Real-World Comparative Effectiveness of Covalent Bruton Tyrosine Kinase Inhibitors Among Patients WithRelapsed/Refractory Mantle Cell Lymphoma
Tycel Phillips, Taavy A. Miller, Jingru Wang, Amy Pierre, Gregory A. Maglinte, Erlene K. Seymour
122233

City of Hope, Duarte, CA, USA; Flatiron, New York, NY, USA; BeiGene USA, Inc, San Mateo, CA, USA
3• The recent availability of covalent Bruton tyrosine kinase inhibitors (cBTKis) has contributed to the rapidly evolving
treatment landscape for relapsed/refractory (R/R) mantle cell lymphoma (MCL)• Newer cBTKis (second-generation acalabrutinib and next-generation zanubrutinib) were developed to addressconcerns with off-target inhibition and side effects, with zanubrutinib being more selective against several off-target
kinases than acalabrutinib and ibrutinib• There is no direct evidence from randomized controlled trials to discern between the efficacy of available cBTKi therapies
for R/R MCL, and little is known about their utilization and comparative effectiveness in the real-world (RW) setting

Patient Baseline Characteristics

OBJECTIVE• Of the 1,377 patients with R/R MCL who received any therapy in the 2L+ setting, 602 patients received 2L/3L cBTKi
monotherapy for MCL and were included in this study• Median age at the start of 2L therapy was 74 years (range 34-85), and the majority of patients were male (74%),
identified as White (76%), did not identify as Hispanic or Latino (75%), had Stage IV disease (63%) and an Eastern
Cooperative Oncology Group Performance Status (ECOG PS) score of 0-1 (60%) (Table 1)• Most patients (96%) had undocumented and/or negative tests for TP53 status
Table 1. Baseline Demographic and Clinical Characteristics of Patients with R/R MCL Who Received 2/3L cBTKi Monotherapy• To describe the RW characteristics and utilization patterns, and evaluate the comparative effectiveness of zanubrutinib,
acalabrutinib, and ibrutinib monotherapy in second- or third-line (2L/3L) treatment among patients with R/R MCL in theUnited States (US)Characteristic
Age at 2L start (range), years
Male, n (%)
Race, n (%)
White
Black or African American
AsianOther race
Unknown/not documented
Ethnicity, n (%)
Hispanic or Latino
Non-Hispanic or Latino
Unknown/not documented
SES index, n (%)
1 – lowest SES
234
5 – highest SES
Unknown/not documented
Disease subtype, n (%)
Blastoid MCL
Pleomorphic MCL
Leukemic MCL
MCL, NOS
Stage at initial diagnosis, n (%)
IIIIIIIV
Unknown/not documented
Bulky disease at initial diagnosis, n (%)
Yes
No/unknown
ECOG PS at index start, n (%)a0-1
2-4Unknown
TP53 status at index start, n (%)b
Positive
Negative or unknown/not documented
Ki67 status at index start, n (%)b<10%11%-30%31%-50%>50%
Unknown/not documented
LDH at index start, n (%)b<0.67 ULN
≥1.50 ULN
0.67-0.99 ULN
1.00-1.49 ULN
Unknown/not documented
Number of LOT prior to index, n (%)c12
Time from start of 1L to index of first BTKi,
median (IQR), months
Patient disposition at data cutoff, n (%)
Confirmed death
Still on therapy at data cutoff

METHODS
Data Source and Study Design• This retrospective observational cohort study used the nationwide, longitudinal, electronic health record-derived,
Flatiron Health database, comprising de-identified patient-level data originated from ~280 US cancer clinics andcurated via technology-enabled abstraction1,2• The study design is shown in Figure 1
Figure 1. Study Design

1 Jan 2018

1 Jan 2011

Data cutoff
30 Nov 2023

Initiation of index therapya

MCL diagnosis(2L/3L cBTKi monotherapy)

Follow-up period

Baseline assessment period(time from the index date to date of death, or lastknow electronic medical encounter date in thedatabase in the absence of an observed death)(period between initial MCL diagnosis[2011 or later] until the index date)Index date(start date of the patient’s first treatment with 2L/3L cBTKi monotherapy:
zanubrutinib, acalabrutinib, or ibrutinib)

