Genomics, Big Data, and Broad Consent: a New Ethics Frontier for Prevention Science

An Analytical Approach that Combines Knowledge from Germline and Somatic Mutations Enhances Tumor Genomic Reanalyses in Precision Oncology

Background: Expanded analysis of tumor genomics data enables current and future patients to gain more benefits, such as improving diagnosis, prognosis, and therapeutics. Methods: Here, we report tumor genomic data from 1146 cases accompanied by simultaneous expert analysis from patients visiting our oncological clinic. We developed an analytical approach that leverages combined germline and cancer genetics knowledge to evaluate opportunities, challenges, and yield of potentially medically relevant data. Results: We identified 499 cases (44%) with variants of interest, defined as either potentially actionable or pathogenic in a germline setting, and that were reported in the original analysis as variants of uncertain significance (VUS). Of the 7405 total unique tumor variants reported, 462 (6.2%) were reported as VUS at the time of diagnosis, yet information from germline analyses identified them as (likely) pathogenic. Notably, we find that a sizable number of these variants (36%-79%) had been reported in heritable disorders and deposited in public databases before the year of tumor testing. Conclusions: This finding indicates the need to develop data systems to bridge current gaps in variant annotation and interpretation and to develop more complete digital representations of actionable pathways. We outline our process for achieving such methodologic integration. Sharing genomics data across medical specialties can enable more robust, equitable, and thorough use of patient's genomics data. This comprehensive analytical approach and the new knowledge derived from its results highlight its multi-specialty value in precision oncology settings.

A contextual integrity approach to genomic information: what bioethics can learn from big data ethics

Genomic data is generated, processed and analysed at an increasingly rapid pace. This data is not limited to the medical context, but plays an important role in other contexts in society, such as commercial DNA testing, the forensic setting, archaeological research, and genetic surveillance. Genomic information also crosses the borders of these domains, e.g. forensic use of medical genetic information, insurance use of medical genomic information, or research use of commercial genomic data. This paper (1) argues that an informed consent approach for genomic information has limitations in many societal contexts, and (2) seeks to broaden the bioethical debate on genomic information by suggesting an approach that is applicable across multiple societal contexts. I argue that the contextual integrity framework, a theory rooted in information technology and big data ethics, is an effective tool to explore ethical challenges that arise from genomic information within a variety of different contexts. Rather than focusing on individual control over information, the contextual integrity approach holds that information should be shared and protected according to the norms that govern certain distinct social contexts. Several advantages of this contextual integrity approach will be discussed. The paper concludes that the contextual integrity framework helps to articulate and address a broad spectrum of ethical, social, and political factors in a variety of different societal contexts, while giving consideration to the interests of individuals, groups, and society at large.

Whole genome sequencing in (recurrent) glioblastoma: challenges related to informed consent procedures and data sharing

Increased use of whole genome sequencing (WGS) in neuro-oncology for diagnostics and research purposes necessitates a renewed conversation about informed consent procedures and governance structures for sharing personal health data. There is currently no consensus on how to obtain informed consent for WGS in this population. In this narrative review, we analyze the formats and contents of frameworks suggested in literature for WGS in oncology and assess their benefits and limitations. We discuss applicability, specific challenges, and legal context for patients with (recurrent) glioblastoma. This population is characterized by the rarity of the disease, extremely limited prognosis, and the correlation of the stage of the disease with cognitive abilities. Since this has implications for the informed consent procedure for WGS, we suggest that the content of informed consent should be tailor-made for (recurrent) glioblastoma patients.

Consent as a compositional act - a framework that provides clarity for the retention and use of data

BACKGROUND

Informed consent is one of the key principles of conducting research involving humans. When research participants give consent, they perform an act in which they utter, write or otherwise provide an authorisation to somebody to do something. This paper proposes a new understanding of the informed consent as a compositional act. This conceptualisation departs from a modular conceptualisation of informed consent procedures.

METHODS

This paper is a conceptual analysis that explores what consent is and what it does or does not do. It presents a framework that explores the basic elements of consent and breaks it down into its component parts. It analyses the consent act by first identifying its basic elements, namely: a) data subjects or legal representative that provides the authorisation of consent; b) a specific thing that is being consented to; and c) specific agent(s) to whom the consent is given.

