incremental cost-effectiveness ratio (ICER)

Hodgkin’s Lymphoma: Analysis Results of Volgograd Regional Registry

LYMPHOID TUMORS , , , , , ,

KD Kaplanov1,2, NP Volkov1, TYu Klitochenko1, IV Matveeva1, AL Shipaeva1, MN Shirokova1, NV Davydova3, EG Gemdzhian4

1 Volgograd Regional Clinical Oncology Dispensary, 78 Zemlyachki str., Volgograd, Russian Federation, 400138

2 Volgograd Medical Scientific Center, 1G Rokossovskogo str., Volgograd, Russian Federation, 400081

3 Consultation and Diagnosis Polyclinic No. 2, 114A Angarskaya str., Volgograd, Russian Federation, 400081

4 National Medical Hematology Research Center, 4а Novyi Zykovskii pr-d, Moscow, Russian Federation, 125167

For correspondence: Kamil Daniyalovich Kaplanov, MD, PhD, 78 Zemlyachki str., Volgograd, Russian Federation, 400138; e-mail: kamilos@mail.ru

For citation: Kaplanov KD, Volkov NP, Klitochenko TYu, et al. Hodgkin’s Lymphoma: Analysis Results of Volgograd Regional Registry. Clinical oncohematology. 2019;12(4):363–76 (In Russ).

DOI: 10.21320/2500-2139-2019-12-4-363-376

ABSTRACT

Background. The present paper discusses feasibility of first- and second-line therapies as well as the significance of different risk factors in the population of all patients with newly diagnosed Hodgkin’s lymphomas (HL) in a 14-year period based on the data of Volgograd regional registry.

Materials & Methods. During the period 2003 to 2017 the population registry of Department of Hematology of Volgograd Regional Clinical Oncology Dispensary included the data of all the patients with newly diagnosed HL (n = 622): 272 (44 %) men and 350 (56 %) women aged 18 to 84 years (mean age 38 years, median age 33 years). There were 97 (16 %) patients with early stages and without risk factors, 165 (27 %) patients with early stages and risk factors, 360 (59 %) patients with advanced stages, 308 (50 %) patients with toxic symptoms (stage B), and 179 (29 %) patients with bulky tumor lesions (≥ 10 cm). ABVD treatment regimen was administered in 190 (30.5 %) patients, increased-dose BEACO(D)PP in 39 (6 %) patients, BEACO(D)PP-14 in 159 (26 %) patients, standard BEACO(D)PP in 200 (32 %) patients, IVDG in 25 (4 %) patients, and other regimens in 9 (1.5 %) patients. The second-line treatment was administered in 120 (19 %) out of 622 patients. By the end of August 2018, the number of followed-up patients was 514 (83 %), 108 (17 %) patients had died. The prognostic value of the International Prognostic Score (IPS), PET, and other factors was assessed by means of Cox’s multivariate regression analysis. Pharmacoeconomic analysis of differences between options of first-line therapy was based on Markov model.

Results. In the group of patients with advanced HL stages treated with escalated BEACO(D)PP (the increased-dose regimen and BEACO(D)PP-14) 5- and 10-year overall survival (OS) was 83 % and 74 %, respectively, OS median was not reached. On standard BEACO(D)PP patients with advanced HL stages had OS median of 139 months (11.6 years) and 5- and 10-year OS of 68 % and 54 %, respectively (p = 0,012). In the group of patients with early stages and poor prognosis treated with escalated regimens BEACO(D)PP 5- and 10- year OS was 100 % and 90 %, respectively, in the combined group treated with ABVD and standard BEACO(D)PP it was 83 % and 75 % (p = 0.035). Replacement of procarbazine with dacarbazine in the standard and increased-dose BEACOPP regimens did not affect treatment efficacy. Markov analysis demonstrated the advantages of the escalated regimens for treatment of early stages with poor prognosis and advanced stages in terms of life years gained. Out of 7 IPS factors male sex, age ≥ 45 years, hemoglobin < 105 g/L, and albumin < 40 mg/L significantly impacted OS. Based on these data an adjusted prognostic index was suggested.

