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Spitz MR, Lam TK, Schully SD, Khoury MJ. The authors reply. Am J Epidemiol 2015; 181:361. [PMID: 25698647 DOI: 10.1093/aje/kwv019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Schully SD, Carrick DM, Mechanic LE, Srivastava S, Anderson GL, Baron JA, Berg CD, Cullen J, Diamandis EP, Doria-Rose VP, Goddard KAB, Hankinson SE, Kushi LH, Larson EB, McShane LM, Schilsky RL, Shak S, Skates SJ, Urban N, Kramer BS, Khoury MJ, Ransohoff DF. Leveraging biospecimen resources for discovery or validation of markers for early cancer detection. J Natl Cancer Inst 2015; 107:djv012. [PMID: 25688116 DOI: 10.1093/jnci/djv012] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts.
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Schully SD, Khoury MJ. What is translational genomics? An expanded research agenda for improving individual and population health. Appl Transl Genom 2014; 3:82-83. [PMID: 26722640 PMCID: PMC4694629 DOI: 10.1016/j.atg.2014.09.006] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Spitz MR, Lam TK, Schully SD, Khoury MJ. The next generation of large-scale epidemiologic research: implications for training cancer epidemiologists. Am J Epidemiol 2014; 180:964-7. [PMID: 25234430 DOI: 10.1093/aje/kwu256] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
There is expanding consensus on the need to modernize the training of cancer epidemiologists to accommodate rapidly emerging technological advancements and the digital age, which are transforming the practice of cancer epidemiology. There is also a growing imperative to extend cancer epidemiology research that is etiological to that which is applied and has the potential to affect individual and public health. Medical schools and schools of public health are recognizing the need to develop such integrated programs; however, we lack the data to estimate how many current training programs are effectively equipping epidemiology students with the knowledge and tools to design, conduct, and analyze these increasingly complex studies. There is also a need to develop new mentoring approaches to account for the transdisciplinary team-science environment that now prevails. With increased dialogue among schools of public health, medical schools, and cancer centers, revised competencies and training programs at predoctoral, doctoral, and postdoctoral levels must be developed. Continuous collection of data on the impact and outcomes of such programs is also recommended.
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Schully SD, Rogers SD, Lam TK, Chang CQ, Clyne M, Cyr J, Watson D, Khoury MJ. The Cancer Genomics and Epidemiology Navigator: An NCI online tool to enhance cancer epidemiology research. Cancer Epidemiol Biomarkers Prev 2014; 23:2610-1. [PMID: 25368405 PMCID: PMC4221803 DOI: 10.1158/1055-9965.epi-14-0902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Chang CQ, Tingle SR, Filipski KK, Khoury MJ, Lam TK, Schully SD, Ioannidis JPA. An overview of recommendations and translational milestones for genomic tests in cancer. Genet Med 2014; 17:431-40. [PMID: 25341115 DOI: 10.1038/gim.2014.133] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Accepted: 08/20/2014] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To understand the translational trajectory of genomic tests in cancer screening, diagnosis, prognosis, and treatment, we reviewed tests that have been assessed by recommendation and guideline developers. METHODS For each test, we marked translational milestones by determining when the genomic association with cancer was first discovered and studied in patients, and when a health application for a specified clinical use was successfully demonstrated and approved or cleared by the US Food and Drug Administration. To identify recommendations and guidelines, we reviewed the websites of cancer, genomic, and general guideline developers and professional organizations. We searched the in vitro diagnostics database of the US Food and Drug Administration for information, and we searched PubMed for translational milestones. Milestones were examined against type of recommendation, Food and Drug Administration approval or clearance, disease rarity, and test purpose. RESULTS Of the 45 tests we identified, 9 received strong recommendations for their usage in clinical settings, 14 received positive but moderate recommendations, and 22 were not currently recommended. For 18 tests, two or more different sources had issued recommendations, with 67% concordance. Only five tests had Food and Drug Administration approval, and an additional five had clearance. The median time from discovery to recommendation statement was 14.7 years. CONCLUSION In general, there were no associations found between translational trajectory and recommendation category.Genet Med 17 6, 431-440.
