Effectiveness of axicabtagene ciloleucel versus conventional treatments as first-line therapy for high-risk large B-cell lymphoma: an external comparator study

doi:10.21203/rs.3.rs-4121274/v1

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Effectiveness of axicabtagene ciloleucel versus conventional treatments as first-line therapy for high-risk large B-cell lymphoma: an external comparator study

https://doi.org/10.21203/rs.3.rs-4121274/v1

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Efficacy of Axicabtagene ciloleucel (Axi-cel) as a frontline regimen for high-risk large B-cell lymphoma (LBCL) has been described in ZUMA-12 single-arm trial, yet there is a paucity of data on head-to-head effectiveness comparison between axi-cel vs. conventional therapy. We conducted an external comparator arm (ECA) study to compare overall survival (OS) and progression-free survival (PFS) in patients treated with axi-cel from ZUMA-12 with ECA treated with conventional therapies from SMC-LCS (Samsung Medical Center-Lymphoma Cohort Study 2017–2023); published summary data from ZUMA-12 and individual patient data from SMC-LCS were used. Matching-adjusted indirect comparison weighting was used to compare OS and PFS, adjusting for the baseline characteristics. Of 279 patients with high-risk LBCL in SMC-LCS, 45 fulfilled ZUMA-12 eligibility criteria. Mortality rates were 13.5% in ZUMA-12 and 49.5% in ECA, corresponding to a lower hazard of death for axi-cel (hazard ratio 0.30 [95% CI 0.13–0.73]). Median PFS of ZUMA-12 was not reached vs 2.7 months in ECA, corresponding to improved PFS for axi-cel (hazard ratio 0.23 [0.11–0.46]). This study leveraged real-world data as a source for external comparator to present clinically meaningful evidence on the comparative effectiveness of axi-cel for high-risk LBCL.

Health sciences/Medical research/Translational research

Health sciences/Health care/Therapeutics/Drug therapy/Chemotherapy

Health sciences/Diseases/Haematological diseases/Haematological cancer/Lymphoma/Non-hodgkin lymphoma/B-cell lymphoma

Large B-cell lymphoma (LBCL) is an aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for up to 40% of all NHLs, and immunochemotherapy regimens with an anti-CD20 monoclonal antibody such as R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone) or dose-adjusted R-EPOCH (rituximab, etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin) have been widely used as first-line therapy for newly diagnosed LBCL (1). However, around 40% of patients eventually relapse and progress to refractory state in spite of salvage chemotherapies.

Axicabtagene ciloleucel (axi-cel), an autologous chimeric antigen receptor (CAR) T-cell therapy targeting CD19, has exhibited significant safety and efficacy in the management of relapsed/refractory (r/r) LBCL (2–4). Axi-cel was approved for patients with r/r LBCL after ≥2 lines of therapy based on the ZUMA-1 trial reporting 82% overall response rate (ORR) and 54% complete response (CR) rate, and patients with primary refractory LBCL or relapse within 12 months of first-line immunochemotherapy based on the ZUMA-7 trial (5, 6). Nevertheless, there are unmet needs for patients with double- or triple-hit high-grade B-cell lymphoma (HGBL) characterized by gene rearrangements of MYC and BCL2 and/or BCL6 because first-line immunochemotherapy such as R-CHOP has shown poor outcome (7, 8). Recently, the ZUMA-12 trial have further elucidated therapeutic potential of axi-cel as part of first-line therapy for high-risk patients who had a positive result (Deauville score 4 or 5) of interim positron emission tomography–computed tomography (PET–CT) after two cycles of conventional first-line immunochemotherapy together with either double- or triple-hit lymphoma or LBCL with high or high-intermediate International Prognostic Index (IPI) (9). However, a knowledge gap exists in directly comparing axi-cel to conventional therapies, impeding our understanding of its relative efficacy. Addressing this gap is crucial for informing clinical decisions and optimizing treatment for patients with high-risk LBCL.

While the emergences of various CAR T-cell therapies are evident, much of their evidence are often derived from single-arm trials with no control arm for comparative effectiveness evaluation (10, 11). In the absence of head-to-head trial comparing the effectiveness of axi-cel vs conventional therapies, indirect treatment comparison may play pivotal role in guiding treatment decision. Moreover, growing interest in utilizing real-world data as an external comparator underscores the need for innovative methodologies in absence of access to individual patient data (IPD) of an intervention arm (12). Thus, this study employed a matched-adjusted indirect comparison (MAIC) approach to minimize potential bias in indirect comparisons across studies. Specifically, this approach involved utilizing IPD from real-world data, and comparing it with the published summary data of axi-cel single arm trial (13).

