Can You Have a Common Approach to the Statistical Analysis Plan When Conducting Real-World Evidence Studies to Meet Multi-HTA Requirements?
Author(s)
Paparrodopoulos S1, Kolovos S1, Gaultney J2
1IQVIA, Athens, Greece, 2IQVIA, London, UK
Presentation Documents
OBJECTIVES: The UK’s National Institute for Health and Care Excellence (NICE) and the French Haute Autorité de Santé (HAS) formalised their requirements for real-world evidence (RWE) studies to support HTA. We reviewed the statistical methods requested by NICE and HAS in these guidelines to assess whether a common statistical analysis plan (SAP) would be feasible. METHODS: The NICE RWE Framework published in June 2022 and the HAS RWE Methodological Guideline published in June 2021 were reviewed and compared, focusing on the statistical methods for addressing confounding bias, information bias, and selection bias. RESULTS: Both guidelines include methods for addressing confounding bias, information bias is covered in more detail in NICE guideline compared to HAS, and selection bias is addressed by both. Both guidelines propose methods for observed confounding, including ‘G-methods’, instrumental methods, and propensity score matching. NICE addresses residual confounding, using negative controls. For addressing information bias, both guidelines propose sensitivity analysis, but NICE also provides more guidance for imputation techniques compared to HAS. For selection bias, HAS suggest consecutive inclusion of patients and sensitivity analysis, whereas NICE highlights the importance of the ‘target trial approach’. CONCLUSIONS: A common SAP might be feasible as there is some alignment in the analytical methods requested by NICE and HAS in terms of approaches to address confounding, potentially allowing for an RWE study to be transferable between the two. Some methods requested by NICE are not requested by HAS and vice versa, and neither NICE nor HAS are prescriptive for all typical SAP requirements. Uncertainty therefore remains whether the methods requested for one would be acceptable to the other. As the need for RWE to fill important HTA evidence gaps increases, so does the need for prescriptive, transparent guidelines and alignment across HTA bodies to maximise the acceptability and utility of RWE studies.
Conference/Value in Health Info
2023-11, ISPOR Europe 2023, Copenhagen, Denmark
Value in Health, Volume 26, Issue 11, S2 (December 2023)
Code
HTA124
Topic
Health Technology Assessment, Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference, Decision & Deliberative Processes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas