Comorbidity and Personalized Treatment of Multiple Myeloma in Real Clinical Practice

NV Skvortsova1, IB Kovynev1, KV Khalzov1, TI Pospelova1, IN Nechunaeva2

1 Novosibirsk State Medical University, 52 Krasnyi pr-t, Novosibirsk, Russian Federation, 630091

2 Municipal Clinical Hospital No. 2, 21 Polzunova str., Novosibirsk, Russian Federation, 630051

For correspondence: Nataliya Valer’evna Skvortsova, MD, PhD, 52 Krasnyi pr-t, Novosibirsk, Russian Federation, 630091; Tel.: 8(905)955-59-91; Fax: 8(383)279-94-06; e-mail: nata_sk78@mail.ru

For citation: Skvortsova NV, Kovynev IB, Khalzov KV, et al. Comorbidity and Personalized Treatment of Multiple Myeloma in Real Clinical Practice. Clinical oncohematology. 2020;13(3):322–34 (In Russ).

DOI: 10.21320/2500-2139-2020-13-3-322-334


ABSTRACT

Aim. To study incidence and structure of comorbidity in multiple myeloma (MM) patients depending on their age; to determine its effect on overall survival, efficacy, and safety of the first-line therapy in real clinical practice.

Materials & Methods. Overall, 369 patients with newly diagnosed MM were enrolled in the trial from January 2012 to December 2017. Among them there were 134 men and 235 women hospitalized at the Unit of Hematology in the Novosibirsk Municipal Clinical Hospital No. 2. Median age of patients was 67 years (range 32–82 years).

Results. The analyzed patients were divided into three age groups: the first group of young/middle age (32–59 years) (n = 105), the second group of elderly patients (60–74 years) (n = 186), and the third group of old age (≥ 75 years) (n = 78). In each patient prior to chemotherapy the comorbidity spectrum was identified and CIRS-G, CCI, and MCI comorbidity scores were calculated. Patients with newly diagnosed MM in real clinical practice prove to have high and increasing with age comorbidity incidence (91 % in patients of young/middle age, 97,7 % and 100 % in patients of elderly and old age, respectively). Comorbidity significantly reduces overall survival (OS) of MM patients. Important OS predictors are rhythm and conduction disorder (odds ratio, OR, 2.762; < 0.002), chronic pancreatitis (OR 1.864; < 0.001), exogenous constitutive obesity (OR 1.948; < 0.002), chronic obstructive pulmonary disease (OR 2.105; < 0.021), chronic kidney disease, stage С4–С5 (OR 2.255; < 0.003), and chronic heart failure, functional class II (OR 1.915; < 0.002). Highest importance in predicting OS, efficacy, and tolerance to chemotherapy in MM patients is attached to MCI score (OR 3.771; < 0.001). MM patients with high risk by MCI are characterized by lower rate and depth of response to the first-line therapy, shorter time before the first relapse, higher incidence of non-hematologic toxicity of grade ≥ 3, and therapy withdrawal or drug dose reduction.

Conclusion. Comorbidity assessment in MM patients is important for outcome prediction and treatment planning.

Keywords: multiple myeloma, comorbidity, comorbidity scores, overall survival, personalized treatment.

Received: April 2, 2020

Accepted: June 18, 2020

Read in PDF


REFERENCES

  1. Plummer С, Driessen C, Szabo Z, et al. Management of cardiovascular risk in patients with multiple myeloma. Blood Cancer J. 2019;9(3):26. doi: 10.1038/s41408-019-0183-y.

  2. National Cancer Institute. Cancer stat facts: myeloma 2017. Available from: https://seer.cancer.gov/statfacts/html/mulmy.html (accessed 12.05.2020).

  3. National Cancer Institute. Common Terminology Criteria for Adverse Events (version 5.0) 2017. Available from: https://ctep.cancer.gov/protocolDevelopment/electronic_applications/docs/С5х11.pdf (accessed 12.05.2020).

  4. National Cancer Institute. SEER Cancer Statistics Review (CSR) 1975–2014, Available from: https://seer.cancer.gov/csr/1975_2014 (accessed 12.05.2020).

