Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

An early post-transplant relapse prediction score in multiple myeloma: a large cohort study from the chronic malignancies working party of EBMT

Bone Marrow Transplantation volume 58, pages 916–923 (2023)Cite this article

Subjects

A Correction to this article was published on 14 June 2023

This article has been updated

Abstract

Early relapse (ER) following Autologous Hematopoietic Cell Transplantation (AHCT) confers a poor prognosis. We therefore developed a novel scoring system to predict ER. A total of 14,367 AHCT-1 patients were transplanted between 2014 and 2019, and were conditioned with Melphalan 200 mg/m2 (Mel200) (n = 7228; 2014–2017) (training cohort); Mel200 (n = 5616; 2018–2019) or Mel140 (n = 1523; 2018–2019) (validation cohorts). PFS-12 and the Cumulative Incidence of Relapse at 12 months were 84.1% and 14.7% (training Mel200), 87.2% and 11.6% (validation Mel200), and 80.3% and 16.9% (validation Mel140), respectively. The points in the risk score were: 0, 1,2 for ISS stages I, II, and III; Disease status: 0 (CR/VGPR); 1 (PR); 2 (SD/MR); 4 (Relapse/Progression); and 1 for Karnofsky ≤ 70. The distribution of scores: 0 (24%), 1 (33.9%), 2 (29.6 %), 3 (9.5%), and ≥4 (2.7%). The score separated PFS-12, with the lowest risk group (n = 1752) having a PFS-12 of 91.7% and the highest risk group (n = 195) 57.1%. This also applied in cytogenetically high-risk patients. If the pre-score baseline risks are 15% (standard risk) and 25% (high-risk), a score of ≥4 confers calculated risks of 38% and 54%, respectively. This novel EBMT ER score, therefore, allows for the identification of five discrete prognostic groups.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: 12-month PFS by score in the 3 cohorts.
Fig. 2: 12-month PFS by score for patients with high-risk cytogenetics in the three cohorts.
Fig. 3: Impact of early relapse score on long-term survival parameters.

Similar content being viewed by others

Data availability

The EBMT database is not open to general access per EBMT regulations.

Change history

References

  1. Attal M, Lauwers-Cances V, Hulin C, Leleu X, Caillot D, Escoffre M, et al. Lenalidomide, bortezomib, and dexamethasone with transplantation for myeloma. N Engl J Med. 2017;376:1311–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Cavo M, Gay F, Beksac M, Pantani L, Petrucci MT, Dimopoulos MA, et al. Autologous haematopoietic stem-cell transplantation versus bortezomib–melphalan–prednisone, with or without bortezomib–lenalidomide–dexamethasone consolidation therapy, and lenalidomide maintenance for newly diagnosed multiple myeloma (EMN02/HO95): a multicentre, randomised, open-label, phase 3 study. Lancet Haematol. 2020;7:e456–68.

    Article  PubMed  Google Scholar 

  3. Stadtmauer EA, Pasquini MC, Blackwell B, Hari P, Bashey A, Devine S, et al. Autologous transplantation, consolidation, and maintenance therapy in multiple myeloma: results of the BMT CTN 0702 Trial. J Clin Oncol. 2019;37:589–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Dimopoulos MA, Moreau P, Terpos E, Mateos MV, Zweegman S, Cook G, et al. Multiple myeloma: EHA-ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2021;32:309–22.

    Article  CAS  PubMed  Google Scholar 

  5. Dhakal B, Shah N, Kansagra A, Kumar A, Lonial S, Garfall A, et al. ASTCT clinical practice recommendations for transplantation and cellular therapies in multiple myeloma. Transpl Cell Ther. 2022;28:284–93.

    Article  CAS  Google Scholar 

  6. Kumar S, Mahmood ST, Lacy MQ, Diapenzieri A, Hayman SR, Buadi FK, et al. Impact of early relapse after auto-SCT for multiple myeloma. Bone Marrow Transpl. 2008;42:413–20.

    Article  CAS  Google Scholar 

  7. Kastritis E, Roussou M, Eleutherakis-Papaiakovou E, Gavriatopoulou M, Migkou M, Gika D, et al. Early relapse after autologous transplant is associated with very poor survival and identifies an ultra-high-risk group of patients with myeloma. Clin Lymphoma Myeloma Leuk. 2020;20:445–52.

