Top

BMC Cancer

Published in:

Open Access 01-12-2015 | Research article

The impact of comorbid disease history on all-cause and cancer-specific mortality in myeloid leukemia and myeloma – a Swedish population-based study

Authors: Mohammad Mohammadi, Yang Cao, Ingrid Glimelius, Matteo Bottai, Sandra Eloranta, Karin E. Smedby

Published in: BMC Cancer | Issue 1/2015

Abstract

Background

Comorbidity increases overall mortality in patients diagnosed with hematological malignancies. The impact of comorbidity on cancer-specific mortality, taking competing risks into account, has not been evaluated.

Methods

Using the Swedish Cancer Register, we identified patients aged >18 years with a first diagnosis of acute myeloid leukemia (AML, N = 2,550), chronic myeloid leukemia (CML, N = 1,000) or myeloma (N = 4,584) 2002–2009. Comorbid disease history was assessed through in- and out-patient care as defined in the Charlson comorbidity index. Mortality rate ratios (MRR) were estimated through 2012 using Poisson regression. Probabilities of cancer-specific death were computed using flexible parametric survival models.

Results

Comorbidity was associated with increased all-cause as well as cancer-specific mortality (cancer-specific MRR: AML = 1.27, 95 % CI: 1.15–1.40; CML = 1.28, 0.96–1.70; myeloma = 1.17, 1.08–1.28) compared with patients without comorbidity. Disorders associated with higher cancer-specific mortality were renal disease (in patients with AML, CML and myeloma), cerebrovascular conditions, dementia, psychiatric disease (AML, myeloma), liver and rheumatic disease (AML), cardiovascular and pulmonary disease (myeloma). The difference in the probability of cancer-specific death, comparing patients with and without comorbidity, was largest among AML patients <70 years, whereas in myeloma the difference did not vary by age among the elderly. The probability of cancer-specific death was generally higher than other-cause death even in older age groups, irrespective of comorbidity.

Conclusion

Comorbidities associated with organ failure or cognitive function are associated with poorer prognosis in several hematological malignancies, likely due to lower treatment tolerability. The results highlight the need for a better balance between treatment toxicity and efficacy in comorbid and elderly AML, CML and myeloma patients.

Available only for authorised users

Siegel R, Ward E, Brawley O, Jemal A. Cancer statistics, 2011. CA Cancer J Clin. 2011;61(4):212–36. doi:10.3322/caac.20121.CrossRefPubMed

GLOBOCAN 2012, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 10 [Internet]. [database on the Internet]. Lyon, France: International Agency for Research on Cancer; 2010. Available from: http://globocan.iarc.fr/Pages/fact_sheets_population.aspx, accessed: on 12/06/2014.

Rose-Inman H, Kuehl D. Acute leukemia. Emerg Med Clin North Am. 2014;32(3):579–96. doi:10.1016/j.emc.2014.04.004.CrossRefPubMed

Berglund A, Garmo H, Tishelman C, Holmberg L, Stattin P, Lambe M. Comorbidity, treatment and mortality: a population based cohort study of prostate cancer in PCBaSe Sweden. J Urol. 2011;185(3):833–9. doi:10.1016/j.juro.2010.10.061.CrossRefPubMed

Jorgensen TL, Hallas J, Friis S, Herrstedt J. Comorbidity in elderly cancer patients in relation to overall and cancer-specific mortality. Br J Cancer. 2012;106(7):1353–60. doi:10.1038/bjc.2012.46.CrossRefPubMedPubMedCentral

Land LH, Dalton SO, Jorgensen TL, Ewertz M. Comorbidity and survival after early breast cancer. A review. Crit Rev Oncol Hematol. 2012;81(2):196–205. doi:10.1016/j.critrevonc.2011.03.001.CrossRefPubMed

