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Contains fulltext : 294548.pdf (Publisher’s version ) (Open Access), OBJECTIVES: Uncertainty is a fundamental component of decision making regarding access to and pricing and reimbursement of drugs. The context-specific interpretation and mitigation of uncertainty remain major challenges for decision makers. Following the 2021 HTAi Global Policy Forum, a cross-sectoral, interdisciplinary HTAi-DIA Working Group (WG) was initiated to develop guidance to support stakeholder deliberation on the systematic identification and mitigation of uncertainties in the regulatory-HTA interface. METHODS: Six online discussions among WG members (Dec 2021-Sep 2022) who examined the output of a scoping review, two literature-based case studies and a survey; application of the initial guidance to a real-world case study; and two international conference panel discussions. RESULTS: The WG identified key concepts, clustered into twelve building blocks that were collectively perceived to define uncertainty: "unavailable," "inaccurate," "conflicting," "not understandable," "random variation," "information," "prediction," "impact," "risk," "relevance," "context," and "judgment." These were converted into a checklist to explain and define whether any issue constitutes a decision-relevant uncertainty. A taxonomy of domains in which uncertainty may exist within the regulatory-HTA interface was developed to facilitate categorization. The real-world case study was used to demonstrate how the guidance may facilitate deliberation between stakeholders and where additional guidance development may be needed. CONCLUSIONS: The systematic approach taken for the identification of uncertainties in this guidance has the potential to facilitate understanding of uncertainty and its management across different stakeholders involved in drug development and evaluation. This can improve consistency and transparency throughout decision processes. To further support uncertainty management, linkage to suitable mitigation strategies is necessary.

Deterministic sensitivity analyses (DSA) remain important to interpret the effect of uncertainties in individual parameters on results of cost-effectiveness analyses. Classic DSA methodologies may lead to wrong conclusions due to a lack of or misleading information regarding marginal effects, non-linearity, likelihood and correlations. In addition, tornado diagrams are misleading in some situations. Recent advances in DSA methods have the potential to provide decision makers with more reliable information regarding the effects of uncertainties in individual parameters. This practical application discusses advances to classic DSA methods and their implications. Three methods are discussed: stepwise DSA, distributional DSA and probabilistic DSA. For each method, the technical specifications, options for presenting results, and its implications for decision making are discussed. Options for visualizing DSA results in incremental cost-effectiveness ratios and in incremental net benefits are presented. The use of stepwise DSA increases interpretability of marginal effects and non-linearities in the model, which is especially relevant when arbitrary ranges are implemented. Using the probability distribution of each parameter in distributional DSA provides insight on the likelihood of model outcomes while probabilistic DSA also includes the effects of correlations between parameters. Probabilistic DSA, preferably expressed in incremental net benefit, is the most appropriate method for providing insight on the effect of uncertainty in individual parameters on the estimate of cost effectiveness. However, the opportunities provided by probabilistic DSA may not always be needed for decision making. Other DSA methods, in particular distributional DSA, can sometimes be sufficient depending on model features. Decision makers must determine to which extent they will accept and implement these new and improved DSA methodologies and adjust guidelines accordingly.

BACKGROUND: Conditional financing (CF) of expensive hospital drugs was applied in the Netherlands between 2006 and 2012; a 4-year coverage with evidence development (CED) framework for expensive hospital drugs. This study aims to evaluate the CF framework, focusing on Health Technology Assessment (HTA) procedures.METHODS: Using a standardised data extraction form, researchers independently extracted information on procedural, methodological and decision-making aspects from HTA reports of drugs selected for CF.RESULTS: Forty-nine drugs were chosen for CF, of which 12 underwent the full procedure. The procedure extended beyond the envisioned 4 years period for 11/12 drugs. Outcomes research studies conducted as part of CF provided insufficient scientific data to reach conclusions on appropriate use and cost-effectiveness of 5/12 drugs. After re-assessment, continuation of reimbursement was advised for 10/12 drugs, with 6 necessitating yet additional conditions for evidence generation. Notably, advice to discontinue reimbursement for 2/12 drugs has not yet been implemented in Dutch healthcare practice.CONCLUSIONS: Theoretically, CF provided an option for quick but conditional access to drugs. However, numerous aspects related to the design and implementation of CF negatively affected its value in practice. Future CED schemes should aim to incorporate learnings from the CF example to increase their impact in healthcare practice.

Objectives: The objective of this study was to construct an early economic evaluation for acalabrutinib for relapsed chronic lymphocytic leukaemia (CLL) to assist early reimbursement decision making. Scenarios were assessed to find the relative impact of critical parameters on incremental costs and quality-adjusted life-years (QALYs). Methods: A partitioned survival model was constructed comparing acalabrutinib and ibrutinib from a UK national health service perspective. This model included states for progression-free survival (PFS), post-progression survival (PPS) and death. PFS and overall survival (OS) were parametrically extrapolated from ibrutinib publications and a preliminary hazard ratio based on phase I/II data was applied for acalabrutinib. Deterministic and probabilistic sensitivity analyses were performed, and 1296 scenarios were assessed. Results: The base-case incr

Objectives: Reimbursement decisions are conventionally based on evidence from randomised controlled trials (RCTs) which often have high internal validity but low external validity. Real-world data (RWD) may provide complimentary evidence for relative effectiveness assessments (REAs) and cost-effectiveness assessments (CEAs). This study examines whether RWD is incorporated in Health Technology Assessment (HTA) of melanoma drugs by European HTA agencies, differences in RWD use between agencies and across time. Methods: HTA reports published between 01.01.2011 and 31.12.2016 were retrieved from websites of agencies representing 5 jurisdictions: England (NICE), Scotland (SMC), France (HAS), Germany (IQWiG) and the Netherlands (ZIN). A standardized data-extraction form was used to extract information on RWD inclusion for both REAs and CEAs. A panel of senior HTA assessors representing the 5 agencies was consulted to check the robustness of data extracted and interpretation. Results: Fifty-two reports were retrieved. All 52 reports contained REAs; CEAs were present in 25. RWD was included in 28 of 52 REAs (54%); mainly to estimate melanoma prevalence. RWD was included in 22 of 25 (88%) of CEAs; mainly to extrapolate long-term effectiveness and/or identify drug-related costs drugs. Differences emerged between agencies regarding RWD use in REAs; ZIN and IQWiG cited RWD for evidence on prevalence whereas NICE, SMC and HAS additionally cited RWD use for drug effectiveness. No visible trend for RWD use in REAs and CEAs over time was observed. Conclusions: In general, RWD inclusion was higher in CEAs than REAs. It was mostly used to estimate melanoma prevalence in REAs or to predict long-term effectiveness in CEAs. Differences emerged between agencies' use of RWD. However, no visible trends for RWD use over time were observed. Future research should explore the use of RWD in HTA of drugs in other disease indications and in conditional reimbursement schemes.