The INGENIOUS trial: Impact of pharmacogenetic testing on adverse events in a pragmatic clinical trial

Adverse drug events (ADEs) account for a significant mortality, morbidity, and cost burden. Pharmacogenetic testing has the potential to reduce ADEs and inefficacy. The objective of this INGENIOUS trial (NCT02297126) analysis was to determine whether conducting and reporting pharmacogenetic panel testing impacts ADE frequency. The trial was a pragmatic, randomized controlled clinical trial, adapted as a propensity matched analysis in individuals (N = 2612) receiving a new prescription for one or more of 26 pharmacogenetic-actionable drugs across a community safety-net and academic health system. The intervention was a pharmacogenetic testing panel for 26 drugs with dosage and selection recommendations returned to the health record. The primary outcome was occurrence of ADEs within 1 year, according to modified Common Terminology Criteria for Adverse Events (CTCAE). In the propensity-matched analysis, 16.1% of individuals experienced any ADE within 1-year. Serious ADEs (CTCAE level ≥ 3) occurred in 3.2% of individuals. When combining all 26 drugs, no significant difference was observed between the pharmacogenetic testing and control arms for any ADE (Odds ratio 0.96, 95% CI: 0.78-1.18), serious ADEs (OR: 0.91, 95% CI: 0.58-1.40), or mortality (OR: 0.60, 95% CI: 0.28-1.21). However, sub-group analyses revealed a reduction in serious ADEs and death in individuals who underwent pharmacogenotyping for aripiprazole and serotonin or serotonin-norepinephrine reuptake inhibitors (OR 0.34, 95% CI: 0.12-0.85). In conclusion, no change in overall ADEs was observed after pharmacogenetic testing. However, limitations incurred during INGENIOUS likely affected the results. Future studies may consider preemptive, rather than reactive, pharmacogenetic panel testing.

Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network

The complexity of genomic medicine can be streamlined by implementing some form of clinical decision support (CDS) to guide clinicians in how to use and interpret personalized data; however, it is not yet clear which strategies are best suited for this purpose. In this study, we used implementation science to identify common strategies for applying provider-based CDS interventions across six genomic medicine clinical research projects funded by an NIH consortium. Each project's strategies were elicited via a structured survey derived from a typology of implementation strategies, the Expert Recommendations for Implementing Change (ERIC), and follow-up interviews guided by both implementation strategy reporting criteria and a planning framework, RE-AIM, to obtain more detail about implementation strategies and desired outcomes. We found that, on average, the three pharmacogenomics implementation projects used more strategies than the disease-focused projects. Overall, projects had four implementation strategies in common; however, operationalization of each differed in accordance with each study's implementation outcomes. These four common strategies may be important for precision medicine program implementation, and pharmacogenomics may require more integration into clinical care. Understanding how and why these strategies were successfully employed could be useful for others implementing genomic or precision medicine programs in different contexts.

Enrollment of Diverse Populations in the INGENIOUS Pharmacogenetics Clinical Trial

Recruitment of diverse populations and subjects living in Medically Underserved Areas and Populations (MUA/P's) into clinical trials is a considerable challenge. Likewise, representation of African-Americans in pharmacogenetic trials is often inadequate, but critical for identifying genetic variation within and between populations. To identify enrollment patterns and variables that predict enrollment in a diverse underserved population, we analyzed data from the INGENIOUS (Indiana GENomics Implementation and Opportunity for the UnderServed), pharmacogenomics implementation clinical trial conducted at a community hospital for underserved subjects (Safety net hospital), and a statewide healthcare system (Academic hospital). We used a logistic regression model to identify patient variables that predicted successful enrollment after subjects were contacted and evaluated the reasons that clinical trial eligible subjects refused enrollment. In both healthcare systems, African-Americans were less likely to refuse the study than non-Hispanic Whites (Safety net, OR = 0.68, and p < 0.002; Academic hospital, OR = 0.64, and p < 0.001). At the Safety net hospital, other minorities were more likely to refuse the study than non-Hispanic Whites (OR = 1.58, p < 0.04). The odds of refusing the study once contacted increased with patient age (Safety net hospital, OR = 1.02, p < 0.001, Academic hospital, OR = 1.02, and p < 0.001). At the Academic hospital, females were less likely to refuse the study than males (OR = 0.81, p = 0.01) and those not living in MUA/P's were less likely to refuse the study than those living in MUA/P's (OR = 0.81, p = 0.007). The most frequent barriers to enrollment included not being interested, being too busy, transportation, and illness. A lack of trust was reported less frequently. In conclusion, African-Americans can be readily recruited to pharmacogenetic clinical trials once contact has been successfully initiated. However, health care initiatives and increased recruitment efforts of subjects living in MUA/Ps are needed. Enrollment could be further enhanced by improving research awareness and knowledge of clinical trials, reducing time needed for participation, and compensating for travel.

