Time to Align: A Call for Consensus on the Assessment of Genetic Testing

A scoping review of the assessment reports of genetic or genomic tests reveals inconsistent consideration of key dimensions of clinical utility

OBJECTIVES

Genetic and genomic tests are the cornerstone of personalized preventive approaches. Inconsistency in evaluating their clinical utility is often cited as a reason for their limited implementation in clinical practice. Previous reviews have primarily focused on theoretical frameworks used for clinical utility evaluations of genetic tests, rather than actual assessments and examined dimensions, rather than specific indicators within these dimensions. We aimed to review the dimensions and the specific indicators measured in published assessment reports of genetic or genomic tests.

STUDY DESIGN AND SETTING

We conducted a scoping review of assessment reports of genetic and genomic tests used for prevention, searching through PubMed, Web of Science, Scopus, the websites of 20 different organizations, Google, and Google Scholar. From the included assessments, we extracted the reported indicators of clinical utility, compiling a list of disease-specific indicators that detailed their numerator, denominator, and calculation methods. We analyzed the extracted indicators by stratifying them according to ten comprehensive dimensions of clinical utility, the assessment framework used, and the type of indicator (categorized as quantitative, qualitative, reference, or no evidence reported). From these indicators, we then distilled a list of general indicators.

RESULTS

We reviewed 3054 unique references and 12,000 results from gray literature searches, ultimately selecting 57 assessment reports. The reference frameworks used were health technology assessment (HTA) (42%), Evaluation of Genomic Applications in Practice and Prevention (EGAPP) (25%), ACCE (21%), and others (12%). We identified 951 disease-specific indicators. The dimensions most frequently evaluated (ie, had at least one indicator) were analytic validity (60%), clinical validity (79%), clinical efficacy (79%), and economic impact (58%). Only 12 assessments compared health outcomes between tested and untested groups, and fewer than 15% of the assessments addressed equity, acceptability, legitimacy, and personal value.

CONCLUSION

Our study illustrates that, although dimensions such as equity and acceptability, are significantly emphasized in traditional evaluation frameworks, these are often not considered in the assessments. Additionally, our study has underscored a significant dearth of reported primary evidence concerning the clinical efficacy of these tests.

PLAIN LANGUAGE SUMMARY

Genetic and genomic tests analyze a person's genes to predict health risks and guide healthcare decisions, potentially identifying who might benefit from certain treatments or check-ups. However, determining whether these tests are genuinely useful for wide use in health services is complex, because there is no standard way to define "clinical utility" of a genetic test. To understand how these tests are evaluated, we reviewed 57 evaluation reports from high-income countries, most of which focused on cancer-related genetic tests. We found that many evaluations looked mainly at how well a test predicted a condition (validity) and considered some form of effectiveness, yet often failed to measure whether the test truly improved patient health outcomes, such as lowering death rates or enhancing the quality of life. Moreover, factors like patient acceptance, equity, and personal relevance (eg, reducing anxiety) were frequently overlooked. Without including these broader considerations, evaluations risk missing critical evidence that would indicate whether a test is helpful, fair, and worth using. From over 900 unique indicators used to measure clinical utility, we created a simpler list of about 150 general indicators that can guide future evaluations. This consolidated list can help test developers decide which factors to investigate, evaluators determine what to measure, and policymakers identify what might be missing before deciding if a test should be adopted in healthcare. By highlighting the gaps-areas that should be assessed but currently are not-our study encourages a more comprehensive approach to evaluating genetic tests. If we fail to consider issues like equity, patient preferences, and proven health benefits, we risk investing in tests that may do little good or even harm patients. Ultimately, recognizing these shortcomings can lead to better-informed decisions, ensuring that genetic testing is used in ways that truly benefit patients and deliver safer, more personalized, and fairer healthcare for everyone.

The current stage of Italy in the implementation of genomics into the National Healthcare System: an application of the B1MG maturity level model

Introduction

Genomics holds significant promise for prevention and clinical care yet integrating it into the national healthcare system (NHS) requires considerable system-wide changes. This study assessed the current stage of Italy in the use of genomics, to map critical areas for improvement and contribute to a strategic plan.

Methods

A total of 18 experts rated individually the level of maturity of the Italian NHS on a scale from 1 (lowest) to 5 (highest) using the B1MG Maturity Level Model tool. This instrument is an European matrix of 49 indicators grouped into eight domains: governance, economic aspects, ethics and legislation, public awareness, workforce skills, clinical organization, clinical guidelines, and data infrastructure. Consensus procedures were performed within each domain to finally agree on one maturity level per indicator.

Results

Despite a few national initiatives, Italy shows a local level of implementation in most indicators. Genomic medicine is considered a priority, but still lacks an updated strategy and investment plans. A higher maturity is reached for ethical and legal aspects, but there is a strong need to invest in workforce training, citizen engagement and literacy, and large-scale adoption of tools and novel technologies. Infrastructures and guidelines to improve data storage, management, analysis, interpretation, and sharing are not yet widespread available.

Discussion

Italy is at the beginning of its journey towards a sustainable implementation of genomics. An updated national strategy with coordinated actions and investment plans is needed to make progress in key areas, including personnel education, public engagement, technical infrastructure, and clinical organization.

Managing the introduction of genomic applications into the National Health Service: A special challenge for health technology assessment in Italy

In recent years, the rapid proliferation of genomic tests for use in clinical practice has prompted healthcare systems to use a health technology assessment (HTA) approach to distinguish valuable from unwarranted applications. In this study, we narratively review the Italian HTA mechanisms for medical devices (MDs), both at the national and regional levels, and discuss the opportunity and benefits of extending them to genomic technologies, for which a dedicated assessment path was advocated by the National Plan for Public Health Genomics in 2017. We found that the National Health Technology Assessment Program for MDs, completed in 2019, had developed a structured pathway for the HTA of MDs; it established a hub-and-spoke structure, run by a governmental institution, and put in place transparent methodological procedures to cover all four HTA phases (i.e., proposal and prioritization, assessment, appraisal, and dissemination). However, several factors have hindered its adoption, and the regions are at different stages of its implementation. For these reasons, efforts should be made to ensure its effective deployment, both at national and regional levels. In addition, we argue that to harmonize the institutional roles and methodological procedures adopted, the time has come to concentrate resources on a single pathway for the assessment of all technologies that include both MDs and genomic applications.