This study aimed to investigate the effectiveness (overall survival [OS] and progression-free survival [PFS]) associated with axi-cel by comparing published summary data from the ZUMA-12 (NCT#03761056) with IPD from the Samsung Medical Center-Lymphoma Cohort study (SMC-LCS; NCT#03117036).

Data source

The primary data source for external comparator was IPD from a single-institute prospective cohort SMC-LCS (NCT#03117036) that enrolled patients diagnosed with NHL between January 2017 and June 2023. The primary objective of the cohort was to develop predictive models related to the progression and outcomes of lymphoma, including Diffuse Large B-Cell Lymphoma (DLBCL). SMC-LCS assessed all risk factors related to lymphoma including diagnostic information, pre-treatment information, and treatment regimen at the time of diagnosis. The data within the study registry comprises de-identified, patient-level longitudinal structured data and variables obtained from unstructured raw data through the expertise of trained human curators and physicians, all executed in adherence to standardized policies and procedures. To assess the effectiveness of axi-cel, we compared full analysis set (FAS) of ZUMA-12 with the external comparator arm of patients diagnosed with high-risk LBCL among SMC-LCS population.

This study was approved by the institutional review board of Samsung Medical Center (IRB No. SMC 2023-02-069), and the board waived the requirement for obtaining informed consent as the study utilized anonymized data.

Study design and study population

This was a retrospective study comparing published summary data of ZUMA-12 and IPD of SMC-LCS. Eligibility criteria of the external comparator arm was adopted from that of ZUMA-12 trial: 1) patients aged 18 years or older; 2) patients with a histologically confirmed diagnosis of high-grade LBCL; 3) patients exhibiting a positive interim PET-CT result according to Cheson criteria, specifically a Deauville five-point scale of 4 or 5, following the completion of 2 cycles (PET2+) of chemoimmunotherapy; 4) patients with double- or triple-hit lymphoma (i.e., MYC, BCL2 or BCL6 translocations) or those with LBCL and an IPI total score of ≥ 3; 5) patients with an absence of any evidence, suspicion, and/or history of central nervous system (CNS) involvement in lymphoma; and 6) patients with an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 (9).

Patients fulfilling any of the following criteria were excluded from the external comparator arm: 1) history of malignancy, excluding nonmelanoma skin cancer or carcinoma in situ (such as cervix, bladder, breast), unless being disease-free for a minimum of 3 years; 2) history of CNS disorders; 3) prior autologous or allogeneic stem cell transplants; 4) previous treatment with CD19-targeted therapy; () prior treatment with chimeric antigen receptor therapy, or other genetically modified T-cell therapy; 6) history of human immunodeficiency virus (HIV) infection, or active or chronic hepatitis B or C (9). Full detail on implementing ZUMA-12 eligibility criteria in SMC-LCS for external comparator selection is available from Table S1. Two individually trained hematologists conducted a comprehensive clinical review of patients fulfilling the eligibility criteria of ZUMA-12 trial by chart review process.

For external comparator arm, the index date was specified as the date of sequential treatment following the 2nd or 3rd cycle of first-line treatment including R-CHOP or R-EPOCH at SMC. Moreover, the determination of sequential treatment was based on the response to the 2nd or 3rd cycle of first-line treatment.

Outcomes

Time-to-event analyses of OS and PFS were conducted to compare effectiveness outcomes between axi-cel and conventional therapies. For the axi-cel group, OS and PFS were evaluated at the time of axi-cel infusion. Kaplan-Meier (KM) curves for OS and PFS in the ZUMA-12 FAS were extracted from Neelapu et al.'s publication (Fig. 1, Panel D and E) (9), and reconstructed using Engauge Digitizer software (Version 12.1) based on the approach outlined by Guyot et al (14, 15). For the external comparator arm, OS was defined as a time interval between initiation of the index treatment and date of all-cause death or last follow-up visit. PFS was defined as a time interval between initiation of the index treatment and occurrence of the events related to disease progression or all-cause death.