IGNITE network: Response of patients to genomic medicine interventions

BACKGROUND

The IGNITE network funds six genomic medicine projects. Though interventions varied, we hypothesized that synergies across projects could be leveraged to better understand the participant experiences with genomic medicine interventions. Therefore, we performed cross-network analyses to identify associations between participant demographics and attitudes toward the intervention (attitude), plan to share results (share), and quality of life (QOL).

METHODS

Data collection for demographics, attitude, share, and QOL surveys were standardized across projects. Recruitment and survey administration varied by each project's protocol.

RESULTS

Participants (N = 6,817) were 67.2% (N = 4,584) female, and 37.4% (N = 3,544) were minority. Mean age = 54.0 (sd 14.a). Younger participants were as follows: (1) more positive in attitude pre-intervention (1.15-fold decrease/10-year age increase (OR)) and more negative after (1.14-fold increase OR); (2) higher in QOL pre-intervention (1.07-fold increase OR) and postintervention; (3) more likely to share results (1.12-fold increase OR). Race was significant when sharing results (white participants increased OR = 1.88), but not for change in QOL pre-postintervention or attitude.

CONCLUSION

Our findings demonstrate the feasibility of this approach and identified a few key themes which are as follows: age was consistently significant across the three outcomes, whereas race had less of an impact than expected. However, these are only associations and thus warrant further study.

Drug-gene and drug-drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial

Background: Tramadol and codeine are metabolized by CYP2D6 and are subject to drug-gene and drug-drug interactions. Methods: This interim analysis examined prescribing behavior and efficacy in 102 individuals prescribed tramadol or codeine while receiving pharmaco-genotyping as part of the INGENIOUS trial (NCT02297126). Results: Within 60 days of receiving tramadol or codeine, clinicians more frequently prescribed an alternative opioid in ultrarapid and poor metabolizers (odds ratio: 19.0; 95% CI: 2.8-160.4) as compared with normal or indeterminate metabolizers (p = 0.01). After adjusting the CYP2D6 activity score for drug-drug interactions, uncontrolled pain was reported more frequently in individuals with reduced CYP2D6 activity (odds ratio: 0.50; 95% CI: 0.25-0.94). Conclusion: Phenoconversion for drug-drug and drug-gene interactions is an important consideration in pharmacogenomic implementation; drug-drug interactions may obscure the potential benefits of genotyping.

Opportunities to implement a sustainable genomic medicine program: lessons learned from the IGNITE Network

Purpose

While there is growing scientific evidence for and significant advances in the use of genomic technologies in medicine, there is a significant lag in the clinical adoption and sustainability of genomic medicine. Here we describe the findings from the National Human Genome Research Institute’s (NHGRI) Implementing GeNomics In pracTicE (IGNITE) Network in identifying key constructs, opportunities, and challenges associated with driving sustainability of genomic medicine in clinical practice.

Methods

Network members and affiliates were surveyed to identify key drivers associated with implementing and sustaining a genomic medicine program. Tallied results were used to develop and weigh key constructs/drivers required to support sustainability of genomic medicine programs.

Results

The top three driver–stakeholder dyads were (1) genomic training for providers, (2) genomic clinical decision support (CDS) tools embedded in the electronic health record (EHR), and (3) third party reimbursement for genomic testing.

Conclusion

Priorities may differ depending on healthcare systems when comparing the current state of key drivers versus projected needs for supporting genomic medicine sustainability. Thus we provide gap-filling guidance based on IGNITE members’ experiences. Although results are limited to findings from the IGNITE network, their implementation, scientific, and clinical experience may be used as a road map by others considering implementing genomic medicine programs.

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group

Purpose

Implementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing GeNomics In PracTicE (IGNITE) Network’s efforts to promote: 1) a broader understanding of genomic medicine implementation research; and 2) the sharing of knowledge generated in the network.

Methods

To facilitate this goal the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide their approach to: identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross network analyses.

Results

CMG identified ten high-priority CFIR constructs as important for genomic medicine. Of those, eight didn’t have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.

Conclusion

We developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

Challenges and strategies for implementing genomic services in diverse settings: experiences from the Implementing GeNomics In pracTicE (IGNITE) network

BACKGROUND

To realize potential public health benefits from genetic and genomic innovations, understanding how best to implement the innovations into clinical care is important. The objective of this study was to synthesize data on challenges identified by six diverse projects that are part of a National Human Genome Research Institute (NHGRI)-funded network focused on implementing genomics into practice and strategies to overcome these challenges.

