Zanubrutinib vs other Bruton’s tyrosine kinase inhibitors in Relapsed/Refractory Chronic Lymphocytic
Leukemia: a Multilevel Network Meta-Regression
Mazyar Shadman*1, Walter Bouwmeester2, Leyla Mohseninejad3, Sheng Xu4, Milica Jevdjevic2, KeriYang5, Rhys Williams5, Aileen Cohen5, Jeroen Jansen2, Constantine Tam6, Jennifer R. Brown7
1Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America,

2PRECISIONheor, Rotterdam, South Holland, The Netherlands, 3BeiGene Netherlands B.V., Schiphol, TheNetherlands, 4BeiGene (Shanghai) Co., Ltd., Shanghai, China, 5BeiGene USA, Inc., San Mateo, CA, UnitedStates of America, 6The Alfred Hospital, Melbourne, Victoria, Australia, 7Dana–Farber Cancer Institute,Boston, United States of America

Background: Improved understanding of the disease biology of chronic lymphocytic leukemia (CLL)
resulted in the development of Bruton’s tyrosine kinase inhibitors (BTKi), which have been investigatedin randomized clinical trials (RCTs) in relapsed/refractory CLL (RR-CLL). These include the ALPINE trial(zanubrutinib vs ibrutinib) and the ELEVATE-RR trial (acalabrutinib vs ibrutinib). Population-adjusted
indirect treatment comparisons (ITC) can be conducted to estimate relative treatment effects between
different BTKis that were not studied head-to-head, while adjusting for between-trial differences inimportant patient characteristics. Commonly used ITC methods are unable to estimate the relative
treatment effect in the true population of interest. Matching adjusted indirect comparisons (MAIC) forinstance, reweight the individual patient data (IPD) from a given trial to reflect the population
characteristics of a comparator trial. Multilevel network meta-regression (ML-NMR) is a newly
developed ITC method in which a network of evidence is built with IPD available from at least one trial in
the network (Phillippo et al. J R Stat Soc Ser A Stat Soc. 2020;183(3):1189-1210). Using the available IPD,
relative treatment effects are estimated as a function of the patient characteristics. This facilitates
estimating relative treatment effects between interventions for different target populations andprovides an opportunity to overcome the common ITC limitations.
Aims: In this study, we use ML-NMR to estimate the treatment effects of zanubrutinib relative to other
BTKis in R/R CLL patients with a profile similar to the ALPINE intention-to-treat (ITT) population.
Treatment effects were also predicted for a population similar to the ALPINE high-risk subgroup, definedby TP53 mutation and/or 17p deletion.
Methods: The analysis included ALPINE and ELEVATE-RR, connected via their common comparator,ibrutinib. Using the IPD from the ALPINE trial and published summary data from ELEVATE-RR, relative
treatment effects were estimated as a function of the patient characteristics by means of an ML-NMR.
Given the timing of the included trials in relation to the COVID-19 pandemic, ALPINE progression-freesurvival (PFS) data were adjusted for death due to COVID-19. Relevant patient characteristics toincorporate in the adjustment of between-trial differences were based on a review of the literature andconsultation with clinical experts and included the following treatment effect-modifiers: Rai/Binet stage,
β2-microglobulin, cytogenetic deletions/mutations (TP53, 11q deletion, 17p deletion), immunoglobulin
heavy chain gene (IGHV) mutation status, and the number of prior treatment lines. Sensitivity analyses
were conducted incorporating additional patient characteristics.

EHA 2024

Results: Zanubrutinib was associated with a higher PFS than acalabrutinib (hazard ratio (HR)= 0.57; 95%
credible interval (CrI): 0.34 - 0.94) and ibrutinib (HR=0.73, 95%CrI: 0.55 - 0.96) for a population as in
ALPINE (Figure). Findings were similar for the high-risk target population and sensitivity analyses
incorporating additional patient characteristics showed consistent results.
Summary/Conclusion: Our findings indicate that zanubrutinib is associated with greater PFS comparedto acalabrutinib, and ibrutinib in a RR CLL population akin to that of the ALPINE trial as well as forpatients characterized by high-risk cytogenetics.
Figure. Comparison of PFS curves in an ALPINE-like population.

EHA 2024