In patients diagnosed with multiple myeloma (MM), the primary complaints at the time of diagnosis are often related to bone involvement, significantly impacting quality of life and increasing both morbidity and mortality. Obesity is associated with a chronic inflammatory state that results in the production of various cytokines and adipokines, which may promote bone destruction. Adiponectin, an adipokine predominantly secreted by adipocytes, is notably diminished in circulation among individuals with obesity, a phenomenon that has also been observed in MM. This reduction may contribute to the disruption of an already compromised bone architecture. The increase in adipose tissue is associated with heightened leptin production, a key adipokine, which can play a significant role in the pathophysiology of MM and its related bone complications. Obesity is associated with hyperinsulinemia and increased levels of free IGF-1. In MM, IGF-1 plays a critical role as a growth factor, produced by both myeloma cells and osteoclasts within the bone marrow microenvironment. Our gathered data indicates a significant relationship between the adipokines produced by adipose tissue and the bone matrix, particularly in the context of obesity and MM. However, it is important to note that the existing body of research on this topic is relatively sparse, with the majority of studies conducted on murine models rather than human subjects. This limitation highlights a critical need for further investigation to elucidate the precise mechanisms that contribute to bone destruction under these conditions.

Background/Objectives: Inflammatory and hematologic indices derived from routine blood tests have been increasingly investigated as prognostic biomarkers in multiple myeloma (MM). However, their clinical utility remains inconsistent, and data on novel composite indices, such as the mean corpuscular volume-to-lymphocyte ratio (MCVL) and the cumulative inflammatory index (IIC), are lacking in MM. Methods: We conducted a retrospective study including 122 patients with newly diagnosed MM. Hematologic and inflammatory indices were evaluated at baseline and after four cycles of induction therapy. Associations with progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan–Meier analysis, Cox regression models, and receiver operating characteristic (ROC) curve analysis. Results: Baseline inflammatory biomarkers, including NLR, PLR, MLR, SII, as well as MCVL and IIC, were not significantly associated with PFS or OS. ROC analysis demonstrated poor discriminative ability for all evaluated markers at both baseline and post-induction timepoints (AUC values close to or below 0.50). In contrast, post-induction inflammatory indices, particularly PLR, MLR, AISI, and SIRI, were significantly associated with PFS in both univariable and multivariable Cox regression analyses. Neither baseline nor post-induction MCVL and IIC showed independent prognostic value. Conclusions: Baseline inflammatory and erythrocyte-derived indices, including the novel composite markers MCVL and IIC, have limited prognostic utility in MM. In contrast, dynamic changes in inflammatory biomarkers during treatment may provide more clinically relevant information regarding disease progression. These findings support the integration of longitudinal biomarker assessment into future risk stratification models in MM.

Background/Objectives: Inflammatory and hematologic indices derived from routine blood tests have been increasingly investigated as prognostic biomarkers in multiple myeloma (MM). However, their clinical utility remains inconsistent, and data on novel composite indices, such as the mean corpuscular volume-to-lymphocyte ratio (MCVL) and the cumulative inflammatory index (IIC), are lacking in MM. Methods: We conducted a retrospective study including 122 patients with newly diagnosed MM. Hematologic and inflammatory indices were evaluated at baseline and after four cycles of induction therapy. Associations with progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan–Meier analysis, Cox regression models, and receiver operating characteristic (ROC) curve analysis. Results: Baseline inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune–inflammation index (SII), MCVL, and IIC, were not significantly associated with PFS or OS. ROC analysis demonstrated poor discriminative ability for all evaluated markers at both baseline and post-induction timepoints (AUC values close to or below 0.50). In contrast, post-induction inflammatory indices, particularly PLR, MLR, AISI, and SIRI, were significantly associated with PFS in both univariable and multivariable Cox regression analyses. Neither baseline nor post-induction MCVL and IIC showed independent prognostic value. Conclusions: Baseline inflammatory and erythrocyte-derived indices, including the novel composite markers MCVL and IIC, have limited prognostic utility in MM. In contrast, dynamic changes in inflammatory biomarkers during treatment may provide more clinically relevant information regarding disease progression. These findings support integrating longitudinal biomarker assessment into future risk stratification models for MM.

Multiple myeloma (MM) represents a hematologic malignancy involving plasma cells and is associated with organ dysfunction classically summarized by the CRAB acronym. Renal impairment is among its major complications, occurring in almost half of patients with MM. Its presence may influence the clinical course of the disease, limit treatment options, and adversely affect survival. Regarding the pathogenesis of kidney injury, it is multifactorial, with the monoclonal component playing a major role, together with precipitating factors such as hypercalcemia, dehydration, infections, and nephrotoxic medications. The characteristic renal lesions associated with MM include light-chain cast nephropathy, light-chain proximal tubulopathy, AL amyloidosis, and monoclonal immunoglobulin deposition disease, each of which has distinct pathophysiological features and a different clinical course. A positive diagnosis relies on integrating clinical findings with laboratory investigations, among which serum free light-chain measurement plays an important role, while renal biopsy may be required in selected cases. Regarding the treatment of renal impairment, the main therapeutic goal is the rapid reduction of the monoclonal free light chains in order to limit further renal damage and promote renal recovery. This objective can be achieved with anti-myeloma agents such as proteasome inhibitor-based regimens and anti-CD38 monoclonal antibodies, while supportive measures remain essential for optimizing kidney function. This chapter discusses the mechanisms underlying myeloma-associated kidney disease, its diagnostic approach, and current treatment strategies, with particular attention to renal recovery and emerging therapeutic options.