Literature DB >> 35245972

Health Technology Assessment to assess value of biomarkers in the decision-making process.

Simona Ferraro1, Elia Mario Biganzoli2, Silvana Castaldi3,4, Mario Plebani5.   

Abstract

Clinical practice guidelines (CPGs) on screening, surveillance, and treatment of several diseases recommend the selective use of biomarkers with central role in clinical decision-making and move towards including patients in this process. To this aim we will clarify the multidisciplinary interactions required to properly measure the cost-effectiveness of biomarkers with regard to the risk-benefit of the patients and how Health Technology Assessment (HTA) approach may assess value of biomarkers integrated within the decision-making process. HTA through the interaction of different skills provides high-quality research information on the effectiveness, costs, and impact of health technologies, including biomarkers. The biostatistical methodology is relevant to HTA but only meta-analysis is covered in depth, whereas proper approaches are needed to estimate the benefit-risk balance ratio. Several biomarkers underwent HTA evaluation and the final reports have pragmatically addressed: 1) a redesign of the screening based on biomarker; 2) a de-implementation/replacement of the test in clinical practice; 3) a selection of biomarkers with potential predictive ability and prognostic value; and 4) a stronger monitoring of the appropriateness of test request. The COVID-19 pandemic has disclosed the need to create a robust and sustainable system to urgently deal with global health concerns and the HTA methodology enables rapid cost-effective implementation of diagnostic tests allowing healthcare providers to make critical patient-management decisions.
© 2022 Simona Ferraro et al., published by De Gruyter, Berlin/Boston.

Entities:  

Keywords:  biomarker; biostatistics; cost-effectiveness; healthcare; statistical model

Mesh:

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Year:  2022        PMID: 35245972     DOI: 10.1515/cclm-2021-1291

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  1 in total

1.  Comprehensive analysis of nine m7G-related lncRNAs as prognosis factors in tumor immune microenvironment of hepatocellular carcinoma and experimental validation.

Authors:  Tao Wang; Zhijia Zhou; Xuan Wang; Liping You; Wenxuan Li; Chao Zheng; Jinghao Zhang; Lingtai Wang; Xiaoni Kong; Yueqiu Gao; Xuehua Sun
Journal:  Front Genet       Date:  2022-08-23       Impact factor: 4.772

  1 in total

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