RESULTS

This paper presents a framework that explores the basic elements of consent and breaks it down into its component parts. It goes beyond only providing choices to potential research participants; it explains the rationale of those choices or consenting acts that are taking place when speaking or writing an authorisation to do something to somebody.

CONCLUSIONS

We argue that by clearly differentiating the goals, the procedures of implementation, and what is being done or undone when one consent, one can better face the challenges of contemporary data-intensive biomedical research, particularly regarding the retention and use of data. Conceptualising consent as a compositional act enhances more efficient communication and accountability and, therefore, could enable more trustworthy acts of consent in biomedical science.

An ethical code for collecting, using and transferring sensitive health data: outcomes of a modified Policy Delphi process in Singapore

One of the core goals of Digital Health Technologies (DHT) is to transform healthcare services and delivery by shifting primary care from hospitals into the community. However, achieving this goal will rely on the collection, use and storage of large datasets. Some of these datasets will be linked to multiple sources, and may include highly sensitive health information that needs to be transferred across institutional and jurisdictional boundaries. The growth of DHT has outpaced the establishment of clear legal pathways to facilitate the collection, use and transfer of potentially sensitive health data. Our study aimed to address this gap with an ethical code to guide researchers developing DHT with international collaborative partners in Singapore. We generated this code using a modified Policy Delphi process designed to engage stakeholders in the deliberation of health data ethics and governance. This paper reports the outcomes of this process along with the key components of the code and identifies areas for future research.

Regulations and Norms for Reuse of Residual Clinical Biospecimens and Health Data

Nurse scientists are increasingly interested in conducting secondary research using real world collections of biospecimens and health data. The purposes of this scoping review are to (a) identify federal regulations and norms that bear authority or give guidance over reuse of residual clinical biospecimens and health data, (b) summarize domain experts' interpretations of permissions of such reuse, and (c) summarize key issues for interpreting regulations and norms. Final analysis included 25 manuscripts and 23 regulations and norms. This review illustrates contextual complexity for reusing residual clinical biospecimens and health data, and explores issues such as privacy, confidentiality, and deriving genetic information from biospecimens. Inconsistencies make it difficult to interpret, which regulations or norms apply, or if applicable regulations or norms are congruent. Tools are necessary to support consistent, expert-informed consent processes and downstream reuse of residual clinical biospecimens and health data by nurse scientists.

Advancing a Data Justice Framework for Public Health Surveillance

BACKGROUND

Bioethical debates about privacy, big data, and public health surveillance have not sufficiently engaged the perspectives of those being surveilled. The data justice framework suggests that big data applications have the potential to create disproportionate harm for socially marginalized groups. Using examples from our research on HIV surveillance for individuals incarcerated in jails, we analyze ethical issues in deploying big data in public health surveillance.

METHODS

We conducted qualitative, semi-structured interviews with 24 people living with HIV who had been previously incarcerated in county jails about their perspectives on and experiences with HIV surveillance, as part of a larger study to characterize ethical considerations in leveraging big data techniques to enhance continuity of care for incarcerated people living with HIV.

RESULTS

Most participants expressed support for the state health department tracking HIV testing results and viral load data. Several viewed HIV surveillance as a violation of privacy, and several had actively avoided contact from state public health outreach workers. Participants were most likely to express reservations about surveillance when they viewed the state's motives as self-interested. Perspectives highlight the mistrust that structurally vulnerable people may have in the state's capacity to act as an agent of welfare. Findings suggest that adopting a nuanced, context-sensitive view on surveillance is essential.

CONCLUSIONS

Establishing trustworthiness through interpersonal interactions with public health personnel is important to reversing historical legacies of harm to racial minorities and structurally vulnerable groups. Empowering stakeholders to participate in the design and implementation of data infrastructure and governance is critical for advancing a data justice agenda, and can offset privacy concerns. The next steps in advancing the data justice framework in public health surveillance will be to innovate ways to represent the voices of structurally vulnerable groups in the design and governance of big data initiatives.

