scholarly journals Regions of homozygosity as risk factors for multiple myeloma

2019 ◽  
Vol 83 (4) ◽  
pp. 231-238
Author(s):  
Molly Went ◽  
Amit Sud ◽  
Ni Li ◽  
David C. Johnson ◽  
Jonathan S. Mitchell ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Regions Of Homozygosity

Analysis of risk factors for lenalidomide-associated skin rash in patients with multiple myeloma

2021 ◽  
pp. 1-12
Author(s):  
Tomiyuki Sugi ◽  
Yasuo Nishigami ◽  
Hirohisa Saigo ◽  
Homare Hanai ◽  
Keisuke Takabatake ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Skin Rash

Pulmonary Hypertension in Multiple Myeloma: Risk Factors and Impact on Outcomes

CHEST Journal ◽  
2014 ◽  
Vol 146 (4) ◽  
pp. 844A
Author(s):  
Rahul Sangani ◽  
Matthew Butler ◽  
Lester Kirchner ◽  
Andrea Berger ◽  
Jason Stamm
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Pulmonary Hypertension

scholarly journals Prognostic significance of advanced lung cancer inflammation index (ALI) in multiple myeloma patients – a retrospective study

2021 ◽  
Author(s):  
Junxia Huang ◽  
Juanjuan Hu ◽  
Yan Gao ◽  
Fanjun Meng ◽  
Tianlan Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Multiple Myeloma ◽  
Overall Survival ◽  
Progression Free Survival ◽  
Advanced Lung Cancer ◽  
Free Survival ◽  
Factors Influencing ◽  
Independent Risk Factors ◽  
Cancer Inflammation

Abstract Background: Advanced lung cancer inflammation index (ALI) is known to predict the overall survival of patients having some solid tumors or B-cell lymphoma. The study investigates the predictive value of ALI in multiple myeloma (MM) patients and the correlation between ALI and prognosis.Methods: A database of 269 MM consecutive patients who underwent chemotherapy between December 2011 and June 2019 in the Affiliated Hospital of Qingdao University was reviewed. ALI cut-off value calculated before the initial chemotherapy and post 4 courses treatment were identified according to the receiver operating characteristic (ROC) curve, and its association with clinical characteristics, treatment response, overall survival (OS), and progression-free survival (PFS) were assessed.Results: Patients in the low ALI group (n=147) had higher risk of β2 microglobulin elevation, more advanced ISS (International Classification System stage), and TP53 gene mutation, with significantly lower median overall survival (OS; 36.29 vs. 57.92 months, P = 0.010) and progression-free survival (PFS; 30.94 vs. 35.67 months, P = 0.013). Independent risk factors influencing the OS of MM patients were ALI (P = 0.007), extramedullary infiltration (P = 0.001), TP53 (P = 0.020), Plt (P = 0.005), and bone destruction (P = 0.024). ALI (P = 0.005), extramedullary infiltration (P = 0.004), TP53 (P = <0.001), Plt (P = 0.017), and complex chromosome karyotype (P = 0.010) were independent risk factors influencing the PFS of MM patients.Conclusions: ALI is a potential independent risk factor predicting the prognosis of newly diagnosed MM patients.

scholarly journals Bortezomib administration is a risk factor associated with the development of tumor lysis syndrome in male patients with multiple myeloma: A retrospective study

2020 ◽  
Author(s):  
Masahiro Kondo ◽  
Yuji Hotta ◽  
Karen Yamauchi ◽  
Akimasa Sanagawa ◽  
Hirokazu Komatsu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Odds Ratio ◽  
Tumor Lysis Syndrome ◽  
Low Risk ◽  
Novel Therapies ◽  
Tumor Lysis ◽  
Factors Associated ◽  
Increased Risk ◽  
Male Patients

