Developing a Simplified Consent Form for Biobanking

BACKGROUND: Consent forms have lengthened over time and become harder for participants to understand. We sought to demonstrate the feasibility of creating a simplified consent form for biobanking that comprises the minimum information necessary to meet ethical and regulatory requirements. We then gathered preliminary data concerning its content from hypothetical biobank participants. METHODOLOGY/PRINCIPAL FINDINGS: We followed basic principles of plain-language writing and incorporated into a 2-page form (not including the signature page) those elements of information required by federal regulations and recommended by best practice guidelines for biobanking. We then recruited diabetes patients from community-based practices and randomized half (n = 56) to read the 2-page form, first on paper and then a second time on a tablet computer. Participants were encouraged to use "More information" buttons on the electronic version whenever they had questions or desired further information. These buttons led to a series of "Frequently Asked Questions" (FAQs) that contained additional detailed information. Participants were asked to identify specific sentences in the FAQs they thought would be important if they were considering taking part in a biorepository. On average, participants identified 7 FAQ sentences as important (mean 6.6, SD 14.7, range: 0-71). No one sentence was highlighted by a majority of participants; further, 34 (60.7%) participants did not highlight any FAQ sentences. CONCLUSIONS: Our preliminary findings suggest that our 2-page form contains the information that most prospective participants identify as important. Combining simplified forms with supplemental material for those participants who desire more information could help minimize consent form length and complexity, allowing the most substantively material information to be better highlighted and enabling potential participants to read the form and ask questions more effectively

DNA databanks and consent: A suggested policy option involving an authorization model

BACKGROUND: Genetic databases are becoming increasingly common as a means of determining the relationship between lifestyle, environmental exposures and genetic diseases. These databases rely on large numbers of research subjects contributing their genetic material to successfully explore the genetic basis of disease. However, as all possible research questions that can be posed of the data are unknown, an unresolved ethical issue is the status of informed consent for future research uses of genetic material. DISCUSSION: In this paper, we discuss the difficulties of an informed consent model for future ineffable uses of genetic data. We argue that variations on consent, such as presumed consent, blanket consent or constructed consent fail to meet the standards required by current informed consent doctrine and are distortions of the original concept. In this paper, we propose the concept of an authorization model whereby participants in genetic data banks are able to exercise a certain amount of control over future uses of genetic data. We argue this preserves the autonomy of individuals at the same time as allowing them to give permission and discretion to researchers for certain types of research. SUMMARY: The authorization model represents a step forward in the debate about informed consent in genetic databases. The move towards an authorization model would require changes in the regulatory and legislative environments. Additionally, empirical support of the utility and acceptability of authorization is required

Genome wide association for substance dependence: convergent results from epidemiologic and research volunteer samples

<p>Abstract</p> <p>Background</p> <p>Dependences on addictive substances are substantially-heritable complex disorders whose molecular genetic bases have been partially elucidated by studies that have largely focused on research volunteers, including those recruited in Baltimore. Maryland. Subjects recruited from the Baltimore site of the Epidemiological Catchment Area (ECA) study provide a potentially-useful comparison group for possible confounding features that might arise from selecting research volunteer samples of substance dependent and control individuals. We now report novel SNP (single nucleotide polymorphism) genome wide association (GWA) results for vulnerability to substance dependence in ECA participants, who were initially ascertained as members of a probability sample from Baltimore, and compare the results to those from ethnically-matched Baltimore research volunteers.</p> <p>Results</p> <p>We identify substantial overlap between the home address zip codes reported by members of these two samples. We find overlapping clusters of SNPs whose allele frequencies differ with nominal significance between substance dependent <it>vs </it>control individuals in both samples. These overlapping clusters of nominally-positive SNPs identify 172 genes in ways that are never found by chance in Monte Carlo simulation studies. Comparison with data from human expressed sequence tags suggests that these genes are expressed in brain, especially in hippocampus and amygdala, to extents that are greater than chance.</p> <p>Conclusion</p> <p>The convergent results from these probability sample and research volunteer sample datasets support prior genome wide association results. They fail to support the idea that large portions of the molecular genetic results for vulnerability to substance dependence derive from factors that are limited to research volunteers.</p

Bridging consent: from toll bridges to lift bridges?