Kobayashi Y, Miura K, Hojo A, Hatta Y, Tanaka T, Kurita D, et al. Charlson comorbidity index is an independent prognostic factor among elderly patients with diffuse large B-cell lymphoma. J Cancer Res Clin Oncol. 2011;137(7):1079–84. doi:10.1007/s00432-010-0973-x.CrossRefPubMed

Plattel WJ, Kluin-Nelemans HC, de Bock GH, van Imhoff GW. Prognostic value of comorbidity for auto-SCT eligibility and outcome in relapsed or refractory aggressive non-Hodgkin’s lymphoma. Bone Marrow Transplant. 2011;46(6):827–34. doi:10.1038/bmt.2010.188.CrossRefPubMed

Janssen-Heijnen ML, van Spronsen DJ, Lemmens VE, Houterman S, Verheij KD, Coebergh JW. A population-based study of severity of comorbidity among patients with non-Hodgkin’s lymphoma: prognostic impact independent of International Prognostic Index. Br J Haematol. 2005;129(5):597–606. doi:10.1111/j.1365-2141.2005.05508.x.CrossRefPubMed

10.

Xhaard A, Porcher R, Chien JW, de Latour RP, Robin M, Ribaud P, et al. Impact of comorbidity indexes on non-relapse mortality. Leukemia. 2008;22(11):2062–9. doi:10.1038/leu.2008.197.CrossRefPubMedPubMedCentral

11.

Breccia M, Frustaci AM, Cannella L, Stefanizzi C, Latagliata R, Cartoni C, et al. Comorbidities and FLT3-ITD abnormalities as independent prognostic indicators of survival in elderly acute myeloid leukaemia patients. Hematol Oncol. 2009;27(3):148–53. doi:10.1002/hon.889.CrossRefPubMed

12.

Djunic I, Virijevic M, Novkovic A, Djurasinovic V, Colovic N, Vidovic A, et al. Comorbidity as a risk factor for overall survival and decision criteria for intensity of chemotherapy in elderly patients with acute myeloid leukemia. Med Oncol. 2012;29(2):1077–81. doi:10.1007/s12032-011-9853-8.CrossRefPubMed

13.

Etienne A, Esterni B, Charbonnier A, Mozziconacci MJ, Arnoulet C, Coso D, et al. Comorbidity is an independent predictor of complete remission in elderly patients receiving induction chemotherapy for acute myeloid leukemia. Cancer. 2007;109(7):1376–83. doi:10.1002/cncr.22537.CrossRefPubMed

14.

Ostgard LS, Norgaard JM, Sengelov H, Severinsen M, Friis LS, Marcher CW, et al. Comorbidity and performance status in acute myeloid leukemia patients: a nation-wide population-based cohort study. Leukemia. 2014;29(3):548–55. doi:10.1038/leu.2014.234.CrossRefPubMed

15.

Farina L, Bruno B, Patriarca F, Spina F, Sorasio R, Morelli M, et al. The hematopoietic cell transplantation comorbidity index (HCT-CI) predicts clinical outcomes in lymphoma and myeloma patients after reduced-intensity or non-myeloablative allogeneic stem cell transplantation. Leukemia. 2009;23(6):1131–8. doi:10.1038/leu.2009.1.CrossRefPubMed

16.

Raimondi R, Tosetto A, Oneto R, Cavazzina R, Rodeghiero F, Bacigalupo A, et al. Validation of the hematopoietic cell transplantation-specific comorbidity index: a prospective, multicenter GITMO study. Blood. 2012;120(6):1327–33. doi:10.1182/blood-2012-03-414573.CrossRefPubMed

17.

Bokhari SW, Watson L, Nagra S, Cook M, Byrne JL, Craddock C, et al. Role of HCT-comorbidity index, age and disease status at transplantation in predicting survival and non-relapse mortality in patients with myelodysplasia and leukemia undergoing reduced-intensity-conditioning hemopoeitic progenitor cell transplantation. Bone Marrow Transplant. 2012;47(4):528–34. doi:10.1038/bmt.2011.138.CrossRefPubMed

18.

