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Prediction of clinical outcomes through assessment of sarcopenia and adipopenia using computed tomography in adult patients with acute myeloid leukemia

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Abstract

Sarcopenia and adipopenia have prognostic significance in cancer. Analysis of a single abdominal computed tomography (CT) section at the third lumbar vertebra has been widely adopted for this purpose. The approach using a single section at the first lumbar vertebra level (L1) may extend clinical viability. We evaluated the prognostic value of sarcopenia and adipopenia assessed using a CT section at L1 in acute myeloid leukemia (AML). Data from 96 patients with available imaging were retrospectively reviewed. Patients with sarcopenia (37.5%) had significantly worse overall survival (OS) (median 17.8 months vs. not reached, p = 0.038) and treatment-related mortality (TRM) (22.2% vs. 3.0%, p = 0.0019) than those without. Subcutaneous adipopenia (51.0%) was significantly associated with inferior OS (median 17.9 months vs. not reached, p = 0.0011), progression-free survival (PFS) (median 6.2 months vs. not reached, p = 0.004), and TRM (16.3% vs. 4%, p = 0.024). Visceral adipopenia (30.2%) was associated with poor OS (12.7 vs. 31.7 months, p = 0.0055) and PFS (3.7 vs. 31.7 months, p = 0.003). Multivariable analyses found sarcopenia, subcutaneous adipopenia and visceral adipopenia were significant negative prognostic factors for OS. Sarcopenia and adipopenia assessed using a single CT section at the L1 level are useful in predicting the prognosis of AML.

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References

  1. Park EH, Lee H, Won YJ, Ju HY, Oh CM, Ingabire C, et al. Nationwide statistical analysis of myeloid malignancies in Korea: incidence and survival rate from 1999 to 2012. Blood Res. 2015;50:204–17.

    Article  Google Scholar 

  2. Yates JW, Wallace HJ Jr, Ellison RR, Holland JF. Cytosine arabinoside (NSC-63878) and daunorubicin (NSC-83142) therapy in acute nonlymphocytic leukemia. Cancer Chemother Rep. 1973;57:485–8.

    CAS  PubMed  Google Scholar 

  3. Dohner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Buchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129:424–47.

    Article  Google Scholar 

  4. Kantarjian HM, Thomas XG, Dmoszynska A, Wierzbowska A, Mazur G, Mayer J, et al. Multicenter, randomized, open-label, phase III trial of decitabine versus patient choice, with physician advice, of either supportive care or low-dose cytarabine for the treatment of older patients with newly diagnosed acute myeloid leukemia. J Clin Oncol. 2012;30:2670–7.

    Article  CAS  Google Scholar 

  5. Bower H, Andersson TM, Bjorkholm M, Dickman PW, Lambert PC, Derolf AR. Continued improvement in survival of acute myeloid leukemia patients: an application of the loss in expectation of life. Blood Cancer J. 2016;6:e390.

    Article  CAS  Google Scholar 

  6. Kim EY, Lee HY, Kim YS, Park I, Ahn HK, Cho EK, et al. Prognostic significance of cachexia score assessed by CT in male patients with small cell lung cancer. Eur J Cancer Care. 2018;27(1):e12695.

    Article  Google Scholar 

  7. Caan BJ, Cespedes Feliciano EM, Prado CM, Alexeeff S, Kroenke CH, Bradshaw P, et al. Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer. JAMA Oncol. 2018;4:798–804.

    Article  Google Scholar 

  8. Black D, Mackay C, Ramsay G, Hamoodi Z, Nanthakumaran S, Park KGM, et al. Prognostic value of computed tomography: measured parameters of body composition in primary operable gastrointestinal cancers. Ann Surg Oncol. 2017;24:2241–51.

    Article  Google Scholar 

  9. Camus V, Lanic H, Kraut J, Modzelewski R, Clatot F, Picquenot JM, et al. Prognostic impact of fat tissue loss and cachexia assessed by computed tomography scan in elderly patients with diffuse large B-cell lymphoma treated with immunochemotherapy. Eur J Haematol. 2014;93:9–18.

    Article  CAS  Google Scholar 

  10. Takeoka Y, Sakatoku K, Miura A, Yamamura R, Araki T, Seura H, et al. Prognostic effect of low subcutaneous adipose tissue on survival outcome in patients with multiple myeloma. Clin Lymphoma Myeloma Leuk. 2016;16:434–41.

    Article  Google Scholar 

  11. Nakamura N, Ninomiya S, Matsumoto T, Nakamura H, Kitagawa J, Shiraki M, et al. Prognostic impact of skeletal muscle assessed by computed tomography in patients with acute myeloid leukemia. Ann Hematol. 2019;98:351–9.

    Article  Google Scholar 

  12. Shen W, Punyanitya M, Wang Z, Gallagher D, St-Onge MP, Albu J, et al. Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image. J Appl Physiol. 1985;2004(97):2333–8.

