TY - JOUR
T1 - A hierarchical and configurational analysis of Health Technology Assessment outcomes for cell and gene therapies
AU - Almalki, Ziyad S.
AU - Alshammari, Renad M.
AU - Dahduli, Nadia A.
AU - Nagi, Mouaddh Abdulmalik
AU - Juweria, Syeda
AU - Alhamdani, Moayad M.
AU - Alzahrani, Yazan M.
AU - Almazrou, Saja H.
AU - Ahmed, Nehad Jaser
AU - Alahmari, Abdullah K.
AU - Alshlowi, Areej A.
N1 - Publisher Copyright:
Copyright © 2025 Almalki, Alshammari, Dahduli, Nagi, Juweria, Alhamdani, Alzahrani, Almazrou, Ahmed, Alahmari and Alshlowi.
PY - 2025
Y1 - 2025
N2 - Background: Cell and gene therapies (CGTs) challenge traditional Health Technology Assessment (HTA), creating a fragmented global access landscape. This study identifies the determinants of CGT reimbursement outcomes by quantifying the influence of key variables and identifying the configurations leading to a positive recommendation. Methods: A dual-methodology approach was employed. We constructed a comprehensive dataset of all HTA decisions for CGTs across seven major jurisdictions between January 2017 and July 2025. Hierarchical Linear Modeling (HLM) was used to identify independent predictors of HTA outcomes, and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) was used to identify sufficient pathways to success. Novel composite indicators were developed to measure system-level adaptability and the influence of patient advocacy groups (PAGs). Results: The HLM analysis, accounting for data clustering (Intraclass Correlation Coefficients (ICCs): 42% country-level, 24% agency-level variance), confirmed that strong clinical efficacy (Coef. = 0.40), high unmet need, and disease rarity were significant positive predictors. High therapy cost was a powerful negative predictor (Coef. = −0.29 per $1M USD). Crucially, high System Adaptability (Coef. = 0.35) and strong PAG Influence (Coef. = 0.28) emerged as major positive determinants. The fsQCA revealed three distinct pathways to a positive recommendation with high consistency: a “Transformative Value” path (consistency: 0.93), a “Strategic Mitigation” path (consistency: 0.90), and an “Economic Dominance” path (consistency: 0.94). The overall QCA solution explained a majority of positive outcomes (solution coverage: 0.68). Conclusion: HTA success for CGTs is not determined by isolated attributes but by the strategic alignment of therapy-level evidence, agency-level processes, and country-level context. The influence of organized patient advocacy and the structural flexibility of HTA systems are critical, previously under-quantified components of this alignment.
AB - Background: Cell and gene therapies (CGTs) challenge traditional Health Technology Assessment (HTA), creating a fragmented global access landscape. This study identifies the determinants of CGT reimbursement outcomes by quantifying the influence of key variables and identifying the configurations leading to a positive recommendation. Methods: A dual-methodology approach was employed. We constructed a comprehensive dataset of all HTA decisions for CGTs across seven major jurisdictions between January 2017 and July 2025. Hierarchical Linear Modeling (HLM) was used to identify independent predictors of HTA outcomes, and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) was used to identify sufficient pathways to success. Novel composite indicators were developed to measure system-level adaptability and the influence of patient advocacy groups (PAGs). Results: The HLM analysis, accounting for data clustering (Intraclass Correlation Coefficients (ICCs): 42% country-level, 24% agency-level variance), confirmed that strong clinical efficacy (Coef. = 0.40), high unmet need, and disease rarity were significant positive predictors. High therapy cost was a powerful negative predictor (Coef. = −0.29 per $1M USD). Crucially, high System Adaptability (Coef. = 0.35) and strong PAG Influence (Coef. = 0.28) emerged as major positive determinants. The fsQCA revealed three distinct pathways to a positive recommendation with high consistency: a “Transformative Value” path (consistency: 0.93), a “Strategic Mitigation” path (consistency: 0.90), and an “Economic Dominance” path (consistency: 0.94). The overall QCA solution explained a majority of positive outcomes (solution coverage: 0.68). Conclusion: HTA success for CGTs is not determined by isolated attributes but by the strategic alignment of therapy-level evidence, agency-level processes, and country-level context. The influence of organized patient advocacy and the structural flexibility of HTA systems are critical, previously under-quantified components of this alignment.
KW - Health Technology Assessment
KW - cell and gene therapies
KW - decision-making
KW - reimbursement
KW - value
UR - https://www.scopus.com/pages/publications/105024820646
U2 - 10.3389/fphar.2025.1695961
DO - 10.3389/fphar.2025.1695961
M3 - Article
AN - SCOPUS:105024820646
SN - 1663-9812
VL - 16
JO - Frontiers in Pharmacology
JF - Frontiers in Pharmacology
M1 - 1695961
ER -