Statistical analyses

Matching-adjusted indirect comparison (MAIC) approach was used to balance average baseline characteristics between ZUMA-12 and external comparator arm. In the MAIC analysis, adjustments for the covariates were conducted on categorical variables that were consistently available in both the ZUMA-12 and the SMC-LCS. The covariates included age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1), disease stage (I/II or III/IV), IPI total score (1/2 or ≥ 3), Deauville five-point scale (4 or 5).

To achieve balance in the average baseline characteristics between ZUMA-12 and external comparator arm, statistical weights were assigned to the patients in the external comparator arm based on the covariates adjusted in the MAIC (13). Balance was assessed by examining the absolute value of the standardized mean difference (aSD) for each covariate; aSD equal to or exceeding 0.25 was regarded as indicating significant disparities between the two groups (16, 17). Following the weighting process, OS and PFS were compared using statistical tests within propensity score-based weighted cohort. Specifically, we conducted a log-rank test to compare the observed KM curve of ZUMA-12 with the weighted KM curve of the external comparator arm. Moreover, a weighted Cox proportional hazard model was performed to estimate the adjusted hazard ratio (aHR) with a 95% confidence interval (CI) (18). This procedure allows for a balanced comparison between ZUMA-12 and external comparator arm. Unweighted comparisons were also presented.

We conducted a sensitivity analysis to explore an individual impact of the clinical variables (i.e., ECOG score, disease stage, IPI total score, Deauville five-point scale) in the balancing performance of MAIC. This was explored by constructing five different MAIC models, with each model exclusively including ECOG score, disease stage, IPI total score or Deauville five-point scale. Specifically, model 1 was constructed with age, sex and histological disease type, and then each clinical variable was added to the model to construct models 2 to 5. Overall balance of the baseline characteristics according to the five models were compared using an average value of the aSDs after weighting. PFS and OS according to the five models were also estimated.

All analyses were conducted using SAS 9.4 software (SAS Institute Inc., Cary, NC, USA), with statistical significance set at a level of 0.05.

Of 279 patients with high-risk LBCL enrolled in the SMC-LCS between 2017 and 2023, there were 45 patients who fulfilled the eligibility criteria of ZUMA-12 (Fig. 1). Substantial imbalance in the baseline characteristics between ZUMA-12 and external comparator arm was noted including proportions of age ≥ 65 years (37.5% vs. 48.9%; aSD = 0.23), male (67.5% vs. 53.3%; aSD = 0.29), HGBL (45.0% vs. 20.0%; aSD = 0.55) and ECOG score of 1 (62.5% vs. 37.8%; aSD = 0.51), IPI total score ≥ 3 (77.5% vs. 97.8%; aSD = 0.65) and Deauville five-point scale of 5 (52.5% vs. 20.0%; aSD = 0.72). After weighting, there was a substantial improvement in the balance of the variables included in the MAIC model, but the imbalances remained for the other variables (Table 1).

