Assessment of quality of data submitted for NICE technology appraisals over two decades

对过去二十年间提交给NICE技术评估的数据质量进行评估

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Abstract

BACKGROUND: The National Institute for Health and Care Excellence (NICE) pioneered the Health Technology Assessment (HTA) processes and methodologies. Technology appraisals (TAs) focus on pharmaceutical products and clinical and economic data, which are presented by the product manufacturers to the NICE appraisal committee for decision-making. Uncertainty in data reduces the chance of a positive outcome from the HTA process or requires a higher discount. OBJECTIVE: To investigate the quality of clinical data (comparator, quality of life (QoL), randomised controlled trials (RCTs) and overall quality of evidence) submitted by the manufacturers to NICE. DESIGN: This retrospective evaluation analysed active TAs published between 2000 and 2019 (up to TA600). METHODS: For all TAs, we extracted data from the Assessment Group and Evidence Review Group reports and Final Appraisal Determinations on (1) the quality of submitted RCTs and (2) the overall quality of evidence submitted for decision-making. For single TAs, we also extracted data and its critique on QoL and comparators. Each category was scored for quality and analysed using descriptive statistics. RESULTS: 409 TAs were analysed (multiple technology appraisals (MTA)=104, single technology appraisal (STA)=305). In two-thirds of TAs, the overall quality of evidence was either poor (n=224, 55%) or unacceptable (n=41, 10%). In 39% (n=119) of the STAs, the quality of comparative evidence was considered poor, and in 17% (n=51) unacceptable. In 44% (n=135) of STAs, the quality of QoL data was considered poor, 15% (n=47) unacceptable, 33% (n=102) acceptable and 7% (n=21) as good. Over 20 years of longitudinal analysis did not show improvements in the quality of evidence submitted to NICE. CONCLUSION: We found that the primary components of clinical evidence influencing NICE's decision-making framework were of poor quality. It is essential to continue to generate robust clinical data for premarket and postmarket introduction of medicines into clinical practice to ensure they deliver benefits to patients.

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