Abstract Background: Novel agents such as proteasome inhibitors have been developed for several years to treat multiple myeloma. Although multiple myeloma is a low-risk disease for developing tumor lysis syndrome (TLS), treatment with these novel therapies might increase TLS risk. Previous studies, mostly case reports or case series, have reported bortezomib-induced TLS in patients with multiple myeloma. This study aimed to investigate risk factors associated with TLS development in multiple myeloma patients.Methods: We retrospectively investigated incidences of laboratory and clinical TLS (LTLS and CTLS, respectively) in patients who received primary therapy for treatment-naive, symptomatic multiple myeloma between May 2007 and January 2018. We used multivariate logistic regression analyses to evaluate the associations between TLS and several parameters previously reported to be associated with increased risk.Results: This study included 210 patients with multiple myeloma, of which ten (4.8%) had LTLS and seven (3.3%) had CTLS. The characteristics of the administered anticancer or prophylactic antihyperuricemic agents were similar between patients with and without TLS. Multivariate analyses revealed that TLS was most strongly associated with bortezomib-containing therapy (odds ratio = 3.40, P = 0.069), followed by male sex (odds ratio = 2.29, P = 0.153). In a subgroup analysis focused on men, treatment with bortezomib-containing therapy was significantly associated with increased risk of TLS (odds ratio = 8.51, P = 0.046).Conclusion: In the present study, we investigated the risk factors associated with TLS development in 210 multiple myeloma patients, which, to the best of our knowledge, is the largest number of patients reported to date. Furthermore, this study is the first to evaluate TLS risk factors in MM by adjusting for the effects of potential confounding factors in patients’ backgrounds. Consequently, we found that bortezomib-containing therapy increases the risk of TLS in male patients with multiple myeloma. TLS risk should be evaluated further in low-risk diseases such as multiple myeloma, since a significant number of novel therapies can achieve high antitumor responses.

scholarly journals Development and Analysis of a Weighed Prognostic Model in Newly Diagnosed Multiple Myeloma Patients

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 47-48
Author(s):  
Xue-Han Mao ◽  
Yan Xu ◽  
Yuting Yan ◽  
Jiahui Liu ◽  
Huishou Fan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Factor ◽  
Prognostic Model ◽  
Cytogenetic Abnormalities ◽  
Total Score Range ◽  
Prognosis Model

