Assessing Decisional Regret Among Biobank Sample Donors

Background: Large biobanks that link biological specimens with specimen donors' health histories are a critical tool for precision medicine, and many health care institutions have invested significant resources in setting up and building up large collections for this purpose. As biobanks require consented participation from thousands of individual donors, much research has focused on the values and preferences of new and prospective donors who are actively contemplating an invitation to participate in the collection. Few studies, however, have focused on participants' opinions about their biobank participation in the months and years following enrollment. Methods: We conducted a survey in a large, established biobank and evaluated participants' levels of decisional regret regarding their decision to enroll in the biobank. Results: We found very low levels of decisional regret among established biobank participants. Multivariable regression analysis found that age, length of time in the biobank, lower educational attainment, inadequate health literacy, and previous invitations to research participation were all significant predictors of elevated regret. Discussion: Among those with elevated regret, several demographic factors may point to elevated likelihood of decisional regret. More research is needed to identify factors associated with long-term satisfaction with biobank participation and with elevated risk of regret and/or withdrawal from the collection.

Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network

The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. Our approach to managing the complexities associated with the differential performance of PRSs serves as a case study that can help future implementers of PRSs to plot an anticipatory course in response to this issue.

Behind the Scenes: Facilitators and Barriers to Developing State Scarce Resource Allocation Plans for the COVID-19 Pandemic

BACKGROUND

In response to COVID-19, many states revised, developed, or attempted to develop plans to allocate scarce critical care resources in the event that crisis standards of care were triggered. No prior analysis has assessed this plan development process, including whether plans were successfully adopted.

RESEARCH QUESTION

How did states develop or revise scarce resource allocation plans during the COVID-19 pandemic, and what were the barriers and facilitators to their development and adoption at the state level?

STUDY DESIGN AND METHODS

Plan authors and state leaders completed a semi-structured interview February to September 2022. Interview transcripts were qualitatively analyzed for themes related to plan development and adoption according to the principles of grounded theory.

RESULTS

Thirty-six participants from 34 states completed an interview, from states distributed across all US regions. Among participants' states with plans that existed prior to 2020 (n = 24), 17 were revised and adopted in response to COVID-19. Six states wrote a plan de novo, with the remaining states failing to develop or adopt a plan. Thirteen states continued to revise their plans in response to disability or aging bias complaints or to respond to evolving needs. Many participants expressed that urgency in the early days of the pandemic prevented an ideal development process. Facilitators of successful plan development and adoption include: coordination or support from the state department of health and existing relationships with key community partners, including aging and disability rights groups and minoritized communities. Barriers include lack of perceived political interest in a plan and development during a public health emergency.

INTERPRETATION

To avoid repeating mistakes from the early days of the COVID-19 response, states should develop or revise plans with community engagement and consider maintaining a standing committee with diverse membership and content expertise to periodically review plans and advise state officials on pandemic preparedness.

Qualitative Analysis of Decision to Pursue Electrical Brain Stimulation by Patients With Drug-Resistant Epilepsy and Their Caregivers

Background and Objectives

To understand why patients with drug-resistant epilepsy (DRE) pursue invasive electrical brain stimulation (EBS).

Methods

We interviewed patients with DRE (n = 20) and their caregivers about their experiences in pursuing EBS approximately 1 year post device implant. Inductive analysis was applied to identify key motivating factors.

Results

The cohort included participants aged from teens to 50s with deep brain stimulation, vagus nerve stimulation, responsive neurostimulation, and chronic subthreshold cortical stimulation. Patients' motivations included (1) improved quality of life (2) intolerability of antiseizure medications, (3) desperation, and (4) patient-family dynamics. Both patients and caregivers described a desire to alleviate burdens of the other. Patient apprehensions about EBS focused on invasiveness and the presence of electrodes in the brain. Previous experiences with invasive monitoring and the ability to see hardware in person during clinical visits influenced patients' comfort in proceeding with EBS. Despite realistic expectations for modest and delayed benefits, patients held out hope for an exceptionally positive outcome.

Discussion

Our findings describe the motivations and decision-making process for patients with DRE who pursue invasive EBS. Patients balance feelings of desperation, personal goals, frustration with medication side effects, fears about surgery, and potential pressure from concerned caregivers. These factors together with the sense that patients have exhausted therapeutic alternatives may explain the limited decisional ambivalence observed in this cohort. These themes highlight opportunities for epilepsy care teams to support patient decision-making processes.

Returning integrated genomic risk and clinical recommendations: The eMERGE study

PURPOSE

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS

To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS

GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION

Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results

BACKGROUND

The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network.

METHODS

Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR, APOB, and PCSK9. FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review.