<p>Abstract</p> <p>Background</p> <p>The ability to share human biological samples, associated data and results across disease-specific and population-based human research biobanks is becoming increasingly important for research into disease development and translation. Although informed consent often does not anticipate such cross-domain sharing, it is important to examine its plausibility. The purpose of this study was to explore the feasibility of bridging consent between disease-specific and population-based research. Comparative analyses of 1) current ethical and legal frameworks governing consent and 2) informed consent models found in disease-specific and population-based research were conducted.</p> <p>Discussion</p> <p>Ethical and legal frameworks governing consent dissuade cross-domain data sharing. Paradoxically, analysis of consent models for disease-specific and population-based research reveals such a high degree of similarity that bridging consent could be possible if additional information regarding bridging was incorporated into consent forms. We submit that bridging of consent could be supported if current trends endorsing a new interpretation of consent are adopted. To illustrate this we sketch potential bridging consent scenarios.</p> <p>Summary</p> <p>A bridging consent, respectful of the spirit of initial consent, is feasible and would require only small changes to the content of consents currently being used. Under a bridging consent approach, the initial data and samples collection can serve an identified research project as well as contribute to the creation of a resource for a range of other projects.</p

Public health and valorization of genome-based technologies: a new model

<p>Abstract</p> <p>Background</p> <p>The success rate of timely translation of genome-based technologies to commercially feasible products/services with applicability in health care systems is significantly low. We identified both industry and scientists neglect health policy aspects when commercializing their technology, more specifically, Public Health Assessment Tools (PHAT) and early on involvement of decision makers through which market authorization and reimbursements are dependent. While Technology Transfer (TT) aims to facilitate translation of ideas into products, Health Technology Assessment, one component of PHAT, for example, facilitates translation of products/processes into healthcare services and eventually comes up with recommendations for decision makers. We aim to propose a new model of valorization to optimize integration of genome-based technologies into the healthcare system.</p> <p>Methods</p> <p>The method used to develop our model is an adapted version of the Fish Trap Model and the Basic Design Cycle.</p> <p>Results</p> <p>We found although different, similarities exist between TT and PHAT. Realizing the potential of being mutually beneficial justified our proposal of their relative parallel initiation. We observed that the Public Health Genomics Wheel should be included in this relative parallel activity to ensure all societal/policy aspects are dealt with preemptively by both stakeholders. On further analysis, we found out this whole process is dependent on the Value of Information. As a result, we present our LAL (Learning Adapting Leveling) model which proposes, based on market demand; TT and PHAT by consultation/bi-lateral communication should advocate for relevant technologies. This can be achieved by public-private partnerships (PPPs). These widely defined PPPs create the innovation network which is a developing, consultative/collaborative-networking platform between TT and PHAT. This network has iterations and requires learning, assimilating and using knowledge developed and is called absorption capacity. We hypothesize that the higher absorption capacity, higher success possibility. Our model however does not address the phasing out of technology although we believe the same model can be used to simultaneously phase out a technology.</p> <p>Conclusions</p> <p>This model proposes to facilitate optimization/decrease the timeframe of integration in healthcare. It also helps industry and researchers to come to a strategic decision at an early stage, about technology being developed thus, saving on resources, hence minimizing failures.</p

Routinely collected data for randomized trials: promises, barriers, and implications

This work was supported by Stiftung Institut für klinische Epidemiologie. The Meta-Research Innovation Center at Stanford University is funded by a grant from the Laura and John Arnold Foundation. The funders had no role in design and conduct of the study; the collection, management, analysis, or interpretation of the data; or the preparation, review, or approval of the manuscript or its submission for publication.Peer reviewedPublisher PD

Processes and factors involved in decisions regarding return of incidental genomic findings in research

Purpose: Studies have begun exploring whether researchers should return incidental findings in genomic studies, and if so, which findings should be returned; however, how researchers make these decisions—the processes and factors involved—has remained largely unexplored. Methods: We interviewed 28 genomics researchers in-depth about their experiences and views concerning the return of incidental findings. Results: Researchers often struggle with questions concerning which incidental findings to return and how to make those decisions. Multiple factors shape their views, including information about the gene variant (e.g., pathogenicity and disease characteristics), concerns about participants’ well-being and researcher responsibility, and input from external entities. Researchers weigh the evidence, yet they face conflicting pressures, with relevant data frequently being unavailable. Researchers vary in who they believe should decide: participants, principal investigators, institutional review boards, and/or professional organizations. Contextual factors can influence these decisions, including policies governing return of results by institutions and biobanks and the study design. Researchers vary in desires for: guidance from institutions and professional organizations, changes to current institutional processes, and community-wide genetics education. Conclusion: These data, the first to examine the processes by which researchers make decisions regarding the return of genetic incidental findings, highlight several complexities involved and have important implications for future genetics research, policy, and examinations of these issues