Conclusion. The advantage of the escalated strategy of first-line therapy in HL is reflected in survival parameters and is based on pharmacoeconomic evidence. The significance of some laboratory IPS risk factors can be reviewed; most obvious is increasing importance of PET for predicting the need for salvage therapy.

Keywords: Hodgkin’s lymphoma, BEACO(D)PP, ABVD, International Prognostic Score, survival analysis, pharmacoeconomics, Markov model, life years gained (LYG), incremental cost-effectiveness ratio (ICER).

Received: February 21, 2019

Accepted: September 17, 2019

Read in PDF

REFERENCES

  1. Jaffe ES, Arber DA, Campo E, et al. Hematopathology, 2nd edition. Elsevier Ltd.; 2017. 1216 p.

  2. Glaser SL, Jarrett RF. The epidemiology of Hodgkin’s disease. Baill Clin Haematol. 1996;9(3):401–16. doi: 10.1016/s0950-3536(96)80018-7.

  3. Злокачественные новообразования в России в 2017 г. (заболеваемость и смертность). Под ред. А.Д. Каприна, В.В. Старинского, Г.В. Петровой. М.: МНИОИ им. П.А. Герцена, 2018. 250 с.

    [Kaprin AD, Starinskii VV, Petrova GV, eds. Zlokachestvennye novoobrazovaniya v Rossii v 2017 godu (zabolevaemost’ i smertnost’). (Malignancies in Russia in 2017: incidence and mortality.) Moscow: MNIOI im. P.A. Gertsena; 2018. 250 p. (In Russ)]

  4. Grufferman S, Cole P, Smith PG, et al. Hodgkin’s disease in siblings. N Engl J Med. 1977;296(5):248–50. doi: 10.1056/NEJM197702032960504.

  5. Lynch HT, Marcus JN, Lynch JF. Genetics of Hodgkin’s and non-Hodgkin’s lymphoma: a review. Cancer Invest. 1992;10(3):247–56. doi: 10.3109/07357909209032768.

  6. Mack TM, Cozen W, Shibata DK, et al. Concordance for Hodgkin’s disease in identical twins suggesting genetic susceptibility to the young-adult form of the disease. N Engl J Med. 1995;332(7):413–8. doi: 10.1056/NEJM199502163320701.

  7. Horwitz M, Wiernik PH. Pseudoautosomal linkage of Hodgkin disease. Am J Hum Genet. 1999;65(5):1413–22. doi: 10.1086/302608.

  8. Weiss LM, Strickler JG, Warnke RA, et al. Epstein-Barr viral DNA in tissues of Hodgkin’s disease. Am J Pathol. 1987;129(1):86–91.

  9. Alexander FE, Jarrett RF, Lawrence D, et al. Risk factors for Hodgkin’s disease by Epstein-Barr virus (EBV) status: prior infection by EBV and other agents. Br J Cancer. 2000;82(5):1117–21. doi: 10.1054/bjoc.1999.1049.

  10. Andrieu JM, Roithmann S, Tourani JM, et al. Hodgkin’s disease during HIV1 infection: the French registry experience. French Registry of HIV-associated Tumors. Ann Oncol. 1993;4(8):635–41. doi: 10.1093/oxfordjournals.annonc.a058617.

  11. Tirelli U, Errante D, Dolcetti R, et al. Hodgkin’s disease and human immunodeficiency virus infection: clinicopathologic and virologic features of 114 patients from the Italian Cooperative Group on AIDS and Tumors. J Clin Oncol. 1995;13(7):1758–67. doi: 10.1200/JCO.1995.13.7.1758.

  12. Tubiana M, Henry-Amar M, Carde P, et al. Toward comprehensive management tailored to prognostic factors of patients with clinical stages I and II Hodgkin’s disease. The EORTC Lymphoma Group controlled clinical trials: 1964–1987. Blood. 1989;73(1):47–56.

  13. Diehl V, Stein H, Hummel M, et al. Hodgkin’s lymphoma: biology and treatment strategies for primary, refractory, and relapsed disease. Hematology. 2003;2003(1):225–47. doi: 10.1182/asheducation-2003.1.225.

