Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Multiple myeloma gammopathies

Defining the vulnerable patient with myeloma—a frailty position paper of the European Myeloma Network

Abstract

As the treatment landscape continues to evolve towards the application of precision medicine in multiple myeloma (MM), there is a clear need to identify those patients who are at risk of not achieving the maximum benefit whilst exposed to the highest level of toxicity. This group of patients, defined as frail, is an unmet clinical need. However, how we define such a vulnerable group of patients with MM remains to be clarified. An integral aspect of this is to define the physiological age and capacity of patients with MM to deal with the burden of their disease and it’s treatment. Such assessments may include not only functional and clinical assessments but also laboratory-based biomarkers of frailty, aging and senescent cellular burden. A need to develop, test and validate clinical screening scores before their adoption into clinical practice is mandated. This position paper from the European Myeloma Network aims to review what is known about defining frailty in MM, and how we can advance this knowledge for the design of clinical trials and ultimately how we deliver treatment in the clinic.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Defining frailty in suscetible populations.
Fig. 2: The Frailty Spiral. The impact of aging, cellualr senescence and comorbidities on the evolution of frailty wiht the myeloma clinical features acting as “accelerants”.

Similar content being viewed by others

References

  1. Pilleron S, Sarfati D, Janssen-Heijnen M, Vignat J, Ferlay J, Bray F, et al. Global cancer incidence in older adults, 2012 and 2035: a population-based study. Int J Cancer. 2019;144:49–58.

    Article  CAS  PubMed  Google Scholar 

  2. Palumbo A, Bringhen S, Ludwig H, Dimopoulos MA, Bladé J, Mateos MV, et al. Personalized therapy in multiple myeloma according to patient age and vulnerability: a report of the European Myeloma Network (EMN). Blood. 2011;118:4519–29.

    Article  CAS  PubMed  Google Scholar 

  3. Cowan AJ, Allen C, Barac A, Basaleem H, Bensenor I, Curado MP, et al. Global burden of multiple myeloma: a systematic analysis for the global burden of disease study 2016. JAMA Oncol. 2018;4:1221–7.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Mellqvist U-H. New prognostic tools for myeloma. Blood. 2015;125:2014–5.

    Article  CAS  PubMed  Google Scholar 

  5. Bringhen S, Mateos MV, Zweegman S, Larocca A, Falcone AP, Oriol A, 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;98:980–7.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Kint N, Delforge M. Concise review—treatment of multiple myeloma in the very elderly: how do novel agents fit in? J Geriatr Oncol. 2016;7:383–9.

    Article  PubMed  Google Scholar 

  7. Pawlyn C, Cairns D, Kaiser M, Striha A, Jones J, Shah V, et al. The relative importance of factors predicting outcome for myeloma patients at different ages: results from 3894 patients in the Myeloma XI trial. Leukemia. 2020;34:604–12.

    Article  CAS  PubMed  Google Scholar 

  8. Walter LC, Covinsky KE. Cancer screening in elderly patients: a framework for individualized decision making. JAMA. 2001;285:2750–6.

    Article  CAS  PubMed  Google Scholar 

  9. Zweegman S, Larocca A. Frailty in multiple myeloma: the need for harmony to prevent doing harm. Lancet Haematol. 2019;6:e117–e118.

    Article  PubMed  Google Scholar 

  10. Mateos M-V, Spencer A, Nooka AK, Pour L, Weisel K, Cavo M, et al. Daratumumab-based regimens are highly effective and well tolerated in relapsed or refractory multiple myeloma regardless of patient age: subgroup analysis of the phase 3 CASTOR and POLLUX studies. Haematologica. 2020;105:468–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Pulte D, Jansen L, Castro FA, Emrich K, Katalinic A, Holleczek B, et al. Trends in survival of multiple myeloma patients in Germany and the United States in the first decade of the 21st century. Br J Haematol. 2015;171:189–96.