METHODS

We used a multiple-case study approach with each project considered as a case and qualitative methods to elicit and describe themes related to implementation challenges and strategies. We describe challenges and strategies in an implementation framework and typology to enable consistent definitions and cross-case comparisons. Strategies were linked to challenges based on expert review and shared themes.

RESULTS

Three challenges were identified by all six projects, and strategies to address these challenges varied across the projects. One common challenge was to increase the relative priority of integrating genomics within the health system electronic health record (EHR). Four projects used data warehousing techniques to accomplish the integration. The second common challenge was to strengthen clinicians' knowledge and beliefs about genomic medicine. To overcome this challenge, all projects developed educational materials and conducted meetings and outreach focused on genomic education for clinicians. The third challenge was engaging patients in the genomic medicine projects. Strategies to overcome this challenge included use of mass media to spread the word, actively involving patients in implementation (e.g., a patient advisory board), and preparing patients to be active participants in their healthcare decisions.

CONCLUSIONS

This is the first collaborative evaluation focusing on the description of genomic medicine innovations implemented in multiple real-world clinical settings. Findings suggest that strategies to facilitate integration of genomic data within existing EHRs and educate stakeholders about the value of genomic services are considered important for effective implementation. Future work could build on these findings to evaluate which strategies are optimal under what conditions. This information will be useful for guiding translation of discoveries to clinical care, which, in turn, can provide data to inform continual improvement of genomic innovations and their applications.

Lessons Learned When Introducing Pharmacogenomic Panel Testing into Clinical Practice

OBJECTIVES

Implementing new programs to support precision medicine in clinical settings is a complex endeavor. We describe challenges and potential solutions based on the Indiana GENomics Implementation: an Opportunity for the Underserved (INGenious) program at Eskenazi Health-one of six sites supported by the Implementing GeNomics In pracTicE network grant of the National Institutes of Health/National Human Genome Research Institute. INGenious is an implementation of a panel of genomic tests.

METHODS

We conducted a descriptive case study of the implementation of this pharmacogenomics program, which has a wide scope (14 genes, 27 medications) and a diverse population (patients who often have multiple chronic illnesses, in a large urban safety-net hospital and its outpatient clinics).

CHALLENGES

We placed the clinical pharmacogenomics implementation challenges into six categories: patient education and engagement in care decision making; clinician education and changes in standards of care; integration of technology into electronic health record systems; translational and implementation sciences in real-world clinical environments; regulatory and reimbursement considerations, and challenges in measuring outcomes. A cross-cutting theme was the need for careful attention to workflow. Our clinical setting, a safety-net health care system, presented some distinctive challenges. Patients often had multiple chronic illnesses and sometimes were taking more than one pharmacogenomics-relevant medication. Reaching patients for recruitment or follow-up was another challenge.

CONCLUSIONS

New, large-scale endeavors in health care are challenging. A description of the challenges that we encountered and the approaches that we adopted to address them may provide insights for those who implement and study innovations in other health care systems.

Implementation of a pharmacogenomics consult service to support the INGENIOUS trial

Hospital systems increasingly utilize pharmacogenomic testing to inform clinical prescribing. Successful implementation efforts have been modeled at many academic centers. In contrast, this report provides insights into the formation of a pharmacogenomics consultation service at a safety-net hospital, which predominantly serves low-income, uninsured, and vulnerable populations. The report describes the INdiana GENomics Implementation: an Opportunity for the UnderServed (INGENIOUS) trial and addresses concerns of adjudication, credentialing, and funding.

Pharmacogenomically actionable medications in a safety net health care system

Objective:

Prior to implementing a trial to evaluate the economic costs and clinical outcomes of pharmacogenetic testing in a large safety net health care system, we determined the number of patients taking targeted medications and their clinical care encounter sites.

Methods:

Using 1-year electronic medical record data, we evaluated the number of patients who had started one or more of 30 known pharmacogenomically actionable medications and the number of care encounter sites the patients had visited.

Results:

Results showed 7039 unique patients who started one or more of the target medications within a 12-month period with visits to 73 care sites within the system.

Conclusion:

Findings suggest that the type of large-scale, multi-drug, multi-gene approach to pharmacogenetic testing we are planning is widely relevant, and successful implementation will require wide-scale education of prescribers and other personnel involved in medication dispensing and handling.

Prerequisites to implementing a pharmacogenomics program in a large health-care system

Pharmacogenomics (PGx) technology is advancing rapidly; however, clinical adoption is lagging. The Indiana Institute of Personalized Medicine (IIPM) places a strong focus on translating PGx research into clinical practice. We describe what have been found to be the key requirements that must be delivered in order to ensure a successful and enduring PGx implementation within a large health-care system.