Table 1

Demographic and clinical characteristics of ZUMA-12 and external comparator (SMC-LCS), before and after weighting
Characteristic	ZUMA-12 (N = 40)	SMC-LCS (N = 45)
Characteristic	ZUMA-12 (N = 40)	Before MAIC, n (%)	aSD	After MAIC, %	aSD
Age, median (range), yrs	61 (23–86)	64 (34–83)		63 (34–83)
≥ 65 years, n (%)	15 (37.5)	22 (48.9)	0.23	37.5	0
Male sex	27 (67.5)	24 (53.3)	0.29	67.5	0
Histological disease type
HGBL (NOS, double or triple hit)	18 (45.0)	9 (20.0)	0.55	45.0	0
DLBCL, NOS	22 (55.0)	36 (80.0)	0.55	55.0	0
ECOG score of 1	25 (62.5)	17 (37.8)	0.51	62.5	0
Disease stage
I or II	2 (5.0)	3 (6.7)	0.07	5.0	0
III or IV	38 (95.0)	42 (93.3)	0.07	95.0	0
IPI total score
1 or 2	9 (22.5)	1 (2.2)	0.65	22.5	0
≥ 3	31 (77.5)	44 (97.8)	0.65	77.5	0
Deauville five point scale
4	19 (47.5)	36 (80.0)	0.72	47.5	0
5	21 (52.5)	9 (20.0)	0.72	52.5	0
Bone marrow assessment
Lymphoma present	10 (25.0)	11 (24.4)	0.01	21.3	0.09
Double or triple hit status by FISH and IPI total score
Double or triple hit and IPI ≥ 3	4 (10.0)	9 (20.0)	0.28	27.6	0.46
Double or triple hit only	6 (15.0)	1 (2.0)	0.47	22.5	0.19
IPI ≥ 3 only	27 (67.5)	35 (78.0)	0.23	49.9	0.36
Double expression	13 (32.5)	9 (20.0)	0.29	20.3	0.28
c-Myc expression	21 (52.5)	30 (66.7)	0.29	76.2	0.51
Alterations by FISH
MYC	19 (47.5)	10 (22.2)	0.55	50.1	0.05
BCL2	15 (37.5)	5 (11.1)	0.65	39.8	0.05
BCL6	10 (25.0)	4 (8.9)	0.44	5.2	0.57
Previous systemic therapy regimen
R-CHOP	19 (47.5)	44 (97.8)	1.37	86.5	0.91
R-EPOCH	18 (45.0)	1 (2.2)	1.17	13.5	0.74
Best response to two cycles of previous systemic therapy
Partial response (PR)	21 (52.5)	36 (80.0)	0.61	47.5	0.10
Stable disease (SD)	2 (5.0)	2 (4.4)	0.03	10.1	0.19
Progressive disease (PD)	16 (40.0)	7 (15.6)	0.57	42.4	0.05
Inevaluable (NE)	1 (2.5)	0 (-)	0.23	-	0.23
Previous radiotherapy	2 (5.0)	0 (-)	0.32	-	0.32
Abbreviations: SMC-LCS, Samsung medical center – lymphoma cohort study; MAIC, matching adjusted indirect comparison; aSD, absolute standardized difference; HGBL, high-grade B-cell lymphoma; DLBCL, diffuse large B-cell lymphoma; ECOG, eastern cooperative oncology group performance status; IPI, international prognostic index; FISH, fluorescence in situ hybridization; R-CHOP, rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone; R-EPOCH, rituximab, etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin. *Matching adjusted indirect comparison weighting based on the following categorical variables: age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1), disease stage (I/II or III/IV), IPI total score (1/2 or ≥ 3), Deauville five point scale (4 or 5).

Of 37 patients included in the efficacy analysis of ZUMA-12, median PFS was not reached. Median PFS in external comparator arm was 5.6 months, which decreased to 2.7 months after weighting. Compared to the treatments received by the external comparator arm, axi-cel demonstrated substantial improvement in PFS, both before (HR 0.29 [95% CI 0.13–0.63]) and after weighting (MAIC-adjusted HR 0.23 [0.11–0.46]) (Table 2; Fig. 2a).

Table 2

Indirect comparison of PFS and OS between ZUMA-12 and external comparator (SMC-LCS)
Endpoint	ZUMA-12* (N = 37)	SMC-LCS (N = 45)
Endpoint	ZUMA-12* (N = 37)	Before MAIC	After MAIC^†
PFS
Median (IQR), month	NR	5.6 (2.6–36.5)	2.7 (1.9–57.5)
Event rate (%)	8 (21.6)	27 (60.0)	65.4
HR (95% CI)	-	0.29 (0.13–0.63)	0.23 (0.11–0.46)
OS
Median (IQR), month	24.5	18.9 (10.9–36.5)	14.7 (9.5–57.5)
Event rate (%)	5 (13.5)	19 (42.2)	49.5
HR (95% CI)	-	0.41 (0.15–1.10)	0.30 (0.13–0.73)
Abbreviations: PFS, progression free survival; OS, overall survival; SMC-LCS, Samsung medical center – lymphoma cohort study; IQR, interquartile range; NR, not reached, HR, hazard ratio; CI, confidence interval. *Of 40 patients enrolled in ZUMA-12, 37 were included in the efficacy analysis. ^†Matching adjusted indirect comparison weighting based on the following categorical variables: age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1), disease stage (I/II or III/IV), IPI total score (1/2 or ≥ 3), Deauville five point scale (4 or 5).

By the end of study period, all-cause mortality rates were 13.5% for ZUMA-12 and 42.2% for external comparator arm (49.5% after weighting). Median OS of ZUMA-12 was 24.5 months, substantially longer than the 18.9 months (14.7 months after weighting) of external comparator arm. This corresponded to a lower hazard of death for axi-cel, with MAIC-adjusted HR of 0.30 (95% CI 0.13–0.73) (Table 2; Fig. 2b).

