Efficacy of Zanubrutinib Versus Acalabrutinib in the Treatment of Relapsed orRefractory Chronic Lymphocytic Leukemia: A Matching-Adjusted Indirect Comparison

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Mazyar Shadman1, Jennifer R Brown2, Rhys Williams3, Leyla Mohseninejad4, Keri Yang3, Pal Rakonczai5, Nicole Lamanna6, Sheng Xu7, Aileen Cleary Cohen3, Susan M. O’Brien8, Alessandra Tedeschi9, and Constantine S. Tam10
1Fred Hutchinson Cancer Center and University of Washington, Seattle, WA, USA; 2Chronic Lymphocytic Leukemia Center, Division of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA; 3BeiGene USA, Inc, San Mateo, CA, USA;
4BeiGene Netherlands B.V., Schiphol, Netherlands; 5Evidera, Budapest, Hungary; 6Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA; 7BeiGene (Shanghai) Co., Ltd., Shanghai, China; 8University of California, Irvine, CA, USA;
9ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy; 10Alfred Hospital and Monash University, Melbourne, VIC, Australia

CONCLUSIONSI NTRODUCTION

M ETH ODSRES ULTS• Zanubrutinib, a next-generation covalent Bruton tyrosine kinase inhibitor (BTKi), isFigure 1. Details of the Overall Methodology

Figure 2. (A) PFS-INV and (B) OS for Zanubrutinib ITT and Postmatching, andAcalabrutinib
A PFS-INV

ALPINE (n=327)• Acalabrutinib, a second-generation BTKi, showed improved PFS vs rituximab-idelalisib/
indirect treatment comparison was performed to evaluate the relative efficacy of these2 treatments• The objective of this study was to compare the efficacy of zanubrutinib in ALPINE

and acalabrutinib in ASCEND using matching-adjusted indirect comparison (MAIC)
methodology

Published aggregate data
(DCO: October 2020;
median follow-up: 36 months)

Individual patient-level data (IPD)(DCO: September 2023;
median follow-up: 39 months)

bendamustine in R/R CLL in the ASCEND trial,2,3 but PFS noninferiority vs ibrutinib inpatients with R/R CLL with chromosome 17p or 11q deletions in the ELEVATE-RR trial4• As no head-to-head clinical trial of zanubrutinib and acalabrutinib in R/R CLL exists, an

ASCEND (n=155)

Zanubrutinib postmatching

1.00

Variables identified as prognostic factors or predictors of treatment effect for matchingAge, gender, ECOG PS, geographic region, mutated IGHV, del(17p), del(11q), TP53 mutation status, complex karyotype,* bulky disease,cancer type, beta2-microglobulin,* Rai/Binet stage, number and type of prior therapies, absolute lymphocyte and neutrophil counts, andplatelet countdata from ASCEND

1-3• An unanchored MAIC was used due to the lack of a common comparator arm between
the ALPINE and ASCEND trials• Given the timing of the study in relation to the COVID-19 pandemic for ASCEND vs ALPINE,
adjustments on ALPINE were made for the impact of COVID-19• Population adjustment in the base case analysis considered all variables identified asreconstructed from the digitized Kaplan-Meier curves reported in the ASCEND publication
using the algorithm by Guyot et al5• A weighted Cox proportional hazard model was used to compare investigator-assessed
PFS (PFS-INV) and OS and a weighted logistic regression model to compare complete
response (CR)HR (95% CI) zanubrutinib (ALPINE) vs acalabrutinib (ASCEND)
Unadjusted population: 0.77 (0.55-1.07); P=.1213
Base case adjusted population: 0.68 (0.46-0.99); P=.0448