Kristinsson SY, Derolf AR, Edgren G, Dickman PW, Bjorkholm M. Socioeconomic differences in patient survival are increasing for acute myeloid leukemia and multiple myeloma in sweden. J Clin Oncol. 2009;27(12):2073–80. doi:10.1200/jco.2008.18.2006.CrossRefPubMed

19.

Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.CrossRefPubMed

20.

Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130–9.CrossRefPubMed

21.

Barlow L, Westergren K, Holmberg L, Talback M. The completeness of the Swedish Cancer Register: a sample survey for year 1998. Acta Oncol. 2009;48(1):27–33. doi:10.1080/02841860802247664.CrossRefPubMed

22.

Socialstyrelsen. The national board of health and welfare, Sweden. Available from: https://www.socialstyrelsen.se/register/halsodataregister/cancerregistret/inenglish. Accessed: 12/06/2014

23.

Ludvigsson JF, Andersson E, Ekbom A, Feychting M, Kim JL, Reuterwall C, et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11:450. doi:10.1186/1471-2458-11-450.CrossRefPubMedPubMedCentral

24.

Abu-Shakra M, Buskila D, Ehrenfeld M, Conrad K, Shoenfeld Y. Cancer and autoimmunity: autoimmune and rheumatic features in patients with malignancies. Ann Rheum Dis. 2001;60(5):433–41.CrossRefPubMedPubMedCentral

25.

Ravindran V, Anoop P. Rheumatologic manifestations of benign and malignant haematological disorders. Clin Rheumatol. 2011;30(9):1143–9. doi:10.1007/s10067-011-1799-x.CrossRefPubMed

26.

Knudsen LM, Hippe E, Hjorth M, Holmberg E, Westin J. Renal function in newly diagnosed multiple myeloma--a demographic study of 1353 patients. The Nordic Myeloma Study Group. Eur J Haematol. 1994;53(4):207–12.CrossRefPubMed

27.

Statistics Sweden. Background Facts, Labour and Education Statistics 2009:1, Integrated database for labour market research. Statistics Sweden, Sweden 2009.

28.

Winkleby MA, Jatulis DE, Frank E, Fortmann SP. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. Am J Public Health. 1992;82(6):816–20.CrossRefPubMedPubMedCentral

29.

Liberatos P, Link BG, Kelsey JL. The measurement of social class in epidemiology. Epidemiol Rev. 1988;10:87–121.PubMed

30.

Johansson LA, Westerling R. Comparing Swedish hospital discharge records with death certificates: implications for mortality statistics. Int J Epidemiol. 2000;29(3):495–502.CrossRefPubMed

31.

Howlader N, Ries LA, Mariotto AB, Reichman ME, Ruhl J, Cronin KA. Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010;102(20):1584–98. doi:10.1093/jnci/djq366.CrossRefPubMedPubMedCentral

32.

Johansson LA, Bjorkenstam C, Westerling R. Unexplained differences between hospital and mortality data indicated mistakes in death certification: an investigation of 1,094 deaths in Sweden during 1995. J Clin Epidemiol. 2009;62(11):1202–9. doi:10.1016/j.jclinepi.2009.01.010.CrossRefPubMed

33.

Hinchliffe SR, Lambert PC. Flexible parametric modelling of cause-specific hazards to estimate cumulative incidence functions. BMC Med Res Methodol. 2013;13:13. doi:10.1186/1471-2288-13-13.CrossRefPubMedPubMedCentral

34.

Juliusson G, Antunovic P, Derolf A, Lehmann S, Mollgard L, Stockelberg D, et al. Age and acute myeloid leukemia: real world data on decision to treat and outcomes from the Swedish Acute Leukemia Registry. Blood. 2009;113(18):4179–87. doi:10.1182/blood-2008-07-172007.CrossRefPubMed

35.