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Carrick DM, Mette E, Hoyle B, Rogers SD, Gillanders EM, Schully SD, Mechanic LE. Abstract 307: The use of biospecimens in cancer population science research. Cancer Res 2014. [DOI: 10.1158/1538-7445.am2014-307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Over the past two decades, researchers have increasingly used human biospecimens to help evaluate hypotheses related to disease risk, outcomes and treatment options. We conducted an analysis of the population science cancer research grants funded by NCI in order to gain a more comprehensive understanding of the biospecimens involved in those studies. Recognizing that there are many pre-existing collections of biospecimens, we investigated the cost and time efficiencies observed with studies involving the use of existing biospecimens versus collecting new specimens. Methods: Data available for 1,018 extramural, peer-reviewed grants (active as of July 2012) supported by the Division of Cancer Control and Population Sciences, (NCI Division that supports cancer control and population science extramural research grants) were analyzed. Results: 455 of the grants were determined to involve biospecimens. The most common specimen types included were DNA (66% of grants involved DNA), whole blood (51%), serum or plasma (40%), and tissue (39%). Grants that involved the use of existing biospecimens resulted in greater cost (serum/plasma studies were 4.2 times less expensive) and time efficiencies (1.4 times more publications per year resulted) than grants that collected new biospecimens. Conclusions: Clearly, there is an opportunity for NCI to promote future sharing. We are currently working to better catalogue our funded resources and make data available to the extramural community. Further work is being done to investigate possible trends based on year of grant award.
Citation Format: Danielle M. Carrick, Eliza Mette, Brittany Hoyle, Scott D. Rogers, Elizabeth M. Gillanders, Sheri D. Schully, Leah E. Mechanic. The use of biospecimens in cancer population science research. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 307. doi:10.1158/1538-7445.AM2014-307
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Lam TK, Chang CQ, Rogers SD, Khoury MJ, Schully SD. Abstract 254: How can epidemiology become more effective in reducing the burden of cancer in the 21st century? An analysis of NCI-funded grants and the scientific literature. Cancer Res 2014. [DOI: 10.1158/1538-7445.am2014-254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Concurrent with an NCI sponsored 2012 workshop on the future of cancer epidemiology, a set of “drivers” were identified to accelerate the field of cancer epidemiology across the translational research continuum in the 21st century: (i) emerging technologies; (ii) multi-level analyses and interventions; (iii) knowledge integration from basic, clinical and population sciences; and (iv) collaboration and team science.
Objective: To map the evolution of identified “drivers” and key translational phases (T0-T4) in the past decade.
Methods: We analyzed grants funded by the NCI's Epidemiology and Genomics Research Program and published literature for 2000, 2005, and 2010. For each year, we evaluated the aims of all new and competing grants and randomly selected 100 cancer epidemiology articles from PubMed. We used two-sample t-tests to compare differences between “drivers” and multivariate logistic regression to investigate the relationship between multi-institutional collaboration and the remaining “drivers”.
Results: Our results show a significant shift from single-institution studies that focused on traditional questionnaire-based epidemiology studies to technology-driven, multi-disciplinary consortia-driven studies for both NCI grants and published literature. Compared to grants that were single-institution-based, consortia grants were significantly more likely to incorporate key contemporary technologies (OR= 3.53; 95% CI=1.44-8.61; p-value = 0.005) and engaged in multi-level analyses (OR =2.27; 95% CI=1.06-4.86, p-value=0.035). The vast majority of grants (82%) and publications (86%) analyzed were discovery (T0) or characterization (T1) research suggesting a critical need for more T2-T4 translational studies. Our evaluation also indicates a dearth of research in two areas: 1) multi-level analyses that takes into account the combination of molecular, individual, social and environmental determinants and 2) knowledge integration that evaluates the robustness and interpretation of scientific evidence derived from basic, clinical and population sciences.
