Prognostic value of low muscle mass at the 12th thoracic vertebral level in multiple myeloma treated with transplantation: CAREMM-2101 study

PURPOSEAutologous hematopoietic stem cell transplantation (ASCT) has been introduced as a standard treatment for newly diagnosed multiple myeloma (NDMM) following novel agent-based induction chemotherapy. This study investigated whether pre-ASCT low muscle mass evaluated using the paraspinal muscle index (PMI) at the 12th thoracic vertebra (T12) level is a reliable prognostic marker in NDMM after chemotherapy.METHODSA multi-center registry database was retrospectively analyzed. Between 2009 and 2020, 190 patients with chest computed tomography images underwent frontline ASCT following induction therapy. The PMI was defined as the value of the paraspinal muscle area at the T12 level divided by the square of the patient’s height. The cut-off value indicating a low muscle mass was sex-specific, using the lowest quintiles.RESULTSOf the 190 patients, 38 (20%) were in the low muscle mass group. The low muscle mass group had a lower 4-year overall survival (OS) rate than the non-low muscle mass group (68.5% vs. 81.2%; P = 0.074). The median progression-free survival (PFS) in the low muscle mass group was significantly shorter compared with the non-low muscle mass group (23.3 months vs. 29.2 months; P = 0.029). The cumulative incidence of transplant-related mortality (TRM) was significantly higher in the low muscle mass group than in the non-low muscle mass group (4-year probability of TRM incidence, 10.6% vs. 0.7%; P < 0.001). In contrast, no significant difference in the cumulative incidence of disease progression was found between the two groups. Multivariate analysis revealed that low muscle mass was associated with significant negative outcomes for OS [(hazard ratio (HR): 2.14; P = 0.047], PFS (HR: 1.78; P = 0.012), and TRM (HR: 12.05; P = 0.025).CONCLUSIONParaspinal muscle mass may have a prognostic role in NDMM patients who undergo ASCT. Patients with low paraspinal muscle mass have lower survival outcomes compared to non-low muscle mass group

Second Primary Glioblastoma Multiforme Following Autologous Hematopoietic Stem Cell Transplantation in a Patient with Acute Myelogenous Leukemia

Glioblastoma multiforme (GM) is one of the most aggressive primary brain tumors, and has a poor prognosis despite intensive treatment. GM is also the most malignant astrocytoma, with histopathological features that include cellular polymorphism, rapid mitotic activity, microvascular proliferation, and necrosis. The causes of GM remain obscure, but several reports have shown associations between GM and genetic alterations and radiation exposure. Furthermore, high-dose chemotherapy/radiotherapy with autologous stem cell transplantation is increasingly being used to treat patients with leukemia, and patients who undergo stem cell transplantation have a higher risk of solid tumor cancer development later in life. Based on these associations, we discuss GM development in a patient who underwent chemoradiotherapy conditioning prior to stem cell transplantation

Serial Measurement of WT1 Expression and Decrement Ratio Until Hematopoietic Cell Transplantation as a Marker of Residual Disease in Patients with Cytogenetically Normal Acute Myelogenous Leukemia

AbstractUsing real-time quantitative PCR, we monitored Wilms tumor gene 1 (WT1) expression from diagnosis to hematopoietic stem cell transplantation (HSCT) in adult patients with cytogenetically normal acute myelogenous leukemia (CN-AML) and FLT3-ITD and NPM1 mutations. The values at diagnosis were evaluated in 104 patients. Data collected after induction chemotherapy were available for all patients, but only 68 patients were treated with HSCT. Significant WT1 expression cut-offs were determined by receiver operation characteristic curve analysis, and rates of overall survival (OS) and disease-free survival (DFS) were estimated. WT1 decrement ratios (DR) at postinduction chemotherapy and at pre- and post-HSCT compared with the diagnostic level were calculated. Higher WT1 expression at diagnosis, postinduction chemotherapy, and pre-HSCT showed inferior OS (P = .015, <.001, and .002) and DFS (P = .006, <.001, and .003). The cut-offs were determined at the median for diagnostic WT1 expression and at the 25% level from the top for other time points excluding post-HSCT. The WT1 DR ≥ 1-log after induction chemotherapy showed superior OS and DFS (P = .009 and .002) and WT1 DR ≥ 1-log preceding HSCT also showed superior OS and DFS (P = .009 and .003). Results of WT1 DR were consistently applicable in each subgroup with higher (≥1.0) and lower (<1.0) WT1 expression at diagnosis and also in NPM1-wild-type/FLT3-ITD–negative CN-AML. The WT1 DR therefore predicted survival outcomes after HSCT more accurately than did the diagnostic WT1 expression. WT1 expression may serve as a reliable marker for residual disease and WT1 DR as a prognostic indicator, particularly in NPM1-wild-type/FLT3-ITD–negative CN-AML. These measures may be applied throughout the course of treatment and even after HSCT

Early Interim Chemotherapy Response Evaluation by F-18 FDG PET/CT in Diffuse Large B Cell Lymphoma

Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) after one cycle of standard chemotherapy in patients with diffuse large B cell lymphoma (DLBCL) was assessed. Prospectively enrolled 51 patients had four PET/CT studies using the same protocol and system: at baseline and after one, three, and six cycles of chemotherapy (PET0, PET1, PET3, PET6). The PET1 and PET6 Deauville five-point score (D5PS) agreed in 60.8%, while PET3 and PET6 D5PS agreed in 90.2%. The absolute and percent changes of peak standard uptake value corrected for lean body mass (SULpeak) compared to baseline were significantly different between PET1 and PET3 (p = 0.001, p &lt; 0.001) and PET1 and PET6 (p = 0.002, p = 0.001), but not between PET3 and PET6 (p = 0.276, p = 0.181). The absolute SULpeak from PET1 predicted treatment failure with accuracy of 78.4% (area under the curve 0.73, p = 0.023). D5PS, SULpeak, and metabolic tumor volume (MTV) were not statistically different between responders versus non-responders, or the one year disease-free versus relapse groups. D5PS and PERCIST responses showed 100% agreement at end-of-therapy. In conclusion, the responses after three and six cycles of therapy showed high degree of agreement. D5PS or MTV after one cycle of chemotherapy could not predict response or one-year disease-free status, but the SULpeak from PET1 was associated with response to first line therapy in DLBCL. Deauville and PERCIST criteria show high concordance

ML-based sequential analysis to assist selection between VMP and RD for newly diagnosed multiple myeloma

Abstract Optimal first-line treatment that enables deeper and longer remission is crucially important for newly diagnosed multiple myeloma (NDMM). In this study, we developed the machine learning (ML) models predicting overall survival (OS) or response of the transplant-ineligible NDMM patients when treated by one of the two regimens—bortezomib plus melphalan plus prednisone (VMP) or lenalidomide plus dexamethasone (RD). Demographic and clinical characteristics obtained during diagnosis were used to train the ML models, which enabled treatment-specific risk stratification. Survival was superior when the patients were treated with the regimen to which they were low risk. The largest difference in OS was observed in the VMP-low risk & RD-high risk group, who recorded a hazard ratio of 0.15 (95% CI: 0.04–0.55) when treated with VMP vs. RD regimen. Retrospective analysis showed that the use of the ML models might have helped to improve the survival and/or response of up to 202 (39%) patients among the entire cohort (N = 514). In this manner, we believe that the ML models trained on clinical data available at diagnosis can assist the individualized selection of optimal first-line treatment for transplant-ineligible NDMM patients