Appelbaum FR, Gundacker H, Head DR, Slovak ML, Willman CL, Godwin JE, et al. Age and acute myeloid leukemia. Blood. 2006;107(9):3481–5. doi:10.1182/blood-2005-09-3724.CrossRefPubMedPubMedCentral

36.

Breccia M, Luciano L, Latagliata R, Castagnetti F, Ferrero D, Cavazzini F, et al. Age influences initial dose and compliance to imatinib in chronic myeloid leukemia elderly patients but concomitant comorbidities appear to influence overall and event-free survival. Leuk Res. 2014;38(10):1173–6. doi:10.1016/j.leukres.2014.06.020.CrossRefPubMed

37.

Oran B, Weisdorf DJ. Survival for older patients with acute myeloid leukemia: a population-based study. Haematologica. 2012;97(12):1916–24. doi:10.3324/haematol.2012.066100.CrossRefPubMedPubMedCentral

38.

Budziszewska BK, Pluta A, Sulek K, Wierzbowska A, Robak T, Giebel S, et al. Treatment of elderly patients with acute myeloid leukemia adjusted for performance status and presence of comorbidities; a Polish Adult Leukemia Group (PALG) study. Leuk Lymphoma. 2014;56(8):2331–8. doi:10.3109/10428194.2014.985672.CrossRef

39.

Bjorkholm M, Ohm L, Eloranta S, Derolf A, Hultcrantz M, Sjoberg J, et al. Success story of targeted therapy in chronic myeloid leukemia: a population-based study of patients diagnosed in Sweden from 1973 to 2008. J Clin Oncol. 2011;29(18):2514–20. doi:10.1200/jco.2011.34.7146.CrossRefPubMedPubMedCentral

40.

Hoglund M, Sandin F, Hellstrom K, Bjoreman M, Bjorkholm M, Brune M, et al. Tyrosine kinase inhibitor usage, treatment outcome, and prognostic scores in CML: report from the population-based Swedish CML registry. Blood. 2013;122(7):1284–92. doi:10.1182/blood-2013-04-495598.CrossRefPubMedPubMedCentral

41.

Breccia M, Molica M, Colafigli G, Zacheo I, Latagliata R, Tafuri A, et al. Correlation between Charlson comorbidity index and outcome in chronic phase chronic myeloid leukemia patients treated with second generation tkis upfront. Leuk Lymphoma. 2014;56(7):2206–7. doi:10.3109/10428194.2014.993391.CrossRef

42.

Iurlo A, Ubertis A, Artuso S, Bucelli C, Radice T, Zappa M, et al. Comorbidities and polypharmacy impact on complete cytogenetic response in chronic myeloid leukaemia elderly patients. Eur J Intern Med. 2014;25(1):63–6. doi:10.1016/j.ejim.2013.11.002.CrossRefPubMed

43.

Marcolino MS, Boersma E, Clementino NC, Macedo AV, Marx-Neto AD, Silva MH, et al. Imatinib treatment duration is related to decreased estimated glomerular filtration rate in chronic myeloid leukemia patients. Ann Oncol. 2011;22(9):2073–9. doi:10.1093/annonc/mdq715.CrossRefPubMed

44.

Latagliata R, Ferrero D, Iurlo A, Cavazzini F, Castagnetti F, Abruzzese E, et al. Imatinib in very elderly patients with chronic myeloid leukemia in chronic phase: a retrospective study. Drugs Aging. 2013;30(8):629–37. doi:10.1007/s40266-013-0088-6.CrossRefPubMed

45.

Breccia M, Latagliata R, Stagno F, Luciano L, Gozzini A, Castagnetti F, et al. Charlson comorbidity index and adult comorbidity evaluation-27 scores might predict treatment compliance and development of pleural effusions in elderly patients with chronic myeloid leukemia treated with second-line dasatinib. Haematologica. 2011;96(10):1457–61. doi:10.3324/haematol.2011.041251.CrossRefPubMedPubMedCentral

46.