Summary: Cancer epidemiology is at the cusp of a paradigm shift–propelled by a need to accelerate the pace of translating scientific discoveries to impart population health benefits. While multi-institutional and technology-drive collaboration is happening, our evaluation of funded grants and published literature in the first decade of the 21st century provide concrete evidence that concerted efforts to incorporate other key elements that influence the future of cancer epidemiology are warranted for the discipline to meet the challenges of this changing landscape.
Citation Format: Tram K. Lam, Christine Q. Chang, Scott D. Rogers, Muin J. Khoury, Sheri D. Schully. How can epidemiology become more effective in reducing the burden of cancer in the 21st century? An analysis of NCI-funded grants and the scientific literature. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 254. doi:10.1158/1538-7445.AM2014-254
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Puggal MA, Schully SD, Srinivas PR, Papanicolaou GJ, Jaquish CE, Fabsitz RR. Translation of genetics research to clinical medicine: the National Heart, Lung, and Blood Institute perspective. ACTA ACUST UNITED AC 2014; 6:634-9. [PMID: 24347619 DOI: 10.1161/circgenetics.113.000227] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Shaikh AR, Butte AJ, Schully SD, Dalton WS, Khoury MJ, Hesse BW. Collaborative biomedicine in the age of big data: the case of cancer. J Med Internet Res 2014; 16:e101. [PMID: 24711045 PMCID: PMC4004150 DOI: 10.2196/jmir.2496] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2012] [Revised: 05/10/2013] [Accepted: 03/03/2014] [Indexed: 11/13/2022] Open
Abstract
Biomedicine is undergoing a revolution driven by high throughput and connective computing that is transforming medical research and practice. Using oncology as an example, the speed and capacity of genomic sequencing technologies is advancing the utility of individual genetic profiles for anticipating risk and targeting therapeutics. The goal is to enable an era of “P4” medicine that will become increasingly more predictive, personalized, preemptive, and participative over time. This vision hinges on leveraging potentially innovative and disruptive technologies in medicine to accelerate discovery and to reorient clinical practice for patient-centered care. Based on a panel discussion at the Medicine 2.0 conference in Boston with representatives from the National Cancer Institute, Moffitt Cancer Center, and Stanford University School of Medicine, this paper explores how emerging sociotechnical frameworks, informatics platforms, and health-related policy can be used to encourage data liquidity and innovation. This builds on the Institute of Medicine’s vision for a “rapid learning health care system” to enable an open source, population-based approach to cancer prevention and control.
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Dotson WD, Douglas MP, Kolor K, Stewart AC, Bowen MS, Gwinn M, Wulf A, Anders HM, Chang CQ, Clyne M, Lam TK, Schully SD, Marrone M, Feero WG, Khoury MJ. Prioritizing genomic applications for action by level of evidence: a horizon-scanning method. Clin Pharmacol Ther 2014; 95:394-402. [PMID: 24398597 PMCID: PMC4689130 DOI: 10.1038/clpt.2013.226] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Accepted: 11/08/2013] [Indexed: 11/09/2022]
Abstract
As evidence accumulates on the use of genomic tests and other health-related applications of genomic technologies, decision makers may increasingly seek support in identifying which applications have sufficiently robust evidence to suggest they might be considered for action. As an interim working process to provide such support, we developed a horizon-scanning method that assigns genomic applications to tiers defined by availability of synthesized evidence. We illustrate an application of the method to pharmacogenomics tests.