RESULTS

The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00-4.53]) and premature CHD (odds ratio, 3.68 [2.34-5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results.

CONCLUSIONS

In a multisite cohort of electronic health record-linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record-linked biobanks to detect FH.

Treating addiction with deep brain stimulation: Ethical and legal considerations

BACKGROUND

The use of neuromodulation in the treatment of psychiatric conditions is controversial despite its lengthy history. This particularly applies to the use of invasive neuromodulation, such as deep brain stimulation (DBS), to treat substance use disorder (SUD) due to the considerable risks of the procedures. However, given the advances in DBS research and the shortcomings of current treatment modalities for addiction, off-label use and clinical trials are being implemented for the management of treatment-refractory patients.

METHODS

Here we conduct an ethical and legal analysis of DBS for SUD, referencing the four foundational principles of medical ethics and key legal concepts.

RESULTS

There are major concerns related to the capacity of a SUD patient to provide informed consent, as well as the risks and benefits of DBS compared to traditional treatment methods. In addition to ethical concerns, we explore potential legal issues that may arise from DBS in the treatment of addiction. These include the potential mandate of these procedures in the context of the criminalization of substance use, and the issue of familial consent in the decision-making process. Given the paucity of relevant clinical guidelines or legal cases, general medico-legal principles serve as the reference in making decisions about the responsible use of DBS as a treatment for addiction.

CONCLUSIONS

Given the rapidly increasing evidence for DBS as a treatment for SUD, it is an urgent imperative to consider the relevant key ethical and legal issues. Incorporating IDEAL (Idea, Development, Exploration, Assessment, Long-term follow-up) framework into future research in DBS is recommended to evaluate patient safety and ethical perspectives. With the broad criminalization of SUD across the globe, legal coercion of DBS is not impossible, especially if proven to be effective to treat SUD. It is advised for stakeholders to urgently consider incorporating DBS-related drug policies so that the potential benefits of DBS within the rights of people with SUD are not hindered by the lack of clinical guidance and legislations.

Examining the Impact of Polygenic Risk Information in Primary Care

BACKGROUND

Polygenic risk testing examines variation across multiple genes to estimate a risk score for a particular disease, including risk scores for many common, chronic health conditions. Although polygenic risk information (PRI) may be a promising tool for enhancing preventive counseling and facilitating early identification of disease, its potential impact on primary-care encounters and disease prevention efforts has not been well characterized.

METHODS

We conducted in-depth, semi-structured interviews of patients to assess their understandings of PRI and their beliefs about its relevance to disease prevention.

RESULTS

We completed interviews with 19 participants. Participants described enthusiasm for the generation of PRI and recognized its utility for disease prevention. Participants also described the value of PRI as limited if not corroborated by non-genetic risk factors. Finally, participants noted that PRI, by itself, would be insufficient as a trigger for initiating many preventive interventions.

CONCLUSION

PRI has the potential to become an important tool in primary care. However, patient views about PRI as well as the complexities of disease prevention in the primary care context may limit the impact of PRI on disease prevention.

Louis EK. Patient values and preferences regarding prognostic counseling in isolated REM sleep behavior disorder

STUDY OBJECTIVES

Isolated REM sleep behavior disorder (iRBD) carries a high lifetime risk for phenoconversion to a defined neurodegenerative disease (NDD) including Parkinson disease, dementia with Lewy bodies, and multiple system atrophy. We aimed to examine iRBD patient values and preferences regarding prognostic counseling.

METHODS

One hundred thirteen iRBD patient participants enrolled in the Mayo Clinic iRBD Patient Registry were sent an email survey concerning their values and preferences concerning NDD prognostic counseling and their experiences following diagnosis with iRBD.

RESULTS

Of 81 respondents (71.7% response rate), the majority were men (74.0%) with an average age of 65.7 (±9.7) years. Responses indicated a strong preference toward receiving prognostic information about possible future NDD development. 92.5% of respondents felt knowledge concerning personal NDD risk was important, while 87.6% indicated prognostic discussions were important to maintaining trust in their physician. 95.7% indicated a desire for more information, while only 4.3% desired less information regarding their NDD prognostic risk. Most respondents strongly agreed that prognostic information was important to discuss with their family and friends and inform future life planning, and most expressed interest in learning more about future neuroprotective therapies and symptomatic treatments for parkinsonism and dementia.

CONCLUSIONS

Most iRBD patients indicated strong preferences for disclosure of NDD prognostic risk and indicated that prognostic information was important for family discussions and future life planning. Future broader surveys and qualitative studies of clinic-based and ultimately community dwelling iRBD patients' values and preferences are needed to guide appropriately tailored and individualized prognostic counseling approaches following iRBD diagnosis.

Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index

OBJECTIVE

Artificial intelligence (AI) models may propagate harmful biases in performance and hence negatively affect the underserved. We aimed to assess the degree to which data quality of electronic health records (EHRs) affected by inequities related to low socioeconomic status (SES), results in differential performance of AI models across SES.

MATERIALS AND METHODS

This study utilized existing machine learning models for predicting asthma exacerbation in children with asthma. We compared balanced error rate (BER) against different SES levels measured by HOUsing-based SocioEconomic Status measure (HOUSES) index. As a possible mechanism for differential performance, we also compared incompleteness of EHR information relevant to asthma care by SES.

RESULTS

Asthmatic children with lower SES had larger BER than those with higher SES (eg, ratio = 1.35 for HOUSES Q1 vs Q2-Q4) and had a higher proportion of missing information relevant to asthma care (eg, 41% vs 24% for missing asthma severity and 12% vs 9.8% for undiagnosed asthma despite meeting asthma criteria).

DISCUSSION

Our study suggests that lower SES is associated with worse predictive model performance. It also highlights the potential role of incomplete EHR data in this differential performance and suggests a way to mitigate this bias.

CONCLUSION

The HOUSES index allows AI researchers to assess bias in predictive model performance by SES. Although our case study was based on a small sample size and a single-site study, the study results highlight a potential strategy for identifying bias by using an innovative SES measure.

Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study

PURPOSE

The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping.

METHODS

Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record.

RESULTS

For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping.

CONCLUSION

Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.

Allocation of Opportunities to Participate in Clinical Trials during the Covid-19 Pandemic and Other Public Health Emergencies

Covid-19 raised many novel ethical issues including regarding the allocation of opportunities to participate in clinical trials during a public health emergency. In this article, we explore how hospitals that have a scarcity of trial opportunities, either overall or in a specific trial, can equitably allocate those opportunities in the context of an urgent medical need with limited therapeutic interventions. We assess the three main approaches to allocating trial opportunities discussed in the literature: patient choice, physician referral, and randomization/lottery. As, we argue, none of the three typical approaches are ethically ideal for allocating trial opportunities in the pandemic context, many hospitals have instead implemented hybrid solutions. We offer practical guidance to support those continuing to face these challenges, and we analyze options for the future.

A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare

Background

While use of artificial intelligence (AI) in healthcare is increasing, little is known about how patients view healthcare AI. Characterizing patient attitudes and beliefs about healthcare AI and the factors that lead to these attitudes can help ensure patient values are in close alignment with the implementation of these new technologies.

Methods

We conducted 15 focus groups with adult patients who had a recent primary care visit at a large academic health center. Using modified grounded theory, focus-group data was analyzed for themes related to the formation of attitudes and beliefs about healthcare AI.

Results

When evaluating AI in healthcare, we found that patients draw on a variety of factors to contextualize these new technologies including previous experiences of illness, interactions with health systems and established health technologies, comfort with other information technology, and other personal experiences. We found that these experiences informed normative and cultural beliefs about the values and goals of healthcare technologies that patients applied when engaging with AI. The results of this study form the basis for a theoretical framework for understanding patient orientation to applications of AI in healthcare, highlighting a number of specific social, health, and technological experiences that will likely shape patient opinions about future healthcare AI applications.

Conclusions

Understanding the basis of patient attitudes and beliefs about healthcare AI is a crucial first step in effective patient engagement and education. The theoretical framework we present provides a foundation for future studies examining patient opinions about applications of AI in healthcare.

Lay understandings of drug-gene interactions: The right medication, the right dose, at the right time, but what are the right words?

As pharmacogenomic (PGx) testing increases in popularity, lay concepts of drug‐gene interactions set the stage for shared decision making in precision medicine. Few studies explore what recipients of PGx results think is happening in their bodies when a drug‐gene interaction is discovered. To characterize biobank participants’ understanding of PGx research results, we conducted a focus group study, which took place after PGx variants conferring increased risk of dihydropyrimidine dehydrogenase (DPD) deficiency were disclosed to biobank contributors. DPD deficiency confers an increased risk of adverse reaction to commonly used cancer chemotherapeutics. Ten focus groups were conducted, ranging from two to eight participants. Fifty‐four individuals participated in focus groups. A framework approach was used for descriptive and explanatory analysis. Descriptive themes included participants’ efforts to make sense of PGx findings as they related to: (1) health implications, (2) drugs, and (3) genetics. Explanatory analysis supplied a functional framework of how participant word choices can perform different purposes in PGx communication. Results bear three main implications for PGx research‐related disclosure. First, participants’ use of various terms suggest participants generally understanding their PGx results, including how positive PGx results differ from positive disease susceptibility genetic results. Second, PGx disclosure in biobanking can involve participant conflation of drug‐gene interactions with allergies or other types of medical reactions. Third, the functional framework suggests a need to move beyond a deficit model of genetic literacy in PGx communication. Together, findings provide an initial evidence base for supporting bidirectional expert‐recipient PGx results communication.