    Article  PubMed  Google Scholar 

  8. Corre J, Montes L, Martin E, Perrot A, Caillot D, Leleu X, et al. Early relapse after autologous transplant for myeloma is associated with poor survival regardless of cytogenetic risk. Haematologica 2020;105:e480–3.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Bygrave C, Pawlyn C, Davies F, Craig Z, Cairns D, Hockaday A, et al. Early relapse after high‐dose melphalan autologous stem cell transplant predicts inferior survival and is associated with high disease burden and genetically high‐risk disease in multiple myeloma. Br J Haematol. 2020;193:551–5.

    Article  PubMed  Google Scholar 

  10. Lahuerta JJ, Paiva B, Vidriales MB, Cordon L, Cedena MT, Puig N, et al. Depth of response in multiple myeloma: a pooled analysis of three PETHEMA/GEM clinical trials. J Clin Oncol. 2017;35:2900–10.

    Article  CAS  PubMed  Google Scholar 

  11. Chakraborty R, Muchtar E, Kumar SK, Jevremovic D, Buadi FK, Dingli D, et al. Impact of post-transplant response and minimal residual disease on survival in myeloma with high-risk cytogenetics. Biol Blood Marrow Transpl. 2017;23:598–605.

    Article  Google Scholar 

  12. Dhakal B, D’Souza A, Callander N, Chhabra S, Fraser R, Davila O, et al. Novel prognostic scoring system for autologous hematopoietic cell transplantation in multiple myeloma. Br J Haematol. 2020;191:442–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Zaccaria GM, Bertamini L, Petrucci MT, Offidani M, Corradini P, Capra A, et al. Development and validation of a simplified score to predict early relapse in newly diagnosed multiple myeloma in a pooled dataset of 2190 patients. Clin Cancer Res Off J Am Assoc Cancer Res. 2021;27:3695–703.

    Article  CAS  Google Scholar 

  14. Harrell, FE (ed) Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. 2nd ed. Springer-Verlag, New York, 2001.

  15. Heagerty PJ, Lumley T, Pepe MS. Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics 2000;56:337–44.

    Article  CAS  PubMed  Google Scholar 

  16. Auner HW, Iacobelli S, Sbianchi G, Knol-Bout C, Blaise D, Russell NH, et al. Melphalan 140 mg/m2 or 200 mg/m2 for autologous transplantation in myeloma: results from the Collaboration to Collect Autologous Transplant Outcomes in Lymphoma and Myeloma (CALM) study. A report by the EBMT Chronic Malignancies Working Party. Haematologica 2017;103:514–21.

    Article  PubMed  Google Scholar 

  17. Cerchione C, Usmani SZ, Stewart AK, Kaiser M, Rasche L, Kortüm M, et al. Gene expression profiling in multiple myeloma: redefining the paradigm of risk-adapted treatment. Front Oncol 2022;12:820768.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Jethava Y, Mitchell A, Zangari M, Waheed S, Schinke C, Thanendrarajan S, et al. Dose-dense and less dose-intense Total Therapy 5 for gene expression profiling-defined high-risk multiple myeloma. Blood Cancer J. 2016;6:e453–e453.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Karam D, Kumar S. Post-transplant maintenance treatment options in multiple myeloma. Oncol Ther. 2021;9:69–88.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Moreau P, Attal M, Hulin C, Arnulf B, Belhadj K, Benboubker L, et al. Bortezomib, thalidomide, and dexamethasone with or without daratumumab before and after autologous stem-cell transplantation for newly diagnosed multiple myeloma (CASSIOPEIA): a randomized, open-label, phase 3 study. Lancet 2019;394:29–38.

    Article  CAS  PubMed  Google Scholar 

  21. Van de Donk NWCJ, Agha M, Cohen A, Cohen YC, Anguille S, Kerre T, et al. Biological correlative analyses and updated clinical data of ciltacabtagene autoleucel (cilta-cel), a BCMA-directed CAR-T cell therapy, in patients with multiple myeloma (MM) and early relapse after initial therapy: CARTITUDE-2, cohort B. J Clin Oncol. 2022;40:8029.

