A Multi-Disciplinary Team Approach to Genomic Testing for Drug-Resistant Epilepsy Patients—The GENIE Study

It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine

Health care is at a turning point. We are shifting from protocolized medicine to precision medicine, and digital health systems are facilitating this shift. By providing clinicians with detailed information for each patient and analytic support for decision-making at the point of care, digital health technologies are enabling a new era of precision medicine. Genomic data also provide clinicians with information that can improve the accuracy and timeliness of diagnosis, optimize prescribing, and target risk reduction strategies, all of which are key elements for precision medicine. However, genomic data are predominantly seen as diagnostic information and are not routinely integrated into the clinical workflows of electronic medical records. The use of genomic data holds significant potential for precision medicine; however, as genomic data are fundamentally different from the information collected during routine practice, special considerations are needed to use this information in a digital health setting. This paper outlines the potential of genomic data integration with electronic records, and how these data can enable precision medicine.

Accessibility, availability and common practices regarding genetic testing for epilepsy across Europe: A survey of the European Reference Network EpiCARE

OBJECTIVE

The increasingly rapid pace of advancement in genetic testing may lead to inequalities in technical and human resources with a negative impact on optimal epilepsy clinical practice. In this view, the European Reference Network (ERN) for Rare and Complex Epilepsies EpiCARE conducted a survey addressing several aspects of accessibility, availability, costs, and standard practices on genetic testing across ERN EpiCARE centers.

METHODS

An online Google form was sent to 70 representatives of ERN EpiCARE centers. Descriptive statistics and qualitative analysis were used for data presentation.

RESULTS

We received 45 responses (1/center) representing 23 European countries with a better representation of Western Europe. Forty-five percent of the centers did not have access to all available types of genetic testing, mainly reflecting the limited availability of whole-genome sequencing (WGS). Thirty-five percent of centers report cost coverage only for some of the available tests, while costs per test varied significantly (interquartile range IQR ranging from 150 to 1173 euros per test across centers). Urgent genetic testing is available in 71.7% of countries (time-to-urgent result: 2 day to 2 months). The average time-to-result of specific tests in case of non-urgent prescription has a significant variance across centers, with the biggest range observed for whole-exome sequencing (6-128 weeks, IQR: 27 weeks). The percentage of agreement among the experts regarding the choice of genetic test at first intention in specific clinical situations was in all cases less than 50 percent (34.9% to 47% according to the proposed scenarios).

SIGNIFICANCE

Costs, time to deliver the results to the clinician, and type of first-line genetic testing vary widely across Europe, even in countries where ERN EpiCARE centers are present. Increased availability of genetic tests and guidance for optimal test choices in epilepsy remains essential to avoid diagnostic delays and excess health costs.

PLAIN LANGUAGE SUMMARY

The survey of the ERN EpiCARE highlights disparities in genetic testing for epilepsy across 45 ERN EpiCARE centers in 23 European countries. The findings reveal variable access to certain genetic tests, with lowest access to WGS. Costs and time-to-results vary widely. Urgent genetic testing is available in 71.7% of countries. Agreement among experts on first-line genetic tests for specific patient scenarios is below 50%. The study emphasizes the need for improved test availability and guidance to avoid diagnostic delays and unnecessary costs. EpiCARE has the mission to contribute in homogenizing best practices across Europe.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

What is the power of a genomic multidisciplinary team approach? A systematic review of implementation and sustainability

Due to the increasing complexity of genomic data interpretation, and need for close collaboration with clinical, laboratory, and research expertise, genomics often requires a multidisciplinary team (MDT) approach. This systematic review aims to establish the evidence for effectiveness of the genomic multidisciplinary team, and the implementation components of this model that can inform precision care. MEDLINE, Embase and PsycINFO databases were searched in 2022 and 2023. We included qualitative and quantitative studies of the genomic MDT, including observational and cohort studies, for diagnosis and management, and implementation outcomes of effectiveness, adoption, efficiency, safety, and acceptability. A narrative synthesis was mapped against the Genomic Medicine Integrative Research framework. 1530 studies were screened, and 17 papers met selection criteria. All studies pointed towards the effectiveness of the genomic MDT approach, with 10-78% diagnostic yield depending on clinical context, and an increased yield of 6-25% attributed to the MDT. The genomic MDT was found to be highly efficient in interpretation of variants of uncertain significance, timeliness for a rapid result, made a significant impact on management, and was acceptable for adoption by a wide variety of subspecialists. Only one study utilized an implementation science based approach. The genomic MDT approach appears to be highly effective and efficient, facilitating higher diagnostic rates and improved patient management. However, key gaps remain in health systems readiness for this collaborative model, and there is a lack of implementation science based research especially addressing the cost, sustainability, scale up, and equity of access.

Early cost-utility analysis of genetically guided therapy for patients with drug-resistant epilepsy

OBJECTIVE

Existing gene panels were developed to understand the etiology of epilepsy, and further benefits will arise from an effective pharmacogenomics panel for personalizing therapy and achieving seizure control. Our study assessed the cost-effectiveness of a pharmacogenomics panel for patients with drug-resistant epilepsy, compared with usual care.

METHODS

A cost-utility analysis was employed using a discrete event simulation model. The microsimulation model aggregated the costs and benefits of genetically guided treatment versus usual care for 5000 simulated patients. The 10-year model combined data from various sources including genomic databases on prevalence of variants, population-level pharmaceutical claims on antiseizure medications, published long-term therapy retention rates, patient-level cost data, and systematic reviews. Incremental cost per quality-adjusted life-year (QALY) gained was computed. Deterministic and probabilistic sensitivity analyses were undertaken to address uncertainty in model parameters.

RESULTS

The mean cost of the genetically guided treatment option was AU$98 199 compared with AU$95 386 for usual care. Corresponding mean QALYs were 4.67 compared with 4.28 for genetically guided and usual care strategies, respectively. The incremental cost per QALY gained was AU$7381. In probabilistic sensitivity analyses, the incremental cost per QALY gained was AU$6321 (95% uncertainty interval = AU$3604-AU$9621), with a 100% likelihood of being cost-effective in the Australian health care system. The most influential drivers of the findings were the monthly health care costs associated with reduced seizures, costs when seizures continued, and the quality-of-life estimates under genetically guided and usual care strategies.

SIGNIFICANCE

This early economic evaluation of a pharmacogenomics panel to guide treatment for drug-resistant epilepsy could potentially be cost-effective in the Australian health care system. Clinical trial evidence is necessary to confirm these findings.

Gene panel to guide antiseizure medication prescribing: Does the cost justify the benefits?

Pharmacogenomics hold the potential to identify variants associated with adverse drug reactions and treatment efficacy of anti-seizure medications. A model-based cost-utility analysis by Gordon and colleagues showed that genetically-guided therapy costs more, yielded higher quality-adjusted life years outcomes, and was considered to be cost-effective compared to usual care. The study provided preliminary evidence on the value of pharmacogenetic testing in patients with drug-resistant epilepsy. However, data input for the model was based on assumptions that need to be empirically tested. Further, there are many other factors that may affect the cost-effectiveness of pharmacogenetic testing that need to be considered, including the model of service delivery, its implementation in complex clinical service, whether clinicians will modify treatment decisions based on pharmacogenetic information, and the fidelity with which recommendation on testing is adhered to in the real-world. The cost-effectiveness analysis should be repeated when more robust data on the effectiveness of pharmacogenetics are available and conducted alongside a budget impact analysis, incorporating the direct health care resources required to implement widespread testing and potential subsequent changes in treatment.