  5. Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538–e548. doi: 10.1016/S1470-2045(14)70442-5.

  6. Morgan GJ, Walker BA, Davies FE. The genetic architecture of multiple myeloma. Nat Rev Cancer. 2012;12(5):335–48. doi: 10.1038/nrc3257.

  7. Bianchi G, Munshi NC. Pathogenesis beyond the cancer clone(s) in multiple myeloma. Blood. 2015;125(20):3049–58. doi: 10.1182/blood-2014-11-568881.

  8. Liwing J, Uttervall K, Lund J, et al. Improved survival in myeloma patients: Starting to close in on the gap between elderly patients and a matched normal population. Br J Haematol. 2014;164(5):684–93. doi: 10.1111/bjh.12685.

  9. Bringhen S, Mateos MV, Zweegman S, et al. Age and organ damage correlate with poor survival in myeloma patients: Meta-analysis of 1435 individual patient data from 4 randomized trials. Haematologica. 2013:98(6):980–7. doi: 10.3324/haematol.2012.075051.

  10. Costa LJ, Brill IK, Omel J, et al. Recent trends in multiple myeloma incidence and survival by age, race, and ethnicity in the United States. Blood Adv. 2017;1(1):282–7. doi: 10.1182/bloodadvances.2016002493.

  11. Hsu P, Lin T, Gau JP, et al. Risk of early mortality in patients with newly diagnosed multiple myeloma. Medicine. 2015;94(50):1–7. doi: 10.1097/MD.0000000000002305.

  12. Holmstrom MO, Gimsing P, Abildgaard N, et al. Causes of early death in multiple myeloma patients who are ineligible for high-dose therapy with hematopoietic stem cell support: A study based on the nationwide Danish Myeloma Database. Am J Hematol. 2015;90(4):E73–E74. doi: 10.1002/ajh.23932.

  13. Chen YK, Han SM, Yang Y, et al. Early mortality in multiple myeloma: Experiences from a single institution. Hematology. 2016;21(7):392–8. doi: 10.1080/10245332.2015.1101969.

  14. Kumar SK, Dispenzieri A, Lacy MQ, et al. Continued improvement in survival in multiple myeloma: Changes in early mortality and outcomes in older patients. Leukemia. 2014;28(5):1122–8. doi: 10.1038/leu.2013.313.

  15. Costa LJ, Gonsalves WI, Kumar SK. Early mortality in multiple myeloma. Leukemia. 2015;29(7):1616–8. doi: 10.1038/leu.2015.33.

  16. Williams GR, Mackenzie A, Magnuson A, et al. Comorbidity in Older Adults with Cancer. J Geriatr Oncol. 2016;7(4):249–57. doi: 1016/j.jgo.2015.12.002.

  17. Романова Е.В. Влияние коморбидности на эффективность лечения пациентов с множественной миеломой. Сибирский медицинский журнал. 2015;134(3):54–7.[Romanova EV. The effect of comorbidity on the efficacy of treatment in patients with multiple myeloma. Sibirskii meditsinskii zhurnal. 2015;134(3):54–7. (In Russ)]

  18. Юрова Е.В., Семочкин С.В. Множественная миелома, осложненная сопутствующей кардиологической патологией. Гематология и трансфузиология. 2017;62(3):140–6. doi: 10.18821/0234-5730-2017-62-3-140-146.[Yurova EV, Semochkin SV. Multiple myeloma complicated by concomitant cardiological pathology. Gematologiya i transfuziologiya. 2017;62(3):140–6. doi: 10.18821/0234-5730-2017-62-3-140-146. (In Russ)]

  19. Zhong Y-P, Zhang Y-Z, Liao A-J, et al. Geriatric Assessment to Predict Survival and Risk of Serious Adverse Events in Elderly Newly Diagnosed Multiple Myeloma Patients: A Multicenter Study in China. Chin Med J (Engl). 2017;130(2):130–4. doi: 10.4103/0366-6999.197977.

  20. Palumbo A, Bringhen S, Mateos M-V, et al. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report. Blood. 2015;125(13):2068–74. doi: 10.1182/blood-2014-12-615187.