    Article  Google Scholar 

Download references

Acknowledgements

The study has been performed within the EBMT database utilizing EBMT resources. SI has performed the statistical analysis that led to this novel ER risk-calculating model.

Author information

Authors and Affiliations

  1. Ankara University, Ankara, Turkey

    Meral Beksac

  2. University of Rome Tor Vergata, Rome, Italy

    Simona Iacobelli

  3. European Society for Blood and Marrow Transplantation Leiden Study Unit, Leiden, the Netherlands

    Linda Koster

  4. Erasmus University Medical Center-Daniel Den Hoed, Rotterdam, the Netherlands

    Jan Cornelissen

  5. Vilnius University Hospital Santariskiu Clinics, Vilnius, Lithuania

    Laimonas Griskevicius

  6. University College London Hospitals NHS Foundation Trust, London, UK

    Neil K. Rabin

  7. Institute Paoli-Calmettes, Marseille, France

    Anne Marie Stoppa

  8. VU University Medical Center, Amsterdam, the Netherlands

    Ellen Meijer

  9. Centre Hospitalier Universitaire de Rennes, Rennes, France

    Jean-Baptiste Mear

  10. University Hospital of Bern, Bern, Switzerland

    Sacha Zeerleder

  11. University Hospital Brno, Brno, Czech Republic

    Jiri Mayer

  12. University Hospital Duesseldorf, Dusseldorf, Germany

    Roland Fenk

  13. CHU Lapeyronie, Montpellier, France

    Nathalie Fegueux

  14. CHU Nantes, Nantes, France

    Patrice Chevallier

  15. Charles University, Prague, Czech Republic

    Eva Konirova

  16. Sheffield Teaching Hospitals NHS Trust, Sheffield, UK

    John A. Snowden

  17. University Medical Center Freiburg, Freiburg, Germany

    Monika Engelhardt

  18. University Hospital Southampton NHS Foundation Trust, Southampton, UK

    Kim Orchard

  19. CHU Bordeaux, Pessac, France

    Cyrille Hulin

  20. Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands

    Nicolaas Schaap

  21. Clinica FOSCAL, Floridablanca, Santander, Colombia

    Claudia Sossa

  22. Universidad Autónoma de Bucaramanga - UNAB, Bucaramanga, Santander, Colombia

    Claudia Sossa

  23. Asklepios Klinik St. Georg, Hamburg, Germany

    Ahmet Elmaagacli

  24. Queen’s University Belfast, Marseille, France

    Donal P. McLornan

  25. Department of Haematology, School of Medicine, Trinity College Dublin, Dublin, Ireland

    Patrick J. Hayden

  26. University of Heidelberg, Heidelberg, Germany

    Stefan Schönland

  27. CHU de Lille, Univ Lille, Infinite, Lille, France

    Ibrahim Yakoub-Agha

Authors
  1. Meral Beksac
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Simona Iacobelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Linda Koster
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jan Cornelissen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Laimonas Griskevicius
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Neil K. Rabin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Anne Marie Stoppa
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ellen Meijer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jean-Baptiste Mear
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Sacha Zeerleder
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jiri Mayer
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Roland Fenk
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Nathalie Fegueux
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Patrice Chevallier
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Eva Konirova
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. John A. Snowden
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Monika Engelhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Kim Orchard
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Cyrille Hulin
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Nicolaas Schaap
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Claudia Sossa
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Ahmet Elmaagacli
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Donal P. McLornan
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Patrick J. Hayden
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Stefan Schönland
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Ibrahim Yakoub-Agha
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MB planned the study and wrote the manuscript, LK prepared the study-specific EBMT database which was presented to SI who performed the statistical analysis and modeled the early relapse score; SI, PH, and IYA contributed to the manuscript preparation; all authors contributed to data enrollment and revised manuscript.

Corresponding author

Correspondence to Meral Beksac.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

The original online version of this article was revised: The affiliations for Dr Claudia Sossa were incomplete and has now been corrected.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Beksac, M., Iacobelli, S., Koster, L. et al. An early post-transplant relapse prediction score in multiple myeloma: a large cohort study from the chronic malignancies working party of EBMT. Bone Marrow Transplant 58, 916–923 (2023). https://doi.org/10.1038/s41409-023-01999-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41409-023-01999-1

Search

Advanced search

Quick links