Presentation (CTI)

OBJECTIVES: Network Meta-Analyses (NMAs) have become a pivotal tool in Health Technology Assessments (HTAs), particularly in oncology, where head-to-head trial data are often lacking. This study evaluates the role of NMAs in NICE oncology appraisals from January 2022 to May 2025, focusing on therapies for non-small-cell lung cancer (NSCLC), ovarian cancer, and hematological malignancies.
METHODS: A structured review of NICE Technology Appraisals (TAs) published between January 2022 and May 2025 was conducted. Data were extracted on NMA methodologies (e.g., Bayesian vs. frequentist), model types (fixed- vs. random-effects), outcomes (e.g., PFS, OS, ORR), and HTA agency critiques. Submissions were screened for inclusion of NMAs, with data abstracted by one investigator and validated by a second. Key metrics included acceptance rates, reasons for rejection, and the influence of NMAs on reimbursement decisions.
RESULTS: Of 85 oncology NICE TAs identified, NMAs were included in 70% of submissions. Bayesian methods (68%) and random-effects models (55%) were most common. HTA agencies accepted 60% of NMAs, with higher acceptance when heterogeneity (assessed via I² or DIC) and transitivity were addressed. Common critiques included small sample sizes (45%), violations of proportional hazards assumptions (30%), and lack of convergence (20%). NMAs influenced reimbursement in 50% of cases, particularly when supported by robust treatment rankings (e.g., SUCRA). However, 25% were rejected due to methodological limitations, leading to alternative approaches like MAIC or STC.
CONCLUSIONS: NMAs are pivotal for oncology HTAs but require rigorous validation to meet agency standards. Pre-submission alignment with HTA guidelines on transparency and heterogeneity adjustment is recommended. These findings highlight NMAs’ dual role in enabling cost-effectiveness assessments while shaping drug reimbursement policies.