Guadagno RE. Concerns about unintended negative consequences of informing the public about multifactorial risks may be premature for young adult smokers. Br J Health Psychol 2013; 19:720-36. [PMID: 24118369 DOI: 10.1111/bjhp.12069] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2012] [Revised: 08/13/2013] [Indexed: 12/18/2022]
Abstract
BACKGROUND Many health risks are associated with both genetic and behavioural factors. Concerns have been raised that learning about such multifactorial risks might have detrimental effects on health-related beliefs, cognitions, and affect. However, experimental evidence is sparse. OBJECTIVE To explore the effects of reading an online news article about the discovery of a genetic basis for nicotine addiction. METHODS Smokers (N = 333) were recruited from the psychology subject pools of two major universities. Participants were randomly assigned to read one of three news articles: one describing a genetic basis for nicotine addiction and lung cancer obtained from a national news source, one altered to indicate no genetic basis for nicotine addiction and lung cancer, or one unrelated attention control. Participants then completed an online questionnaire, which assessed smoking-related cognitions and affect, and beliefs about nicotine addiction, quitting smoking, and whether the harms of tobacco use are delayed. RESULTS There was no statistically significant influence of experimental condition on smoking-related cognitions/affect (ps > .05, η(2) < .002), beliefs about addiction and quitting (Wilks' λ = .98, p = .66, η(2) = .01), or delayed harm (ps > .05, η(2) < .002). CONCLUSION Reading an online news article about the presence or absence of a genetic basis for nicotine addiction was not found to change smoking-related cognitions/affect or beliefs among young adult smokers. Concerns about negative effects of multifactorial risk information on health beliefs may be premature. Nevertheless, to effectively translate basic genomics research into effective public health practice, further research should investigate these issues in different populations, via different communication modalities, and for different health outcomes. STATEMENT OF CONTRIBUTION What is already known on this subject? Information about the health implications of the interaction between genetics and behaviour is becoming prevalent. Learning about these interactions may reduce perceived risk and intentions to engage in health behaviours. What does this study add? Informing young adult smokers about the genetic basis for nicotine addiction does not affect health beliefs negatively. Responses are not moderated by endorsing the idea of genetic causation or current/experimenter smoking status.
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Affiliation(s)
- Erika A Waters
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
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Fashoyin-Aje L, Sanghavi K, Bjornard K, Bodurtha J. Integrating genetic and genomic information into effective cancer care in diverse populations. Ann Oncol 2013; 24 Suppl 7:vii48-54. [PMID: 24001763 DOI: 10.1093/annonc/mdt264] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
This paper provides an overview of issues in the integration of genetic (related to hereditary DNA) and genomic (related to genes and their functions) information in cancer care for individuals and families who are part of health care systems worldwide, from low to high resourced. National and regional cancer plans have the potential to integrate genetic and genomic information with a goal of identifying and helping individuals and families with and at risk of cancer. Healthcare professionals and the public have the opportunity to increase their genetic literacy and communication about cancer family history to enhance cancer control, prevention, and tailored therapies.
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Affiliation(s)
- L Fashoyin-Aje
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, 600 N. Wolfe St., Baltimore, MD 21287, USA.
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Birmingham WC, Agarwal N, Kohlmann W, Aspinwall LG, Wang M, Bishoff J, Dechet C, Kinney AY. Patient and provider attitudes toward genomic testing for prostate cancer susceptibility: a mixed method study. BMC Health Serv Res 2013; 13:279. [PMID: 23870420 PMCID: PMC3750463 DOI: 10.1186/1472-6963-13-279] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2012] [Accepted: 06/27/2013] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND The strong association between family history and prostate cancer (PCa) suggests a significant genetic contribution, yet specific highly penetrant PCa susceptibility genes have not been identified. Certain single-nucleotide-polymorphisms have been found to correlate with PCa risk; however uncertainty remains regarding their clinical utility and how to best incorporate this information into clinical decision-making. Genetic testing is available directly to consumers and both patients and healthcare providers are becoming more aware of this technology. Purchasing online allows patients to bypass their healthcare provider yet patients may have difficulty interpreting test results and providers may be called upon to interpret results. Determining optimal ways to educate both patients and providers, and strategies for appropriately incorporating this information into clinical decision-making are needed. METHODS A mixed-method study was conducted in Utah between October 2011 and December 2011. Eleven focus group discussions were held and surveys were administered to 23 first-degree relatives of PCa patients living in Utah and 24 primary-care physicians and urologists practicing in Utah to present specific information about these assessments and determine knowledge and attitudes regarding health implications of using these assessments. RESULTS Data was independently coded by two researchers (relative Kappa = .88; provider Kappa = .77) and analyzed using a grounded theory approach. Results indicated differences in attitudes and behavioral intentions between patient and provider. Despite the test's limitations relatives indicated interest in genetic testing (52%) while most providers indicated they would not recommend the test for their patients (79%). Relatives expected providers to interpret genetic test results and use results to provide personalized healthcare recommendations while the majority of providers did not think the information would be useful in patient care (92%) and indicated low-levels of genetic self-efficacy. CONCLUSIONS Although similarities exist, discordance between provider and patient attitudes may influence the effective translation of novel genomic tests into clinical practice suggesting both patient and provider perceptions and expectations be considered in development of clinical decision-support tools.
