Training the Twenty-First Century Cancer Epidemiologist.

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

Prioritizing genomic applications for action by level of evidence: a horizon-scanning method.

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.

Potential increased risk of cancer from commonly used medications: an umbrella review of meta-analyses.

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.

Public health action in genomics is now needed beyond newborn screening.

For decades, newborn screening was the only public health program in the US focused on reducing morbidity, mortality and disability in people affected by genetic conditions. The landscape has changed, however, as evidence-based recommendations are now available for several other genomic applications that can save lives now in the US. Many more such applications are expected to emerge in the next decade. An action plan, based on evidence, provides the impetus for a new paradigm for public health practice in genomics across the lifespan using established multilevel processes as a guide. These include policy interventions, education, clinical interventions, and surveillance. Applying what we know today in hereditary breast/ovarian cancer, Lynch syndrome and familial hypercholesterolemia has the potential to affect thousands of people in the US population every year. Enhanced partnerships between genetic and nongenetic providers of clinical medicine and public health are needed to overcome the challenges for implementing genomic medicine applications both now and in the future.

The impact of genomics on public health practice: the case for change.

Public health practice will not be able in the 21st century to ignore the impact of genomics, cell and molecular biology. It will need to take into consideration issues that include, among others: the complementary nature of social and biological models of disease, genetic exceptionalism, the readiness of public and patient to respond to genomic information, the relationship between individuals and populations, and concepts of population stratification. Health systems will need to adapt their practice and organisation to include new sequencing technologies, bioinformatic expertise and proper evaluation of genetic and molecular tests. Links with the commercial sector will increase in importance. The impact on developing countries cannot be ignored and will require special attention.

Implications of Internet availability of genomic information for public health practice.

Tensions in the field have emerged over how best to communicate to the public about genomic discoveries in an era of direct-to-consumer (DTC) DNA testing services available through the Internet. Concerns over what the psychological and behavioral response might be to a nuanced, multiplex risk message have spurred some to offer caution in communicating to the public about personalized risk until the necessary research has been completed on how to communicate effectively. The popularization of DTC testing services, along with a spreading Internet culture on transparency for personal data, may make 'waiting to communicate' a moot point. To steer communication efforts in the midst of increasing access to personal genomic information, a self-regulation framework is presented. The framework emphasizes the importance of presenting a coherent message in all communiqués about public health genomics. Coherence should be based on an evidence-based model of how the public processes information about health conditions and an emphasis on risk-to-action links. Recommendations from the President's Council of Advisors for Science and Technology are reviewed as a way of identifying targets of opportunity for structured communications both within the healthcare system and in the broader external ecosystem of publicly available health information technologies.

Translational research in cancer genetics: the road less traveled.

Gene discoveries in cancer have the potential for clinical and public health applications. To take advantage of such discoveries, a translational research agenda is needed to take discoveries from the bench to population health impact. To assess the current status of translational research in cancer genetics, we analyzed the extramural grant portfolio of the National Cancer Institute (NCI) from Fiscal Year 2007, as well as the cancer genetic research articles published in 2007. We classified both funded grants and publications as follows: T0 as discovery research; T1 as research to develop a candidate health application (e.g., test or therapy); T2 as research that evaluates a candidate application and develops evidence-based recommendations; T3 as research that assesses how to integrate an evidence-based recommendation into cancer care and prevention; and T4 as research that assesses health outcomes and population impact. We found that 1.8% of the grant portfolio and 0.6% of the published literature was T2 research or beyond. In addition to discovery research in cancer genetics, a translational research infrastructure is urgently needed to methodically evaluate and translate gene discoveries for cancer care and prevention.

Synopsis of preterm birth genetic association studies: the preterm birth genetics knowledge base (PTBGene).

