Literature DB >> 30136642

EVIDENCE REQUIRED BY HEALTH TECHNOLGY ASSESSMENT AND REIMBURSEMENT BODIES EVALUATING DIAGNOSTIC OR PROGNOSTIC ALGORITHMS THAT INCLUDE OMICS DATA.

Alexandre Barna1, Teresita M Cruz-Sanchez2, Karen Berg Brigham2, Cong-Tri Thuong3, Finn Boerlum Kristensen4, Isabelle Durand-Zaleski2.   

Abstract

OBJECTIVES: Multi-analyte assays with algorithmic analyses (MAAAs) use combinations of circulating and clinical markers including omics-based sources for diagnostic and/or prognostic purposes. Assessing MAAAs is challenging under existing health technology assessment (HTA) methods or practices. We undertook a scoping review to explore the HTA methods used for MAAAs to identify the criteria used for clinical research and reimbursement purposes.
METHODS: This review included only non-companion (stand-alone) tests that are actionable and that have been evaluated by leading HTA or insurer/reimbursement bodies up to September 2017.
RESULTS: Twenty-five reports and articles evaluating seventeen MAAAs were examined, most of which have been developed in oncology. The two main models used were the EUnetHTA Core model and the Evaluation of Genomic Applications in Practice and Prevention ACCE framework. Clinical validity and utility criteria were used, as were economic, ethical, legal, and social aspects. Economic evidence on MAAAs was scarce, and there is no consensus on whether the perspectives used are sufficiently broad to include all relevant stakeholders.
CONCLUSIONS: Clinical utility and efficiency were the most used criteria, with stronger evidence needed linking the use of the algorithm with the clinical outcomes in real-life practice. HTA bodies must as well consider questions related to the analytical validity of MAAAs or with organizational aspects. The two main models, the EUnetHTA Core model and the ACCE framework, could be adapted to the assessment of MAAAs.

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Keywords:  Assessment and regulation; Biomarkers; Personalized medicine; Reimbursement policy

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Year:  2018        PMID: 30136642     DOI: 10.1017/S026646231800048X

Source DB:  PubMed          Journal:  Int J Technol Assess Health Care        ISSN: 0266-4623            Impact factor:   2.188


  2 in total

1.  Early-stage economic analysis of research-based comprehensive genomic sequencing for advanced cancer care.

Authors:  Deirdre Weymann; Janessa Laskin; Steven J M Jones; Robyn Roscoe; Howard J Lim; Daniel J Renouf; Kasmintan A Schrader; Sophie Sun; Stephen Yip; Marco A Marra; Dean A Regier
Journal:  J Community Genet       Date:  2021-11-29

Review 2.  Precision Oncology-The Quest for Evidence.

Authors:  Theodoros G Soldatos; Sajo Kaduthanam; David B Jackson
Journal:  J Pers Med       Date:  2019-09-05
  2 in total

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