  14. Hasenclever D, Diehl V, Armitage JO, et al. A prognostic score for advanced Hodgkin’s disease. International Prognostic Factors Project on Advanced Hodgkin’s Disease. N Engl J Med. 1998;339(21):1506–14. doi: 10.1056/NEJM199811193392104.

  15. Andre MP, Girinsky T, Federico M, et al. Early positron emission tomography response-adapted treatment in stage I and II Hodgkin lymphoma: final results of the randomized EORTC/LYSA/FIL H10 trial. J Clin Oncol. 2017;35(16):1786–94. doi: 10.1200/JCO.2016.68.6394.

  16. Johnson P, Federico M, Kirkwood A, et al. Adapted treatment guided by interim PET-CT scan in advanced Hodgkin’s lymphoma. N Engl J Med. 2016;374(25):2419–29. doi: 10.1056/NEJMoa1510093.

  17. Green MR, Monti S, Rodig SJ, et al. Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma. Blood. 2010;116(17):3268–77. doi: 10.1182/blood-2010-05-282780.

  18. Roemer MG, Advani RH, Ligon AH, et al. PD-L1 and PD-L2 genetic alterations define classical Hodgkin lymphoma and predict outcome. J Clin Oncol. 2016;34(23):2690–7. doi: 10.1200/JCO.2016.66.4482.

  19. Roemer MGM, Redd RA, Cader FZ, et al. Major histocompatibility complex Class II and programmed death ligand 1 expression predict outcome after programmed death 1 blockade in classic Hodgkin lymphoma. J Clin Oncol. 2018;36(10):942–50. doi: 10.1200/JCO.2017.77.3994.

  20. Liu L, Giusti F, Schaapveld M, et al. Survival differences between patients with Hodgkin lymphoma treated inside and outside clinical trials. A study based on the EORTC-Netherlands Cancer Registry linked data with 20 years of follow-up. Br J Haematol. 2017;176(1):65–75. doi: 10.1111/bjh.14379.

  21. Капланов К.Д., Шипаева А.Л., Васильева В.А. и др. Эффективность программ химиотерапии первой линии при различных стадиях лимфомы Ходжкина. Клиническая онкогематология. 2012;5(1):22–9.

    [Kaplanov KD, Shipaeva AL, Vasil’eva VA, et al. Efficacy of first line chemotherapy programs for different stages of Hodgkin’s lymphomas. Klinicheskaya onkogematologiya. 2012;5(1):22–9. (In Russ)]

  22. Капланов К.Д., Шипаева А.Л., Васильева В.А. и др. Международный прогностический индекс при распространенных стадиях лимфомы Ходжкина в условиях современной терапии. Клиническая онкогематология. 2013;6(3):294–302.

    [Kaplanov KD, Shipaeva AL, Vasil’eva VA, et al. International prognostic score in advanced Hodgkin’s lymphoma. Klinicheskaya onkogematologiya. 2013;6(3):294–302. (In Russ)]

  23. Капланов К.Д., Волков Н.П., Клиточенко Т.Ю. и др. Первая линия терапии лимфомы из клеток зоны мантии: анализ эффективности и клинико-экономическая оценка. Клиническая онкогематология. 2018;11(2):150–9. doi: 10.21320/2500-2139-2018-11-2-150-159.

    [Kaplanov KD, Volkov NP, Klitochenko TYu, et al. First-Line Treatment of Mantle-Cell Lymphoma: Analysis of Effectiveness and Cost-Effectiveness. Clinical oncohematology. 2018;11(2):150–9. doi: 10.21320/2500-2139-2018-11-2-150-159. (In Russ)]

  24. Капланов К.Д., Волков Н.П., Клиточенко Т.Ю. и др. Результаты анализа регионального регистра пациентов с диффузной В-крупноклеточной лимфомой: факторы риска и проблемы иммунохимиотерапии. Клиническая онкогематология. 2019;12(2):154–64. doi: 10.21320/2500-2139-2019-12-2-154-164.