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Verma M, Rogers S, Divi RL, Schully SD, Nelson S, Joseph Su L, Ross SA, Pilch S, Winn DM, Khoury MJ. Epigenetic research in cancer epidemiology: trends, opportunities, and challenges. Cancer Epidemiol Biomarkers Prev 2013; 23:223-33. [PMID: 24326628 DOI: 10.1158/1055-9965.epi-13-0573] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Epigenetics is emerging as an important field in cancer epidemiology that promises to provide insights into gene regulation and facilitate cancer control throughout the cancer care continuum. Increasingly, investigators are incorporating epigenetic analysis into the studies of etiology and outcomes. To understand current progress and trends in the inclusion of epigenetics in cancer epidemiology, we evaluated the published literature and the National Cancer Institute (NCI)-supported research grant awards in this field to identify trends in epigenetics research. We present a summary of the epidemiologic studies in NCI's grant portfolio (from January 2005 through December 2012) and in the scientific literature published during the same period, irrespective of support from the NCI. Blood cells and tumor tissue were the most commonly used biospecimens in these studies, although buccal cells, cervical cells, sputum, and stool samples were also used. DNA methylation profiling was the focus of the majority of studies, but several studies also measured microRNA profiles. We illustrate here the current status of epidemiologic studies that are evaluating epigenetic changes in large populations. The incorporation of epigenomic assessments in cancer epidemiology studies has and is likely to continue to provide important insights into the field of cancer research.
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Ioannidis JPA, Zhou Y, Chang CQ, Schully SD, Khoury MJ, Freedman AN. Potential increased risk of cancer from commonly used medications: an umbrella review of meta-analyses. Ann Oncol 2013; 25:16-23. [PMID: 24310915 DOI: 10.1093/annonc/mdt372] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Several commonly used medications have been associated with increased cancer risk in the literature. Here, we evaluated the strength and consistency of these claims in published meta-analyses. We carried out an umbrella review of 74 meta-analysis articles addressing the association of commonly used medications (antidiabetics, antihyperlipidemics, antihypertensives, antirheumatics, drugs for osteoporosis, and others) with cancer risk where at least one meta-analysis in the medication class included some data from randomized trials. Overall, 51 articles found no statistically significant differences, 13 found some decreased cancer risk, and 11 found some increased risk (one reported both increased and decreased risks). The 11 meta-analyses that found some increased risks reported 16 increased risk estimates, of which 5 pertained to overall cancer and 11 to site-specific cancer. Six of the 16 estimates were derived from randomized trials and 10 from observational data. Estimates of increased risk were strongly inversely correlated with the amount of evidence (number of cancer cases) (Spearman's correlation coefficient = -0.77, P < 0.001). In 4 of the 16 topics, another meta-analysis existed that was larger (n = 2) or included better controlled data (n = 2) and in all 4 cases there was no statistically significantly increased risk of malignancy. No medication or class had substantial and consistent evidence for increased risk of malignancy. However, for most medications we cannot exclude small risks or risks in population subsets. Such risks are unlikely to be possible to document robustly unless very large, collaborative studies with standardized analyses and no selective reporting are carried out.
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Ioannidis JPA, Chang CQ, Lam TK, Schully SD, Khoury MJ. The geometric increase in meta-analyses from China in the genomic era. PLoS One 2013; 8:e65602. [PMID: 23776510 PMCID: PMC3680482 DOI: 10.1371/journal.pone.0065602] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Accepted: 04/25/2013] [Indexed: 02/08/2023] Open
Abstract
Meta-analyses are increasingly popular. It is unknown whether this popularity is driven by specific countries and specific meta-analyses types. PubMed was used to identify meta-analyses since 1995 (last update 9/1/2012) and catalogue their types and country of origin. We focused more on meta-analyses from China (the current top producer of meta-analyses) versus the USA (top producer until recently). The annual number of meta-analyses from China increased 40-fold between 2003 and 2011 versus 2.4-fold for the USA. The growth of Chinese meta-analyses was driven by genetics (110-fold increase in 2011 versus 2003). The HuGE Navigator identified 612 meta-analyses of genetic association studies published in 2012 from China versus only 109 from the USA. We compared in-depth 50 genetic association meta-analyses from China versus 50 from USA in 2012. Meta-analyses from China almost always used only literature-based data (92%), and focused on one or two genes (94%) and variants (78%) identified with candidate gene approaches (88%), while many USA meta-analyses used genome-wide approaches and raw data. Both groups usually concluded favorably for the presence of genetic associations (80% versus 74%), but nominal significance (P<0.05) typically sufficed in the China group. Meta-analyses from China typically neglected genome-wide data, and often included candidate gene studies published in Chinese-language journals. Overall, there is an impressive rise of meta-analyses from China, particularly on genetic associations. Since most claimed candidate gene associations are likely false-positives, there is an urgent global need to incorporate genome-wide data and state-of-the art statistical inferences to avoid a flood of false-positive genetic meta-analyses.