Do research participants share genomic screening results with family members?

The public health impact of genomic screening can be enhanced by cascade testing. However, cascade testing depends on communication of results to family members. While the barriers and facilitators of family communication have been researched following clinical genetic testing, the factors impacting the dissemination of genomic screening results are unknown. Using the pragmatic Electronic Medical Records and Genomics Network-3 (eMERGE-3) study, we explored the reported sharing practices of participants who underwent genomic screening across the United States. Six eMERGE-3 sites returned genomic screening results for mostly dominant medically actionable disorders and surveyed adult participants regarding communication of results with first-degree relatives. Across the sites, 279 participants completed a 1-month and/or 6-month post-results survey. By 6 months, only 34% of the 156 respondents shared their results with all first-degree relatives and 4% did not share with any. Over a third (39%) first-degree relatives were not notified of the results. Half (53%) of participants who received their results from a genetics provider shared them with all first-degree relatives compared with 11% of participants who received their results from a non-genetics provider. The most frequent reasons for sharing were a feeling of obligation (72%) and that the information could help family members make medical decisions (72%). The most common reasons indicated for not sharing were that the family members were too young (38%), or they were not in contact (25%) or not close to them (25%). These data indicate that the professional returning the results may impact sharing patterns, suggesting that there is a need to continue to educate healthcare providers regarding approaches to facilitate sharing of genetic results within families. Finally, these data suggest that interventions to increase sharing may be universally effective regardless of the origin of the genetic result.

Patient apprehensions about the use of artificial intelligence in healthcare

While there is significant enthusiasm in the medical community about the use of artificial intelligence (AI) technologies in healthcare, few research studies have sought to assess patient perspectives on these technologies. We conducted 15 focus groups examining patient views of diverse applications of AI in healthcare. Our results indicate that patients have multiple concerns, including concerns related to the safety of AI, threats to patient choice, potential increases in healthcare costs, data-source bias, and data security. We also found that patient acceptance of AI is contingent on mitigating these possible harms. Our results highlight an array of patient concerns that may limit enthusiasm for applications of AI in healthcare. Proactively addressing these concerns is critical for the flourishing of ethical innovation and ensuring the long-term success of AI applications in healthcare.

Factors that Influence Intent to Share Genetic Information Related to Cancer Risk with Family Members

We describe factors influencing patient decisions to share positive cancer genetic test results with family members. We focused on patients who were diagnosed with several different cancer types but did not have a family history that was suggestive of an inherited risk. Participants were recruited from Mayo Clinic and had been recently diagnosed with cancer. An 80+ gene panel was performed. Before receiving genetic test results, patients completed a 49-item survey on their intent to share their results with relatives. 1,721 (57.7%) of 2,984 individuals who elected to pursue genetic testing completed the survey. Most patients planned to share cancer-related genetic results with a spouse or partner (97.0%), at least one adult child (92.2%), at least one sibling (86.2%), and with at least one parent (70.3%). Familial support scores and familial communication scores were predictive of intent to share cancer-related genetic test results. Our data highlight differences in family communication capacity and support that are important for clinicians to consider when supporting patients who wish to share cancer-related genetic test results with family members. Our data point to several potential interventional strategies that might increase the likelihood of cancer-related genetic test results being shared with family members at risk.

Measuring Attitudes About Genomic Medicine: Validation of the Genomic Orientation Scale (GO Scale)

OBJECTIVES

Assessing public attitudes about genomic medicine is critical for anticipating patient receptivity to clinical applications of genomics. Although scholars have highlighted the importance of assessing stakeholder opinions and views regarding advances in clinical genomics, to date there has not been a robust tool for measuring these attitudes. We designed a study to evaluate the validity of an instrument we developed for measuring attitudes about genomic medicine.

METHODS

We used psychometric methods to validate the Genomic Orientation Scale (GO Scale). Our goal was to create an easy-to-use tool for evaluating positive and negative attitudes about genomic medicine.

RESULTS

We describe the validation testing of the GO Scale in a nationally representative sample of 1536 individuals residing in the United States. We report results from convergent and divergent validity testing and Rasch modeling analysis. The study produced a 26-item scale with 2 dimensions-optimism and pessimism.

CONCLUSIONS

The GO Scale may be used to characterize attitudinal perspectives among patients, clinicians, and the public. The GO Scale may also be useful in evaluating shifts in attitude over time, for example, following educational interventions, which has not been feasible to date.