AIM: Our goal wasto produce a field synopsis of genetic associations with preterm birth and to set up a publicly available online database summarizing the data. METHODS: We performed a systematic review and meta-analyses to identify genetic associations with preterm birth. We have set up a publicly available online database of genetic association data on preterm birth called PTBGene (http://ric.einstein.yu.edu/ptbgene/index.html) and report on a structured synopsis thereof as of December 1, 2008. RESULTS: Data on 189 polymorphisms in 84 genes have been included and 36 meta-analyses have been performed. Five gene variants (4 in maternal DNA, one in newborn DNA) have shown nominally significant associations, but all have weak epidemiological credibility. CONCLUSION: After publishing this field synopsis, the PTBGene database will be regularly updated to keep track of the evolving evidence base of genetic factors in preterm birth with the goal of promoting knowledge sharing and multicenter collaboration among preterm birth research groups.

Dealing with the evidence dilemma in genomics and personalized medicine.

In this commentary, I discuss how the promise of genomics and personalized medicine (GPM) is currently not matched by the evidence that supports its use in clinical practice. The mismatch between expectations and reality can be addressed by placing greater emphasis on multidisciplinary translation research and by stakeholder-driven collaboration that uses such research to address various and occasionally competing factors affecting the integration of genomic discoveries into clinical practice.

Family history of diabetes and prevalence of the metabolic syndrome in U.S. adults without diabetes: 6-year results from the National Health and Nutrition Examination Survey (1999-2004).

BACKGROUND/AIMS: Type 2 diabetes and cardiovascular disease share risk factors. The influence of family history of diabetes on the odds of having metabolic syndrome has not been estimated for the U.S. population. Our objective was to quantify this association in a national sample of U.S. adults without diabetes. METHODS: The sample included 4,937 individuals from the National Health and Nutrition Examination Survey (NHANES) (1999-2004). Familial risk of diabetes was classified in 3 strata according to the combination of relatives affected. Metabolic syndrome was defined according to guidelines issued by 4 groups or organizations. The prevalence and odds of this syndrome were compared among familial risk strata after controlling for relevant risk factors. RESULTS: Overall, depending on the definition and after controlling for key variables, people with a moderate familial risk of diabetes, and people with a high familial risk of diabetes were between 1.4 and 1.6, and 1.6 and 1.8 times as likely, respectively, to have metabolic syndrome compared to people with average familial risk. CONCLUSION: In a nationally representative sample of U.S. adults without diabetes, family history of diabetes shows a significant, independent association with metabolic syndrome and its traits. This association supports the idea that shared genes and environment contribute to the expression of complex traits such as diabetes and the metabolic syndrome.

Population screening for genetic disorders in the 21st century: evidence, economics, and ethics.

BACKGROUND: Proposals for population screening for genetic diseases require careful scrutiny by decision makers because of the potential for harms and the need to demonstrate benefits commensurate with the opportunity cost of resources expended. METHODS: We review current evidence-based processes used in the United States, the United Kingdom, and the Netherlands to assess genetic screening programs, including newborn screening programs, carrier screening, and organized cascade testing of relatives of patients with genetic syndromes. In particular, we address critical evidentiary, economic, and ethical issues that arise in the appraisal of screening tests offered to the population. Specific case studies include newborn screening for congenital adrenal hyperplasia and cystic fibrosis and adult screening for hereditary hemochromatosis. RESULTS: Organizations and countries often reach different conclusions about the suitability of screening tests for implementation on a population basis. Deciding when and how to introduce pilot screening programs is challenging. In certain cases, e.g., hereditary hemochromatosis, a consensus does not support general screening although cascade screening may be cost-effective. CONCLUSION: Genetic screening policies have often been determined by technological capability, advocacy, and medical opinion rather than through a rigorous evidence-based review process. Decision making should take into account principles of ethics and opportunity costs.

Phenopedia and Genopedia: disease-centered and gene-centered views of the evolving knowledge of human genetic associations.

SUMMARY: We developed web-based applications that encourage the exploration of the literature on human genetic associations by using a database that is continuously updated from PubMed. These applications provide user-friendly interfaces for searching summarized information on human genetic associations, using either genes or diseases as the starting point. AVAILABILITY: Phenopedia and Genopedia can be freely accessed at http://www.hugenavigator.net/HuGENavigator/startPagePhenoPedia.do and http://www.hugenavigator.net/HuGENavigator/startPagePedia.do, respectively.