    [Kaplanov KD, Volkov NP, Klitochenko TYu, et al. Analysis Results of the Regional Registry of Patients with Diffuse Large B-cell Lymphoma: Risk Factors and Chemo-Immunotherapy Issues. Clinical oncohematology. 2019;12(2):154–64. doi: 10.21320/2500-2139-2019-12-2-154-164. (In Russ)]

  25. Kaplanov K, Klitochenko T, Shipaeva A, et al. Combination of idarubicin, vinblastine, dacarbazine, and gemcitabine (IVDG) as therapy for elderly patients with Hodgkin lymphoma with cardiac and pulmonary comorbidity. Hematol Oncol. 2017;35(Suppl 2):317. doi: 1002/hon.2439_57.

  26. Капланов К.Д., Клиточенко Т.Ю., Шипаева А.Л. и др. Программа IVDG — возможный выбор первой линии терапии лимфомы Ходжкина у пациентов пожилого возраста с сопутствующими сердечно-сосудистыми и легочными заболеваниями. Клиническая онкогематология. 2017;10(3):358–65. doi: 10.21320/2500-2139-2017-10-3-358-365.

    [Kaplanov KD, Klitochenko TYu, Shipaeva АL, et al. The IVDG Regimen is the Possible Treatment of Choice as First Line Therapy For Hodgkin’s Lymphoma in Elderly Patients with Cardiovascular and Pulmonary Comorbidity. Clinical oncohematology. 2017;10(3):358–65. doi: 10.21320/2500-2139-2017-10-3-358-365. (In Russ)]

  27. Bosh TM. Pharmacogenomics of drug-metabolizing enzymes and drug transporters in chemotherapy. Meth Mol Biol. 2008;448:63–76. doi: 10.1007/978-1-59745-205-2_5.

  28. Lee NH. Pharmacogenetics of drug metabolizing enzymes and transporters: effects on pharmacokinetics and pharmacodynamics of anticancer agents. Anti-cancer Agents Med Chem. 2010;10(8):583–92. doi: 10.2174/187152010794474019.

  29. Ekhart C, Rodenhuis S, Smits PH, et al. An overview of the relations between polymorphisms in drug metabolising enzymes and drug transporters and survival after cancer drug treatment. Cancer Treat Rev. 2009;35(1):18–31. doi: 10.1016/j.ctrv.2008.07.003.

  30. Von Treschkow B, Kreissl S, Goergen H, et al. Intensive treatment strategies in advanced stage Hodgkin’s lymphoma (HD9 and HD12): analysis of long-term survival in two randomised trial. Lancet Haematol. 2018;5(10):e462–e473. doi: 10.1016/S2352-3026(18)30140-6.

  31. Skoetz N, Will A, Monsef I. Comparison of first-line chemotherapy including escalated BEACOPP versus chemotherapy including ABVD for people with early unfavorable or advanced stage Hodgkin lymphoma. Cochrane Database Syst Rev. 2017;5:CD007941. doi: 10.1002/14651858.CD007941.pub3.

  32. Rancea M, Monsef I, von Tresckow B, et al. High-dose chemotherapy followed by autologous stem cell transplantation for patients with relapsed/refractory Hodgkin lymphoma. Cochrane Database Syst Rev. 2013;6:CD009411. doi: 10.1002/14651858.CD009411.pub2.

  33. von Tresckow B, Moskowitz CH. Treatment of relapsed and refractory Hodgkin lymphoma. Semin Hematol. 2016;53(3):180–5. doi: 10.1053/j.seminhematol.2016.05.010.

  34. Kobe C, Goergen H, Baues C, et al. Outcome-based interpretation of early interim PET in advanced-stage Hodgkin lymphoma. Blood. 2018;132(21):2273–9. doi: 10.1182/blood-2018-05-852129.

  35. Diehl V, Franklin J, Pfreundschuh M, et al. Standard and increased-dose BEACOPP chemotherapy compared with COPP-ABVD for advanced Hodgkin’s disease. N Engl J Med. 2003;348(24):2386–95. doi: 10.1056/NEJMoa022473.

  36. Moccia AA, Donaldson J, Chhanabhai M, et al. International Prognostic Score in Advanced-Stage Hodgkin’s Lymphoma: Altered Utility in the Modern Era. J Clin Oncol. 2012;30(27):3383–8. doi: 10.1200/JCO.2011.41.0910.

