The increasing use of population-adjusted indirect comparisons in the NICE Health Technology Assessment (HTA) submission process and the response to these methods

Pooley N, Kisomi M, Embleton N, Langham S. The increasing use of population-adjusted indirect comparisons in the NICE Health Technology Assessment (HTA) submission process and the response to these methods (CO163). Poster presented at ISPOR Europe; 6-9th November 2022; Vienna: Austria, 2022

OBJECTIVES: The use of indirect comparisons to estimate efficacy estimates is established in the NICE HTA process. Network meta-analysis (NMA) allows a comparison to be made between interventions that have been assessed in different clinical trials where common comparators link studies. However, in cases where only single arm trials,  trials with very different populations or non-linking trials are available, alternative statistical approaches such as matching-adjusted treatment comparison (MAIC) and simulated treatment comparison (STC) can be used. We reviewed NICE technology appraisals (TAs) to investigate how the use and acceptance of single arm indirect comparisons has developed over time.

METHODS: NICE technology assessments (TAs) that included a MAIC or STA were identified using the following search terms: matched adjusted, matching adjusted, MAIC, simulated treatment, STC, adjusted indirect. The statistical methods, clinical evidence, assessments and recommendations were extracted and summarised. 

RESULTS: Sixty two TAs were identified: 45 included a MAIC (published 2014–2022), ten an adjusted indirect comparison (published 2006–2019), and seven an STC (published 2015–2021). Use of the MAIC approach has increased over time: Nearly 50% (22/45) were published from 2019 to midway through 2022. MAICs have predominantly been used in oncology HTAs (38/45), often where only phase II single-arm data are available. The response of NICE to the use of MAIC and STCs is dependent upon the individual cases. Where the approach is justified NICE support the use of these methods, whilst acknowledging the inherent uncertainty these approaches bring.

CONCLUSIONS: The NICE Decision Support Unit technical support document on methods for population-adjusted indirect comparisons in submissions highlights the need for standardisation for MAIC and STC approaches. Such standardisation is essential with the increasing use of these methodologies in NICE submissions in situations of data scarcity.