Unadjusted
Population
Age ≥75, %Male, %ECOG PS score=0 (vs ≥1), %Geographic region
United States and Canada, %Australia and New Zealand, %Asia, %Europe, %Genomic status
Mutated IGHV, %Del(17p), %Del(11q), %TP53 mutation, %Complex karyotype ≥3, %*Bulky disease, LD in cm, ≥5, %Cancer type, CLL, %Beta2-microglobulin >3.5 mg/L, %*Rai stage 0-II or Binet A/B, %Number of prior therapies
2, %
3, %
≥4, %
Prior therapy
Anti-CD20 antibody, %Sensitivity Analyses

Base Case
Adjusted
Population

S1

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✓

S2
✓✓

S3
✓
✓
✓

S4✓✓
✓

S5
✓
✓
✓

S6
✓✓✓✓✓✓
✓

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✓

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✓
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✓

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✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓

Alkylators other thanbendamustine, %✓✓✓✓✓Bendamustine, %Purine analog, %✓✓✓✓0ALPINE (IPD)

✓✓

✓✓✓
✓

Absolute lymphocyte count,
109 cells/L, median✓

✓

✓

✓

Absolute neutrophil count,
109 cells/L, median✓

✓

✓

✓

Platelet count, 109 cells/L, median

✓

✓✓

✓

* Covariates not matched in the base case.
Del (11q), chromosome 11q deletion; del (17p), chromosome 17p deletion; ECOG PS, Eastern Cooperative Oncology Group Performance
Status; IGHV, immunoglobulin heavy-chain variable; LD, longest diameter.

618243036424854

treatment efficacy across trials, the gold standard for evaluating evidence of relative
efficacy remains randomized controlled trials

Balance

Outcomes
HRs for PFS-INV and OS: Weighted Cox proportional hazard model
OR for CR: Weighted logistic regression model

165

149

141

127

94

76

200

155

142

133

121

107

94

43

000

327

300

286

259

243

218

153

118

38

00

61218

24

30

36

42

48

54

Zanubrutinib postmatching• PFS-INV was significantly improved for zanubrutinib postmatching (Figure 2A); OS wasAcalabrutinib

Zanubrutinib ITT

Table 2. Baseline Characteristics of the Zanubrutinib and Acalabrutinib Populations
Acalabrutinib
ASCEND(n=155)

Zanubrutinib
ALPINE(n=327)

Zanubrutinib
ALPINE
Postmatching(ESS=184.8)

21.9
69.7
37.4

22.6
65.1
39.9

21.9
69.7
37.4

5.2
5.8
4.5
84.5

15.9
8.6
15.0
60.6

5.2
5.8
4.5
84.5

16.2
17.4
25.2
25.2
32.4
49.0
100
77.4
58.1

25.0
13.8
27.8
15.3
26.8
44.3
96
62.6
58.0

16.2
17.4
25.2
25.2
28.6
49.0
100
62.8
58.1

25.8
11.0
10.3

26.3
7.6
7.3

25.8
11.0
10.3

83.9
85.8
30.3
70.3
48.9
3.8119.5

83.8
83.8
25.7
54.4
36.0
4.0
126.0

83.9
85.8
30.3
70.3
494
119.0

Bold values imply a statistically significant difference between zanubrutinib and acalabrutinib prematching* Covariates not matched in the base case.
ECOG PS, Eastern Cooperative Oncology Group Performance Status; ESS, effective sample size; IGHV, immunoglobulin heavy-chain variable;
LD, longest diameter.

differences can be entirely explained by variables selected for matching• Independent review committee-assessed PFS was not analyzed in the current MAIC dueacross all indications― A recent meta-analysis of 61 trials involving 6,959 patients who received ibrutinib,

0.75

potentially improved for zanubrutinib postmatching (Figure 2B)• There is a potential for bias resulting from the strong assumption that cross-trial• The study did not compare safety for zanubrutinib vs acalabrutinib― Safety of a drug is best evaluated via meta-analyses that use all available evidence

1.00

Efficacy outcomes

LIMITATIONS

to unavailability of data in ASCEND and the latest ALPINE data cut-off

B OS

RES ULTSAge ≥75, %Male, %
ECOG PS score=0 (vs ≥1), %Geographic region
United States and Canada, %Australia and New Zealand, %Asia, %Europe, %Genomic status
Mutated IGHV, %Del(17p), %Del(11q), %TP53 mutation, %Complex karyotype ≥3, %*Bulky disease, LD in cm, ≥5, %Cancer type, CLL, %Beta2-microglobulin >3.5 mg/L, %*Rai stage 0-II or Binet A/B, %Number of prior therapies
2, %
3, %
≥4, %
Prior therapy
Anti-CD20 antibody, %Alkylators other than bendamustine, %Bendamustine, %Purine analog, %Absolute lymphocyte count, 109 cells/L, medianAbsolute neutrophil count, 109 cells/L, median
Platelet count, 109 cells/L, median• While MAICs provide a scientific basis for evaluating hypotheses with regards toTime, months
Number at risk
185
172

Covariates

12ASCEND (aggregate)• CR favored zanubrutinib in the unadjusted and base case adjusted populations (Table 3)• Results for the sensitivity analyses were consistent with the base case (Table 3)

Table 1. Covariates Matched in the Base Case and Sensitivity Analyses

by Kittai et al had several important limitations, including different follow-ups
between ALPINE and ASCEND, lack of any adjustment for COVID-19, andincomplete matching variables (eg, no granularity in geographic regions andnumber and types of prior therapies)

0.00

OS• Pseudo IPD for PFS and overall survival (OS) in the acalabrutinib arm of ASCEND were

• In a previous publication, Kittai et al presented a MAIC to compare the efficacy andZanubrutinib ITT

0.50* Covariates not matched in the base case.
DCO, data cut-off; del(11q), chromosome 11q deletion; del(17p), chromosome 17p deletion; ECOG PS, Eastern Cooperative Oncology
Group Performance Status; ESS, effective sample size; HR, hazard ratio; IGHV, immunoglobulin heavy-chain variable; ITT, intent-to-treat;OR, odds ratio; SLL, small lymphocytic lymphoma.

prognostic factors or predictors of treatment effect (Table 1; Figure 1)

Main Analysis• Zanubrutinib unadjusted (ITT) population (ALPINE), n=327• Zanubrutinib ITT population filtered to patients with existing data on theselected baseline characteristics and excluding patients with SLL, n=308• After population adjustment, ESS=184.8 for zanubrutinib (60% of the starting
filtered population)

PFS-INVOSCR― Results were robust across multiple sensitivity analyses― The efficacy results differ from those presented here because the analysis

Matching, reweighting, and adjusting for variables• Individual patient-level data (IPD) from ALPINE were matched against the aggregate

potentially improved OS for zanubrutinib compared with acalabrutinib

safety of zanubrutinib (ALPINE, aggregate) vs acalabrutinib (ASCEND, IPD)
in R/R CLL. Findings showed similar efficacy for zanubrutinib and acalabrutinib(PFS-INV) and different adverse event profiles7

0.25

Sensitivity analyses of scenarios to consider impact of matching for different sets of variables

METHODS

Acalabrutinib• This comprehensive MAIC demonstrated a significant PFS and CR advantage, and0.75

Adjustment for impact of COVID-19 within ALPINEPFS -INV

the only BTKi that demonstrated progression-free survival (PFS) superiority vs ibrutinib(first-generation BTKi) in relapsed or refractory (R/R) chronic lymphocytic leukemia (CLL)in the ALPINE trial1ibrutinib ± anti-CD20 antibody, acalabrutinib, and zanubrutinib extensively analyzed
the AE profiles of zanubrutinib and acalabrutinib across several indications andreported differences between the 2 treatments60.50
HR (95% CI) zanubrutinib (ALPINE) vs acalabrutinib (ASCEND)
Unadjusted population: 0.60 (0.37-0.97); P=.0354
Base case adjusted population: 0.60 (0.35-1.02); P=.0575

