RESUMEN
OBJECTIVES: This study aims to review the National Institute of Health and Care Excellence (NICE) technology assessments to gain insights into the implementation of treatment effect (TE) waning, whereby the hazard or survival in an assessed technology converges to that of the comparator. This analysis aims to contribute to inform future guidance in this area. METHODS: Technology appraisals published October 20, 2021 to September 20, 2023 were reviewed and data extracted on TE waning circumstances, methods, and rationale to compile a database based on 3 research questions: When are TE waning assumptions used? What methods are used? Why have the company/Evidence Assessment Group/committee preferred these methods? RESULTS: Both the evidence assessment group/company and the committee included TE waning assumptions in 28 appraisals. There was no pattern of waning assumptions between shorter (<20 years) and longer (>20 years) time horizons. The most prominent time point for applying waning assumptions was at 5 years, with 30 out of 59 (50.8%) of the methods applied used 5 years. Stopping rules were used in 21 out of 30 (70.1%) of the appraisals for which the committee included waning, and waning assumptions were used more in oncology. The most common reason given for including TE waning assumptions was precedent from prior appraisals. CONCLUSIONS: Considerable heterogeneity existed in both the methods used and justifications given for TE waning assumptions. This variability poses a risk of inconsistent decision making. Reliance on past appraisals emphasizes the necessity to advocate for evidence-driven approaches and underscores the demand for guidance on suitable methods for incorporating assumptions.
RESUMEN
BACKGROUND: Managed Access Agreements (MAAs) are a commercial arrangement that provide patients earlier access to innovative health technologies while uncertainties in the evidence base are resolved through data collection. In the UK, data collection agreements (DCAs) outline the evidence that will be collected during the MAA period and are intended to resolve uncertainties in the clinical- and cost-effectiveness of a technology sufficient for the National Institute of Health and Care Excellence (NICE) committee to make a final decision on reimbursement. OBJECTIVE: The aim of this study was to identify the primary uncertainties leading to a recommendation for entry to the Cancer Drugs Fund (CDF) and evaluate how the corresponding DCAs attempt to address these. METHODS: A database of MAAs agreed within the CDF was compiled with coverage between July 2016 and December 2020 (the time during which evidence generation was routinely collected within the CDF up until the time of analysis). Uncertainties in the evidence base for technologies entering the CDF were analysed alongside the outcomes planned for data collection during the MAA. These data provide an overview of the key uncertainties surrounding health technologies in the CDF on entry and the types of evidence targeted by DCAs. RESULTS: In the assessment of 39 Cancer Drugs Fund (CDF) cases, NICE committees identified a total of 108 key uncertainties in cost-effectiveness estimates. Overall survival was the most commonly identified uncertainty, followed by generalisability of the evidence to the target population. DCAs specified a range of outcomes relevant to understanding the clinical effectiveness of the technology, though fewer than half (43.6%) of the DCAs addressed all the key uncertainties identified by the NICE committee. CONCLUSION: The analysis indicated that data collection within the CDF is not sufficient to resolve all the uncertainties identified by the NICE committee, meaning that other approaches will be needed at re-appraisal to ensure that the NICE committee can reach a final decision on reimbursement.