Recurrent Patient-Reported Outcome (PRO)-Based Symptomatic Deterioration Predicts
Progression-Free Survival (PFS): Results from RATIONALE-305
Markus Moehler,1 Daniel Serrano,2 Hui Xu,3 Tao Sheng,4 Liyun Li,3 Bryant Barnes,4 Gisoo Barnes,4 Do-Youn Oh5

1Conclusions

Johannes Gutenberg-University Clinic, Department of Internal Medicine, Mainz, Germany; 2The Psychometrics Team, Sheridan, WY, USA; 3BeiGene (Beijing) Co., Ltd, Beijing, China; 4BeiGene USA, Inc., San Mateo, CA, USA;
5Seoul National University Hospital, Cancer Research Institute, Seoul, Korea

After predicting progression-free survival (PFS) from the risk of recurrent
symptomatic deterioration events, the tislelizumab arm remained superior to theplacebo arm, with estimated hazard ratios (HRs) for the tislelizumab arm between
0.70 to 0.78, reflecting a 30% to 22% reduced risk of disease progression

BackgroundPRO-based symptom endpoints are routinely employed in time to deterioration (TTD) analyses– However, these endpoints are rarely associated with treatment efficacy in oncology trials involving patients withG/GEJ adenocarcinoma• In contrast to outcomes with a clear terminal event, such as PFS, recurrent PRO symptom deterioration may
result in endpoints with “transient” terminal event times, better addressed by recurrent event survival models than
the single-event TTD framework• The objective of the current analyses was to develop a joint survival model linking time to recurrent PRO-based
deterioration and disease progression (defined as PFS events) within the RATIONALE-305 trial population

These analyses were conducted using data from RATIONALE-305 (NCT03777657), a phase 3, randomized,
double-blind, placebo-controlled trial assessing the addition of tislelizumab to chemotherapy as first-line
treatment for patients with locally advanced, unresectable, or metastatic G/GEJ adenocarcinoma– Patients were randomized 1:1 to receive tislelizumab 200 mg or placebo intravenously once every 3 weeks plus
investigator’s choice of chemotherapy regimen until disease progression, unacceptable toxicity, or patient withdrawal

PRO Measures

PRO-based symptoms were assessed using the European Organisation for Research and Treatment of Cancer(EORTC) Quality of Life Questionnaire – Core 30 (QLQ-C30) and Gastric Cancer Module (QLQ-STO22)1– Two QLQ-C30 domains were analyzed: appetite loss and fatigue– Four QLQ-STO22 domains were analyzed: dietary restrictions, dysphagia, pain/discomfort, and UGI symptoms• Both the QLQ-C30 and QLQ-STO22 were administered at baseline and then every 3-week cycle until the end oftreatment•Number of Recurrent Events
01
2345References

1. Blazeby JM, et al. Eur J Cancer. 2004;40:2260–68.
2. Osoba D, et al. J Clin Oncol. 1998;16(1):139-44.

BGNE-25704-1 ESMO24 RATIONALE-305 JM Poster CG09.indd 1

Patients, N (%)
514 (57.4)
254 (28.3)
83 (9.3)
26 (2.9)
16 (1.8)
3 (0.3)

The tislelizumab arm demonstrated statistically significant greater protection against PFS compared with the•placebo arm
The association parameter for CFBL in symptomatic PRO scores and risk of recurrent corresponding symptomatic•

deterioration was statistically significant for all domains (as is to be expected); however, the association parameter for
CFBL in symptomatic PRO scores and risk of PFS was not statistically significant

Table 2. Joint Survival Model for Recurrent Symptomatic Deterioration and PFS Adjusting for CFBL in
PRO Domains, Treatment Arm, and Stratification Factors

Table 1. Observed Number of Recurrent QLQ-STO22 Upper Gastrointestinal
Symptom Deterioration Events up to Cycle 38a

DomainEffectHR (95% CI)

PȒaTIS arm versus PBO arm: R-Det

1.20 (0.85, 1.71)

0.31761.0206

TIS arm versus PBO arm: PFS

0.74 (0.57, 0.95)

0.0216

1.0570

CFBL: R-Det

1.08 (1.07, 1.09)

0.00001.0819

CFBL: PFS

1.00 (1.00, 1.01)

0.38641.0020R-Det frailty: PFSb

20.49 (2.84, 259.82)

