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Based on the lack of differences in progression-free and overall survival after a median follow-up of 93 months in our HOVON-65/GMMG-HD4 trial (German part; n = 395) randomizing VAD induction (vincristin/adriamycin/dexamthasone)/tandem-transplantation/thalidomide-maintenance vs. PAD induction (bortezomib/adriamycin/dexamethasone)/tandem transplantation/bortezomib maintenance, we discern how chromosomal aberrations determine long-term prognosis by different patterns of association with proliferation and treatment-dependent response, whether responses achieved by different regimens are equal regarding prognosis, and whether subpopulations of patients could be defined as treatable without upfront "novel agents" in cases of limited resources, e.g., in low- or middle-income countries. Serum parameters and risk factors were assessed in 395 patients. CD138-purified plasma cells were subjected to fluorescence in situ hybridization (n = 354) and gene expression profiling (n = 204). We found chromosomal aberrations to be associated in four patterns with survival, proliferation, and response: deletion (del) del17p13, del8p21, del13q14, (gain) 1q21+, and translocation t(4;14) (all adverse) associate with higher proliferation. Of these, del17p is associated with an adverse response (pattern 1), and 1q21+, t(4;14), and del13q14 with a treatment-dependent better response (pattern 2). Hyperdiploidy associates with lower proliferation without impacting response or survival (pattern 3). Translocation t(11;14) has no association with survival but a treatment-dependent adverse response (pattern 4). Significantly fewer patients reach a near-complete response or better with "conventional" (VAD) vs. bortezomib-based treatment after induction or high-dose melphalan. These patients, however, show significantly better median progression-free and overall survival. Molecularly, patients responding to the two regimens differ in gene expression, indicating distinct biological properties of the responding myeloma cells. Patients with normal renal function (89.4%), low cytogenetic risk (72.5%), or low proliferation rate (37.9%) neither benefit in progression-free nor overall survival from bortezomib-based upfront treatment. We conclude that response level, the treatment by which it is achieved, and molecular background determine long-term prognosis. Chromosomal aberrations are associated in four patterns with proliferation and treatment-dependent responses. Associations with faster and deeper responses can be deceptive in the case of prognostically adverse aberrations 1q21+ and t(4;14). Far from advocating a return to "outdated" treatments, if resources do not permit state-of-the-art-treatment, normal renal function and/or molecular profiling identifies patient subpopulations doing well without upfront "novel agents". [ABSTRACT FROM AUTHOR]

Simple Summary: It is recognized that patients with multiple myeloma (MM) experience a high burden of disease and treatment-related symptoms that impact upon their quality of life (QoL). In these patients, patient-reported outcome (PRO) measures are important in providing information on how treatment affects their QoL. In the past 10 years in the MM setting, the main focus has been to achieve the most durable remission with the best QoL as primary goals of therapy. Optimizing the QoL of patients with MM is an important treatment goal and the use of PROs in clinical trials has the potential to improve treatment outcomes. The present report, on behalf of the European Hematology Association (EHA), provides evidence-based guidelines for the use and reporting of PROs in patients with MM that have been developed according to the EHA's core Guidelines Development Methodology. Currently, there is considerable variation in the measurement of QoL in MM trials, thus underlining the importance of systematic measurements. These Guidelines will aid clinicians, regulatory agencies and the pharmaceutical industry in the measurement of QoL in patients with MM in clinical trials. In the era of personalized medicine there is an increasing need for the assessment of patient-reported outcomes (PROs) to become a standard of patient care. Patient-reported outcome measures (PROM) are important in assessing significant and meaningful changes as a result of an intervention based on a patient's own perspective. It is well established that active multiple myeloma (MM) can be characterized by a high burden of disease and treatment-related symptoms, with considerable worsening of quality of life (QoL). In general, and over the past decade, the focus has shifted to obtaining the most durable remissions with the best QoL as primary goals for MM treatment. Patients place considerable value on their QoL and communicating about QoL data prior to treatment decisions allows them to make informed treatment choices. Consequently, optimization of QoL of patients with MM is an important therapeutic goal and the incorporation of PROs into clinical trials has the potential of improving treatment outcomes. In this regard, guidance for the use and reporting of PROMs in MM in clinical trials is warranted. Under the auspices of the European Hematology Association, evidence-based guidelines for the use and reporting of PROs in patients with MM have been developed according to the EHA's core Guidelines Development Methodology. This document provides general considerations for the choice of PROMs in MM clinical trials as well as a series of recommendations covering a selection of PROMs in MM clinical trials; the mode of administration; timing of assessments; strategies to minimize missing data; sample size calculation; reporting of results; and interpretation of results. [ABSTRACT FROM AUTHOR]

Background: The main goal of this post hoc analysis of the Collaboration to Collect Autologous Transplant Outcomes in Lymphoma and Myeloma (CALM) study was to evaluate the rate of short- and long-term infectious and non-infectious complications occurring after ASCT in patients with multiple myeloma (MM). Methods: The analysis included all patients with MM from the CALM study who underwent ≥1 ASCT. The primary endpoint of the analysis was to determine the rate of infectious and non-infectious complications after ASCT and to compare them in three time periods: 0–100 days, 101 days–1 year, and >1 year after the first transplant. Results: The analysis included a total of 3552 patients followed up for a median of 56.7 months (range 0.4–108.1). Complication rates decreased with the time from ASCT with 24.85 cases per 100 patient-years from day 0 to 100 days after the transplant, and <2.31 cases per 100 patient-years from the 101st day. At 100 days after ASC T, 45.7% of patients had complications, with infectious events being twice as frequent as non-infectious complications. Bacterial infections (6.5 cases per 100 patient-years, 95% CI: 6.1–7.0) and gastrointestinal complications (4.7 cases per 100 patient-years, 95% CI: 4.3–5.1) were the most common early events. The pattern of complications changed with time from ASCT. The presence of complications after ASCT was not associated with overall survival. Conclusions: Our data provide a solid basis for comparing ASCT-related complications to those caused by emerging treatments in multiple myeloma, such as CAR T-cell therapy and other immunotherapies. [ABSTRACT FROM AUTHOR]