  37. Gordon LI, Hong F, Fisher RI, et al. Randomized phase III trial of ABVD versus Stanford V with or without radiation therapy in locally extensive and advanced-stage Hodgkin lymphoma: an intergroup study coordinated by the Eastern Cooperative Oncology Group (E2496). J Clin Oncol. 2013;31(6):684–91. doi: 10.1200/JCO.2012.43.4803.

  38. Dann EJ, Blumenfeld Z, Bar-Shalom R, et al. A 10-year experience with treatment of high and standard risk Hodgkin disease: six cycles of tailored BEACOPP, with interim scintigraphy, are effective and female fertility is preserved. Am J Hematol. 2012;87(1):32–6. doi: 10.1002/ajh.22187.

  39. Dann EJ, Bairey O, Bar-Shalom R, et al. Modification of initial therapy in early and advanced Hodgkin lymphoma, based on interim PET/CT is beneficial: a prospective multicenter trial of 355 patients. Br J Haematol. 2017;178(5):709–18. doi: 10.1111/bjh.14734.

  40. Sieber M, Bredenfeld H, Josting A, et al. 14-day variant of the bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone regimen in advanced-stage Hodgkin’s lymphoma: results of a pilot study of the German Hodgkin’s Lymphoma Study Group. J Clin Oncol. 2003;21(9):1734–9. doi: 10.1200/JCO.2003.06.028.

  41. Engert A, Haverkamp H, Kobe C, et al. Reduced-intensity chemotherapy and PET-guided radiotherapy in patients with advanced stage Hodgkin’s lymphoma (HD15 trial): a randomised, open-label, phase 3 non-inferiority trial. Lancet. 2012;379(9828):1791–9. doi: 10.1016/S0140-6736(11)61940-5.

  42. Engert A, Diehl V, Franklin J, et al. Escalated-dose BEACOPP in the treatment of patients with advanced-stage Hodgkin’s lymphoma: 10 years of follow-up of the GHSG HD9 study. J Clin Oncol. 2009;27(27):4548–54. doi: 10.1200/JCO.2008.19.8820.

  43. Skoetz N, Trelle S, Rancea M, et al. Effect of initial treatment strategy on survival of patients with advanced-stage Hodgkin’s lymphoma: a systematic review and network meta-analysis. Lancet Oncol. 2013;14(10):943–52. doi: 10.1016/S1470-2045(13)70341-3.

Analysis Results of the Regional Registry of Patients with Diffuse Large B-cell Lymphoma: Risk Factors and Chemo-Immunotherapy Issues

LYMPHOID TUMORS , , , , , ,

KD Kaplanov1,2, NP Volkov1, TYu Klitochenko1, IV Matveeva1, AL Shipaeva1, MN Shirokova1, NV Davydova3, EG Gemdzhian4, DS Abramov5, DM Konovalov5, GL Snigur2, NA Red’kina1

1 Volgograd Regional Clinical Oncology Dispensary No. 1, 78 Zemlyachki str., Volgograd, Russian Federation, 400138

2 Volgograd Medical Scientific Center, 1G Rokossovskogo str., Volgograd, Russian Federation, 400081

3 Consultation and Diagnosis Polyclinic No. 2, 114A Angarskaya str., Volgograd, Russian Federation, 400081

4 National Medical Hematology Research Center, 4а Novyi Zykovskii pr-d, Moscow, Russian Federation, 125167

5 Dmitry Rogachev National Research Center of Pediatric Hematology, Oncology and Immunology, 1 Samory Mashela str., Moscow, Russian Federation, 117997

For correspondence: Kamil’ Daniyalovich Kaplanov, MD, PhD, 78 Zemlyachki str., Volgograd, Russian Federation, 400138; e-mail: kamilos@mail.ru

For citation: Kaplanov KD, Volkov NP, Klitochenko TYu, et al. Analysis Results of the Regional Registry of Patients with Diffuse Large B-cell Lymphoma: Risk Factors and Chemo-Immunotherapy Issues. Clinical oncohematology. 2019;12(2):154–64.

