METHODOLOGICAL DIVERGENCE AND POLICY IMPACT OF HTAS FOR IMMUNE CHECKPOINT INHIBITORS IN NSCLC
Author(s)
Nai-Chia Chen, MS1, Ash Bullement, BSc, MSc2, Antal Tamas Zemplenyi, MSc, PhD1, Cindy L. OBryant, PharmD, BCOP, FCCP, FHOPA1, Alex M. Kaizer, PhD3, Kelly E. Anderson, PhD4, Robert Brett McQueen, BA, MA, PhD1.
1University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA, 2Petauri, Nottingham, United Kingdom, 3University of Colorado Anschutz Medical Campus, Colorado School of Public Health, Aurora, CO, USA, 4Brigham and Women’s Hospital and Harvard Medical School, Program on Regulation, Therapeutics, and Law (PORTAL), Boston, MA, USA.
1University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA, 2Petauri, Nottingham, United Kingdom, 3University of Colorado Anschutz Medical Campus, Colorado School of Public Health, Aurora, CO, USA, 4Brigham and Women’s Hospital and Harvard Medical School, Program on Regulation, Therapeutics, and Law (PORTAL), Boston, MA, USA.
OBJECTIVES: Immune checkpoint inhibitors (ICIs) present methodological challenges for health technology assessment (HTA), as it is difficult to adequately capture their mechanism of action and long-term outcomes when HTA submissions rely on immature data. This study aimed to characterize methodological convergence and divergence between the National Institute for Health and Care Excellence (NICE) and Canada’s Drug Agency (CDA) in the assessment of ICIs for non-small-cell lung cancer (NSCLC).
METHODS: A total of 34 published technology appraisals from NICE and CDA were reviewed using a pre-specified, systematic approach. Data extracted from each appraisal included characteristics of the referenced randomized clinical trials, the chosen comparators, cost-effectiveness conclusions, and details regarding modeling settings and assumptions, including but not limited to: modeling methods, time horizon, utility values, survival extrapolations, treatment duration, effect waning, and cure.
RESULTS: The overall concordance for cost-effectiveness conclusions was 53.33%, with NICE issuing positive conclusions more frequently (83.33%) than CDA (41.18%). Notable inconsistencies in process and methodological inputs were identified, highlighting divergence between NICE and CDA as well as differences in assessments undertaken within each agency, including comparator selection, reimbursement request populations, and modeling assumptions. Modeling of treatment-effect waning shifted from abrupt loss of effect assumptions to more nuanced models reflecting gradual decline, while the assumed extension of continued effect beyond this point often varied between agencies and appraisals due to differences in data maturity. NICE appeared to prioritize technical accuracy in cost-effectiveness estimates, whereas CDA appeared to adopt a more pragmatic approach emphasizing drug wastage and time horizon for budget impact.
CONCLUSIONS: Differences in NICE and CDA reimbursement decisions for ICIs used to treat populations with NSCLC appear to stem from systematic methodological and procedural differences, rather than purely economic considerations, highlighting the influence of evidence standards, uncertainty handling, and procedural scope on final recommendations.
METHODS: A total of 34 published technology appraisals from NICE and CDA were reviewed using a pre-specified, systematic approach. Data extracted from each appraisal included characteristics of the referenced randomized clinical trials, the chosen comparators, cost-effectiveness conclusions, and details regarding modeling settings and assumptions, including but not limited to: modeling methods, time horizon, utility values, survival extrapolations, treatment duration, effect waning, and cure.
RESULTS: The overall concordance for cost-effectiveness conclusions was 53.33%, with NICE issuing positive conclusions more frequently (83.33%) than CDA (41.18%). Notable inconsistencies in process and methodological inputs were identified, highlighting divergence between NICE and CDA as well as differences in assessments undertaken within each agency, including comparator selection, reimbursement request populations, and modeling assumptions. Modeling of treatment-effect waning shifted from abrupt loss of effect assumptions to more nuanced models reflecting gradual decline, while the assumed extension of continued effect beyond this point often varied between agencies and appraisals due to differences in data maturity. NICE appeared to prioritize technical accuracy in cost-effectiveness estimates, whereas CDA appeared to adopt a more pragmatic approach emphasizing drug wastage and time horizon for budget impact.
CONCLUSIONS: Differences in NICE and CDA reimbursement decisions for ICIs used to treat populations with NSCLC appear to stem from systematic methodological and procedural differences, rather than purely economic considerations, highlighting the influence of evidence standards, uncertainty handling, and procedural scope on final recommendations.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
HTA10
Topic
Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
SDC: Oncology