Richard C. Franzese: No relevant disclosure to display
Objectives: Oncology trials are prone to cross-study heterogeneity from multiple sources, including varying trial designs, diverse patients with numerous treatment options, and different prior therapies. Model-based meta-analysis (MBMA) has quantified distinct treatment effects and correlations between objective response rate (ORR) and survival for non-small cell lung cancer [1,2], whilst accounting for explained and unexplained variability. Once developed, MBMA allows for indirect comparisons between compounds and predictions of future trial outcomes. Head and neck cancer ranks globally as the third most prevalent cancer [3]. Accordingly, we use MBMA to characterize head and neck squamous cell carcinoma (HNSCC) efficacy outcomes and evaluate the link between short- and long-term efficacy.
Methods: MBMA with mixed-effects logistic regression was applied to quantify treatment-specific and covariate effects on ORR. MBMA with a semi-parametric longitudinal mixed-effects model of overall survival (OS) (Kaplan–Meier curves) was developed as a function of observed ORR, with treatment type-specific relationships. A non-parametric reference survival curve described the baseline hazard, and covariates were tested using the proportional hazards assumption. Key treatments were PD-(L)1-based therapies as monotherapy and in combination with chemotherapy, other immunotherapy agents, and/or targeted therapy. Randomized trials with chemotherapy and targeted therapy in combination were also included. Simulations predicted how changes in ORR, in impactful covariate effects, and in sample size affected OS hazard ratios.
Results: Data comprised ORR for 37 treatments. A total of 57 and 47 studies were analyzed for ORR and OS, respectively. Significant ORR-OS correlations were established for each general treatment type. The estimated relationships were different for PD-1 versus PD-L1-containing treatments. Treatment line (higher ORR for earlier lines) and mean PD-L1 expression (higher ORR for higher expression if PD-(L)1-treated) were included as covariate effects in the ORR model. PD-1 monotherapy or combination with another immunotherapy agent had the steepest relationship between drop in OS hazard per unit increase in ORR.
Conclusions: ORR is significantly correlated with OS in HNSCC. This work provides further evidence of treatment-type specific relationships between ORR and OS for solid tumor cancers and adds to the growing body of evidence that establishes MBMA methodology as tool to support evidence-based decision-making for late-stage trial designs.
Citations: 1. D. C. Turner, R. Wada, H. Zhou, et al., “Model-Based Meta-Analysis of Non-Small Cell Lung Cancer With Standard of Care PD-1 Inhibitors and Chemotherapy for Early Development Decision Making,” CPT: Pharmacometrics & Systems Pharmacology 12, no. 11 (2023): 1751–1763.
2. R. C. Franzese, L. Qin, S. Fu, et al., “Model-Based Meta-Analysis (MBMA) of Objective Response Rate (ORR), Progression-Free Survival (PFS), and Overall Survival (OS) to Compare PD-1 and PD-L1 Treatment Outcomes In Metastatic (m) Non-Small-Cell Lung Cancer (NSCLC),” Annual Meeting of the American Society of Clinical Pharmacology and Therapeutics. March 27–29, 2024. Poster PII-058
3. H Sung, J Ferlay, R. L. Siegel et al., “Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries,” CA. Cancer J. Clin., 71 (2021): 209-249