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Affiliation(s)
- Wendy C Birmingham
- Department of Psychology, Brigham Young University, 1054 SWKT, Provo, UT 84602, USA
| | - Neeraj Agarwal
- Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112, USA
- Department of Internal Medicine, University of Utah, 30 North 1900 East, Room 4C104, Salt Lake City, UT 84132, USA
| | - Wendy Kohlmann
- Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112, USA
| | - Lisa G Aspinwall
- Department of Psychology, University of Utah, 380 South 1530 East, BEHS 502, Salt Lake City, UT 84112, USA
| | - Mary Wang
- Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112, USA
| | - Jay Bishoff
- Intermountain Health Care, 5169 Cottonwood St Ste 420, Murray, UT 84107, USA
| | - Christopher Dechet
- Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112, USA
- Department of Urology, University of Utah, 30 North 1900 East, Salt Lake City, 84132 UT, USA
| | - Anita Y Kinney
- Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112, USA
- Department of Internal Medicine, University of Utah, 30 North 1900 East, Room 4C104, Salt Lake City, UT 84132, USA
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Glasgow RE, Doria-Rose VP, Khoury MJ, Elzarrad M, Brown ML, Stange KC. Comparative effectiveness research in cancer: what has been funded and what knowledge gaps remain? J Natl Cancer Inst 2013; 105:766-73. [PMID: 23578853 DOI: 10.1093/jnci/djt066] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Russell E Glasgow
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20852, USA.
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Syurina EV, Schulte In den Bäumen T, Brand A, Ambrosino E, Feron FJ. Concepts for the translation of genome-based innovations into public health: a comprehensive overview. Per Med 2013; 10:163-176. [PMID: 29758851 DOI: 10.2217/pme.13.5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Recent vast and rapid development of genome-related sciences is followed by the development of different assessment techniques or attempts to adapt the existing ones. The aim of this article is to give an overview of existing concepts for the assessment and translation of innovations into healthcare, applying a descriptive analysis of their present use by public health specialists and policy makers. The international literature review identified eight concepts including Health Technology Assessment, analytic validity, clinical validity, clinical utility, ethical, legal and social implications, Public Health Wheel and others. This study gives an overview of these concepts (including the level of current use) applying a descriptive analysis of their present use by public health specialists and policy makers. Despite the heterogeneity of the analyzed concepts and difference in use in everyday healthcare practice, the cross-integration of these concepts is important in order to improve translation speed and quality. Finally, some recommendations are made regarding the most applicable translational concepts.
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Affiliation(s)
- Elena V Syurina
- Department of Social Medicine, School for Public Health & Primary Care (CAPHRI), Faculty of Health, Medicine & Life Sciences, Maastricht University, The Netherlands.