    Article  PubMed  Google Scholar 

  12. Delforge M, Minuk L, Eisenmann J-C, Arnulf B, Canepa L, Fragasso A, et al. Health-related quality-of-life in patients with newly diagnosed multiple myeloma in the FIRST trial: lenalidomide plus low-dose dexamethasone versus melphalan, prednisone, thalidomide. Haematologica. 2015;100:826–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Benboubker L, Dimopoulos MA, Dispenzieri A, Catalano J, Belch AR, Cavo M, et al. Lenalidomide and dexamethasone in transplant-ineligible patients with myeloma. N Engl J Med. 2014;371:906–17.

    Article  CAS  PubMed  Google Scholar 

  14. Facon T, Dimopoulos MA, Meuleman N, Belch A, Mohty M, Chen W-M, et al. A simplified frailty scale predicts outcomes in transplant-ineligible patients with newly diagnosed multiple myeloma treated in the FIRST (MM-020) trial. Leukemia. 2020;34:224–33.

    Article  PubMed  Google Scholar 

  15. Stege CAM, van der Holt B, Dinmohamed AG, Sonneveld P, Levin M-D, van de Donk NWCJ, et al. Validation of the FIRST simplified frailty scale using the ECOG performance status instead of patient-reported activities. Leukemia. 2020. https://doi.org/10.1038/s41375-020-0713-4.

  16. Palumbo A, Avet-Loiseau H, Oliva S, Lokhorst HM, Goldschmidt H, Rosinol L, et al. Revised international staging system for multiple myeloma: a report from international myeloma working group. J Clin Oncol. 2015;33:2863–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Facon T, Anderson K. Treatment approach for the older, unfit patient with myeloma from diagnosis to relapse: perspectives of a European hematologist. Hematology Am Soc Hematol Educ Program. 2018;2018:83–87.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Fried LP, Hadley EC, Walston JD, Newman AB, Newman A, Guralnik JM, et al. From bedside to bench: research agenda for frailty. Sci Aging Knowledge Environ. 2005;2005:pe24.

    Article  PubMed  Google Scholar 

  19. Collard RM, Boter H, Schoevers RA, Oude Voshaar RC. Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc. 2012;60:1487–92.

    Article  PubMed  Google Scholar 

  20. Engelhardt M, Domm A-S, Dold SM, Ihorst G, Reinhardt H, Zober A, et al. A concise revised Myeloma Comorbidity Index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients. Haematologica. 2017;102:910–21.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146–156.

    Article  CAS  PubMed  Google Scholar 

  22. Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007;62:722–7.

    Article  PubMed  Google Scholar 

  23. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:601.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cesari M. The frailty phenotype and sarcopenia: similar but not the same. Aging Med (Milton). 2019;2:97–98.

    Article  Google Scholar 

  25. Mohile SG, Dale W, Somerfield MR, Schonberg MA, Boyd CM, Burhenn PS, et al. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology. J Clin Oncol. 2018;36:2326–47.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Kuroda J, Shimura Y, Ohta K, Tanaka H, Shibayama H, Kosugi S, et al. Limited value of the international staging system for predicting long-term outcome of transplant-ineligible, newly diagnosed, symptomatic multiple myeloma in the era of novel agents. Int J Hematol. 2014;99:441–9.

    Article  CAS  PubMed  Google Scholar 

  27. Wildes TM, Campagnaro E. Management of multiple myeloma in older adults: gaining ground with geriatric assessment. J Geriatr Oncol. 2017;8:1–7.

    Article  PubMed  Google Scholar 

  28. Wildes TM, Tuchman SA, Klepin HD, Mikhael J, Trinkaus K, Stockerl-Goldstein K, et al. Geriatric assessment in older adults with multiple myeloma. J Am Geriatr Soc. 2019;67:987–91.

    Article  PubMed  Google Scholar 

  29. Palumbo A, Bringhen S, Mateos M-V, Larocca A, Facon T, Kumar SK, et al. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report. Blood. 2015;125:2068–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kojima G. Quick and simple FRAIL scale predicts incident activities of daily living (ADL) and instrumental ADL (IADL) disabilities: a systematic review and meta-analysis. J Am Med Dir Assoc. 2018;19:1063–8.