Lessons learned and recommendations for data coordination in collaborative research: The CSER consortium experience

Integrating data across heterogeneous research environments is a key challenge in multi-site, collaborative research projects. While it is important to allow for natural variation in data collection protocols across research sites, it is also important to achieve interoperability between datasets in order to reap the full benefits of collaborative work. However, there are few standards to guide the data coordination process from project conception to completion. In this paper, we describe the experiences of the Clinical Sequence Evidence-Generating Research (CSER) consortium Data Coordinating Center (DCC), which coordinated harmonized survey and genomic sequencing data from seven clinical research sites from 2020 to 2022. Using input from multiple consortium working groups and from CSER leadership, we first identify 14 lessons learned from CSER in the categories of communication, harmonization, informatics, compliance, and analytics. We then distill these lessons learned into 11 recommendations for future research consortia in the areas of planning, communication, informatics, and analytics. We recommend that planning and budgeting for data coordination activities occur as early as possible during consortium conceptualization and development to minimize downstream complications. We also find that clear, reciprocal, and continuous communication between consortium stakeholders and the DCC is equally important to maintaining a secure and centralized informatics ecosystem for pooling data. Finally, we discuss the importance of actively interrogating current approaches to data governance, particularly for research studies that straddle the research-clinical divide.

An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology

Current best practices in tumor registries provide a glimpse into a limited time frame over the natural history of disease, usually a narrow window around diagnosis and biopsy. This creates challenges meeting public health and healthcare reimbursement policies that increasingly require robust documentation of long-term clinical trajectories, quality of life, and health economics outcomes. These challenges are amplified for underrepresented minority (URM) and other disadvantaged populations, who tend to view the institution of clinical research with skepticism. Participation gaps leave such populations underrepresented in clinical research and, importantly, in policy decisions about treatment choices and reimbursement, thus further augmenting health, social, and economic disparities. Cloud computing, mobile computing, digital ledgers, tokenization, and artificial intelligence technologies are powerful tools that promise to enhance longitudinal patient engagement across the natural history of disease. These tools also promise to enhance engagement by giving participants agency over their data and addressing a major impediment to research participation. This will only occur if these tools are available for use with all patients. Distributed ledger technologies (specifically blockchain) converge these tools and offer a significant element of trust that can be used to engage URM populations more substantively in clinical research. This is a crucial step toward linking composite cohorts for training and optimization of the artificial intelligence tools for enhancing public health in the future. The parameters of an idealized clinical genomic registry are presented.

“Data is the new oil”: citizen science and informed consent in an era of researchers handling of an economically valuable resource

As with other areas of the social world, academic research in the contemporary healthcare setting has undergone adaptation and change. For example, research methods are increasingly incorporating citizen participation in the research process, and there has been an increase in collaborative research that brings academic and industry partners together. There have been numerous positive outcomes associated with both of these growing methodological and collaborative processes; nonetheless, both bring with them ethical considerations that require careful thought and attention. This paper addresses the ethical considerations that research teams must consider when using participatory methods and/or when working with industry and outlines a novel informed consent matrix designed to maintain the high ethical standard to which academic research in the healthcare arena has traditionally adhered.

Chronic Heart Failure Patients’ Attitudes towards Digital Device Data for Self-Documentation and Research in Germany: A Cross-Sectional Survey Study (Preprint)

Background

In recent years, the use of digital mobile measurement devices (DMMDs) for self-documentation in cardiovascular care in Western industrialized health care systems has increased. For patients with chronic heart failure (cHF), digital self-documentation plays an increasingly important role in self-management. Data from DMMDs can also be integrated into telemonitoring programs or data-intensive medical research to collect and evaluate patient-reported outcome measures through data sharing. However, the implementation of data-intensive devices and data sharing poses several challenges for doctors and patients as well as for the ethical governance of data-driven medical research.

Objective

This study aims to explore the potential and challenges of digital device data in cardiology research from patients’ perspectives. Leading research questions of the study concerned the attitudes of patients with cHF toward health-related data collected in the use of digital devices for self-documentation as well as sharing these data and consenting to data sharing for research purposes.

Methods

A cross-sectional survey of patients of a research in cardiology was conducted at a German university medical center (N=159) in 2020 (March to July). Eligible participants were German-speaking adult patients with cHF at that center. A pen-and-pencil questionnaire was sent by mail.

