Luca Franceschini

Background: Early relapse in multiple myeloma (MM) is a major predictor of poor prognosis, regardless of cytogenetic risk or treatment intensity. Methods: Here we analyzed 1026 MM patients treated across 12 Italian hematology centers. FHR was defined as progression-free survival (PFS) ≤18 months in transplant-eligible (TE) and ≤12 months in non-transplant-eligible (NTE) patients. Logistic regression and ROC analysis were used to identify significant predictors of FHR and build a risk score. Results: FHR status was identified in 175 patients (17%). These patients had significantly shorter PFS (7 vs. 57.5 months) and overall survival (19 months vs. not reached; p < 0.001). FHR status was associated with higher median LDH, lower Hb level, higher creatinine level and lower platelets count. Modified EASIX formula was built by these significant continuous variables, to be tested in a logistic analysis: [(LDH × creatinine)/(Hb × PLT) × 100]. A significantly higher rate of FHR was found with a score > 2.0 (89% vs. 11%, p < 0.001). Multivariate logistic analysis selected the above formula, ECOG PS ≥ 2 and ISS III as factors associated with FHR. Scoring these variables according to OR, three groups of patients were segregated with a rate of FHR patients of 7%, 29.5%, and 63.5%, respectively. Treatment with anti-CD38 monoclonal antibodies was associated with lower FHR frequency. Conclusions: This study proposes a simple, clinically applicable model to identify FHR MM patients early in their disease course. However, very in-depth biological tools, not available in clinical practice, are needed to identify singularly risk of becoming FHR.

Background/Objectives: Treatments for multiple myeloma (MM) have expanded in the last decade, and the overall survival (OS) of MM patients (pts) is in continuous improvement. With the availability of new treatments and the use of high-dose chemotherapy, followed by autologous hematopoietic stem cell transplantation (ASCT), the median OS of newly diagnosed MM (NDMM) pts is 6–8 years. To date, approximately 50% and 28% of MM patients are still alive at 5 years and 10 years. Few data are reported concerning the characteristics of the long-term survival MM pts. Methods: the aim of this observational multicenter study is to analyze the clinical profile of MM pts who have survived 10 years or longer, to identify possible predictors of long-term survival. Conclusions: this is a real-life observation of a cohort of 344 long-term survivors with MM. The median age of the entire cohort was 59 years (range 27–83). The median years from diagnosis was 13.4 (range 11.3–16.3). Our analysis identified age more than 60 years, hypoalbuminemia at diagnosis, and a number of anti-myeloma therapies equal or more than 3 as significant independent prognostic factors for reduced OS. These finding underline the importance of designing prospective studies to identify clinical, biological, and molecular characteristics that could be used to better stratify newly diagnosed multiple myeloma pts in order to incorporate reproducible biomarkers and to identify tailored optimal target therapies.

Flow cytometry is a highly sensitive and specific approach for discriminating between normal and clonal plasma cells in multiple myeloma. Uniform response criteria after treatment have been established by the International Myeloma Working Group and the EuroFlow Group; however, the way in which flow cytometry data are reported has suffered from no collaborative or multicentre efforts. This study, involving 8 expert laboratories and 12 clinical hematology units of the Lazio region in Italy, aims to produce a uniform and shared report among the various Centres. From the pre-analytical phase to sample processing, data acquisition, analysis, and evaluation of the potential limitations and pitfalls of the entire process, the study reaches a final conclusion shared by laboratories and clinicians according to the most updated principles and recommendations. The aim was to identify the necessary data to be included in the clinical report by using multiple-choice questionnaires at every single stage of the process. An agreement of more than 75% of the laboratories was considered mandatory for the data to be included in the report. By ensuring the operational autonomy of each laboratory, this study provides a clear report that limits subjective interpretations and highlights possible bias in the process, better supporting clinical decision-making.