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Simonds NI, Khoury MJ, Schully SD, Armstrong K, Cohn WF, Fenstermacher DA, Ginsburg GS, Goddard KAB, Knaus WA, Lyman GH, Ramsey SD, Xu J, Freedman AN. Comparative effectiveness research in cancer genomics and precision medicine: current landscape and future prospects. J Natl Cancer Inst 2013; 105:929-36. [PMID: 23661804 DOI: 10.1093/jnci/djt108] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
A major promise of genomic research is information that can transform health care and public health through earlier diagnosis, more effective prevention and treatment of disease, and avoidance of drug side effects. Although there is interest in the early adoption of emerging genomic applications in cancer prevention and treatment, there are substantial evidence gaps that are further compounded by the difficulties of designing adequately powered studies to generate this evidence, thus limiting the uptake of these tools into clinical practice. Comparative effectiveness research (CER) is intended to generate evidence on the "real-world" effectiveness compared with existing standards of care so informed decisions can be made to improve health care. Capitalizing on funding opportunities from the American Recovery and Reinvestment Act of 2009, the National Cancer Institute funded seven research teams to conduct CER in genomic and precision medicine and sponsored a workshop on CER on May 30, 2012, in Bethesda, Maryland. This report highlights research findings from those research teams, challenges to conducting CER, the barriers to implementation in clinical practice, and research priorities and opportunities in CER in genomic and precision medicine. Workshop participants strongly emphasized the need for conducting CER for promising molecularly targeted therapies, developing and supporting an integrated clinical network for open-access resources, supporting bioinformatics and computer science research, providing training and education programs in CER, and conducting research in economic and decision modeling.
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Khoury MJ, Lam TK, Ioannidis JPA, Hartge P, Spitz MR, Buring JE, Chanock SJ, Croyle RT, Goddard KA, Ginsburg GS, Herceg Z, Hiatt RA, Hoover RN, Hunter DJ, Kramer BS, Lauer MS, Meyerhardt JA, Olopade OI, Palmer JR, Sellers TA, Seminara D, Ransohoff DF, Rebbeck TR, Tourassi G, Winn DM, Zauber A, Schully SD. Transforming epidemiology for 21st century medicine and public health. Cancer Epidemiol Biomarkers Prev 2013; 22:508-16. [PMID: 23462917 PMCID: PMC3625652 DOI: 10.1158/1055-9965.epi-13-0146] [Citation(s) in RCA: 95] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving toward more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical, and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating "big data" science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy, and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology, in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.
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Ghazarian AA, Simonds NI, Bennett K, Pimentel CB, Ellison GL, Gillanders EM, Schully SD, Mechanic LE. A review of NCI's extramural grant portfolio: identifying opportunities for future research in genes and environment in cancer. Cancer Epidemiol Biomarkers Prev 2013; 22:501-7. [PMID: 23462918 PMCID: PMC3617050 DOI: 10.1158/1055-9965.epi-13-0156] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Genetic and environmental factors jointly influence cancer risk. The NIH has made the study of gene-environment (GxE) interactions a research priority since the year 2000. METHODS To assess the current status of GxE research in cancer, we analyzed the extramural grant portfolio of the National Cancer Institute (NCI) from Fiscal Years 2007 to 2009. Publications attributed to selected grants were also evaluated. RESULTS From the 1,106 research grants identified in our portfolio analysis, a random sample of 450 grants (40%) was selected for data abstraction; of these, 147 (33%) were considered relevant. The most common cancer type was breast (20%, n = 29), followed by lymphoproliferative (10%, n = 14), colorectal (9%, n = 13), melanoma/other skin (9%, n = 13), and lung/upper aerodigestive tract (8%, n = 12) cancers. The majority of grants were studies of candidate genes (68%, n = 100) compared with genome-wide association studies (GWAS) (8%, n = 12). Approximately one-third studied environmental exposures categorized as energy balance (37%, n = 54) or drugs/treatment (29%, n = 43). From the 147 relevant grants, 108 publications classified as GxE or pharmacogenomic were identified. These publications were linked to 37 of the 147 grant applications (25%). CONCLUSION The findings from our portfolio analysis suggest that GxE studies are concentrated in specific areas. There is room for investments in other aspects of GxE research, including, but not limited to developing alternative approaches to exposure assessment, broadening the spectrum of cancer types investigated, and conducting GxE within GWAS. IMPACT This portfolio analysis provides a cross-sectional review of NCI support for GxE research in cancer.