Study Population• Eligible adults were included from the real-world database• Inclusion criteria were:– International Classification of Disease code for non-Hodgkin lymphoma (NHL), as identified by structured data
– ≥2 documented clinical visits on different days occurring on or after January 1, 2011
– Diagnosis of MCL on or after January 1, 2011, as confirmed by a review ofunstructured data
– Received treatment with ≥2 lines of treatment, where 2L treatment for MCL was received on or after January 1, 2018
– Treated with zanubrutinib, acalabrutinib, or ibrutinib monotherapy in the 2L/3L setting• Patients were excluded if they were treated with a BTKi prior to their first cBTKi monotherapy in the 2L/3L setting

Study Outcomes• Patient baseline demographic and clinical characteristics were described• RW treatment patterns were evaluated, as well as clinical outcomes:– RW time to next treatment (rwTTNT), defined as time from index date to the start of the next treatment or death,
whichever occurred first– RW overall survival (rwOS), defined as time from index date to date of death

Statistical Methods• For continuous variables, descriptive statistics included medians, interquartile range (IQR), and minimum and maximum
values; for categorical variables, frequencies and percentages were reported• Survival curves were generated using Kaplan-Meier analyses and log-rank test was used
to compare the survival distributions across treatment groups• In unadjusted analyses, rwTTNT and rwOS were compared between 2L/3L cBTKi treatment groups without any
covariate adjustment. Median survival estimates, survival probabilities at 1, 3, 6, 9, and 12 months after the index date,and 95% confidence intervals (CIs) were reported• In adjusted analyses, propensity scores were estimated using multivariable logistic regression models, and inverse
probability of treatment weighting was conducted to estimate the average treatment effect• Cox proportional hazards regression models were used to generate unadjusted or adjusted hazard ratios (HR) for thetreatment comparisons with associated 95% CIs and P values

PRESENTER: Erlene K. Seymour
Correspondence: Tycel Phillips, tphillips@coh.org

Overall(N=602)74 (34, 85)
448 (74%)

Zanubrutinib(n=107)74 (46, 85)
79 (74%)

Acalabrutinib(n=301)74 (34, 85)
229 (76%)

Ibrutinib(n=194)72 (38, 85)
140 (72%)458 (76%)
21 (3.5%)
9 (1.5%)48 (8.0%)66 (11%)82 (77%)≤5≤55 (4.7%)
17 (16%)231 (77%)
11 (3.7%)
7 (2.3%)24 (8.0%)28 (9.3%)

145 (75%)
9 (4.6%)≤5
19 (9.8%)
21 (11%)34 (5.6%)451 (75%)
117 (19%)

7 (6.5%)80 (75%)20 (19%)15 (5.0%)227 (75%)
59 (20%)12 (6.2%)
144 (74%)
38 (20%)70 (12%)
97 (16%)118 (20%)143 (24%)112 (19%)62 (10%)41 (6.8%)
20 (3.3%)
30 (5.0%)511 (85%)
11 (1.8%)
18 (3.0%)68 (11%)381 (63%)
124 (21%)9 (8.4%)21 (20%)16 (15%)31 (29%)23 (21%)7 (6.5%)≤5≤5≤595 (89%)≤5≤59 (8.4%)
71 (66%)24 (22%)29 (9.6%)
48 (16%)62 (21%)
67 (22%)59 (20%)36 (12%)23 (7.6%)
11 (3.7%)
17 (5.6%)250 (83%)
6 (2.0%)6 (2.0%)38 (13%)186 (62%)65 (22%)32 (16%)28 (14%)40 (21%)45 (23%)30 (15%)19 (9.8%)

rwTTNT and rwOS

• Among patients with R/R MCL treated with cBTKi monotherapies in the US,
patients who received 2L/3L zanubrutinib had significantly longer rwTTNT andrwOS compared with 2L/3L ibrutinib, and there was a trend favoring improved
clinical outcomes for 2L/3L zanubrutinib compared with 2L/3L acalabrutinib• Among patients who received 2L/3L cBTKi monotherapy, 107 (17.8%), 301 (50.0%) and 194 (32.2%) patients received
2L/3L zanubrutinib, acalabrutinib, and ibrutinib, respectively• Median (IQR) follow-up from the start of index 2L/3L cBTKi monotherapy was 14 (8-26), 32 (18-48), 51 (31-61) months forzanubrutinib, acalabrutinib, and ibrutinib, respectively• Among the overall population, unadjusted median rwTTNT and rwOS were 11.1 (95% CI 9.2-12.9) and 29.2 (95% CI 24.3‑36.5)
months, respectively (Figure 2)• Unadjusted median rwTTNT were 16.8 (95% CI 11.8-23.7) months for 2L/3L zanubrutinib, 11.5 (95% CI 8.6-14.6) months
for 2L/3L acalabrutinib, and 8.6 (95% CI 7.2-11.3) months for 2L/3L ibrutinib• Median rwOS was not reached for 2L/3L zanubrutinib (95% CI 23.7-NR), and the unadjusted median rwOS was 27.4
(95% CI 22.7-36.5) months for 2L/3L acalabrutinib and 29.3 (95% CI 21.1-40.5) months for 2L/3L ibrutinib (Figure 2)