0.00001.6812

TIS arm versus PBO arm: R-Det

1.07 (0.70, 1.68)

0.7762

1.0252

TIS arm versus PBO arm: PFS

0.78 (0.65, 0.93)

0.00691.0223

CFBL: R-Det

1.16 (1.13, 1.19)

0.00001.1233

CFBL: PFS

1.00 (0.99, 1.01)

0.95331.0118R-Det frailty: PFSb

2.77 (0.18, 87.03)

0.34331.2353

TIS arm versus PBO arm: R-Det

0.89 (0.61, 1.31)

0.55841.0198

TIS arm versus PBO arm: PFS

0.78 (0.63, 0.94)

0.0116

1.0070

CFBL: R-Det

1.10 (1.08, 1.11)

0.00001.1874

CFBL: PFS

1.01 (1.00, 1.01)

0.09781.0106R-Det frailty: PFSb

3.81 (0.98, 20.66)

0.05161.2261

TIS arm versus PBO arm: R-Det

0.96 (0.73, 1.27)

0.77241.0210

TIS arm versus PBO arm: PFS

0.72 (0.55, 0.93)

0.0162

1.0224

CFBL: R-Det

1.08 (1.07, 1.09)

0.00001.0212

CFBL: PFS

1.00 (1.00, 1.01)

0.3002

1.0269R-Det frailty: PFSb

53.06 (10.11, 375.30)

0.00001.2619TIS arm versus PBO arm: R-Det

1.01 (0.75, 1.37)

0.92001.0287

TIS arm versus PBO arm: PFS

0.70 (0.53, 0.92)

0.0084

1.1073

CFBL: R-Det

1.10 (1.08, 1.11)

0.00001.07392

CFBL: PFS

1.00 (0.99, 1.01)

0.6702

1.0482

3

R-Det frailty: PFSb

52.39 (7.68, 864.09)

0.00001.3480

TIS arm versus PBO arm: R-Det

0.88 (0.65, 1.20)

0.48041.0215

TIS arm versus PBO arm: PFS

0.73 (0.56, 0.94)

0.00731.0020

CFBL: R-Det

1.11 (1.10, 1.13)

0.00001.0443

CFBL: PFS

1.00 (0.99, 1.01)

0.78271.0189R-Det frailty: PFSb

29.35 (2.94, 400.21)

0.00001.0687

Cumulative N (%)
514 (57.4)
768 (85.7)
851 (95.0)
877 (97.9)
893 (99.7)
896 (100)

Appetite

Patients who completed baseline and ≥1 post-baseline QLQ-C30 and QLQ-STO22 were eligible.
QLQ-C30, Quality of Life Questionnaire – Core 30; QLQ-STO22, Quality of Life Questionnaire – Gastric Cancer Module.

aJoint Models•Dysphagia

Convergence plots for the joint models indicated satisfactory convergence of the Bayesian integral-based
marginalization (illustrated by examples from the UGI frailty parameter in Figure 1)
Figure 1. Convergence Density and Trace Plots for the Upper Gastrointestinal Frailty Markov Joint ModelDensity Plot

Dietary restrictions

Statistical Analyses

Density

100

Chain
1250

3

Fatigue

0-0.015-0.010-0.005

Trace Plot

Value

0.000

0.005

0.005
Chain0.000
Value

All randomized patients in the intent-to-treat (ITT) population who completed the baseline and ≥1 post-baseline
QLQ-C30 and QLQ-STO22 were eligible• Change from baseline (CFBL) scores in each symptom domain were analyzed for up to 21 cycles between
cycle 2 and cycle 38 (≈114 weeks)• A recurrent deterioration event was defined as a CFBL score ≥10 points2, and recurrent events defined as 2events had to be separated by non-events– For a deterioration event to qualify as recurrent, it had to be a unique event– Patients without recurrent deterioration events or disease progression to end of study were censored• Treatment effect was coded as tislelizumab arm versus placebo arm with tislelizumab arm as the effect group• The terminal survival event was investigator-assessed PFS• A joint survival model was specified for PRO symptom deterioration and PFS terminal events that linked thefollowing components:– PRO symptom deterioration was modeled via a recurrent events frailty Cox model, to account for time torecurrent deterioration events, with treatment arm and stratification factor covariates– PFS terminal events were modeled via a Cox proportional hazards model to evaluate the recurrent
deterioration frailty prediction of PFS• The joint model provides a comprehensive adjustment for missing data bias, allowing for deeper exploration into
later treatment cycles• This model was adjusted for the following randomization factors: geographic region (Asia vs. non-Asia),
programmed death-ligand 1 (PD-L1) expression status (tumor area positivity ≥5% vs. <5%), and presence of
peritoneal metastasis (yes vs. no)• Analyses were conducted using the JMBayes2 package in R (version 4.3.2)– Model and parameter convergence were evaluated using trace and density plots, survival model HRs, and theȒ statistic