Results

Most participants (77/105, 73.3%) approved digital documentation, as they expected the device data to help them observe their body and its functions more objectively. Digital device data were believed to provide cognitive support, both for patients’ self-assessment and doctors’ evaluation of their patients’ current health condition. Interestingly, positive attitudes toward DMMD data providing cognitive support were, in particular, voiced by older patients aged >65 years. However, approximately half of the participants (56/105, 53.3%) also reported difficulty in dealing with self-documented data that lay outside the optimal medical target range. Furthermore, our findings revealed preferences for the self-management of DMMD data disclosed for data-intensive medical research among German patients with cHF, which are best implemented with a dynamic consent model.

Conclusions

Our findings provide potentially valuable insights for introducing DMMD in cardiovascular research in the German context. They have several practical implications, such as a high divergence in attitudes among patients with cHF toward different data-receiving organizations as well as a large variance in preferences for the modes of receiving information included in the consenting procedure for data sharing for research. We suggest addressing patients’ multiple views on consenting and data sharing in institutional normative governance frameworks for data-intensive medical research.

Assessing Perceptions of Broad Consent Concerning Biological Specimen Collection in a Cohort of Young Sexual Minority Men

The use of broad consent to store human biospecimens to be used in future research studies has increased over the years. However, it is currently unknown how young sexual minority men (YSMM) perceive broad consent in these specific types of studies. Therefore, in this study we aimed to determine the extent to which YSMM are comfortable with providing broad consent concerning their identifiable biological specimens to a variety of entities, including external researchers and pharmaceutical companies and to examine the relationship between mistrust based on racial/ethnic identity or sexual orientation and attitudes toward broad consent. YSMM (N = 239) ages 24-27 years were recruited from a prospective cohort study in New York City in 2018 to complete a survey assessing attitudes about the use of broad consent concerning biospecimens for secondary research. We found that YSMM were most willing to provide broad consent to the researcher from the study they were enrolled in (85.3%), other researchers within the same university (82.4%), and researchers at other universities (74.5%). Participants were least willing to provide broad consent to government organizations (64.4%) and pharmaceutical companies (53.8%). Further, we found that medical mistrust based on racial/ethnic identity or sexual orientation was associated with attitudes toward the use of broad consent. Research institutions should consider modifying consent procedures around the use of broad consent in order to maximize recruitment and retention, especially among minority populations.

Citizens' views on sharing their health data: the role of competence, reliability and pursuing the common good

Background

In this article, we address questions regarding how people consider what they do or do not consent to and the reasons why. This article presents the findings of a citizen forum study conducted by the University of Geneva in partnership with the Geneva University Hospitals to explore the opinions and concerns of members of the public regarding predictive oncology, genetic sequencing, and cancer.

Methods

This paper presents the results of a citizen forum that included 73 participants. A research tool titled "the mechanics of consent" was designed for this study. This tool is a table encouraging participants to reflect on social and research actors, types of data, and desired levels of control while sharing different types of data with different actors. Participants’ discussion that led to the completion of each table were audio-recorded, transcribed, and analyzed using thematic analysis.

Results

The results are a compilation of responses from the mechanics of consent tool divided into two sections; the first presents quantitative results of collective responses regarding attitudes to consent to donate their data. The second section present qualitative findings emerged from the discussion amongst participants.

Discussion

Choice and control of personal data is crucial for the public to be able to decide who and how to trust. Key information to be disclosed to potential research participants shall include information about potential risks and benefits; who will be accessing and using their data; as well as assurances that their choice will be respected. Furthermore, researchers ought to make sure they are trustworthy, by acting in a competent, reliable, and honest manner. Governance systems ought to be better equipped to address ethical issues raise by the growing presence of non-traditional research actors, consent of exchanges of data via digital devices and online activity such as social media and fairness of data trading. Finally, informed consent is one of the various elements that contribute to conducting ethical research. More needs to be done to strengthen governance and ensure adequate protection of research participants, particularly to address issues related to predictive health analytics.