| | - Tobias Schulte In den Bäumen
- Institute for Public Health Genomics, School for Public Health & Primary Care (CAPHRI), Cluster of Genetics & Cell Biology, Faculty of Health, Medicine & Life Sciences, Maastricht University, The Netherlands
| | - Angela Brand
- Institute for Public Health Genomics, School for Public Health & Primary Care (CAPHRI), Cluster of Genetics & Cell Biology, Faculty of Health, Medicine & Life Sciences, Maastricht University, The Netherlands
| | - Elena Ambrosino
- Institute for Public Health Genomics, School for Public Health & Primary Care (CAPHRI), Cluster of Genetics & Cell Biology, Faculty of Health, Medicine & Life Sciences, Maastricht University, The Netherlands
| | - Frans Jm Feron
- Department of Social Medicine, School for Public Health & Primary Care (CAPHRI), Faculty of Health, Medicine & Life Sciences, Maastricht University, The Netherlands
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Lynch JA, Khoury MJ, Borzecki A, Cromwell J, Hayman LL, Ponte PR, Miller GA, Lathan CS. Utilization of epidermal growth factor receptor (EGFR) testing in the United States: a case study of T3 translational research. Genet Med 2013; 15:630-8. [PMID: 23448725 DOI: 10.1038/gim.2013.5] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2012] [Accepted: 01/07/2013] [Indexed: 01/14/2023] Open
Abstract
PURPOSE We examined hospital use of the epidermal growth factor receptor assay in patients with lung cancer in the United States. Our goal was to inform the development of a model to predict phase 3 translation of guideline-directed molecular diagnostic tests. METHODS This was a retrospective observational study. Using logistic regression, we analyzed the association between hospitals' institutional and regional characteristics and the likelihood that an epidermal growth factor receptor assay would be ordered. RESULTS Significant institutional predictors included affiliation with an academic medical center (odds ratio, 1.48; 95% confidence interval, 1.20-1.83), participation in a National Cancer Institute clinical research cooperative group (odds ratio, 2.06, 1.66-2.55), and -availability of positron emission tomography scan (odds ratio, 1.44, 1.07-1.94) and cardiothoracic surgery (odds ratio, 1.90, 1.52-2.37) services. Significant regional predictors included metropolitan county (odds ratio, 2.08, 1.48-2.91), population with above-average education (odds ratio, 1.46, 1.09-1.96), and population with above-average income (odds ratio, 1.46, 1.04-2.05). Distance from a National Cancer Institute cancer center was a negative predictor (odds ratio, 0.996, 0.995-0.998), with a 34% decrease in likelihood for every 100 miles. CONCLUSION In 2010, only 12% of US acute-care hospitals ordered the epidermal growth factor receptor assay, suggesting that most patients with lung cancer did not have access to this test. This case study illustrated the need for: (i) increased dissemination and implementation research, and (ii) interventions to improve adoption of guideline-directed molecular diagnostic tests by community hospitals.
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Affiliation(s)
- Julie A Lynch
- Veterans Health Administration, University of Massachusetts Boston & Dana Farber Cancer Institute, Boston, MA, USA.
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Lam TK, Spitz M, Schully SD, Khoury MJ. "Drivers" of translational cancer epidemiology in the 21st century: needs and opportunities. Cancer Epidemiol Biomarkers Prev 2013; 22:181-8. [PMID: 23322363 PMCID: PMC3565029 DOI: 10.1158/1055-9965.epi-12-1262] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Cancer epidemiology is at the cusp of a paradigm shift--propelled by an urgent need to accelerate the pace of translating scientific discoveries into health care and population health benefits. As part of a strategic planning process for cancer epidemiologic research, the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is leading a "longitudinal" meeting with members of the research community to engage in an on-going dialogue to help shape and invigorate the field. Here, we review a translational framework influenced by "drivers" that we believe have begun guiding cancer epidemiology toward translation in the past few years and are most likely to drive the field further in the next decade. The drivers include: (i) collaboration and team science, (ii) technology, (iii) multilevel analyses and interventions, and (iv) knowledge integration from basic, clinical, and population sciences. Using the global prevention of cervical cancer as an example of a public health endeavor to anchor the conversation, we discuss how these drivers can guide epidemiology from discovery to population health impact, along the translational research continuum.
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Affiliation(s)
- Tram Kim Lam
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD, USA.
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Getting our priorities straight: a novel framework for stakeholder-informed prioritization of cancer genomics research. Genet Med 2012; 15:115-22. [PMID: 23037935 DOI: 10.1038/gim.2012.103] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Prioritization of translational research on genomic tests is critically important given the rapid pace of innovation in genomics. The goal of this study was to evaluate a stakeholder-informed priority-setting framework in cancer genomics. METHODS An external stakeholder advisory group including patients/consumers, payers, clinicians, and test developers used a modified Delphi approach to prioritize six candidate cancer genomic technologies during a 1-day meeting. Nine qualitative priority-setting criteria were considered. We used a directed, qualitative content-analysis approach to investigate the themes of the meeting discussion. RESULTS Stakeholders primarily discussed six of the original nine criteria: clinical benefits, population health impacts, economic impacts, analytical and clinical validity, clinical trial implementation and feasibility, and market factors. Several new priority-setting criteria were identified from the workshop transcript, including "patient-reported outcomes," "clinical trial ethics," and "trial recruitment." The new criteria were incorporated with prespecified criteria to develop a novel priority-setting framework. CONCLUSION This study highlights key criteria that stakeholders can consider when prioritizing comparative effectiveness research for cancer genomic applications. Applying an explicit priority-setting framework to inform investment in comparative effectiveness research can help to ensure that critical factors are weighed when deciding between many potential research questions and trial designs.