Figure 2. Kaplan-Meier Curves Reflecting rwTTNT for (A) cBTKi Overall, (B) by cBTKi Therapy, andrwOS for (C) cBTKi Overall, (D) by cBTKi Therapy, Among Patients with R/R MCL Who Received 2L/3L
cBTKi Monotherapy
A
1.00

≤5
10 (5.2%)
21 (11%)124 (64%)35 (18%)105 (17%)497 (83%)

15 (14%)92 (86%)46 (15%)255 (85%)

44 (23%)150 (77%)364 (60%)
60 (10.0%)
178 (30%)

68 (64%)9 (8.4%)30 (28%)185 (61%)33 (11%)
83 (28%)111 (57%)
18 (9.3%)
65 (34%)27 (4.5%)575 (96%)

6 (5.6%)101 (94%)

17 (5.6%)
284 (94%)≤5190 (98%)

27 (4.5%)
122 (20%)116 (19%)159 (26%)
178 (30%)

7 (6.5%)22 (21%)16 (15%)32 (30%)30 (28%)11 (3.7%)
61 (20%)59 (20%)74 (25%)96 (32%)9 (4.6%)39 (20%)41 (21%)53 (27%)52 (27%)111 (18%)
46 (7.6%)
190 (32%)
79 (13%)176 (29%)

22 (21%)6 (5.6%)33 (31%)13 (12%)33 (31%)49 (16%)23 (7.6%)
95 (32%)38 (13%)96 (32%)40 (21%)17 (8.8%)
62 (32%)28 (14%)47 (24%)487 (81%)115 (19%)

85 (79%)22 (21%)240 (80%)
61 (20%)162 (84%)
32 (16%)22 (7, 46)

25 (10, 57)

19 (7, 45)

22 (6, 43)

273 (45%)135 (22%)26 (24%)41 (38%)145 (48%)
54 (18%)102 (53%)
40 (21%)

0.50

Table 2. Unadjusted, Multivariate, and Propensity-Score Adjusted Hazard Ratios for rwTTNT and rwOS Comparing
2L/3L cBTKi Monotherapy Among Patients with R/R MCL

0.25

Zanubrutinib vs Acalabrutinib

0Number at risk
All 602

B

20132

40Time, months
32

P ValueHR (95% CI)

P Value

Unadjusted

0.77 (0.56-1.06).11

0.66 (0.48-0.92).01

Multivariate (Cox model)

0.82 (0.59-1.12).20

0.68 (0.49-0.94).02

IPTW minimally adjustedb

0.81 (0.59-1.11).20

0.67 (0.48-0.94).02

IPTW fully adjustedc

0.84 (0.61-1.17).30

0.64 (0.44-0.93).02

Unadjusted

0.66 (0.44-1.01).06

0.66 (0.43-1.02).06

Multivariate (Cox model)

0.69 (0.46-1.06).09

0.64 (0.41-0.99)

.04

80

IPTW minimally adjustedb

0.69 (0.45-1.05).08

0.61 (0.40-0.95).03000IPTW fully adjustedc

0.74 (0.48-1.13).20

0.56 (0.35-0.91).0280

60rwTTNT

Zanubrutinib
Acalabrutinib
Ibrutinib

0.75
0.50

rwOS

0.25
0.00

0

Number at risk
Zanubrutinib 107
Acalabrutinib 301
Ibrutinib 194

20157245

40Time, months
11615600241.00

Reference treatment was acalabrutinib for zanubrutinib vs acalabrutinib, and ibrutinib for zanubrutinib vs ibrutinib.
b
The minimally adjusted model adjusted for: age, sex, time from 1L to 2L, time from 2L to 3L; absolute SMDs post-IPTW were <0.2, indicating that balance between cohorts
was achieved.
cThe IPTW fully adjusted model adjusted for: age, sex, time from 1L to 2L, time from 2L to 3L, ECOG stage at initial diagnosis, LDH status, bulky disease status, and Ki67 status; absoluteSMDs post-IPTW were <0.2, indicating that balance between cohorts was achieved.
IPTW, inverse probability of treatment weighting; LDH, lactose dehydrogenase; MCL, mantle cell lymphoma; SMD, standardized mean difference.
a0.75

