Skip to main content
SpringerLink
Log in

Development and validation of a novel risk stratification model and a survival rate calculator for diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study

  • Original Article
  • Published:
Annals of Hematology Aims and scope Submit manuscript

Abstract

Background

This study aimed to develop and validate a novel risk stratification model and a web-based survival rate calculator to improve discriminative and predictive accuracy for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.

Methods

We retrospectively collected pre-treatment data from 873 primary DLBCL patients who received R-CHOP-based immunochemotherapy regimens at the Cancer Hospital, Chinese Academy of Medical Sciences, from January 1, 2005, to December 31, 2018. An independent cohort of 175 DLBCL patients from Fujian Cancer Hospital was used for external validation.

Findings

Age, ECOG PS, number of extranodal sites, Ann Arbor stage, bulky disease, and LDH levels were screened to develop the nomogram and web-based survival rate calculator. The C-index of the nomogram in the training, internal validation, and external validation cohorts was 0.761, 0.758, and 0.768, respectively. The risk stratification model generated based on the nomogram effectively stratified patients into three distinct risk groups. K-M survival curves demonstrated that the novel risk stratification model exhibited a superior level of predictive accuracy compared to IPI, R-IPI, and NCCN-IPI both in training and two validation cohorts. Additionally, the area under the curve (AUC) value of the novel model (0.763) for predicting 5-year overall survival rates was higher than those of IPI (0.749), R-IPI (0.725), and NCCN-IPI (0.727) in the training cohort. Similar results were observed in both internal and external validation cohort.

Conclusions

In conclusion, we have successfully developed and validated a novel risk stratification model and a web-based survival rate calculator that demonstrated superior discriminative and predictive accuracy compared to IPI, R-IPI, and NCCN-IPI in the rituximab era.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

DLBCL :

Diffuse large B-cell lymphoma

NHL :

Non-Hodgkin lymphoma

R-CHOP :

Rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone

IPI :

International Prognostic Index

R-IPI :

Revised International Prognostic Index

NCCN-IPI :

National Comprehensive Cancer Network International Prognostic Index

CBC :

Complete blood cell

CHCAMS :

Cancer Hospital, Chinese Academy of Medical Sciences

FJCH :

Fujian Cancer Hospital

DLBCL-NOS :

Diffuse large B-cell lymphoma, not otherwise specified

ECOG :

Eastern Cooperative Oncology

PS :

Performance status

LDH :

Lactate dehydrogenase

GCB :

Germinal center B-cell type

HBV :

Hepatitis B virus

CI :

Confidence interval

HR :

Hazard ratio

OS :

Overall survival

GCB :

Germinal center B-cell-like

LASSO :

Absolute shrinkage and selection operator

AUC :

Area under the curve

ROC :

Receiver operating characteristic curve

CI :

Confidence intervals

DCA :

Decision curve analysis

ASH :

American Society of Hematology

GELA :

Groupe d’Etude des Lymphomes de l’Adulte

MInT :

MabThera International Trial Group

References

  1. Teras L et al (2016) 2016 US lymphoid malignancy statistics by World Health Organization subtypes. CA: Cancer J Clin 66:443–459. https://doi.org/10.3322/caac.21357

    Article  PubMed  Google Scholar 

  2. Tilly H et al (2022) Polatuzumab vedotin in previously untreated diffuse large B-cell lymphoma. N Engl J Med 386:351–363. https://doi.org/10.1056/NEJMoa2115304

    Article  PubMed  CAS  Google Scholar 

  3. Friedberg J (2011) Relapsed/refractory diffuse large B-cell lymphoma. Hematology 2011:498–505. https://doi.org/10.1182/asheducation-2011.1.498

    Article  PubMed  Google Scholar 

  4. (1993) A predictive model for aggressive non-Hodgkin’s lymphoma. N Eng J Med 329:987–994. https://doi.org/10.1056/nejm199309303291402

  5. Sehn L et al (2007) The revised International Prognostic Index (R-IPI) is a better predictor of outcome than the standard IPI for patients with diffuse large B-cell lymphoma treated with R-CHOP. Blood 109:1857–1861. https://doi.org/10.1182/blood-2006-08-038257

    Article  PubMed  CAS  Google Scholar 

  6. Zhou Z et al (2014) An enhanced International Prognostic Index (NCCN-IPI) for patients with diffuse large B-cell lymphoma treated in the rituximab era. Blood 123:837–842. https://doi.org/10.1182/blood-2013-09-524108

