Multiple Myeloma

Multiple myeloma is a hematologic malignancy of plasma cells. The median age of patients at initial diagnosis is 65-70 years. For the assessment of a patients general health and for the choice of available therapies, not only the numerical age is important, but also a variety of other factors, such as comorbidities and frailty. Complications in therapy are often increased in patients with comorbidities. Therefore, a predictive risk score has been suggested to be highly useful, which takes these risks into account, rather than choosing therapeutic measures purely based on the numerical age of a patient. This seems also important for the management of therapy selections, therapeutic dose-banding and for the preservation of patients quality of life.

Previous studies at the University Medical Center Freiburg assessed different organ comorbidities of myeloma patients in their value to predict risk groups that differed in progression-free survival and overall survival. As significant prognostic factors for overall survival the following were determined: 1. reduced pulmonary function, 2. impaired renal function and 3. reduced Karnofsky Performance Status (KPS). Using these 3 parameters, the initial Myeloma Comorbidity Index (I-MCI) was developed: with 0 risk factors, an excellent prognosis was determined, with 1 risk factor, an intermediate prognosis and with 2 or 3 risk factors, an unfavorable prognosis was determined.

In order to develop and further improve this score, an even larger group of myeloma patients was analyzed. A total of 13 risk and comorbidity factors were thereby assessed. In addition to the 3 parameters from the I-MCI, age and frailty proved to be important prognostic factors. Frailty is defined according to Fried, which includes KPS, Time Up/Go, IADL and subjective fitness. With these 5 factors, in addition to unfavorable cytogenetics, the revised MCI (R-MCI) was developed and validated. Thus, the R-MCI provides a simple tool to classify myeloma patients into distinct risk groups based on their comorbidities: namely lung and kidney function, general condition, age and frailty, as well as unfavorable cytogenetics. This R-MCI may provide an orientation for upcoming treatment decisions.


The R-MCI is calculated from the regression coefficients of prognostic factors: lung and kidney function, Karnofsky performance status, physical frailty, age and cytogenetics. The underlying regression coefficients are estimated by means of a multivariable Cox proportional hazards regression model based on a backward variable selection. Score weighting results from rounded regression coefficients of the linear predictor (i.e. natural logarithm of odds ratios) multiplied by 5. To simplify this score, it was reduced to a 9 point scale. The classification into "high", "intermediate" and "low risk" patients is based on the 25% and 75% quartile of the R-MCI score determined in our population. For detailed listing of the weightings see: Table.


  1. Engelhardt M, Domm AS, Dold SM, Ihorst G, Reinhardt H, Zober A, Hieke S, Baayen C, Müller SJ, Einsele H, Sonneveld P, Landgren O, Schumacher M, Wäsch R. A concise revised Myeloma Comorbidity Index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients. Haematologica. 2017; 102(5).
  2. Engelhardt M, Dold SM, Ihorst G, Zober A, Möller M, Reinhardt H, Hieke S, Schumacher M, Wäsch R. 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).
  3. Engelhardt M, Terpos E., Kleber M, Gay F, Wäsch R, Morgan G, et al. European Myeloma Network recommendations on the evaluation and treatment of newly diagnosed patients with multiple myeloma. Haematologica. 2014; 99(2).
  4. Terpos E, Kleber M, Engelhardt M, et al. European Myeloma Network Guidelines for the Management of Multiple Myeloma - related Complications. Haematologica. 2015 (in press).
  5. Engelhardt M, Gaiser F, Waldschmidt J, Wäsch R, Kleber M. Basisdiagnose, klinisches Spektrum von plasmazellerkrankungen und Risikostratifizierung. Onkologe. 2014; 20:217-228.
  6. Kleber M, Ihorst G, Groß B, Koch B, Reinhardt H, Wäsch R, Engelhardt M. Validation of the Freiburg Comorbidity Index in 466 Multiple Myeloma Patients and Combination With the International Stating System Are High Predictive for Outcome. Clin Lymphoma Myeloma Leuk. 2013 Oct;13(5):541-51.
  7. Kleber M, Ihorst G, Terhorst M, Koch B, Deschler B, Wäsch R, Engelhardt M. Comorbidity as a prognostic variable in multiple myeloma: comparative evaluation of common comorbidity scores and use of novel MM-comorbidity score. Blood Cancer J. 2011; 1(9).
  8. Reinhardt H, Metzke B, Udi J, Kleber M, Engelhardt M. Innovative Substanzen und Behandlungsmedthoden beim multiplen Myelom. Krankenhauspharmazie. 2012; 33:467-74.
  9. Fried LP, Tangen CM, Walston J, et al.: Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56: M146–56


Department of Hematology and Oncology
Medical Center - University of Freiburg - Interdisziplinäres Tumorzentrum (ITZ)
Hugstetter Str. 53
79106 Freiburg
Phone: +49 (0)761 270 32460
Prof. Dr. med. Monika Engelhardt
Mandy-Deborah Möller , Stephanie Lavielle , Matthias Weiß
Ehemalige Mitarbeiter: Sandra Dold, Alexander Zober

Statistics & Website

Institute for Medical Biometry and Statistics
Center for Medical Biometry and Medical Informatics
Medical Center - University of Freiburg
Stefan-Meier-Str. 26
79104 Freiburg
Prof. Dr. Harald Binder (previous administration: Prof. Dr. Martin Schumacher)
Gabriele Ihorst (Statistics), Jochen Knaus (Website) Stefanie Hieke, Corine Baayen
University medical center Freiburg Deutsche Krebshilfe