LIMITATIONS0.50• The limited sample size and follow-up period with 2L/3L zanubrutinib restricted the ability to discern smallerdifferences in effectiveness compared with the other evaluated cBTKis• The included oncology practices may not have represented all practice sites within the US

0.25
0.00

• Lack of certain data (eg, specific variables, loss to follow-up) could have introduced bias

0

Number at risk
All 602

DOutcomea

Zanubrutinib vs Ibrutinib

HR (95% CI)

60

1.00

C

• Future research into identifying factors influencing utilization of cBTKis, andreasons for differences in rwTTNT and rwOS across cBTKis are warranted• Adjusted models showed significantly longer rwTTNT and rwOS for 2L/3L zanubrutinib vs 2L/3L ibrutinib and trends for
improved outcomes for 2L/3L zanubrutinib over 2L/3L acalabrutinib (Table 2)– In the fully adjusted model, rwTTNT (HR 0.64, 95% CI 0.44-0.93, P=.02) and rwOS (HR 0.56, 95% CI 0.35-0.91, P=.02)
was significantly improved with 2L/3L zanubrutinib vs 2L/3L ibrutinib– Fully adjusted HRs for rwTTNT and rwOS for 2L/3L zanubrutinib vs 2L/3L acalabrutinib were 0.84 (95% CI 0.61-1.17;P=.30) and 0.74 (95% CI 0.48-1.13; P=.20), respectively

0.75

0.00

13 (6.7%)
7 (3.6%)8 (4.1%)166 (86%)

Extracted from unstructured documents using natural language processing when ECOG information from structured data were unavailable in the baseline ECOG table. ECOG
values represent the score closest to the index date. ECOG values of 5 were transformed to “unknown” for de-identification purposes. Additional information is provided in
Flatiron’s Knowledge Center.
bAs documented with dates occurring at any point from initial diagnosis to 30 days after index date (either 2L or 3L start).
cIndex referred to start of 2L for the total R/R MCL (2L+) cohort, the start of 3L for the 3L subcohort who initiated 3L, and the earliest BTKi monotherapy start date (either 2L or 3L)
for the BTKi monotherapy 2L/3L subcohort.
1L, first-line, LDH, lactose dehydrogenase; LOT, line of treatment; MCL, mantle cell lymphoma; NOS, not otherwise specified; ES, socioeconomic status; ULN; upper limit of normal.
aCONCLUSIONS

Real-world timeto next treatment

RESULTSReal-world timeto next treatment

INTRODUCTION

Treatment Patterns (Table 1)

Real-world
Overall Survival

22027040Time, months
7260801401.00
Real-world
Overall Survival

1

Zanubrutinib
Acalabrutinib
Ibrutinib

0.75
0.50
0.25
0.00

REFERENCES
1. Ma X, Long L, Moon S, et al. Comparison of Population Characteristics in Real-World Clinical Oncology Databases inthe US: Flatiron Health, SEER, and NPCR. medRxiv. 2023. doi: https://doi.org/10.1101/2020.03.16.20037143
2. Birnbaum B, Nussbaum N, Seidl-Rathkopf K, Agrawal M, et al. Model-assisted cohort selection withbias analysis for generating large-scale cohorts from the EHR for oncology research. ArXiv. 2020.
https://doi.org/10.48550/arXiv.2001.09765

DISCLOSURES
0Number at risk
Zanubrutinib 107
Acalabrutinib 301
Ibrutinib 194

2015724540Time, months
11615

60

80

024000

TP: Consultant: BeiGene. TAM, JW, AP: Employment, Flatiron Health, Inc., an independent member of the Roche Group,and stock ownership in Roche. GAM, EKS: Employment and may hold stock: BeiGene.

ACKNOWLEDGEMENTS

This study was sponsored by BeiGene, Ltd. Editorial assistance was provided by SNELL, and supported by BeiGene.
Presented at the 2024 Pan Pacific Lymphoma Conference; July 15-19, 2024, Lahaina, HI
Previously presented at EHA 2024; June 13-16, 2024; Madrid, Spain/Virtual Conference