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. 2025 Jun 2;15:19300. doi: 10.1038/s41598-025-05053-6

Potential surrogate endpoint for B-cell hematologic malignancy: A systematic review and meta-analysis

Satoshi Hirano 1, Keisuke Hanada 2, Hideki Maeda 1,✉
PMCID: PMC12130302  PMID: 40456850

Abstract

Confirming the patient benefit of progression-free survival (PFS) in B-cell non-Hodgkin lymphoma (B-NHL) and multiple myeloma (MM) has become increasingly challenging due to the improved outcomes brought by novel therapies. In parallel, the U.S. Food and Drug Administration recommends conducting randomized trials, focusing on evaluating early endpoints to compare study and control arms for accelerated approval (AA). From both the clinical and regulatory perspectives, identifying early surrogate endpoints for PFS is imperative. In principle, the complete response rate (CRR) is a potential early endpoint for granting AA. This study aimed to evaluate whether the CRR is a surrogate early endpoint for PFS in patients with B-cell malignancies. We investigated the results of randomized trials with data on CRR and PFS using a combined approach of PubMed and Clinical Trial.gov (CTG), identifying 52 trials after applying exclusion criteria. A meta-regression plot showed a significant correlation between the CRR and PFS with an R-squared of 0.822 in 13 trials of aggressive B-NHL, 0.941 in the 8 trials of indolent N-NHL and 0.492 in the 31 trials of MM. This meta-analysis suggests that the CRR can be considered an early surrogate endpoint for PFS in B-NHL and MM.

Keywords: Lymphomas, Multiple myeloma, Meta analysis

Subject terms: Haematological cancer, Scientific data

Introduction

Progression-free survival (PFS) has traditionally been a common primary endpoint in confirmatory trials of approved drugs in aggressive B-cell non-Hodgkin lymphoma (aB-NHL), indolent B-NHL (iB-NHL), and multiple myeloma (MM)1. However, confirming the patient benefit of PFS in these diseases has become increasingly challenging as novel therapies have improved their outcome2–5. Two-year PFS using approved regimens of polatuzumab vedotin with rituximab and chemotherapy in treatment-naïve aB-NHL2 and daratumumab with lenalidomide and dexamethasone in treatment-naïve MM was reported to be over 70%3,4. In treatment-naïve patients with iB-NHL, 2-year PFS was > 80% in both the study arm of rituximab with lenalidomide and the control arm of rituximab with chemotherapy5.

The response rate has traditionally been regarded as an early endpoint for accelerated approval (AA) in the U.S. and conditional approval (CA) in the EU in the field of oncology, including B-cell malignancy1,6. Positive response rates from single-arm trials have, to date, fulfilled the criteria for granting AA or CA; however, the U.S. Food and Drug Administration (FDA) issued draft guidance on “Clinical Trial Considerations to Support Accelerated Approval of Oncology Therapeutics” in 20237. The FDA recommended pharmaceutical companies demonstrate comparative results in a randomized trial to obtain AA. The guidance document also addresses the “one-trial approach,” which requires a new therapeutic arm to be evaluated and compared with the control arm at early (e.g., response rate) and late endpoints (e.g., PFS). When a positive result is achieved at an early endpoint, a new therapy can be applied for AA. In this context, overall response rate (ORR) is a candidate for early endpoints in randomized trials for AA. However, because of recent advances in therapies, a high ORR has been observed in the study and control arms; therefore, a more stringent early endpoint might be necessary for the development of future therapies2,3,5.

Complete response rate (CRR) is a potential early endpoint for AA1. A report suggested that CRR serves as a surrogate endpoint for PFS in untreated diffuse large B-cell lymphoma (DLBCL), a subtype of aB-NHL, in a CD20 antibody-based regimen8. However, the precedents were limited; the only example of AA granted based on CRR in a randomized trial in DLBCL is polatuzumab vedotin in combination with bendamustine and rituximab9. In MM, CRR was also reported as a candidate for a surrogate endpoint for PFS in a subpopulation of the treatment-naïve population10.