In the sensitivity analysis, MAIC model using Deauville five-point scale showed the best balancing performance with an average aSD of 0.25, followed by ECOG score (0.32), IPI total score (0.33) and disease stage (0.37) (Table 3). Axi-cel was consistently associated with lower hazards of disease progression and death, compared with the weighted external comparator arm, across all models (Table 4).

Table 3

Comparison of average baseline characteristics of ZUMA-12 and external comparator arm (SMC-LCS) according to different sets of variables for MAIC weighting
Characteristic	ZUMA-12 (N = 40)	SMC-LCS after MAIC (N = 45), %
Characteristic	ZUMA-12 (N = 40)	Main analysis^a	aSD	MAIC Model 1^b	aSD	MAIC Model 2^c	aSD	MAIC Model 3^d	aSD	MAIC Model 4^e	aSD	MAIC Model 5^f	aSD
Mean aSD			0.19		0.37		0.32		0.37		0.33		0.25
Age, median (range), yrs	61 (23–86)	63 (34–83)		61 (34–83)		61 (34–83)		61 (34–83)		60 (34–83)		63 (34–83)
≥ 65 years, n (%)	15 (37.5)	37.5	0	37.5	0	37.5	0	37.5	0	37.5	0	37.5	0
Male sex	27 (67.5)	67.5	0	67.5	0	67.5	0	67.5	0	67.5	0	67.5	0
Histological disease type
HGBL (NOS, double or triple hit)	18 (45.0)	45.0	0	45.0	0	45.0	0	45.0	0	45.0	0	45.0	0
DLBCL, NOS	22 (55.0)	55.0	0	55.0	0	55.0	0	55.0	0	55.0	0	55.0	0
ECOG score of 1	25 (62.5)	62.5	0	41.4	0.43	62.5	0	41.6	0.43	51.2	0.23	51.5	0.22
Disease stage
I or II	2 (5.0)	5.0	0	5.3	0.01	3.4	0.08	5.0	0	5.2	0.01	7.4	0.10
III or IV	38 (95.0)	95.0	0	94.7	0.01	96.6	0.08	95.0	0	94.8	0.01	92.6	0.10
IPI total score
1 or 2	9 (22.5)	22.5	0	6.2	0.48	8.6	0.39	6.2	0.48	22.5	0	3.8	0.58
≥ 3	31 (77.5)	77.5	0	93.8	0.48	91.4	0.39	93.8	0.48	77.5	0	96.2	0.58
Deauville five point scale
4	19 (47.5)	47.5	0	82.6	0.79	79.4	0.70	82.7	0.79	85.0	0.86	47.5	0
5	21 (52.5)	52.5	0	17.4	0.79	20.6	0.70	17.3	0.79	15.0	0.86	52.5	0
Bone marrow assessment
Lymphoma present	10 (25.0)	21.3	0.09	30.5	0.12	30.9	0.13	30.6	0.12	21.8	0.08	35.3	0.23
Double or triple hit status by FISH and IPI total score
Double or triple hit and IPI ≥ 3	4 (10.0)	27.6	0.46	40.5	0.75	37.5	0.68	40.5	0.75	23.9	0.38	45.7	0.87
Double or triple hit only	6 (15.0)	22.5	0.19	6.2	0.29	8.6	0.20	6.2	0.29	22.5	0.19	3.8	0.39
IPI ≥ 3 only	27 (67.5)	49.9	0.36	53.4	0.29	53.9	0.28	53.3	0.29	53.6	0.29	50.5	0.35
Double expression	13 (32.5)	20.3	0.28	16.6	0.38	16.5	0.38	16.7	0.37	15.6	0.40	18.4	0.33
c-Myc expression	21 (52.5)	76.2	0.51	78.9	0.58	77.7	0.55	79.1	0.58	78.2	0.56	76.2	0.51
Alterations by FISH
MYC	19 (47.5)	50.1	0.05	46.7	0.02	46.1	0.03	46.7	0.02	46.4	0.02	49.5	0.04
BCL2	15 (37.5)	39.8	0.05	25.6	0.26	28.4	0.19	25.6	0.26	33.7	0.08	32.7	0.10
BCL6	10 (25.0)	5.2	0.57	19.4	0.13	16.6	0.21	19.4	0.13	11.2	0.36	12.3	0.33
Previous systemic therapy regimen
R-CHOP	19 (47.5)	86.5	0.91	93.8	1.18	91.4	1.08	93.8	1.18	96.9	1.32	79.6	0.71
R-EPOCH	18 (45.0)	13.5	0.74	6.2	0.99	8.6	0.90	6.2	0.99	3.1	1.12	20.4	0.54
Best response to two cycles of previous systemic therapy
Partial response (PR)	21 (52.5)	47.5	0.10	82.6	0.68	79.4	0.59	82.7	0.68	85.0	0.75	47.5	0.10
Stable disease (SD)	2 (5.0)	10.1	0.19	2.8	0.11	3.1	0.10	2.8	0.11	2.9	0.11	8.1	0.12
Progressive disease (PD)	16 (40.0)	42.4	0.05	14.6	0.60	17.5	0.51	14.5	0.60	12.1	0.67	44.4	0.09
Inevaluable (NE)	1 (2.5)	-	0.23	-	0.23	-	0.23	-	0.23	-	0.23	-	0.23
Previous radiotherapy	2 (5.0)	-	0.32	-	0.32	-	0.32	--	0.32	--	0.32	--	0.32
Abbreviations: SMC-LCS, Samsung medical center – lymphoma cohort study; MAIC, matching adjusted indirect comparison; aSD, absolute standardized difference; HGBL, high-grade B-cell lymphoma; DLBCL, diffuse large B-cell lymphoma; ECOG, eastern cooperative oncology group performance status; IPI, international prognostic index; FISH, fluorescence in situ hybridization; R-CHOP, rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone; R-EPOCH, rituximab, etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin. ^a Main analysis: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1), disease stage (I/II or III/IV), IPI total score (1/2 or ≥ 3), Deauville five point scale (4 or 5). ^b Model 1: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL). ^c Model 2: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1). ^d Model 3: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), disease stage (I/II or III/IV). ^e Model 4: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), IPI total score (1/2 or ≥ 3). ^f Model 5: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), Deauville five point scale (4 or 5).