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Interpretation of melanoma risk feedback in first-degree relatives of melanoma patients. J Cancer Epidemiol 2012; 2012:374842. [PMID: 22888347 PMCID: PMC3410311 DOI: 10.1155/2012/374842] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2012] [Revised: 05/28/2012] [Accepted: 05/31/2012] [Indexed: 11/24/2022] Open
Abstract
Little is known about how individuals might interpret brief genetic risk feedback. We examined interpretation and behavioral intentions (sun protection, skin screening) in melanoma first-degree relatives (FDRs) after exposure to brief prototypic melanoma risk feedback. Using a 3 by 2 experimental pre-post design where feedback type (high-risk mutation, gene environment, and nongenetic) and risk level (positive versus negative findings) were systematically varied, 139 melanoma FDRs were randomized to receive one of the six scenarios. All scenarios included an explicit reminder that melanoma family history increased their risk regardless of their feedback. The findings indicate main effects by risk level but not feedback type; positive findings led to heightened anticipated melanoma risk perceptions and anticipated behavioral intentions. Yet those who received negative findings often discounted their family melanoma history. As such, 25%, 30%, and 32% of those who received negative mutation, gene-environment, and nongenetic feedback, respectively, reported that their risk was similar to the general population. Given the frequency with which those who pursue genetic testing may receive negative feedback, attention is needed to identify ideal strategies to present negative genetic findings in contexts such as direct to consumer channels where extensive genetic counseling is not required.
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Abstract
Three articles in this issue of Genetics in Medicine describe examples of "knowledge integration," involving methods for generating and synthesizing rapidly emerging information on health-related genomic technologies and engaging stakeholders around the evidence. Knowledge integration, the central process in translating genomic research, involves three closely related, iterative components: knowledge management, knowledge synthesis, and knowledge translation. Knowledge management is the ongoing process of obtaining, organizing, and displaying evolving evidence. For example, horizon scanning and "infoveillance" use emerging technologies to scan databases, registries, publications, and cyberspace for information on genomic applications. Knowledge synthesis is the process of conducting systematic reviews using a priori rules of evidence. For example, methods including meta-analysis, decision analysis, and modeling can be used to combine information from basic, clinical, and population research. Knowledge translation refers to stakeholder engagement and brokering to influence policy, guidelines and recommendations, as well as the research agenda to close knowledge gaps. The ultrarapid production of information requires adequate public and private resources for knowledge integration to support the evidence-based development of genomic medicine.
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Affiliation(s)
- Muin J Khoury
- Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA, USA.
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Khoury MJ, Gwinn ML, Glasgow RE, Kramer BS. A population approach to precision medicine. Am J Prev Med 2012; 42:639-45. [PMID: 22608383 PMCID: PMC3629731 DOI: 10.1016/j.amepre.2012.02.012] [Citation(s) in RCA: 77] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2011] [Revised: 12/21/2011] [Accepted: 02/23/2012] [Indexed: 01/20/2023]
Abstract
The term P4 medicine is used to denote an evolving field of medicine that uses systems biology approaches and information technologies to enhance wellness rather than just treat disease. Its four components include predictive, preventive, personalized, and participatory medicine. In the current paper, it is argued that in order to fulfill the promise of P4 medicine, a "fifth P" must be integrated-the population perspective-into each of the other four components. A population perspective integrates predictive medicine into the ecologic model of health; applies principles of population screening to preventive medicine; uses evidence-based practice to personalize medicine; and grounds participatory medicine on the three core functions of public health: assessment, policy development, and assurance. Population sciences-including epidemiology; behavioral, social, and communication sciences; and health economics, implementation science, and outcomes research-are needed to show the value of P4 medicine. Balanced strategies that implement both population- and individual-level interventions can best maximize health benefits, minimize harm, and avoid unnecessary healthcare costs.
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Affiliation(s)
- Muin J Khoury
- Office of Public Health Genomics, CDC, Atlanta, GA 30333, USA.
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