DOI: 10.21320/2500-2139-2019-12-2-154-164

ABSTRACT

Background & Aims. At least one third of patients with diffuse large B-cell lymphoma (DLBCL) are resistant to first-line therapy. R-CHOP chemo-immunotherapy does not yield acceptable results in high-risk patients. Effectiveness of options based either on increasing the dose intensity or on including auto-HSCT into the first-line therapy was not supported by the results of controlled studies. With this background the present study focuses on options, issues and failures of first-line on the basis of long-term follow-up of DLBCL patient population in the Volgograd Region.

Materials & Methods. From 2004 to 2017 the population-based registry of the Hematology Department in the Volgograd Regional Clinical Oncology Dispensary included all 492 primary DLBCL patients: 235 (48 %) men and 257 (52 %) women aged 18 to 88 years. Mean and median age was 59 and 61 years, respectively. CHOP therapy was administered to 206 (42 %) patients, and 223 (45 %) patients received R-CHOP. Other regimens including NHL-BFM-90 and R-DA-EPOCH were used only in 63 (13 %) patients. Second- and third-line therapies were administered to 145 (30 %) and 54 (11 %) patients, respectively. Value of the International Prognostic Index (IPI) and immunomorphologic characteristics was determined by multivariate Cox regression analysis. Pharmacoeconomic aspect of first-line therapy failures was analyzed using Markov model.

Results. Improvement of DLBCL therapy effects with the use of R-CHOP chemo-immunotherapy is particularly obvious in the groups with favorable and intermediate prognosis with 5-year overall survival (OS) of 90 % and 69 %, respectively. R-CHOP results are not considered to be satisfactory in the high-risk group: 5-year OS was 38 %. Pharmacoeconomic analysis proves the advantage of chemo-immunotherapy strategy in comparison with the period before rituximab era in terms of the life years gained (LYG) and the incremental cost-effectiveness ratio (ICER). With respect to immunotherapy effects the most significant immunomorphologic parameter is bcl-2 tumor cell expression. In the group of patients with bcl-2 > 50 % 5-year OS was 61 % with median of 88 months, event-free survival (EFS) was 52 % with median of 62 months. In the group without bcl-2 expression above the threshold 5-year OS and EFS were 88 % and 75 %, respectively, medians were not achieved. With c-myc and bcl-2 coexpression EFS and OS appeared to be even worse: 5-year EFS was 29 % with median of 6 months, and 5-year OS was 31 % with median of 15 months.

Conclusion. The analysis of actual practice demonstrates the need for new options of first-line therapy for DLBCL high-risk patients and also for introducing new discriminating prognostic factors which include the IPI-independent ones.

Keywords: diffuse large B-cell lymphoma, R-CHOP, chemoimmunotherapy, survival, pharmacoeconomics, Markov model, life years gained (LYG), incremental cost-effectiveness ratio (ICER).

Received: July 16, 2018

Accepted: January 10, 2019

Read in PDF 

REFERENCES

  1. Armitage JO, Weisenburger DD. New approach to classifying non-Hodgkin’s lymphomas: clinical features of the major histologic subtypes. Non-Hodgkin’s Lymphoma Classification Project. J Clin Oncol. 1998;16(8):2780–95. doi: 10.1200/JCO.1998.16.8.2780.

  2. Smith A, Howell D, Patmore R, et al. Incidence of haematological malignancy by sub-type: a report from the Haematological Malignancy Research Network. Br J Cancer. 2011;105(11):1684–92. doi: 10.1038/bjc.2011.450.

  3. Cunningham D, Hawkes EA, Jack A, et al. Rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisolone in patients with newly diagnosed diffuse large B-cell non-Hodgkin lymphoma: a phase 3 comparison of dose intensification with 14-day versus 21-day cycles. Lancet. 2013;381(9880):1817–26. doi: 10.1016/S0140-6736(13)60313-X.

  4. Ziepert, M, Hasenclever D, Kuhnt E, et al. Standard international prognostic index remains a valid predictor of outcome for patients with aggressive CD20+ B-cell lymphoma in the rituximab era. J Clin Oncol. 2010;28(14):2373–80. doi: 10.1200/JCO.2009.26.2493.

  5. Swerdlow SH, Campo E, Pileri SA, et al. The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood. 2016;127(20):2375–90. doi: 10.1182/blood-2016-01-643569.