This study evaluated CRR as a surrogate endpoint for PFS in B-cell lymphoma and MM using a meta-analysis approach.

Results

As a result of exploring phase 2 or 3 trials with start dates from January 2000 to December 2023 in CTG, 3778 trials were identified for non-Hodgkin lymphoma, DLBCL, mantle cell lymphoma (MCL), follicular lymphoma, and MM. Of these, the results of 324 randomized trials are publicly available in PubMed. In total, 324 randomized trials were screened using the exclusion criteria, and 52 were subsequently analyzed (Fig. 1; Table 1).

Fig. 1.

Fig. 1

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Flow diagram of the search strategy. CTG, PubMed and Clinical Trial.gov.

Table 1.

Exclusion criteria.

Exclusion criteria No. of trials
1) Not two-arm randomized controlled trials 83
2) Outcome of CRR or HR of PFS is not available 63
3) Either arm has maintenance or consolidation therapy 56
4) Not anti-cancer drug evaluation 36
5) Not target cancer in this study 24
6) CRR was not observed in the study arm and control arm (CRR ≤ 5%) 13
7) Biosimilar evaluation 6
8) Prevention therapy 4
9) Two or more randomization 3
10) Comparison of conditioning therapy in transplant 2
Total 290
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CRR, complete response rate; PFS, progression-free survival; HR, hazard ratio

The characteristics of the 52 included trials are listed in Table 2. The trials comprised 5 phase 2 trials, 1 phase 2/3 trial, and 46 phase 3 trials. Regarding disease characteristics, 13 trials involved aB-NHL, including MCL and DLBCL; 8 trials focused on iB-NHL, including follicular lymphoma and other iB-NHLs; and 31 trials focused on MM. The study arms were categorized into several groups, primarily consisting of 45 small-molecule-containing regimens (86.5%) and 27 antibody-containing regimens (51.9%) (Table 3).

Table 2.

Characteristics of the 52 randomized trials in B-cell malignancy.

