Literature DB >> 27320024

How real-world data compensate for scarce evidence in HTA.

Elisabeth George1.   

Abstract

Most guidance developed by NICE is based on a value assessment using clearly articulated and published clinical and cost effectiveness criteria. In order to enable consistency and fairness across all decisions, NICE uses as a unit of health benefit the quality-adjusted life year (QALY). Both QALYs and costs for a technology are estimated by long-term disease modelling. This requires a variety of clinical input parameters, and often extrapolation beyond the trial period, and of intermediate or surrogate to final outcomes. RCT data will remain the main data source for the majority of appraisals, but because the data necessary for disease modelling is often not available from RCTs, particularly for the UK context, the use of non-RCT data is the norm in NICE technology appraisals. This does not only apply to data on resource use, service provision and HRQL data, but also to efficacy data. In some situations non-RCT data are more relevant to a decision context than the RCT data, and in some situations, as illustrated by 3 examples, it would be unreasonable, not to take account of existing non-RCT data. The use of non-RCT clinical evidence is most common for devices, interventions where RCTs are difficult, and in conditions with poor prognosis where single arm studies are often carried out. Therefore, a pragmatic approach to the available evidence is needed for many decision made by the NICE Appraisal Committees to come to a reasonable and defendable decision.
Copyright © 2016. Published by Elsevier GmbH.

Entities:  

Keywords:  Extrapolation von Studiendaten; Langzeitkrankheitsmodelle; NHS-based observational studies; NHS-basierte Beobachtungsstudien; Nutzenbewertung; Value assessment; extrapolation of trial data; long-term disease modelling

Mesh:

Year:  2016        PMID: 27320024     DOI: 10.1016/j.zefq.2016.04.012

Source DB:  PubMed          Journal:  Z Evid Fortbild Qual Gesundhwes        ISSN: 1865-9217


  1 in total

1.  Identification and Mapping Real-World Data Sources for Heart Failure, Acute Coronary Syndrome, and Atrial Fibrillation.

Authors:  Rachel Studer; Claudio Sartini; Kiliana Suzart-Woischnik; Rumjhum Agrawal; Harshul Natani; Simrat K Gill; Sara Bruce Wirta; Folkert W Asselbergs; Richard Dobson; Spiros Denaxas; Dipak Kotecha
Journal:  Cardiology       Date:  2021-11-15       Impact factor: 1.869

  1 in total

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