    Article  PubMed  Google Scholar 

  31. Mina R, Bringhen S, Wildes TM, Zweegman S, Rosko AE. Approach to the older adult with multiple myeloma. Am Soc Clin Oncol Educ Book. 2019;39:500–18.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Salazar AS, Recinos LM, Mian HS, Stoll C, Simon LE, Sekhon S, et al. Geriatric assessment and frailty scores predict mortality in myeloma: systematic review and meta-analysis. Clin Lymphoma Myeloma Leuk. 2019;19:488–496.e6.

    Article  PubMed  Google Scholar 

  33. Engelhardt M, Dold SM, Ihorst G, Zober A, Möller M, Reinhardt H, 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;101:1110–9.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Milani P, Vincent Rajkumar S, Merlini G, Kumar S, Gertz MA, Palladini G, et al. N-terminal fragment of the type-B natriuretic peptide (NT-proBNP) contributes to a simple new frailty score in patients with newly diagnosed multiple myeloma. Am J Hematol. 2016;91:1129–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Dold SM, Möller M-D, Ihorst G, Langer C, Pönisch W, Mügge L-O et al. Validation of the revised myeloma comorbidity index and other comorbidity scores in a multicenter German study group multiple myeloma trial. Haematologica. 2020. https://doi.org/10.3324/haematol.2020.254235.

  36. Offidani M, Corvatta L, Polloni C, Centurioni R, Visani G, Brunori M, 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 Myeloma Leuk. 2012;12:423–32.

    Article  PubMed  Google Scholar 

  37. Cook G, Royle K-L, Pawlyn C, Hockaday A, Shah V, Kaiser MF, et al. A clinical prediction model for outcome and therapy delivery in transplant-ineligible patients with myeloma (UK Myeloma Research Alliance Risk Profile): a development and validation study. Lancet Haematol. 2019;6:e154–e166.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Redder L, Klausen TW, Vangsted AJ, Gregersen H, Andersen NF, Pedersen RS, et al. Validation of a new clinical prediction model for outcome in newly diagnosed multiple myeloma patients not eligible for autologous stem-cell transplantation; a population-based study from the danish national multiple myeloma registry. Blood. 2019;134:1849–1849.

    Article  Google Scholar 

  39. Barnwell-Ménard J-L, Li Q, Cohen AA. Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable. Stat Med. 2015;34:936–49.

    Article  PubMed  Google Scholar 

  40. Giri S, Williams G, Rosko A, Grant SJ, Mian HS, Tuchman S, et al. Simplified frailty assessment tools: are we really capturing frailty or something else? Leukemia. 2020. https://doi.org/10.1038/s41375-020-0712-5.

  41. Razjouyan J, Naik AD, Horstman MJ, Kunik ME, Amirmazaheri M, Zhou H, et al. Wearable sensors and the assessment of frailty among vulnerable older adults: an observational cohort study. Sensors (Basel). 2018;18. https://doi.org/10.3390/s18051336.

  42. Engelhardt M, Ihorst G, Duque-Afonso J, Wedding U, Spät-Schwalbe E, Goede V, et al. Structured assessment of frailty in multiple myeloma as a paradigm of individualized treatment algorithms in cancer patients at advanced age. Haematologica. 2020;105:1183–8.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Sorror ML, Maris MB, Storb R, Baron F, Sandmaier BM, Maloney DG, et al. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106:2912–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Isaacs A, Fiala M, Tuchman S, Wildes TM. A comparison of three different approaches to defining frailty in older patients with multiple myeloma. J Geriatr Oncol. 2020;11:311–5.

    Article  PubMed  Google Scholar 

  45. Mian H, Brouwers M, Kouroukis CT, Wildes TM. Comparison of frailty scores in newly diagnosed patients with multiple myeloma: a review. J Frailty Aging. 2019;8:215–21.

    CAS  PubMed  Google Scholar 

  46. Guerard EJ, Deal AM, Chang Y, Williams GR, Nyrop KA, Pergolotti M, et al. Frailty index developed from a cancer-specific geriatric assessment and the association with mortality among older adults with cancer. J Natl Compr Canc Netw. 2017;15:894–902.