Trends in pharmacogenomic epidemiology: 2001-2007.

BACKGROUND: Pharmacogenomic epidemiology (PGxE) assesses the range of responses to pharmacologic agents in relation to genetic variation in population groups. We analyzed publication trends to describe the emerging field of PGxE. METHODS: We analyzed PGxE literature published from 2001 to 2007 by using the HuGE Navigator, a curated database of abstracts on human genome epidemiology extracted from PubMed. We summarized trends by gene and study design and, for the 4 most cited genes, by associated health outcomes and drugs. RESULTS: In all, 1,855 PGxE articles were indexed from 2001 through 2007, with annual publications increasing more than 15-fold during this period. Observational studies outnumbered clinical trials by a ratio of 10 to 1 (1,660 vs. 178). Just 4 genes together accounted for nearly one-fifth of all publications: ABCB1, CYP2C9, CYP2C19, and CYP2D6. For these 4 genes, the most frequently cited therapeutic category was antineoplastic agent, followed by anticoagulant, antiulcer, and antidepressant. Warfarin was the single most frequently cited drug. CONCLUSIONS: The field of PGxE is growing rapidly, encompassing a large spectrum of diseases and drugs important in clinical practice. Systematic tracking and synthesis of the published literature in PGxE can help identify promising applications and guide translation research.

A decade of public health genomics in the United States: centers for disease control and prevention 1997-2007.

Since 1997, the Centers for Disease Control and Prevention (CDC) has collaborated with numerous partners to develop and chart the course of the multidisciplinary field of public health genomics in the USA and globally. During this period, CDC has developed major initiatives for the appropriate integration of genomics into public health research, policy and programs. In this paper, we review briefly the progress in public health genomics made over the past decade in the USA, including population research, the human genome epidemiology network (HuGENet(TM)), the evaluation of genomic applications in practice and prevention (EGAPP), the family history public health initiative, and efforts in building the public health genomics capacity. We also outline a vision for public health genomics for the next decade.

Health-related direct-to-consumer genetic tests: a public health assessment and analysis of practices related to Internet-based tests for risk of thrombosis.

BACKGROUND: Recent years have seen increased concern about direct-to-consumer (DTC) genetic testing (i.e., the sale and use of genetic tests without involving a health care provider). Numerous professional organizations have developed policies in this area. However, little systematic evidence exists to inform public policy about these tests. METHODS: We conducted a systematic search to identify genetic tests that are sold DTC without involving a health care provider. We evaluated the practices of companies offering DTC genetic tests for risk of thrombosis using criteria from multiple sources and a minimal set of key practices. RESULTS: We identified 84 instances of currently available health-related DTC genetic tests sold on 27 Web sites; the most common were for pharmacogenomics (12), risk of thrombosis (10), and nutrigenomics (10). For the DTC genetic tests for risk of thrombosis, we found low adherence to recommendations. Online information was frequently incomplete and had low agreement with professional recommendations. CONCLUSION: Our findings document the rapid growth in the availability of health-related DTC genetic tests and highlight the need to improve the delivery of DTC genetic tests. A major implication of this study is the need for the scientific and medical community to develop consistent recommendations to increase their impact.

Tests of trait-haplotype association when linkage phase is ambiguous, appropriate for matched case-control and cohort studies with competing risks.

The impact of competing risks on tests of association between disease and haplotypes has been largely ignored. We consider situations in which linkage phase is ambiguous and show that tests for disease-haplotype association can lead to rejection of the null hypothesis, even when true, with more than the nominal 5 per cent frequency. This problem tends to occur if a haplotype is associated with overall mortality, even if the haplotype is not associated with disease risk. A small simulation study illustrates the magnitude of bias (high type I error rate) in the context of a cohort study in which a modest number of disease cases (about 350) occur over time. The bias remains even if the score test is based on a logistic model that includes age as a covariate. For cohort studies, we propose a new test based on a modification of the proportional hazards model and for case-control studies, a test based on a conditional likelihood that have the correct size under the null even in the presence of competing risks, and that can be used when haplotype is ambiguous.