Impact of industry 4.0 to create advancements in orthopaedics

Scientists and health professional are focusing on improving the medical sciences for the betterment of patients. The fourth industrial revolution, which is commonly known as Industry 4.0, is a significant advancement in the field of engineering. Industry 4.0 is opening a new opportunity for digital manufacturing with greater flexibility and operational performance. This development is also going to have a positive impact in the field of orthopaedics. The purpose of this paper is to present various advancements in orthopaedics by the implementation of Industry 4.0. To undertake this study, we have studied the available literature extensively on Industry 4.0, technologies of Industry 4.0 and their role in orthopaedics. Paper briefly explains about Industry 4.0, identifies and discusses the major technologies of Industry 4.0, which will support development in orthopaedics. Finally, from the available literature, the paper identifies twelve significant advancements of Industry 4.0 in orthopaedics. Industry 4.0 uses various types of digital manufacturing and information technologies to create orthopaedics implants, patient-specific tools, devices and innovative way of treatment. This revolution is to be useful to perform better spinal surgery, knee and hip replacement, and invasive surgeries.

Ethical Considerations in HIV eHealth Intervention Research: Implications for Informational Risk in Recruitment, Data Maintenance, and Consent Procedures

PURPOSE OF REVIEW

Along with the benefits of eHealth HIV interventions are challenges to participant privacy and confidentiality inherent in the use of online strategies. This paper reviews current guidelines and recent publications to identify ethical issues and suggested solutions in recruitment, data management, and informed consent.

RECENT FINDINGS

Across eHealth HIV research, recruitment, data collection, and storage efforts to protect informational risk highlight the tension between the investigators' ability to protect participant confidentiality and the evolving informational risk posed by the online platforms on which they are operating. Adequately addressing these challenges requires updating technical competencies and educating participants on their own responsibilities to guard against privacy violations. Additional protections are required when interventions involve peer or community support, especially with minors. The rapid progression of technology presents challenges in solidifying best practices for future interventions. This article draws on published works describing investigator experiences to contribute to the ongoing development of guidance in this area.

Consent and Privacy in the Era of Precision Medicine and Biobanking Genomic Data

"Big Data represents a challenge that points to the need for collective and political approaches to self-protection rather than solely individual, atomistic approaches."- Anita Allen, "Protecting One's Own Privacy in a Big Data Economy".

The benefit of foresight? An ethical evaluation of predictive testing for psychosis in clinical practice

Risk prediction for psychosis has advanced to the stage at which it could feasibly become a clinical reality. Neuroimaging biomarkers play a central role in many risk prediction models. Using such models to predict the likelihood of transition to psychosis in individuals known to be at high risk has the potential to meaningfully improve outcomes, principally through facilitating early intervention. However, this compelling benefit must be evaluated in light of the broader ethical ramifications of this prospective development in clinical practice. This paper advances ethical discussion in the field in two ways: firstly, through in-depth consideration of the distinctive implications of the clinical application of predictive tools; and, secondly, by evaluating the manner in which newer predictive models incorporating neuroimaging alter the ethical landscape. We outline the current state of the science of predictive testing for psychosis, with a particular focus on emerging neuroimaging biomarkers. We then proceed to ethical analysis employing the four principles of biomedical ethics as a conceptual framework. We conclude with a call for scientific advancement to proceed in tandem with ethical consideration, informed by empirical study of the views of high risk individuals and their families. This collaborative approach will help ensure that predictive testing progresses in an ethically acceptable manner that minimizes potential adverse effects and maximizes meaningful benefits for those at high risk of psychosis.

Sexual and gender minority youth's perspectives on sharing de-identified data in sexual health and HIV prevention research

Funding agencies encourage and sometimes require data sharing. However, there is limited empirical research on participant perspectives on sharing de-identified data from research on sensitive topics (e.g., HIV, sexual health) with other researchers, and virtually none from adolescents or sexual and gender minority (SGM) participants. SGM teens (N = 197) ages 14-17 completed an online survey with multiple choice and open-ended items assessing perspectives toward sharing survey responses and blood samples from sexual health and HIV testing studies with other researchers. SGM youth were willing to share data but frequently cited confidentiality and privacy concerns, including fears about parents finding out about their identities even after de-identification was explained. Researchers need to ensure youth understand explanations of data security protections in order to make well-informed decisions about participating in research.