NCT number Phase Disease Study arm Control arm Number of pts in study arm Number of pts in control arm Ref.
NCT03274492 Phase3 aB-NHL Polatuzumab Vedotin with R-CHP R-CHOP 440 439 2
NCT01040871 Phase2 aB-NHL Bortezomib with R-CAP R-CHOP 84 80 11
NCT03575351 Phase3 aB-NHL Lisocabtagene maraleucel Transplant 92 92 12
NCT03570892 Phase3 aB-NHL Tisagenlecleucel Transplant 162 160 13
NCT03391466 Phase3 aB-NHL Axicabtagene Ciloleucel Transplant 180 179 14,15
NCT02703272 Phase3 aB-NHL Ibrutinib with RICE RVICI 35 16 16
NCT02285062 Phase3 aB-NHL Lenalidomide with R-CHOP R-CHOP 285 285 17
NCT01646021 Phase3 aB-NHL Ibrutinib Temsirolimus 139 141 18
NCT01287741 Phase3 aB-NHL Obinutuzumab with CHOP R-CHOP 704 710 19
NCT00722137 Phase3 aB-NHL Bortezomib with R-CAP R-CHOP 243 244 20,21
NCT00129090 Phase3 aB-NHL MegaCHOEP CHOEP-14 132 130 22,23
NCT00088530 Phase3 aB-NHL Pixantrone dimaleate Physician’s choice 70 70 24
NCT01855750 Phase3 aB-NHL Ibrutinib with R-CHOP R-CHOP 419 419 25
NCT03332017 Phase2 iB-NHL Zanubrutinib with Obinutuzumab Obinutuzumab 145 72 26
NCT00147121 Phase2/3 iB-NHL R-CHOP-14 R-CHOP-21 151 148 27
NCT02367040 Phase3 iB-NHL Copanlisib with Rituxumab Rituximab 307 151 28
NCT01974440 Phase3 iB-NHL Ibrutinib wirh BR or R-CHOP BR or R-CHOP 202 201 29
NCT01938001 Phase3 iB-NHL Lenaludomide with Rituximab Rituximab 178 180 30
NCT01200589 Phase3 iB-NHL Ofatumumab Rituximab 219 219 31
NCT01077518 Phase3 iB-NHL Ofatumumab with Bendemustine Bendemustine 173 173 32
NCT00312845 Phase3 iB-NHL Bortezomib with Rituximab Rituximab 336 340 33
NCT02252172 Phase3 MM Daratumumab with Rd Rd 368 369 3,4
NCT03336073 Phase2 MM Kd KCd 100 97 34
NCT02654132 Phase2 MM Elotuzumab with Pd Pd 60 57 35,36
NCT00531453 Phase2 MM VDTC with transplant VDT with transplant 49 49 37,38
NCT04181827 Phase3 MM Ciltacabtagene autoleucel PVd or DPd 208 211 39
NCT04162210 Phase3 MM Belantamab mafodotin Pd 218 107 40
NCT03651128 Phase3 MM Idecabtagene vicleucel Physician’s choice* 254 132 41
NCT03275285 Phase3 MM Isatuximab with Kd Kd 179 123 42
NCT03217812 Phase3 MM Daratumumab with VMP VMP 146 74 43
NCT03234972 Phase3 MM Daratumumab with Vd Vd 141 70 44
NCT03180736 Phase3 MM Daratumumab with Pd Pd 151 153 45,46
NCT03158688 Phase3 MM Daratumumab with Kd Kd 312 154 47,48
NCT02755597 Phase3 MM Venetoclax with Vd Vd 194 97 49
NCT03110562 Phase3 MM Selinexor with Vd Vd 195 207 50
NCT02412878 Phase3 MM Kd (once a week) Kd (twice a week) 240 238 51
NCT02195479 Phase3 MM Daratumumab with VMP VMP 350 356 52
NCT02136134 Phase3 MM Daratumumab with Vd Vd 251 247 53–55
NCT02076009 Phase3 MM Daratumumab with Rd Rd 286 283 56,57
NCT01734928 Phase3 MM PVd Vd 281 278 58
NCT01818752 Phase3 MM KMP VMP 478 477 59
NCT01564537 Phase3 MM Ixazomib with Rd Rd 360 362 60,61
NCT01568866 Phase3 MM Kd Vd 464 465 62,63
NCT01335399 Phase3 MM Elotuzumab with Rd Rd 374 374 64
NCT01239797 Phase3 MM Elotuzumab with Rd Rd 321 325 65,66
NCT01023308 Phase3 MM Panobinostat with Vd Vd 387 381 67,68
NCT01080391 Phase3 MM KRd Rd 396 396 69,70
NCT00773747 Phase3 MM Vorinostat with V V 317 320 71
NCT00722566 Phase3 MM V (subcutaneous) V (intravenous) 148 74 72
NCT00057564 Phase3 MM Td d 235 235 73
NCT00111319 Phase3 MM VMP MP 344 338 74,75
NCT01850524 Phase3 MM Ixazomib with Rd Rd 351 354 76
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R, Rituximab; C, Cyclophosphamide; A or H, Doxorubicin; O, Vincristine; P, Prednisolone; E, Etoposide; B, Bendamustine; K, Carfilzomib; d, Dexamethasone; P, Pomalidomide; V, Bortezomib; D, Daratumumab; T, Thalidomide; M, Melphalan; R, Lenalidomide; aB-NHL, aggressive B-cell non-Hodgkin lymphoma; iB-NHL, indolent B-cell non-Hodgkin lymphoma; MM, multiple myeloma

* For physician choice, the investigator chose treatments for patients in the control arm based on the settings of each protocol.

Table 3.

Treatment categories in the 52 trials.