Klepin HD, Rizzieri D, Palumbo A, Magarotto V, Eichhorst B. Individualizing treatment decisions for older adults with hematologic malignancies. American Society of Clinical Oncology educational book / ASCO American Society of Clinical Oncology Meeting. 2013:208–19. doi:10.1200/EdBook_AM.2013.33.208.

47.

Kristinsson SY, Landgren O, Dickman PW, Derolf AR, Bjorkholm M. Patterns of survival in multiple myeloma: a population-based study of patients diagnosed in Sweden from 1973 to 2003. J Clin Oncol. 2007;25(15):1993–9. doi:10.1200/jco.2006.09.0100.CrossRefPubMed

48.

Ludwig H, Sonneveld P, Davies F, Blade J, Boccadoro M, Cavo M, et al. European perspective on multiple myeloma treatment strategies in 2014. Oncologist. 2014;19(8):829–44. doi:10.1634/theoncologist.2014-0042.CrossRefPubMedPubMedCentral

49.

Kleber M, Ihorst G, Gross B, Koch B, Reinhardt H, Wasch R, 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.CrossRefPubMed

50.

Kleber M, Ihorst G, Terhorst M, Koch B, Deschler B, Wasch R, 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.CrossRefPubMedPubMedCentral

51.

Eleutherakis-Papaiakovou V, Bamias A, Gika D, Simeonidis A, Pouli A, Anagnostopoulos A, et al. Renal failure in multiple myeloma: incidence, correlations, and prognostic significance. Leuk Lymphoma. 2007;48(2):337–41. doi:10.1080/10428190601126602.CrossRefPubMed

52.

Sarfati D, Gurney J, Stanley J, Salmond C, Crampton P, Dennett E, 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:10.1016/j.jclinepi.2013.11.012.CrossRefPubMed

53.

Palumbo A, Gay F. How to treat elderly patients with multiple myeloma: combination of therapy or sequencing. Hematology / the Education Program of the American Society of Hematology American Society of Hematology Education Program. 2009:566–77. doi:10.1182/asheducation-2009.1.566.

54.

Eloranta S, Adolfsson J, Lambert PC, Stattin P, Akre O, Andersson TM, et al. How can we make cancer survival statistics more useful for patients and clinicians: an illustration using localized prostate cancer in Sweden. Cancer Causes Control. 2013;24(3):505–15. doi:10.1007/s10552-012-0141-5.CrossRefPubMed

Title: The impact of comorbid disease history on all-cause and cancer-specific mortality in myeloid leukemia and myeloma – a Swedish population-based study
Authors: Mohammad Mohammadi
Yang Cao
Ingrid Glimelius
Matteo Bottai
Sandra Eloranta
Karin E. Smedby
Publication date: 01-12-2015
Publisher: BioMed Central
Published in: BMC Cancer / Issue 1/2015
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-015-1857-x

Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras

Prof. Fabrice Barlesi

Developed by: Springer Medicine

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 1/2015

Matrix metalloproteases as maestros for the dual role of LPS- and IL-10-stimulated macrophages in cancer cell behaviour

Secreted frizzled-related protein promotors are hypermethylated in cutaneous squamous carcinoma compared with normal epidermis

Population-based SEER trend analysis of overall and cancer-specific survival in 5138 patients with gastrointestinal stromal tumor

Phage display screening identifies a novel peptide to suppress ovarian cancer cells in vitro and in vivo in mouse models

Differences in clinical importance of Bcl-2 in breast cancer according to hormone receptors status or adjuvant endocrine therapy

Platelets enhance tissue factor protein and metastasis initiating cell markers, and act as chemoattractants increasing the migration of ovarian cancer cells

Keynote webinar | Spotlight on antibody–drug conjugates in cancer