domains, with higher rates of recurrent deterioration events predicting increased risk of progression (Table 2)

ITT population (N=997; tislelizumab arm, n=501; placebo arm, n=496), cut-off date =February 28, 2023
– Patient demographics and baseline disease characteristics were generally balanced across the arms, with 465
patients in the tislelizumab arm and 467 patients in the placebo arm completing the questionnaires• The number of recurrent deterioration events ranged from 0 (censored) to 5 (see Table 1 for the number of recurrent
UGI deterioration events as an example)– A total of 42.3% of the sample had at least 1 recurrent event

Study Design and Patients

These preliminary analyses provide a mechanism for modeling PRO data inoncology clinical trials that may help illuminate additional clinically interpretable
treatment effects that might enhance clinician-patient dialogue

The prediction of PFS was statistically significant for the appetite loss, fatigue, pain/discomfort, and UGI symptoms••

Methods•

Recurrent patient-reported outcome (PRO) symptomatic deterioration in appetite,
fatigue, pain/discomfort, and upper gastrointestinal [UGI] symptoms) were leading
predictors for risk of disease progression, indicating a potential need for increased
clinical monitoringResults••

Poster No: 1449P Presented at the European Society for
Medical Oncology (ESMO) Congress; September 13–17, 2024;
Barcelona, Spain

1-0.005

Pain/discomfort-0.010-0.015
01000

2000

3000

UGI symptoms

IterationChain 1• Represents one sequence of sampledvalues starting from an initial value• Essentially used to explore the parameter
space independently of the other chains

Acknowledgments
We would like to thank the investigators, site support staff, and especially the patients for participating in thisstudy. This study was sponsored by BeiGene, Ltd. Medical writing support, under the direction of the authors,
was provided by Jason Allaire, PhD of Generativity Solutions Group and was funded by BeiGene. Editorial
support, under the direction of the authors, was provided by Steven Moore, PhD, and Smitha Reddy, PhD, ofEnvision Pharma Inc., and funded by BeiGene.

Chain 2• Represents another independent sequence ofsampled values from a different starting point• Provides an additional path through theparameter space for comparison

Chain 3
• Represents a third independent sequence ofsampled values• Helps ensure robustness and thoroughexploration of the parameter space

Presenter Disclosures
Markus Moehler received consulting fees from Bayer, MSD, Merck Serono, Amgen, Taiho Pharmaceutical, Pfizer, Roche,Lilly, Servier, BeiGene, BMS, AstraZeneca, Astellas, Dragonfly and Novartis; received honoraria from Amgen, Roche/Genentech, Merck Serono, MSD Oncology, Bristol-Myers Squibb, AstraZeneca/MedImmune, Servier, Pierre Fabre,Sanofi, Falk foundation, Transcenta, Daiichi, Astellas and Nordic; has other financial or non-financial interests in Amgen,Merck Serono, Roche, Bayer, ASCO, German Cancer Society, MSD, ESMO, BeiGene and EORTC.

Based on Ȓ statistic with values of 1 indicating acceptable convergence; all estimates except some frailty predictions (highlighted in bold) achieved acceptable convergence. bAssociation parameter and not HR. Significant effects
are highlighted in blue.
CFBL, change from baseline; CI, confidence interval; HR, hazard ratio; PBO, placebo; PFS: progression-free survival; PRO, patient-reported outcomes; TIS, tislelizumab; R-Det, recurrent deterioration;
UGI, upper gastrointestinal.
aPlease scan the Quick Response (QR) code to the right to downloada digital copy of this poster. Copies of this poster obtained through QR(Quick Response) and/or text key codes are for personal use only andmay not be reproduced without written permission of the authors.

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