Category Study arm, N (%) Control arm, N (%)
Small molecule-containing regimen 45 (86.5) 4 (84.6)
Antibody-containing regimen 27 (51.9) 17 (32.7)
ADC-containing regimen 2 (3.8) 0 (0.0)
Transplant-containing regimen 1 (1.9) 4 (7.7)
CAR-T therapy-containing regimen 5 (9.6) 0 (0.0)
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ADC, antibody-drug conjugate; CAR-T, Chimeric antigen receptor T cell therapy

The correlation between CRR difference and PFS Hazard Ratio (HR) in aB-NHL, iB-NHL and MM is shown in Fig. 2. The meta-regression plot showed a significant correlation of CRR difference and PFS HR with an R-squared of 0.822 in the 13 trials of aB-NHL, 0.941 in the 8 trials of iB-NHL and 0.492 in the 31 trials in MM. Compared to R-squared of 0.763, 0.826 and 0.26 in the correlation between ORR and PFS in aB-NHL, iB-NHL and MM, the correlation between CRR and PFS consistently had a higher R-squared value in the diseases.

Fig. 2.

Fig. 2

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Meta-regression plot comparing difference of response rate and PFS Hazard Ratio (HR). (a) CRR and PFS HR in aB-NHL, (b) ORR and PFS HR in aB-NHL, (c) CRR and PFS HR in iB-NHL, (d) ORR and PFS HR in iB-NHL, (e) CRR and PFS HR in MM, (f) ORR and PFS HR in MM.

In the context that MRD negativity has been recently considered as one of the potential early endpoints in MM, we analyzed the relationship between CRR and MRD negativity difference, and PFS HR in the 12 trials of MM which have available MRD negativity data (Fig. 3). The meta-regression plot showed similar correlation with the R-squared value between CRR and PFS and between MRD negativity and PFS (R-squared of 0.575 vs. 0.602).

Fig. 3.

Fig. 3

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Meta-regression plot in MM in the 12 trials with available MRD negativity data. (a) CRR difference and PFS HR and (b) MRD negativity and PFS HR.

Discussion

The correlation between the CRR and PFS was evaluated using a meta-analysis of 52 clinical trials. Consistent correlations with high R-squared values were observed for aB-NHL, iB-NHL, and MM (Figs. 2 and 3). This finding suggests that the CRR can be considered an early surrogate endpoint for PFS in these diseases.

PFS has traditionally been a common primary endpoint in confirmatory trials of approved drugs in aB-NHL, iB-NHL, and MM1. However, confirming the patient benefit of PFS in these diseases has become increasingly challenging as novel therapies have improved their outcome2–5.

In aB-NHL, positron emission tomography (PET)-CRR has been reported as a potential surrogate endpoint for PFS in rituximab-containing therapies in a treatment-naïve population of DLBCL8. The outcome was the HR of PFS between the PET-CRR and non-PET-CRR groups in four regimens: G-CHOP in the GATER study, G-CHOP in the GOYA study, R-CHOP in the GOYA study, and R2-CHOP in the MAYO study. Of these three trials, the GOYA study was the only trial compatible with the analysis; the GATHER and MAYO trials were not randomized controlled trials (RCTs). A direct comparison was not feasible, as they did not report quantitative differences in the CRR in their analysis; however, this study’s results are not contradictory to theirs.

In MM, response rate and minimal residual disease (MRD) negativity have been reported as potential surrogates in a subpopulation of the treatment-naïve population10. Their analysis revealed a correlation between CRR and PFS of 0.22 (unadjusted) and 0.632 (adjusted). In this context, our analysis showed a correlation with an R-squared value of 0.492 in all MM populations, including treatment-naïve and second-line or later populations, by treatments with several modes of action, including CAR-T therapies. Although a direct comparison would be challenging due to differences in populations, their results and ours are not contradictory. Recently, the possibility of an early endpoint in MM was discussed at ODAC in 2024, and MRD negativity has been considered an early endpoint in MM77,78. This trend can be interpreted against the backdrop of enhanced clinical demand for identifying a surrogate early endpoint for PFS in MM. Our analysis showed similar R-squared values between CRR and PFS, and MRD negativity and PFS in the pooled analysis by using the data in the 12 trials. The potential utilities of MRD negativity are under exploration in lymphoma and MM78,79; however, based on the flow required for complete response confirmation before testing for MRD negativity, the CRR would serve as an earlier endpoint than MRD negativity80.