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Lam TK, Schully SD, Rogers SD, Benkeser R, Reid B, Khoury MJ. Provocative questions in cancer epidemiology in a time of scientific innovation and budgetary constraints. Cancer Epidemiol Biomarkers Prev 2013; 22:496-500. [PMID: 23413299 DOI: 10.1158/1055-9965.epi-13-0101] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In a time of scientific and technological developments and budgetary constraints, the National Cancer Institute's (NCI) Provocative Questions Project offers a novel funding mechanism for cancer epidemiologists. We reviewed the purposes underlying the Provocative Questions Project, present information on the contributions of epidemiologic research to the current Provocative Questions portfolio, and outline opportunities that the cancer epidemiology community might capitalize on to advance a research agenda that spans a translational continuum from scientific discoveries to population health impact.
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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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Mechanic LE, Simonds NI, Ghazarian A, Benedicto CB, Schully SD, Ellison GL, Gillanders EM. Abstract 46: A review of the gene-environment interaction literature in cancer: What do we know? Cancer Epidemiol Biomarkers Prev 2012. [DOI: 10.1158/1055-9965.gwas-46] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
Risk of cancer is determined by a complex interplay of genetic and environmental factors. Therefore, the study of gene-environment interactions has been an active area of research for several years. To examine the state of the science in the field of gene-environment interactions research in cancer, we performed a systematic review of the published literature. A total of 3019 articles were identified using the gene-environment or pharmacogenomic flags from the HuGE literature finder and CancerGAMAdb, curated databases of genetic association studies, from January 1, 2001 to January 31, 2010. From these articles, 243 articles were determined to be relevant based on the inclusion criteria of at least 1000 cases in the interaction studied, examining the combination of genes and environment, and investigating the interaction as related to cancer risk. Information from these articles was abstracted regarding cancer type, environmental exposure variables, genetic variables, and estimates of interaction effects. In these papers, over 3500 interactions were investigated. The majority of these interactions were examined in colon, rectal, or colorectal cancer types (40%) followed by breast cancer (30%). Most of these interactions were explored using candidate gene polymorphisms (82%) compared with polymorphisms identified from genome wide association studies (GWAS). The most common environmental exposure categories observed were “energy balance” (41%), e.g. BMI or diet, followed by “Lifestyle” (21%), e.g. smoking or alcohol intake. Further analysis regarding commonly observed interactions, analytical tests performed, number of statistically significant interactions and magnitudes of interactions is on-going. In conclusion, observations of published literature suggest that opportunity exists for more of an agnostic approach to the study of gene-environment interactions and exploring alternative environmental exposures.
Citation Format: Leah E. Mechanic, Naoko I. Simonds, Armen Ghazarian, Camilla B. Benedicto, Sheri D. Schully, Gary L. Ellison, Elizabeth M. Gillanders. A review of the gene-environment interaction literature in cancer: What do we know? [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 46.