  21. Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised international staging system for multiple myeloma: A report from international myeloma working group. J Clin Oncol. 2015;33(26):2863–9. doi: 10.1200/JCO.2015.61.2267.

  22. Greipp PR, San Miguel J, Durie BG, et al. International staging system for multiple myeloma. J Clin Oncol. 2005;23(15):3412–20. doi: 10.1200/jco.2005.04.242.

  23. Bila J, Jelicic J, Djurasinovic V, et al. Prognostic effect of comorbidity indices in elderly patients with multiple myeloma. Clin Lymphoma Myel Leuk. 2015;15(7):416–9. doi: 10.1016/j.clml.2015.03.004.

  24. Onec B, Okutan H, Albayrak M, et al. Comparative Evaluation of Common Comorbidity Scores and Freiburger Comorbidity Index as Prognostic Variables in a Real Life Multiple Myeloma Population. Indian J Hematol Blood Transfus. 2016;32(4):424–30. doi: 10.1007/s12288-015-0618-y.

  25. Kim SM, Kim MJ, Jung HA, et al. Comparison of the Freiburg and Charlson Comorbidity Indices in Predicting Overall Survival in Elderly Patients with Newly Diagnosed Multiple Myeloma. BioMed Res Intern. 2014;2014:1–11. doi: 10.1155/2014/437852.

  26. Pompei P, Ales KL, Mac Kenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40(5):373–83. doi: 10.1016/0021-9681(87)90171-8.

  27. Sorror ML, Maris MB, Storb R, et al. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106(8):2912–9. doi: 10.1182/blood-2005-05-2004.

  28. Linn BS, Linn MW, Gurel L. Cumulative illness rating scale. J Am Geriatr Soc. 1968;16(5):622–6. doi: 10.1111/j.1532-5415.1968.tb02103.x.

  29. Kaplan MH, Feinstein AR. The importance of classifying initial co-morbidity in evaluating the outcome of diabetes mellitus. J Chron Dis. 1974;27(7–8):387–404. doi: 10.1016/0021-9681(74)90017-4.

  30. Miller M, Towers A. A manual of guidelines for scoring the cumulative illness rating scale for geriatrics (CIRS-G). May 1991. Available from: https://www.anq.ch/fileadmin/redaktion/deutsch/20121211_CIRSG_Manual_E.pdf (accessed 12.05.2020).

  31. Engelhardt M, Dold SM, Ihorst G, et al. Geriatric assessment in multiple myeloma patients: validation of the International Myeloma Working Group (IMWG) score and comparison with other common comorbidity scores. Haematologica. 2016;101(9):1110–9. doi: 10.3324/haematol.2016.148189.

  32. Engelhardt M, Domm AS, Dold SM, et al. A concise revised Myeloma Comorbidity Index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients. Haematologica. 2017;102(5):910–21. doi: 10.3324/haematol.2016.162693.

  33. Kleber M, Ihorst G, Terhorst M, et al. Comorbidity as a prognostic variable in multiple myeloma: comparative evaluation of common comorbidity scores and use of a novel MM-comorbidity score. Blood Cancer J. 2011;1(9):e35. doi: 10.1038/bcj.2011.34.

  34. Kleber M, Ihorst G, Gross B, et al. Validation of the Freiburg Comorbidity Index in 466 multiple myeloma patients and combination with the international staging system are highly predictive for outcome. Clin Lymphoma Myeloma Leuk. 2013;13(5):541–51. doi: 10.1016/j.clml.2013.03.013.

  35. Mohammadi M, Cao Y, Glimelius I, et al. The impact of comorbid disease history on all-cause and cancer-specific mortality in myeloid leukemia and myeloma – a Swedish population-based study. BMC Cancer. 2015;15(1):850. doi: 10.1186/s12885-015-1857-x.

  36. Gregersen H, Vangsted A, Abildgaard N, et al. The impact of comorbidity on mortality in multiple myeloma: a Danish nationwide population- based study. Cancer Med. 2017;6(7):1807–16. doi: 10.1002/cam4.1128.