Table 4

Indirect comparison of PFS and OS between ZUMA-12 and external comparator arm (SMC-LCS) according to different sets of variables for MAIC weighting
Endpoint	Median (IQR), month	Event rate, %	HR (95% CI)
PFS
ZUMA-12 (N = 37)*	NR	21.6	Ref.
SMC-LCS (N = 45)
Before MAIC	5.6 (2.6–36.5)	60.0	0.29 (0.13–0.63)
After MAIC
Main analysis^a	2.7 (1.9–57.5)	65.4	0.23 (0.11–0.46)
Model 1^b	6.7 (2.6–45.0)	55.8	0.32 (0.15–0.65)
Model 2^c	5.6 (2.4–45.0)	57.2	0.30 (0.15–0.62)
Model 3^d	5.6 (2.6–45.0)	55.9	0.31 (0.16–0.64)
Model 4^e	25.4 (4.3–59.0)	46.7	0.41 (0.20–0.84)
Model 5^f	2.6 (1.6–18.9)	74.3	0.18 (0.09–0.37)
OS
ZUMA-12 (N = 37)	24.5	13.5	Ref.
SMC-LCS (N = 45)
Before MAIC	18.9 (10.9–36.5)	42.2	0.41 (0.15–1.10)
After MAIC
Main analysis^a	14.7 (9.5–57.5)	49.5	0.30 (0.13–0.73)
Model 1^b	18.9 (11.1–45.0)	43.3	0.39 (0.15–0.96)
Model 2^c	16.0 (10.9–45.0)	47.8	0.34 (0.14–0.84)
Model 3^d	18.9 (11.1–45.0)	43.3	0.38 (0.16–0.93)
Model 4^e	31.1 (11.5–59.0)	34.1	0.53 (0.21–1.32)
Model 5^f	11.5 (7.0-27.4)	60.3	0.22 (0.09–0.53)
Abbreviations: PFS, progression free survival; OS, overall survival; SMC-LCS, Samsung medical center – lymphoma cohort study; IQR, interquartile range; NR, not reached, HR, hazard ratio; CI, confidence interval. *Of 40 patients enrolled in ZUMA-12, 37 were included in the efficacy analysis. ^a Main analysis: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1), disease stage (I/II or III/IV), IPI total score (1/2 or ≥ 3), Deauville five point scale (4 or 5). ^b Model 1: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL). ^c Model 2: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), ECOG score (0 or 1). ^d Model 3: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), disease stage (I/II or III/IV). ^e Model 4: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), IPI total score (1/2 or ≥ 3). ^f Model 5: MAIC weighting based on age (< 65 or ≥ 65 years), sex (male or female), histological disease type (HGBL or DLBCL), Deauville five point scale (4 or 5).