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Alizadeh A et al (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403:503–511. https://doi.org/10.1038/35000501

    Article  PubMed  CAS  Google Scholar 

  8. Chapuy B et al (2018) Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes. Nat Med 24:679–690. https://doi.org/10.1038/s41591-018-0016-8

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Malumbres R et al (2008) Paraffin-based 6-gene model predicts outcome in diffuse large B-cell lymphoma patients treated with R-CHOP. Blood 111:5509–5514. https://doi.org/10.1182/blood-2008-02-136374

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Alizadeh A et al (2011) Prediction of survival in diffuse large B-cell lymphoma based on the expression of 2 genes reflecting tumor and microenvironment. Blood 118:1350–1358. https://doi.org/10.1182/blood-2011-03-345272

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Schmitz R et al (2018) Genetics and pathogenesis of diffuse large B-cell lymphoma. N Engl J Med 378:1396–1407. https://doi.org/10.1056/NEJMoa1801445

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Lossos I et al (2004) Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N Engl J Med 350:1828–1837. https://doi.org/10.1056/NEJMoa032520

    Article  PubMed  CAS  Google Scholar 

  13. Qin Y et al (2021) BCL2Prognostic value of and genetic alterations for diffuse large B-cell lymphoma patients treated with R-CHOP. Cancer Biol Med. https://doi.org/10.20892/j.issn.2095-3941.2021.0193

    Article  PubMed  PubMed Central  Google Scholar 

  14. Adams H, Nievelstein R, Kwee T (2015) Prognostic value of complete remission status at end-of-treatment FDG-PET in R-CHOP-treated diffuse large B-cell lymphoma: systematic review and meta-analysis. Br J Haematol 170:185–191. https://doi.org/10.1111/bjh.13420

    Article  PubMed  CAS  Google Scholar 

  15. Wright G et al (2020) A probabilistic classification tool for genetic subtypes of diffuse large B cell lymphoma with therapeutic implications. Cancer Cell 37:551-568.e514. https://doi.org/10.1016/j.ccell.2020.03.015

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Scott D et al (2015) Prognostic significance of diffuse large B-cell lymphoma cell of origin determined by digital gene expression in formalin-fixed paraffin-embedded tissue biopsies. J Clin Oncol 33:2848–2856. https://doi.org/10.1200/jco.2014.60.2383

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Johnson N et al (2012) Concurrent expression of MYC and BCL2 in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone. J Clin Oncol 30:3452–3459. https://doi.org/10.1200/jco.2011.41.0985

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Wilcox R et al (2011) The absolute monocyte and lymphocyte prognostic score predicts survival and identifies high-risk patients in diffuse large-B-cell lymphoma. Leukemia 25:1502–1509. https://doi.org/10.1038/leu.2011.112

    Article  PubMed  CAS  Google Scholar 

  19. Bento L et al (2020) New prognosis score including absolute lymphocyte/monocyte ratio, red blood cell distribution width and beta-2 microglobulin in patients with diffuse large B-cell lymphoma treated with R-CHOP: Spanish Lymphoma Group Experience (GELTAMO). Br J Haematol 188:888–897. https://doi.org/10.1111/bjh.16263

    Article  PubMed  CAS  Google Scholar 

  20. Cheng C et al (2020) Hepatitis B surface antigen positivity is an independent unfavorable prognostic factor in diffuse large B-cell lymphoma in the rituximab era. Oncologist 25:793–802. https://doi.org/10.1634/theoncologist.2019-0756

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Wei Y et al (2020) Albumin improves stratification in the low IPI risk patients with diffuse large B-cell lymphoma. Int J Hematol 111:681–685. https://doi.org/10.1007/s12185-020-02818-9

    Article  PubMed  CAS  Google Scholar 

  22. Luan C, Wang F, Wei N, Chen B (2020) Prognostic nutritional index and the prognosis of diffuse large b-cell lymphoma: a meta-analysis. Cancer Cell Int 20:455. https://doi.org/10.1186/s12935-020-01535-x

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Cai J et al (2021) A nomogram prognostic index for risk-stratification in diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study. Br J Cancer 125:402–412. https://doi.org/10.1038/s41416-021-01434-6

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Wang J, Zhou M, Zhou R, Xu J, Chen B (2020) Nomogram for predicting the overall survival of adult patients with primary gastrointestinal diffuse large B cell lymphoma: a SEER-based study. Front Oncol 10:1093. https://doi.org/10.3389/fonc.2020.01093