    Google Scholar 

  13. Derstine BA, Holcombe SA, Ross BE, Wang NC, Su GL, Wang SC. Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population. Sci Rep. 2018;8:11369.

    Article  Google Scholar 

  14. Kim EY, Kim YS, Park I, Ahn HK, Cho EK, Jeong YM, et al. Evaluation of sarcopenia in small-cell lung cancer patients by routine chest CT. Support Care Cancer. 2016;24:4721–6.

    Article  Google Scholar 

  15. Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–405.

    Article  CAS  Google Scholar 

  16. Budczies J, Klauschen F, Sinn BV, Gyorffy B, Schmitt WD, Darb-Esfahani S, et al. Cutoff finder: a comprehensive and straightforward web application enabling rapid biomarker cutoff optimization. PLoS ONE. 2012;7:e51862.

    Article  CAS  Google Scholar 

  17. Donohoe CL, Ryan AM, Reynolds JV. Cancer cachexia: mechanisms and clinical implications. Gastroenterol Res Pract. 2011;2011:601434.

    Article  Google Scholar 

  18. Fearon KC, Voss AC, Hustead DS, Cancer Cachexia Study G. Definition of cancer cachexia: effect of weight loss, reduced food intake, and systemic inflammation on functional status and prognosis. Am J Clin Nutr. 2006;83:1345–50.

    Article  Google Scholar 

  19. Tisdale MJ. Mechanisms of cancer cachexia. Physiol Rev. 2009;89:381–410.

    Article  CAS  Google Scholar 

  20. Tisdale MJ. Cancer cachexia. Curr Opin Gastroenterol. 2010;26:146–51.

    Article  Google Scholar 

  21. McMillan DC, Preston T, Fearon KC, Burns HJ, Slater C, Shenkin A. Protein synthesis in cancer patients with inflammatory response: investigations with [15N]glycine. Nutrition. 1994;10:232–40.

    CAS  PubMed  Google Scholar 

  22. Bachmann J, Heiligensetzer M, Krakowski-Roosen H, Buchler MW, Friess H, Martignoni ME. Cachexia worsens prognosis in patients with resectable pancreatic cancer. J Gastrointest Surg. 2008;12:1193–201.

    Article  Google Scholar 

  23. Morishita S, Kaida K, Tanaka T, Itani Y, Ikegame K, Okada M, et al. Prevalence of sarcopenia and relevance of body composition, physiological function, fatigue, and health-related quality of life in patients before allogeneic hematopoietic stem cell transplantation. Support Care Cancer. 2012;20:3161–8.

    Article  Google Scholar 

  24. Orgel E, Mueske NM, Sposto R, Gilsanz V, Freyer DR, Mittelman SD. Limitations of body mass index to assess body composition due to sarcopenic obesity during leukemia therapy. Leuk Lymphoma. 2018;59:138–45.

    Article  Google Scholar 

  25. Martin L, Birdsell L, Macdonald N, Reiman T, Clandinin MT, McCargar LJ, et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013;31:1539–47.

    Article  Google Scholar 

  26. Othus M, Mukherjee S, Sekeres MA, Godwin J, Petersdorf S, Appelbaum FR, et al. Prediction of CR following a second course of ‘7+3’ in patients with newly diagnosed acute myeloid leukemia not in CR after a first course. Leukemia. 2016;30:1779–80.

    Article  CAS  Google Scholar 

  27. Appelbaum FR, Gundacker H, Head DR, Slovak ML, Willman CL, Godwin JE, et al. Age and acute myeloid leukemia. Blood. 2006;107:3481–5.

    Article  CAS  Google Scholar 

  28. Giles FJ, Borthakur G, Ravandi F, Faderl S, Verstovsek S, Thomas D, et al. The haematopoietic cell transplantation comorbidity index score is predictive of early death and survival in patients over 60 years of age receiving induction therapy for acute myeloid leukaemia. Br J Haematol. 2007;136:624–7.

    Article  Google Scholar 

  29. Stone RM, Mandrekar SJ, Sanford BL, Laumann K, Geyer S, Bloomfield CD, et al. Midostaurin plus chemotherapy for acute myeloid leukemia with a FLT3 mutation. N Engl J Med. 2017;377:454–64.

    Article  CAS  Google Scholar 

  30. Stein EM, DiNardo CD, Pollyea DA, Fathi AT, Roboz GJ, Altman JK, et al. Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood. 2017;130:722–31.

    Article  CAS  Google Scholar 

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Acknowledgements

This study was supported by the National Cancer Center, Korea, Grant NCCCDA2018-07 and NCC-1810160-2. Presented at the International Conference and 60th Annual Meeting (ICKSH), Korean Society of Hematology (KSH), 2019.

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Correspondence to Hyewon Lee.

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Jung, J., Lee, E., Shim, H. et al. Prediction of clinical outcomes through assessment of sarcopenia and adipopenia using computed tomography in adult patients with acute myeloid leukemia. Int J Hematol 114, 44–52 (2021). https://doi.org/10.1007/s12185-021-03122-w

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