  6. Sehn LH, Gascoyne RD. Diffuse large B-cell lymphoma: optimizing outcome in the context of clinical and biologic heterogeneity. Blood. 2015;125(1):22–32. doi: 10.1182/blood-2014-05-577189.

  7. Tilly H, Gomes da Silva M, Vitolo U, et al. Diffuse large B-cell lymphoma (DLBCL): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2015;26(Suppl 5):v116–25. doi: 10.1093/annonc/mdv304.

  8. Prochazka KT, Melchardt T, Posch F, et al. NCCN-IPI score-independent prognostic potential of pretreatment uric acid levels for clinical outcome of diffuse large B-cell lymphoma patients. Br J Cancer. 2016;115(10):1264–72. doi: 10.1038/bjc.2016.325.

  9. Montalban C, Diaz-Lopez A, Dlouhy I, et al. Validation of the NCCN-IPI for diffuse large B-cell lymphoma (DLBCL): the addition of beta2-microglobulin yields a more accurate GELTAMO-IPI. Br J Haematol. 2017;176(6):918–28. doi: 10.1111/bjh.14489.

  10. Wight J, Chong G, Grigg A, et al. Prognostication of diffuse large B-cell lymphoma in the molecular era: moving beyond the IPI. Blood. 2018;32(5):400–15. doi: 10.1016/j.blre.2018.03.005.

  11. Khor S, Beca J, Krahm M, et al. Real world costs and cost-effectiveness of Rituximab for diffuse large B-cell lymphoma patients: A population-based analysis. BMC Cancer. 2014;14(1):586. doi: 10.1186/1471-2407-14-586.

  12. Van Keep M, Gairy K, Seshagiri D, et al. Cost-effectiveness analysis of bortezomib in combination with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (VR-CAP) in patients with previously untreated mantle cell lymphoma. BMC Cancer. 2016;16(1):598. doi: 10.1186/s12885-016-2633-2.

  13. Капланов К.Д., Шипаева А.Л., Васильева В.А. и др. Международный прогностический индекс при распространенных стадиях лимфомы Ходжкина в условиях современной терапии. Клиническая онкогематология. 2013;6(3):294–302.

    [Kaplanov KD, Shipaeva AL, Vasil’eva VA, et al. International prognostic score in advanced Hodgkin’s lymphoma. Klinicheskaya onkogematologiya. 2013;6(3):294–302. (In Russ)]

  14. Капланов К.Д., Шипаева А.Л., Васильева В.А. и др. Эффективность программ химиотерапии первой линии при различных стадиях лимфомы Ходжкина. Клиническая онкогематология. 2012;5(1):22–9.

    [Kaplanov KD, Shipaeva AL, Vasil’eva VA, et al. Efficacy of first line chemotherapy programs for different stages of Hodgkin’s lymphomas. Klinicheskaya onkogematologiya. 2012;5(1):22–9. (In Russ)]

  15. Капланов К.Д., Волков Н.П., Клиточенко Т.Ю. и др. Первая линия терапии лимфомы из клеток зоны мантии: анализ эффективности и клинико-экономическая оценка. Клиническая онкогематология. 2018;11(2):150–9. doi: 10.21320/2500-2139-2018-11-2-150-159.

    [Kaplanov KD, Volkov NP, Klitochenko TYu, et al. First-Line Treatment of Mantle-Cell Lymphoma: Analysis of Effectiveness and Cost-Effectiveness. Clinical oncohematology. 2018;11(2):150–9. doi: 10.21320/2500-2139-2018-11-2-150-159. (In Russ)]

  16. Abner EL, Charnigo RJ, Kryscio RJ, et al. Markov chains and semi-Markov models in time-to-event analysis. J Biom Biostat. 2013;S1:e001. doi: 10.4172/2155-6180.S1-e001.

  17. Wyndham W, Jung sin-Ho, Brandelyn P, et al. Phase III Randomized Study of R-CHOP Versus DA-EPOCH-R and Molecular Analysis of Untreated Diffuse Large B-Cell Lymphoma: CALGB/Alliance 50303. Blood. 2016;128:469.