    Article  PubMed  PubMed Central  Google Scholar 

  25. Wight J, Chong G, Grigg A, Hawkes E (2018) Prognostication of diffuse large B-cell lymphoma in the molecular era: moving beyond the IPI. Blood Rev 32:400–415. https://doi.org/10.1016/j.blre.2018.03.005

    Article  PubMed  CAS  Google Scholar 

  26. Wu G, Keating A (2006) Biomarkers of potential prognostic significance in diffuse large B-cell lymphoma. Cancer 106:247–257. https://doi.org/10.1002/cncr.21586

    Article  PubMed  CAS  Google Scholar 

  27. Touijer K, Scardino P (2009) Nomograms for staging, prognosis, and predicting treatment outcomes. Cancer 115:3107–3111. https://doi.org/10.1002/cncr.24352

    Article  PubMed  Google Scholar 

  28. De Paepe P, De Wolf-Peeters C (2007) Diffuse large B-cell lymphoma: a heterogeneous group of non-Hodgkin lymphomas comprising several distinct clinicopathological entities. Leukemia 21:37–43. https://doi.org/10.1038/sj.leu.2404449

    Article  PubMed  CAS  Google Scholar 

  29. Hong F, Kahl B, Gray R (2013) Incremental value in outcome prediction with gene expression-based signatures in diffuse large B-cell lymphoma. Blood 121:156–158. https://doi.org/10.1182/blood-2012-08-450106

    Article  PubMed  CAS  Google Scholar 

  30. Jelicic J, Larsen T, Maksimovic M, Trajkovic G (2019) Available prognostic models for risk stratification of diffuse large B cell lymphoma patients: a systematic review. Crit Rev Oncol Hematol 133:1–16. https://doi.org/10.1016/j.critrevonc.2018.10.006

    Article  PubMed  Google Scholar 

  31. Rodríguez J et al (1992) A proposal for a simple staging system for intermediate grade lymphoma and immunoblastic lymphoma based on the ‘tumor score’. Ann Oncol 3:711–717. https://doi.org/10.1093/oxfordjournals.annonc.a058324

    Article  PubMed  Google Scholar 

  32. Danieu L, Wong G, Koziner B, Clarkson B (1986) Predictive model for prognosis in advanced diffuse histiocytic lymphoma. Can Res 46:5372–5379

    CAS  Google Scholar 

  33. Hoskins P, Ng V, Spinelli J, Klimo P, Connors J (1991) Prognostic variables in patients with diffuse large-cell lymphoma treated with MACOP-B. J Clin Oncol 9:220–226. https://doi.org/10.1200/jco.1991.9.2.220

    Article  PubMed  CAS  Google Scholar 

  34. Savage K et al (2006) Favorable outcome of primary mediastinal large B-cell lymphoma in a single institution: the British Columbia experience. Ann Oncol 17:123–130. https://doi.org/10.1093/annonc/mdj030

    Article  PubMed  CAS  Google Scholar 

  35. Tomita N et al (2008) Adjuvant radiotherapy to an initial bulky mass in diffuse large B-cell lymphoma: lack of survival benefit. Int J Lab Hematol 30:53–57. https://doi.org/10.1111/j.1751-553X.2007.00900.x

    Article  PubMed  CAS  Google Scholar 

  36. Pfreundschuh M et al (2008) Prognostic significance of maximum tumour (bulk) diameter in young patients with good-prognosis diffuse large-B-cell lymphoma treated with CHOP-like chemotherapy with or without rituximab: an exploratory analysis of the MabThera International Trial Group (MInT) study. Lancet Oncol 9:435–444. https://doi.org/10.1016/s1470-2045(08)70078-0

    Article  PubMed  Google Scholar 

  37. Habermann T et al (2006) Rituximab-CHOP versus CHOP alone or with maintenance rituximab in older patients with diffuse large B-cell lymphoma. J Clin Oncol 24:3121–3127. https://doi.org/10.1200/jco.2005.05.1003

    Article  PubMed  CAS  Google Scholar 

  38. Coiffier B et al (2002) CHOP chemotherapy plus rituximab compared with CHOP alone in elderly patients with diffuse large-B-cell lymphoma. N Engl J Med 346:235–242. https://doi.org/10.1056/NEJMoa011795