In the present study, we leveraged real-world data as a source for external comparator to present clinically meaningful evidence on the comparative effectiveness of axi-cel for treatment of high-risk LBCL. This was done by using indirect comparison method to compare published summary data of ZUMA-12 and IPD of SMC-LCS, adjusting for imbalance in the important prognostic factors of treatment outcomes between the two population. We found that axi-cel therapy led to more than 70% reduction in the risk of disease progression and death, compared with the conventional therapies received by patients with high-risk LBCL from routine care setting in South Korea.

High-risk LBCL represents the highest unmet need in LBCL as patients with high-risk LBCL have poor prognosis with the current frontline treatment regimens (19). In a retrospective analysis of the Canadian lymphoid cancer database, MYC rearrangement was associated with inferior PFS (HR 3.28 [95% CI 1.49–7.21]) and OS (2.98 [1.28–6.95]) among LBCL patients treated with R-CHOP (20). Several alternative treatment strategies including dose-escalating regimens and/or consolidation with hematopoietic stem cell transplantation have been proposed for this high-risk group but with modest efficacy (21). Of 129 cases of high-grade LBCL (i.e., double-hit lymphoma; translocation of MYC plus BCL2 and/or BCL6) in the US MD Anderson Cancer Center, those treated with R-hyper-CVAD (rituximab, hyperfractionated cyclophosphamide, vincristine, doxorubicin and dexamethasone) had better CR rate of 68% vs. 40% with R-CHOP, whereas no significant difference was observed for OS (22). In the Alliance/CALGB 50303 trial, CR rates among who received dose-adjusted R-EPOCH or R-CHOP as a frontline therapy for LBCL were 59% and 60%, respectively. Proportion with high-risk LBCL was low in this trial, with only 37% having IPI score of ≥ 3 and 5.2% with MYC rearrangement at enrollment (23). In this context, CR rate of 78% (95% CI 62–90) from ZUMA-12 highlights the promising benefit of axi-cel as a part of frontline therapy for high-risk LBCL (9).

There is a growing number of studies using indirect comparison method to better understand the findings from single arm trials that are increasingly being submitted as pivotal evidence for accelerated product approval. This is especially noticeable in the therapeutic area for CAR T-cell therapies, with the real-world data serving as a source for external comparator to demonstrate comparative effectiveness of the CAR T-cell therapies. In a recent indirect comparison study on CAR T-cell therapy, patients with r/r follicular lymphoma who received axi-cel from ZUMA-5 (NCT03105336) (24), compared with those treated in a routine care setting (SCHOLAR-5; International, multicohort retrospective non-Hodgkin lymphoma research), had substantial improvement in OS (HR 0.42 [95% CI, 0.21–0.83]) and PFS (HR 0.30 [95% CI, 0.18–0.49]) (25). Substantial survival benefit with another CAR T-cell therapy, tisagenlecleucel, was also reported from a study that compared its single arm trial (JULIET; NCT02445248) against patients treated with standard therapy from CORAL (Collaborative Trial in Relapsed Aggressive Lymphoma; NCT00137995) studies (26, 27), in which 56% improvement of OS in the intervention group was observed (HR 0.44 [95% CI, 0.32–0.59]) (28). As these studies all had IPDs from both intervention and external comparator groups, cross-trial imbalances were controlled using propensity score-based weighting methods to create the external comparator arms that resembled the CAR T-cell therapy groups.

