Autor(es):
Pezzullo, Angelo Maria ; Gris, Angelica Valz ; Scarsi, Nicolò ; Tona, Diego Maria ; Porcelli, Martina ; Di Pumpo, Matteo ; Piko, Peter ; Adany, Roza ; Kannan, Pragathy ; Perola, Markus ; Cardoso, Maria Luis ; Costa, Alexandra ; Vicente, Astrid M. ; Reigo, Anu ; Vaht, Mariliis ; Metspalu, Andres ; Kroese, Mark ; Pastorino, Roberta ; Boccia, Stefania
Data: 2025
Identificador Persistente: http://hdl.handle.net/10400.18/10570
Origem: Repositório Científico do Instituto Nacional de Saúde
Assunto(s): Clinical Utility; Genetic Testing; Genomics; Health Technology Assessment; Personalized Prevention; Precision Medicine; Scoping Review; Precision Medicine; Medicina Personalizada
Descrição
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.
Highlights: - Few genetic test evaluations measure personal value, equity, and acceptability; - Genetic test evaluations rarely include evidence that show direct clinical efficacy; - We offer a catalog of indicators used for test evaluations.