    Article  PubMed  CAS  Google Scholar 

  39. Takasaki H et al (2015) Post-treatment PET-CT Findings may predict the prognosis of DLBCL with a bulky mass. Indian J Hematol Blood Transfus 31:346–351. https://doi.org/10.1007/s12288-014-0479-9

    Article  PubMed  Google Scholar 

  40. Ribera J (2008) Adverse prognosis of bulky disease in good-risk DLBCL. Lancet Oncol 9:406–407. https://doi.org/10.1016/s1470-2045(08)70111-6

    Article  PubMed  Google Scholar 

  41. Tokola S, Kuitunen H, Turpeenniemi-Hujanen T, Kuittinen O (2020) Significance of bulky mass and residual tumor-treated with or without consolidative radiotherapy-To the risk of relapse in DLBCL patients. Cancer Med 9:1966–1977. https://doi.org/10.1002/cam4.2798

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Gutierrez A et al (2020) Evaluation of the MD Anderson tumor score for diffuse large B-cell lymphoma in the rituximab era. Eur J Haematol 104:400–408. https://doi.org/10.1111/ejh.13364

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Bari A et al (2010) Prognostic models for diffuse large B-cell lymphoma in the rituximab era: a never-ending story. Ann Oncol 21:1486–1491. https://doi.org/10.1093/annonc/mdp531

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to thank all the doctors, nurses, and patients as well as their families for their contribution to this study.

Funding

This work was financially supported by the Scientific Research Foundation of Fujian Cancer Hospital (grant numbers 2021YNY02); Natural Science Foundation of Fujian Province (grant numbers 2023J05241); China Postdoctoral Science Foundation (grant numbers 2023M734015); and China National Major Project for New Drug Innovation (grant numbers 2017ZX09304015).

Author information

Authors and Affiliations

  1. Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China

    Qiaofeng Zhong, Haizhu Chen, Yan Qin, Xiaohui He, Jianliang Yang, Peng Liu, Shengyu Zhou, Sheng Yang, Yu Zhou, Le Tang & Yuankai Shi

  2. Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fujian Provincial Key Laboratory of Translational Cancer Medicine, 420 Fuma Road, Fuzhou, 350014, China

    Qiaofeng Zhong

  3. Interdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, China

    Qiaofeng Zhong

  4. Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Road, Fuzhou, 350014, China

    Daoguang Chen & Yu Yang

  5. Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Road, Fuzhou, 350014, China

    Chuanben Chen

Authors
  1. Qiaofeng Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haizhu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daoguang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yan Qin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xiaohui He
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jianliang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Peng Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Shengyu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Sheng Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Le Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Chuanben Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yuankai Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Yuankai Shi: conceptualization, methodology, resources, writing—review and editing, supervision, funding acquisition; Chuanben Chen: conceptualization, methodology, resources, writing—review and editing, project administration; Qiaofeng Zhong: methodology, software, formal analysis, investigation, data curation, writing—original draft, writing—review and editing, visualization, project administration, funding acquisition; Haizhu Chen: formal analysis, investigation, data curation, writing—original draft, writing—review and editing, visualization; Daoguang Chen: validation, investigation, resources, data curation, visualization, project administration; Yan Qin: investigation, resources, data curation; Xiaohui He: investigation, resources, data curation; Yu Yang: resources, data curation; Jianliang Yang: resources, data curation; Peng Liu: resources, data curation; Shengyu Zhou: resources, data curation; Sheng Yang: resources, data curation; Yu Zhou: investigation, data curation; Le Tang: investigation, data curation.

Corresponding authors

Correspondence to Chuanben Chen or Yuankai Shi.

Ethics declarations

Ethics approval

This study was performed in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Cancer Hospital, Chinese Academy of Medical Sciences (No. NCC2018JJJ-004) and Fujian Cancer Hospital (No. SQ2022-090–01).

Competing interests

The authors declare no competing interests.

Informed consent

Informed consent was waived due to the retrospective nature of the present study, and data of the participants have been anonymized.

Additional information

Publisher’s note

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

Qiaofeng Zhong, Haizhu Chen, and Daoguang Chen contributed equally to this work as co-first authors.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 530 KB)

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

Zhong, Q., Chen, H., Chen, D. et al. Development and validation of a novel risk stratification model and a survival rate calculator for diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study. Ann Hematol 103, 211–226 (2024). https://doi.org/10.1007/s00277-023-05491-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00277-023-05491-0

Keywords

Search

Navigation