0.25

REFERENCES

0.00
06

1218

2430

36

4248

54Time, moNumber at risk
185178

173

159

156

148

120

92

41

1155

150

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1. Brown JR, et al. N Engl J Med. 2023; 388: 319-332.
2. Ghia P, et al. J Clin Oncol. 2020; 38: 2849-2861.
3. Ghia P, et al. Hemasphere. 2022; 6(12):e801.
4. Byrd JC, et al. J Clin Oncol. 2021; 39: 3441–3452.
5. Guyot P, et al. BMC Med Res Methodol. 2012; 12: 9.
6. Hwang S, et al. Hemasphere. 2023;7(S3):1134.
7. Kittai AS, et al. Am J Hematol. 2023;98(12):E387-E390.

DISCLOSURES
Table 3. Relative Treatment Effects for Base Case and Sensitivity Analyses
Main Analysis

Sensitivity Analyses

Unadjusted
Population

Base Case
Adjusted
Population

S1S2

S3

S4

S5

S6Sample size
for ALPINE
zanubrutinib

n=327

ESS=184.8

ESS=188.9

ESS=210.3

ESS=208.1

ESS=188.2

ESS=187.4

ESS=78.2

HR PFS-INV
zanubrutinib vsacalabrutinib(95% CI, P value)

0.77(0.55-1.07,P=.1213)

0.68(0.46-0.99,P=.0448)

0.68(0.47-1.00,P=.0483)

0.72(0.5-1.04,P=.0842)

0.73(0.51-1.05,P=.0921)

0.67(0.46-0.98,P=.0410)

0.67(0.46-0.98,P=.0386)

0.71(0.43-1.17,P=.1822)

HR OS
zanubrutinib vsacalabrutinib(95% CI, P value)

0.6(0.37-0.97,P=.0354)

0.6(0.35-1.02,P=.0575)

0.59(0.35-1.00,P=.0481)

0.63(0.38-1.04,P=.0720)

0.66(0.40-1.09,P=.1030)

0.61(0.36-1.03,P=.0627)

0.61(0.36-1.03,P=.0667)

0.68(0.33-1.39,P=.2872)

OR CR
zanubrutinib vsacalabrutinib(95% CI, P value)

2.88(1.18-7.02,P=.0198)

2.90(1.13-7.43,P=.0270)

2.88(1.13-7.38,P=.0273)

2.69(1.06-6.85,P=.0377)

2.78(1.09-7.07,P=.0316)

2.85(1.11-7.31,P=.0294)

2.80(1.09-7.19,P=.0326)

3.34(1.15-9.71,P=.0264)

MS reports receiving funding from BeiGene paid to Fred Hutchinson Cancer ResearchCenter and the University of Washington (Seattle, WA, USA), with regards to the submittedwork; research funding from Pharmacyclics (Inst), Acerta Pharma (Inst), Merck (Inst), TG
Therapeutics (Inst), BeiGene (Inst), Celgene (Inst), Genentech (Inst), MustangBio (Inst),AbbVie (Inst), Sunesis Pharmaceuticals (Inst), Bristol Myers Squibb/Celgene, Genmab(Inst), and Vincerx Pharma (Inst); and consulting or advisory roles with AbbVie, Genentech,
AstraZeneca, Sound Biologics, Cellectar, Pharmacyclics, BeiGene, Bristol Myers Squibb/Celgene, MorphoSys, Innate Pharma, Kite, a Gilead Company, Adaptive Biotechnologies,Epizyme, Fate Therapeutics, Lilly, Regeneron, Adaptimmune, MustangBio, TG
Therapeutics, and MEI Pharma, outside the submitted work.

ACKNOW LEDGEMENTS
This study was sponsored by BeiGene, Ltd. Editorial assistance was provided by SNELL
and was supported by BeiGene.

Bold values indicate P<.05.

Presented at EHA 2024; June 13-16, 2024; Madrid, Spain/Virtual Conference