    Article  PubMed  Google Scholar 

  47. Campisi J, Kapahi P, Lithgow GJ, Melov S, Newman JC, Verdin E. From discoveries in ageing research to therapeutics for healthy ageing. Nature. 2019;571:183–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Saedi AA, Feehan J, Phu S, Duque G. Current and emerging biomarkers of frailty in the elderly. Clin Interv Aging. 2019;14:389–98.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Muscedere J, Kim PM, Afilalo J, Balion C, Baracos VE, Bowdish D, et al. Proceedings of the Canadian frailty network workshop: identifying biomarkers of frailty to support frailty risk assessment, diagnosis and prognosis. Toronto, January 15, 2018. J Frailty Aging. 2019;8:106–16.

    CAS  PubMed  Google Scholar 

  50. Oldenhuis CNaM, Oosting SF, Gietema JA, de Vries EGE. Prognostic versus predictive value of biomarkers in oncology. Eur J Cancer. 2008;44:946–53.

    Article  CAS  PubMed  Google Scholar 

  51. Picca A, Calvani R. Biomarkers of frailty: moving the field forward. Exp Gerontol. 2020;133:110868.

    Article  PubMed  Google Scholar 

  52. Hayflick L, Moorhead PS. The serial cultivation of human diploid cell strains. Exp Cell Res. 1961;25:585–621.

    Article  CAS  PubMed  Google Scholar 

  53. Coppé J-P, Patil CK, Rodier F, Sun Y, Muñoz DP, Goldstein J, et al. Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol. 2008;6:2853–68.

    Article  PubMed  CAS  Google Scholar 

  54. Matjusaitis M, Chin G, Sarnoski EA, Stolzing A. Biomarkers to identify and isolate senescent cells. Ageing Res Rev. 2016;29:1–12.

    Article  CAS  PubMed  Google Scholar 

  55. Zhou J, Wang J, Shen Y, Yang Y, Huang P, Chen S, et al. The association between telomere length and frailty: a systematic review and meta-analysis. Exp Gerontol. 2018;106:16–20.

    Article  CAS  PubMed  Google Scholar 

  56. Franceschi C, Zaikin A, Gordleeva S, Ivanchenko M, Bonifazi F, Storci G, et al. Inflammaging 2018: an update and a model. Semin Immunol. 2018;40:1–5.

    Article  PubMed  Google Scholar 

  57. Fulop T, Larbi A, Dupuis G, Le Page A, Frost EH, Cohen AA, et al. Immunosenescence and inflamm-aging as two sides of the same coin: friends or foes? Front Immunol. 2017;8:1960.

    Article  PubMed  CAS  Google Scholar 

  58. Franceschi C, Bonafè M, Valensin S, Olivieri F, De Luca M, Ottaviani E, et al. Inflamm-aging. An evolutionary perspective on immunosenescence. Ann NY Acad Sci. 2000;908:244–54.

    Article  CAS  PubMed  Google Scholar 

  59. Vatic M, von Haehling S, Ebner N. Inflammatory biomarkers of frailty. Exp Gerontol. 2020;133:110858.

    Article  PubMed  Google Scholar 

  60. Fulop T, McElhaney J, Pawelec G, Cohen AA, Morais JA, Dupuis G, et al. Frailty, inflammation and immunosenescence. Interdiscip Top Gerontol Geriatr. 2015;41:26–40.

    Article  PubMed  Google Scholar 

  61. McElhaney JE, Zhou X, Talbot HK, Soethout E, Bleackley RC, Granville DJ, et al. The unmet need in the elderly: how immunosenescence, CMV infection, co-morbidities and frailty are a challenge for the development of more effective influenza vaccines. Vaccine. 2012;30:2060–7.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019;393:2636–46.

    Article  PubMed  Google Scholar 

  63. Zakaria HM, Llaniguez JT, Telemi E, Chuang M, Abouelleil M, Wilkinson B, et al. Sarcopenia predicts overall survival in patients with lung, breast, prostate, or myeloma spine metastases undergoing stereotactic body radiation therapy (sbrt), independent of histology. Neurosurgery. 2020;86:705–16.