  18. The International Non-Hodgkin’s Lymphoma Prognostic Factors Project. A predictive model for aggressive non-Hodgkin’s lymphoma. N Engl J Med. 1993;329(14):987–94. doi: 10.1056/NEJM199309303291402.

  19. Wang HI, Smith A, Aas E, et al. Treatment cost and life expectancy of diffuse large B-cell lymphoma (DLBCL): a discrete event simulation model on a UK population-based observational cohort. Eur J Health Econ. 2017;18(2):255–67. doi: 10.1007/s10198-016-0775-4.

  20. Gisselbrecht C, Glass B, Mounier N, et al. Salvage regimens with autologous transplantation for relapsed large B-cell lymphoma in the rituximab era. J Clin Oncol. 2010; 28(27):4184–90. doi: 10.1200/JCO.2010.28.1618.

  21. Gisselbrecht C, Schmitz N, Mounier N, et al. Rituximab maintenance therapy after autologous stem-cell transplantation in patients with relapsed CD20(+) diffuse large B-cell lymphoma: final analysis of the collaborative trial in relapsed aggressive lymphoma. J Clin Oncol. 2012;30(36):4462–9. doi: 10.1200/JCO.2012.41.9416.

  22. Crump M, Neelapu SS, Farooq U, et al. Outcomes in refractory diffuse large B-cell lymphoma: results from the international SCHOLAR-1 study. Blood. 2017;130(16):1800–8. doi: 10.1182/blood-2017-11-817775.

  23. Sehn LH, Berry B, Chhanabhai M, et al. 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. 2007;109(5):1857–61. doi: 10.1182/blood-2006-08-038257.

  24. Gang AO, Pedersen M, d’Amore F, et al. A clinically based prognostic index for diffuse large B-cell lymphoma with a cut-off at 70 years of age significantly improves prognostic stratification: population-based analysis from the Danish Lymphoma Registry. Leuk Lymphoma. 2015;56(9):2556–62. doi: 10.3109/10428194.2015.1010078.

  25. Zhou Z, Sehn LH, Rademaker AW, et al. An enhanced International Prognostic Index (NCCN-IPI) for patients with diffuse large B-cell lymphoma treated in the rituximab era. Blood 2014;123(6):837–42. doi: 10.1182/blood-2014-06-583476.

  26. Royston P, Altman DG, Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med. 2006;25(1):127–41. doi: 10.1002/sim.2331.

  27. Harrell FE. Regression modeling strategies. New York: Springer-Verlag; 2001. doi: 10.1007/978-1-4757-3462-1.

  28. Biccler J, Eloranta S, de Nully Brown P, et al. Simplicity at the cost of predictive accuracy in diffuse large B-cell lymphoma: a critical assessment of the R-IPI, IPI, and NCCN-IPI. Cancer Med. 2018;7(1):114–22. doi: 10.1002/cam4.1271.

  29. Johnson NA, Slack GW, Savage KJ, et al. Concurrent expression of MYC and BCL2 in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone. J Clin Oncol. 2012;30(28):3452–9. doi: 10.1200/JCO.2011.41.0985.

  30. Schneider KMС, Banks PM, Collie AM, et al. Dual expression of MYC and BCL2 proteins predicts worse outcomes in diffuse large B-cell lymphoma. Leuk Lymphoma. 2016;57(7):1640–8. doi: 10.3109/10428194.2015.1101099.

  31. Barrans SL, Evans PA, O’Connor SJ, et al. The t(14;18) is associated with germinal center-derived diffuse large B-cell lymphoma and is a strong predictor of outcome. Clin Cancer Res. 2003;9(6):2133–9.

  32. Tsuyama N, Sakata S, Baba S, et al. BCL2 expression in DLBCL: reappraisal of immunohistochemistry with new criteria for therapeutic biomarker evaluation. Blood. 2017;130(4):489–500. doi: 10.1182/blood-2016-12-759621.

  33. Burton C, Barrans S, Ahmed S, et al. Cross-Platform validation of gene expression profiling (GEP) based cell of origin classification in a clinical laboratory setting. Hematol Oncol. 2017;35(S2):107. doi: 10.1002/hon.2437_96.