We investigated the prognostic impact of time-dependent serum free light chain ratio (FLCr) normalization in 590 patients with secretory multiple myeloma (MM) during first-line treatment within the German-Speaking Myeloma Multicenter Group MM5 trial. Serum free light chains (sFLC) were assessed by the Freelite test at baseline, after induction, mobilization, autologous blood stem cell transplantation, consolidation and every three months during maintenance or follow up within two years after the start of maintenance. The proportion of patients with a normal or normalized FLCr increased from 3.6% at baseline to 23.2% after induction and 64.7% after consolidation. The achievement of FLCr normalization at any one time before the start of maintenance was associated with significantly prolonged progression-free survival (PFS) ( p < 0.01, hazard ratio (HR) = 0.61, 95% confidence interval (95% CI) = 0.47-0.79) and overall survival (OS) ( p = 0.02, HR = 0.67, 95% CI = 0.48-0.93) in multivariable time-dependent Cox regression analyses. Furthermore, reaching immune reconstitution, defined as the normalization of uninvolved immunoglobulins, before maintenance was associated with superior PFS ( p = 0.04, HR = 0.77, 95% CI = 0.60-0.99) and OS ( p = 0.01, HR = 0.59, 95% CI = 0.41-0.86). We conclude that FLCr normalization during therapy is an important favorable prognostic factor in MM. Therefore, we recommend serial measurements of sFLC during therapy until achieving FLCr normalization, even in patients with secretory MM., Competing Interests: E.-M.K.: travel, accommodations, expenses: AMGEN, BMS, Janssen. D.T.: no COI. H.J.S.: honoraria: Janssen Cilag, Takeda, Amgen, BMS/Celgene, Sanofi, Oncopeptides, Abbvie, GSK, Chugai, Pfizer; travel, accommodations, expenses: Janssen, Takeda, Amgen, BMS/Celgene, Sanofi, GSK. E.K.M.: honoraria: Janssen, Celgene, Takeda, GSK; consulting or advisory role: Janssen, Celgene, Takeda, GSK; research funding: Takeda, Celgene/BMS, GSK; travel, accommodations, expenses: Janssen, Takeda, Celgene/BMS, Onyx, Mundipharma, GSK. J.D.: consulting or advisory role: Celgene; speakers bureau: Celgene; travel, accommodations, expenses: Celgene. K.C.W.: honoraria: AMGEN, BMS, Celgene, Novartis, Janssen, Takeda; consulting or advisory role: AMGEN, BMS, Celgene, Juno, Janssen, Adaptive, Sanofi, Takeda; research funding: AMGEN, Celgene, Sanofi, Janssen. A.B.: no COI. U.B.: travel, accommodations, expenses: Sanofi. M.A.: no COI. B.B.: no COI. M.M.: honoraria: Janssen, BMS, Takeda, Celgene, Amgen; consulting or advisory role: Janssen, BMS, Takeda, Celgene, Amgen; research funding: BMS, Incyte; travel, accommodations, expenses: Janssen, BMS, Takeda, Amgen. H.-W.L.: no COI. D.H.: consulting or advisory role: I. Lamkap Bio AG, Discoveric AG; research funding: Celgene AG, Sanofi, Engmab AG; travel, accommodations, expenses: Celgene. A.S.: consulting or advisory role: I. Lamkap Bio AG, Discoveric AG; research funding: Celgene AG, Sanofi, Engmab AG. S.L.: no COI. A.J.: no COI. A.E.: consulting or advisory role: Amgen; travel, accommodations, expenses: Janssen, Amgen. S.F.: consulting or advisory role: Sanofi, BMS, Amgen. P.B.: consulting or advisory role: BMS, AMGEN, Roche, MSD; research funding: BMS; travel, accommodations, expenses: BMS. M.G.: no COI. H.B.: no COI. M.S.R.: honoraria: Celgene, BMS, Novartis, Janssen, Takeda; consulting or advisory role: Celgene, BMS, Novartis, Janssen, Takeda; research funding: Celgene, Novartis, AMGEN; travel, accommodations, expenses: Janssen, BMS, Takeda. I.W.B.: research funding: Celgene, BMS, Janssen. M.H.: honoraria: Novartis, Amgen, Roche, Takeda; consulting or advisory role: Celgene. C.S.: honoraria: BMS, Janssen, Celgene, Novartis, Amgen, Takeda; consulting or advisory role: BMS, Janssen, Celgene, Novartis, Amgen, Takeda; speakers bureau: Takeda; research funding: Takeda, Novartis; travel, accommodations, expenses: BMS, Janssen, Celgene, Novartis, Amgen, Takeda. H.G.: honoraria: Amgen, BMS, Celgene, Chugai, Janssen, Novartis, Takeda; consulting or advisory role: Amgen, BMS, Celgene, Chugai, Janssen, Novartis, Takeda; speakers bureau: Amgen, BMS, Celgene, Janssen, Novartis, Takeda; research funding: Amgen, BMS, Celgene, Chugai, Janssen, Novartis, Takeda; travel, accommodations, expenses: BMS, Celgene, Janssen, Novartis, Takeda. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.