    Article  PubMed  Google Scholar 

  64. Codari M, Zanardo M, di Sabato ME, Nocerino E, Messina C, Sconfienza LM, et al. MRI-derived biomarkers related to sarcopenia: a systematic review. J Magn Reson Imaging. 2020;51:1117–27.

    Article  PubMed  Google Scholar 

  65. Khan AI, Reiter DA, Sekhar A, Sharma P, Safdar NM, Patil DH, et al. MRI quantitation of abdominal skeletal muscle correlates with CT-based analysis: implications for sarcopenia measurement. Appl Physiol Nutr Metab. 2019;44:814–9.

    Article  PubMed  Google Scholar 

  66. Cawthon PM, Orwoll ES, Peters KE, Ensrud KE, Cauley JA, Kado DM, et al. Strong relation between muscle mass determined by D3-creatine dilution, physical performance, and incidence of falls and mobility limitations in a prospective cohort of older men. J Gerontol A Biol Sci Med Sci. 2019;74:844–52.

    Article  PubMed  Google Scholar 

  67. Stege CAM, Nasserinejad K, Levin M-D, Klein SK, Waal E, de, Eeltink C, et al. Geriatric impairments and low muscle mass are associated with treatment discontinuation and overall survival in newly diagnosed non-transplant eligible multiple myeloma patients (nte-NDMM) treated with dose-adjusted melphalan-prednisone-bortezomib (MPV)—results of the Dutch HOVON 123 study. Blood. 2018;132:1889–1889.

    Article  Google Scholar 

  68. Chew J, Tay L, Lim JP, Leung BP, Yeo A, Yew S, et al. Serum myostatin and IGF-1 as gender-specific biomarkers of frailty and low muscle mass in community-dwelling older adults. J Nutr Health Aging. 2019;23:979–86.

    Article  CAS  PubMed  Google Scholar 

  69. Shah JJ, Abonour R, Gasparetto C, Hardin JW, Toomey K, Narang M, et al. Analysis of common eligibility criteria of randomized controlled trials in newly diagnosed multiple myeloma patients and extrapolating outcomes. Clin Lymphoma Myeloma Leuk. 2017;17:575–583.e2.

    Article  PubMed  Google Scholar 

  70. Gregersen H, Vangsted AJ, Abildgaard N, Andersen NF, Pedersen RS, Frølund UC, et al. The impact of comorbidity on mortality in multiple myeloma: a Danish nationwide population-based study. Cancer Med. 2017;6:1807–16.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Valdiglesias V, Sánchez-Flores M, Marcos-Pérez D, Lorenzo-López L, Maseda A, Millán-Calenti JC, et al. Exploring genetic outcomes as frailty biomarkers. J Gerontol A Biol Sci Med Sci. 2019;74:168–75.

    Article  CAS  PubMed  Google Scholar 

  72. Woo J, Tang NLS, Suen E, Leung JCS, Leung PC. Telomeres and frailty. Mech Ageing Dev. 2008;129:642–8.

    Article  CAS  PubMed  Google Scholar 

  73. Nagasawa M, Takami Y, Akasaka H, Kabayama M, Maeda S, Yokoyama S, et al. High plasma adiponectin levels are associated with frailty in a general old-old population: The Septuagenarians, Octogenarians, Nonagenarians Investigation with Centenarians study. Geriatr Gerontol Int. 2018;18:839–46.

    Article  PubMed  Google Scholar 

  74. Tsai J-S, Wu C-H, Chen S-C, Huang K-C, Chen C-Y, Chang C-I, et al. Plasma adiponectin levels correlate positively with an increasing number of components of frailty in male elders. PLoS ONE. 2013;8:e56250.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Kurz DJ, Decary S, Hong Y, Erusalimsky JD. Senescence-associated (beta)-galactosidase reflects an increase in lysosomal mass during replicative ageing of human endothelial cells. J Cell Sci. 2000;113(Pt 20):3613–22.