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Ioannidis JPA, Schully SD, Lam TK, Khoury MJ. Knowledge integration in cancer: current landscape and future prospects. Cancer Epidemiol Biomarkers Prev 2012; 22:3-10. [PMID: 23093546 DOI: 10.1158/1055-9965.epi-12-1144] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Knowledge integration includes knowledge management, synthesis, and translation processes. It aims to maximize the use of collected scientific information and accelerate translation of discoveries into individual and population health benefits. Accumulated evidence in cancer epidemiology constitutes a large share of the 2.7 million articles on cancer in PubMed. We examine the landscape of knowledge integration in cancer epidemiology. Past approaches have mostly used retrospective efforts of knowledge management and traditional systematic reviews and meta-analyses. Systematic searches identify 2,332 meta-analyses, about half of which are on genetics and epigenetics. Meta-analyses represent 1:89-1:1162 of published articles in various cancer subfields. Recently, there are more collaborative meta-analyses with individual-level data, including those with prospective collection of measurements [e.g., genotypes in genome-wide association studies (GWAS)]; this may help increase the reliability of inferences in the field. However, most meta-analyses are still done retrospectively with published information. There is also a flurry of candidate gene meta-analyses with spuriously prevalent "positive" results. Prospective design of large research agendas, registration of datasets, and public availability of data and analyses may improve our ability to identify knowledge gaps, maximize and accelerate translational progress or-at a minimum-recognize dead ends in a more timely fashion.
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Khoury MJ, Coates RJ, Fennell ML, Glasgow RE, Scheuner MT, Schully SD, Williams MS, Clauser SB. Multilevel research and the challenges of implementing genomic medicine. J Natl Cancer Inst Monogr 2012; 2012:112-20. [PMID: 22623603 DOI: 10.1093/jncimonographs/lgs003] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Advances in genomics and related fields promise a new era of personalized medicine in the cancer care continuum. Nevertheless, there are fundamental challenges in integrating genomic medicine into cancer practice. We explore how multilevel research can contribute to implementation of genomic medicine. We first review the rapidly developing scientific discoveries in this field and the paucity of current applications that are ready for implementation in clinical and public health programs. We then define a multidisciplinary translational research agenda for successful integration of genomic medicine into policy and practice and consider challenges for successful implementation. We illustrate the agenda using the example of Lynch syndrome testing in newly diagnosed cases of colorectal cancer and cascade testing in relatives. We synthesize existing information in a framework for future multilevel research for integrating genomic medicine into the cancer care continuum.
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Goddard KAB, Knaus WA, Whitlock E, Lyman GH, Feigelson HS, Schully SD, Ramsey S, Tunis S, Freedman AN, Khoury MJ, Veenstra DL. Building the evidence base for decision making in cancer genomic medicine using comparative effectiveness research. Genet Med 2012; 14:633-42. [PMID: 22516979 PMCID: PMC3632438 DOI: 10.1038/gim.2012.16] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. The aim of this study was to identify approaches to help stakeholders make evidence-based decisions and to describe potential challenges and opportunities in using CER to produce evidence-based guidance. We identified general CER approaches for genomic applications through literature review, the authors' experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Evidence generation and synthesis approaches used in CER include comparative observational and randomized trials, patient-reported outcomes, decision modeling, and economic analysis. Significant challenges to conducting CER in cancer genomics include the rapid pace of innovation, lack of regulation, and variable definitions and evidence thresholds for clinical and personal utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. CER offers a variety of methodological approaches that can address stakeholders' needs and help ensure an effective translation of genomic discoveries.
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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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Khoury MJ, Freedman AN, Gillanders EM, Harvey CE, Kaefer C, Reid BC, Rogers S, Schully SD, Seminara D, Verma M. Frontiers in cancer epidemiology: a challenge to the research community from the Epidemiology and Genomics Research Program at the National Cancer Institute. Cancer Epidemiol Biomarkers Prev 2012; 21:999-1001. [PMID: 22665580 PMCID: PMC3392448 DOI: 10.1158/1055-9965.epi-12-0525] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
The Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is developing scientific priorities for cancer epidemiology research in the next decade. We would like to engage the research community and other stakeholders in a planning effort that will include a workshop in December 2012 to help shape new foci for cancer epidemiology research. To facilitate the process of defining the future of cancer epidemiology, we invite the research community to join in an ongoing web-based conversation at http://blog-epi.grants.cancer.gov/ to develop priorities and the next generation of high-impact studies.
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