  37. Larocca A, Bringhen S, Evangelista A, et al. A simple score, based on geriatric assessment, improves prediction of survival, and risk of serious adverse events in elderly newly diagnosed multiple myeloma patients. Blood. 2013;122(21):687. doi: 10.1182/blood.v122.21.687.687.

  38. Sarfati D, Gurney J, Stanley J, et al. Cancer-specific administrative data-based comorbidity indices provided valid alternative to Charlson and National Cancer Institute Indices. J Clin Epidemiol. 2014;67(5):586–95. doi: 1016/j.jclinepi.2013.11.012.

  39. Offidani M, Corvatta L, Polloni C, et al. Assessment of vulnerability measures and their effect on survival in a real- life population of multiple myeloma patients registered at Marche Region Multiple Myeloma Registry. Clin Lymphoma Myel Leuk. 2012;12(6):423–32. doi: 10.1016/j.clml.2012.06.008.

  40. Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538–е548. doi: 10.1016/S1470-2045(14)70442-5.

  41. Durie BGM, Salmon SE. A clinical staging system for multiple myeloma. Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival. Cancer. 1975;36(3):842– doi: 10.1002/1097-0142(197509)36:3<842::aid-cncr2820360303>3.0.co;2-u.

  42. Менделеева Л.П., Вотякова О.М., Покровская О.С. и др. Национальные клинические рекомендации по диагностике и лечению множественной миеломы. Гематология и трансфузиология. 2016;61(1, прил. 2):1–24. doi: 10.18821/0234-5730-2016-61-1-S2-1-24.[Mendeleeva LP, Votyakova OM, Pokrovskaya OS, et al. National clinical guidelines on diagnosis and treatment of multiple myeloma. Gematologiya i transfuziologiya. 2016;61(1, Suppl 2):1–24. doi: 10.18821/0234-5730-2016-61-1-S2-1-24. (In Russ)]

  43. Durie BG, Harousseau JL, Miguel JS, et al. International uniform response criteria for multiple myeloma. Leukemia. 2006;20(9):1467–73. doi: 10.1038/sj.leu.2404284.

  44. S. Department of Health and Human Services. Common Terminology Criteria for Adverse Events (CTCAE). Version 4.0. Available from: https://evs.nci.nih.gov/ftp1/CTCAE/CTCAE_4.03_2010-06-14._QuickReference_5x7.pdf (accessed 12.05.2020).

  45. Blade J, Fernandez-Llama P, Bosch F, et al. Renal failure in multiple myeloma. Intern Med. 1998;158(17):1889–93. doi: 10.1001/archinte.158.17.1889.

  46. Hari P, Romanus D, Luptakova K, et al. The impact of age and comorbidities on practice and outcomes in patients with relapsed/refractory multiple myeloma in the era of novel therapies. J Geriatr Oncol. 2018;9(2):138–44. doi: 10.1016/j.jgo.2017.09.007.

  47. Dimopoulos MA, Terpos E, Niesvizky R, Palumbo A. Clinical characteristics of patients with relapse multiple myeloma. Cancer Treat Rev. 2015;41(10):827–35. doi: 10.1016/j.ctrv.2015.07.005.

  48. Dimopoulos MA, Palumbo A, Hajek R, et al. Factors that influence health-related quality of life in newly diagnosed patients with multiple myeloma aged ≥ 65 years treated with melphalan, prednisone and lenalidomide followed by lenalidomide maintenance: Results of a randomized trial. Leuk Lymphoma. 2014;55(7):1489–97. doi: 10.3109/10428194.2013.847933.

  49. Chien JW, Chen XC, Chen XZ. Carbon monoxide diffusion capacity: how low can you go for hematopoietic cell transplantation eligibility. Biol Blood Marrow Transplant. 2009;15(4):447–53. doi: 10.1016/j.bbmt.2008.12.509.

  50. Labonte L, Iqbal T, Zaidi MA, et al. Utility of comorbidity assessment in predicting transplantation-related toxicity following autologous hematopoietic stem cell transplantation for multiple myeloma. Biol Blood Marrow Transplant. 2008;14(9):1039–44. doi: 10.1016/j.bbmt.2008.06.019.