    Article  CAS  PubMed  Google Scholar 

  76. Gunawardene P, Al Saedi A, Singh L, Bermeo S, Vogrin S, Phu S, et al. Age, gender, and percentage of circulating osteoprogenitor (COP) cells: the COP study. Exp Gerontol. 2017;96:68–72.

    Article  PubMed  Google Scholar 

  77. Yin M-J, Xiong Y-Z, Xu X-J, Huang L-F, Zhang Y, Wang X-J, et al. Tfh cell subset biomarkers and inflammatory markers are associated with frailty status and frailty subtypes in the community-dwelling older population: a cross-sectional study. Aging (Albany NY). 2020;12:2952–73.

    Article  CAS  Google Scholar 

  78. Duggal NA, Pollock RD, Lazarus NR, Harridge S, Lord JM. Major features of immunesenescence, including reduced thymic output, are ameliorated by high levels of physical activity in adulthood. Aging Cell. 2018;17. https://doi.org/10.1111/acel.12750.

  79. Hekmatimoghaddam S, Dehghani Firoozabadi A, Zare-Khormizi MR, Pourrajab F. Sirt1 and Parp1 as epigenome safeguards and microRNAs as SASP-associated signals, in cellular senescence and aging. Ageing Res Rev. 2017;40:120–41.

    Article  CAS  PubMed  Google Scholar 

  80. Portal D, Hofstetter L, Eshed I, Dan-Lantsman C, Sella T, Urban D, et al. L3 skeletal muscle index (L3SMI) is a surrogate marker of sarcopenia and frailty in non-small cell lung cancer patients. Cancer Manag Res. 2019;11:2579–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Kwak JY, Hwang H, Kim S-K, Choi JY, Lee S-M, Bang H, et al. Prediction of sarcopenia using a combination of multiple serum biomarkers. Sci Rep. 2018;8:8574.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Boreskie KF, Oldfield CJ, Hay JL, Moffatt TL, Hiebert BM, Arora RC, et al. Myokines as biomarkers of frailty and cardiovascular disease risk in females. Exp Gerontol. 2020;133:110859.

    Article  CAS  PubMed  Google Scholar 

  83. Waldschmidt JM, Keller A, Ihorst G, Grishina O, Müller S, Wider D, et al. Safety and efficacy of vorinostat, bortezomib, doxorubicin and dexamethasone in a phase I/II study for relapsed or refractory multiple myeloma (VERUMM study: vorinostat in elderly, relapsed and unfit multiple myeloma). Haematologica. 2018;103:e473–e479.

    Article  PubMed  PubMed Central  Google Scholar 

  84. Larocca A, Salvini M, De Paoli L, Cascavilla N, Benevolo G, Galli M, et al. Efficacy and feasibility of dose/schedule-adjusted Rd-R vs. continuous Rd in elderly and intermediate-fit newly diagnosed multiple myeloma (NDMM) patients: RV-MM-PI-0752 phase III randomized study. Blood. 2018;132:305–305.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

GC, AL, SZ, TF and ME designed the manuscript content and GC wrote the first draft. GC, AL, SZ, TF and ME edited and produced the final draft for submission.

Corresponding author

Correspondence to Gordon Cook.

Ethics declarations

Conflict of interest

GC—Honoraria: Amgen, Bristol-Myers Squibb, Celgene, Janssen, Sanofi, Karyopharm and GSK; Research funding: Celgene, Janssen, Takeda. AL—Honoraria: Amgen, Bristol-Myers Squibb, Celgene, Janssen and GSK; Advisory Board: Bristol-Myers Squibb, Celgene, Janssen, Takeda. SZ—Advisory board: Celgene, Janssen, Takeda, Sanofi, Oncopeptides; Research support: Celgene, Janssen, Takeda. TF and ME—no relevant conflicts.

Additional information

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cook, G., Larocca, A., Facon, T. et al. Defining the vulnerable patient with myeloma—a frailty position paper of the European Myeloma Network. Leukemia 34, 2285–2294 (2020). https://doi.org/10.1038/s41375-020-0918-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-020-0918-6

This article is cited by

Search

Quick links