Besides these clinical demands for an early endpoint, the FDA recommends conducting RCTs for filing for AA. One suggested approach is to adapt comparisons at early endpoints within a single trial7. In the one-trial approach, the trial is required to identify both the early and late primary endpoints. If an early endpoint meets the positive criteria, the result will be submitted to the FDA to grant AA in advance of confirming the late primary endpoint. This study’s findings suggest that the CRR can be adapted as an early endpoint in a single-trial approach.

This study has some limitations. First, it was based solely on publicly available data and did not include patient-level analysis. Second, tumor assessment criteria were revised for NHL and MM between 2000 and 2023, and this analysis did not assess the impact of the revision in tumor assessment81,82. Third, for the primary analysis, Egger’s test was insignificant (p = 0.9459), and the I-squared statistic was 41.54%, indicating low heterogeneity across the studies. These results suggest that publication bias was either absent or minimal.

In conclusion, this meta-analysis suggests that the CRR can be considered an early surrogate endpoint for PFS in aB-NHL, iB-NHL, and MM. The meta-regression plot showed a significant correlation between cross-disease and disease-specific populations. This finding should be interpreted in the context of improved outcomes due to novel therapies and the requirement for conducting RCTs to file for AA from a regulatory perspective.

Methods

Data analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines83.

Data collection

In this study, the results of randomized trials with data on CRR and PFS were investigated using a combined approach from PubMed and Clinical Trial.gov (CTG). The scheme is shown in Fig. 1. The data were manually collected by one person and independently reviewed by another. When the person identified the wrong number or missing data in draft data set another person had made, both had discussion and confirmed the data we should refer for this study. Clinical trials for this analysis were identified by searching CTG using the terms “non-Hodgkin lymphoma,” “diffuse large B-cell lymphoma,” “mantle cell lymphoma,” “follicular lymphoma,” or “multiple myeloma | Phase: 2, 3 | Interventional studies | Study start from 01/01/2000 to 12/31/2023|”. To narrow down the clinical trials with reported results, clinical trials were investigated by searching their NCT numbers in PubMed and randomized trials were subsequently selected. Details of the exclusion criteria for manual selection are listed in Table 1. Besides excluding trials without available data on response rate or hazard ratio (HR) for PFS, trials on maintenance therapies and conditioning therapies were also excluded. The HR of event-free survival was used as an alternative for PFS in NCT03570892 and NCT02703272 because PFS results were not available. The HR of time to progression was used as an alternative to PFS, owing to the availability of PFS data. The rate of CRR or better was used as CRR; however, CRR, including unconfirmed CRR, was adapted as CRR in NCT00129090 owing to the limited available data. In MM population, trials with available MRD negativity data were identified among the trials based on the reported results.

Statistical analysis

A meta-analysis of studies was performed to evaluate the CRR and PFS in patients with B-cell malignancies. A meta-regression analysis was conducted using the ‘metafor’ package in R, where the log HR of PFS was the dependent variable, and the difference in CRR between treatment groups was the independent variable84,85. The weighted Pearson correlation coefficients, which are the square roots of the coefficient of determination, were derived to evaluate the correlation between CRR and PFS using the ‘wCorr’ package in R (https://cran.r-project.org/web/packages/wCorr/index.html). A random-effects model was applied to account for between-study heterogeneity, which was assessed using the I-squared statistic86. Publication bias was evaluated using Egger’s regression test for funnel plot asymmetry87. Subgroup analysis was conducted for aB-NHL, iB-NHL, and MM to evaluate the relationship between CRR and PFS. In MM population, same analysis was conducted between MRD negativity and PFS.

Acknowledgements

The authors would like to thank Editage (https://www.editage.jp/) for English language editing.

Author contributions

S.H. and K.H. wrote the manuscript; S.H. and K.H. designed the research; S.H. and K.H. performed the research; K.H. analyzed the data; H.M. supervised the study.

Funding

This study was partially funded by a grant from JSPS KAKENHI (Grant Number JP 23 K11940) (Dr. Maeda).

Data availability

Data is provided within the manuscript.

Declarations

Competing interests

The authors declare no competing interests.

Institutional review board statement

This study did not require institutional review board approval or informed patient consent because it was based on publicly available information and did not involve patient records.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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