In this study, we applied key ZUMA-12 eligibility criteria to select patients from SMC-LCS, simulating randomized controlled trial condition. As only IPD from SMC-LCS was available, we used MAIC approach to assign weight to each individual in external comparator arm to resemble the mean baseline characteristics of ZUMA-12. Overlap of the covariate distributions is reported to be a key property of population adjusted indirect comparison as it correlates with the balancing performance of MAIC (29). In our case, the overlap was poor as indicated by average aSD of 0.46 before applying MAIC. The poor overlap was partly attributed to difference in the proportions of high-risk LBCL subtypes in each group. Patients in ZUMA-12 had relatively even distribution of HGBL (i.e., double or triple hit lymphoma) and high-risk LBCL (i.e., IPI total score ≥ 3), whereas 80% of eligible patients in SMC-LCS were diagnosed with high-risk LBCL. As fewer patients in the external comparator arm presented with the gene rearrangements, this difference led to poor covariate overlap between the two groups, and it was certainly possible that they were at lower risk for disease progression and death, compared with ZUMA-12 patients, because the feature of HGBL such as gene rearrangements of MYC, BCL2 and BCL6 are known as poor prognostic markers for LBCL (30). Although IPI total score is also a strong predictor for long-term survival in patients with LBCL, the two components of IPI (age and performance status) might not reflect biological aggressiveness of LBCL compared to gene rearrangements (31). Left-shift of risk estimate (i.e., HR favoring axi-cel) after adjusting for these imbalances in the key prognostic markers suggests patients from ZUMA-12 were at higher risk for poor prognosis at enrollment and before receiving the treatment. Thus, even though the ZUMA-12 group had a greater number of patients with high-risk than external comparator group, our comparison has shown the superior outcome of axi-cel to that of conventional treatments. The substantial survival benefit conferred by axi-cel is a promising finding to patients with high-risk LBCL for whom response to the existing frontline therapies are poor. Moreover, in a recent phase 3 randomized controlled trial on patients with r/r LBCL, the magnitude of survival benefit demonstrated by axi-cel (HR for PFS 0.49 [95% CI 0.37–0.65]), compared with the investigator-selected standard care chemotherapies, was comparable to that observed in our study (32). Along with this, our study further supports axi-cel as a frontline therapy for high-risk LBCL.

The main strength of this study was the use of external comparator derived from real-world data to aid in interpretating the findings from single arm trial. Despite the absence of IPD from ZUMA-12, we implemented MAIC approach in effort to produce unbiased risk estimates for OS and PFS associated with axi-cel therapy. However, limitations related to non-randomized analysis need to be considered when interpretating this study’s findings. First, only the variables included in MAIC model were balanced between the two groups, and residual confounding by the remaining unbalanced variables cannot be ruled out. Although these would favor treatment outcomes toward external comparator arm and thus likely to underestimate the survival benefit associated with axi-cel therapy, our findings supported the benefit of early use of axi-cel for the management of high-risk LBCL as mentioned earlier. Second, poor overlap of the covariates may have resulted in an extreme weight assigned to the selected individuals from external comparator arm to resemble ZUMA-12 population. Large reduction in effective sample size (ESS), which can be calculated from the MAIC weights, is an indicator for poor covariate overlap (29). In our case, ESS was 15.3 after MAIC, which means that the comparison was dependent on those selected individuals from the 45 patients in external comparator arm. To overcome this limitation, future studies with larger population pool for external comparator setup are needed to address the poor covariate overlap.

In conclusion, we used real-world data as a source for external comparator to explore comparative effectiveness of axi-cel for treatment of high-risk LBCL. As IPD of published single arm trial is not readily accessible, we made indirect comparison between the published summary data of ZUMA-12 and IPD of SMC-LCS using MAIC. This method enabled us to account for the differences of clinical characteristics between the two group by creating weighted comparator arm that would resemble ZUMA-12 population characteristics. Our finding supports axi-cel therapy over the existing chemotherapies for treating patients with high-risk LBCL who show incomplete response with the first two cycles of frontline chemotherapies.

Authorship Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Competing Interests

J.Y.S. received grants from the Ministry of Food and Drug Safety, the Ministry of Health and Welfare, the National Research Foundation of Korea and pharmaceutical companies, including Pfizer, UCB, and Yuhan, outside the submitted work. Others declare no competing interests.

Acknowledgments

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI22C0999).

Data Availability Statement

No additional data available. Data cannot be made publicly available for ethical and legal reasons, that is public availability would compromise patient confidentiality as data tables list single counts of individuals rather than aggregated data.

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There is NO conflict of interest to disclose.

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Effectiveness of axicabtagene ciloleucel versus conventional treatments as first-line therapy for high-risk large B-cell lymphoma: an external comparator study

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