Background and Objective: Multiple myeloma (MM) is characterized with significant cytogenetic changes and complex tumor microenvironment, thus patient survival is extremely heterogeneous. Various disease-related or patient-related factors affect the prognosis of patients. This study tried to analyze the prognostic indicators of patients with newly-treated MM, especially explored the prognosis of multiple cytogenetic abnormalities and the ratio of lymphocytes to monocytes (LMR). Additionally, we established a comprehensive prognostic model to help determine the patient prognosis. Methods: After screening, 603 patients of untreated MM from January 2008 to June 2017, with complete baseline indicators were enrolled into the study. By univariate and multivariate Cox analysis, risk factors related to the prognosis of patients were evaluated, and a weighted prognosis model was established to compare the survival differences of patients in each risk stratification. Result: Optimal thresholds of ALC, LWR, NLR and LMR were determined by ROC curve and Youdex index: ALC = 1.415, LWR = 0.325, NLR = 1.935, LMR = 2.95. Survival analysis showed that patients with LMR ≤ 2.95, ALC ≥ 1.415 and LWR ≥ 0.325 had significantly better survival compared with their respective control groups. Cox multivariate analysis showed that among the four indicators, only LMR≤2.95 was an independent adverse prognostic factor for overall survival (OS)(Figure 1A). 17p deletion, 1q21 amplification, t (4; 14) / t (14; 16) were define as high-risk cytogenetic abnormalities (HRA). Of the 603 patients, about 60% were associated with at least one high-risk cytogenetic event. Among them, the occurrence of cumulative 0, 1, 2, and 3 HRA were 39.6% (239/603), 42.5% (256/603), 16.6% (100/603), and 1.3% (8/603), respectively. There was no significant difference in survival among patients with same number of HRAs. The median OS of patients with 0, 1 and ≥ 2 HRA were not reached, 62.1 months (95% CI, 49.3-74.9) and 30.4 months (95% CI, 24.5-36.3), respectively (p &lt;0.001)(Figure 1B).Final Cox regression model showed that age 65 ~ 74 (HR=1.77, 95%CI, 1.24-2.51, p=0.001), age ≥75 (HR=2.46, 95%CI, 1.69-3.58, p &lt; 0.001), LDH≥247 U/L (HR =1.65, 95%CI, 1.07-2.51, p=0.023), ISS stage III (HR=1.76, 95%CI, 1.24-2.50, p=0.002), LMR≤2.95 (HR=1.53, 95%CI, 1.08-2.18, p=0.017), 1 HRA (HR=1.87, 95%CI, 1.27-2.75, p=0.002) and ≥2 HRA (HR=3.48, 95%CI, 2.22-5.45, p&lt;0.001) are independent adverse prognostic factors for OS. Then weighted risk factors were summed to establish a comprehensive prognosis model, with a total score range of 0-6 points. Accordingly, the whole cohort was divided into low risk (0-1 points, 45.4%), intermediate risk (2 points, 27.9%), high risk (3 points, 19.2%) and ultra-high risk (4-6 points, 7.5 %) groups. The median OS of the four risk groups were 85.8 months (67.1-104.5), 49.0 months (44.7-53.3), 35.4 months (31.3-39.5), and 23.2 months (18.8-27.6), respectively (p&lt;0.001). The C-statistics of this prognostic model is 0.68 (95% CI, 0.64-0.71), which is significantly better than the D-S stage (C-statistics = 0.52, 95% CI, 0.50-0.55, p &lt;0.001), ISS (C-statistics = 0.60, 95% CI, 0.57-0.64, p &lt;0.001) and R-ISS stage (C-statistics = 0.60, 95% CI, 0.57-0.63, p &lt;0.001). Bootstrap resampling and calibration curve showed that the model has an accurate predictive effect on both short-term and long-term prognosis of patients(Figure 1C). Conclusion: In our analysis, ALC, LWR, LMR were associated with poor prognosis in NDMM patients, while NLR had no significant prognostic significance. Among the four indicators, LMR≤2.95 was the only independent prognostic factor. In NDMM patients, survival of patients with the same number of high-risk cytogenetic abnormalities were comparable with each other, regardless of whichever combination of HRA. Higher number of high-risk cytogenetic abnormalities were associated with worse prognosis. Cox multivariate analysis showed that, old age (65-74 years old, ≥75 years old), increased LDH (≥247 U/L), decreased LMR (≤2.95), ISS III, 1 HRA and ≥ 2 HRA were independent adverse prognostic factors that affect the OS of MM patients. 4. A comprehensive weighted prognostic model was established with the above factors, which was proved to effectively distinguish different prognosis of patients. Figure 1 Disclosures No relevant conflicts of interest to declare.

scholarly journals Incidence, Management and Outcomes of Arterial and Venous Thromboembolism after Chimeric Antigen Receptor Modified T Cells for B-Cell Lymphoma and Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 7-7
Author(s):  
Anna L. Parks ◽  
Swetha Kambhampati ◽  
Bita Fakhri ◽  
Charalambos Andreadis ◽  
Lissa Gray ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
T Cells ◽  
Venous Thromboembolism ◽  
B Cell ◽  
Research Funding ◽  
Vte Prophylaxis ◽  
Therapeutic Anticoagulation ◽  
Car T ◽  
History Of

Introduction: Chimeric antigen receptor modified T Cell (CAR-T) therapy is a rapidly developing treatment for patients with relapsed/refractory (R/R) B-cell non-Hodgkin lymphoma (NHL) or multiple myeloma (MM). Although this population is at high risk for thrombosis, there are few data about rates of venous thromboembolism (VTE) and arterial thromboembolism (ATE) with CAR-T. Additionally, treatment with anticoagulation is complicated because of the prevalence of thrombocytopenia following CAR-T. Our goal was to determine the incidence, associated risk factors, management and outcomes of VTE and ATE in the 60 days following CAR-T therapy. Methods: We performed a single-center, retrospective cohort study of all patients who received inpatient CAR-T cells at UCSF Medical Center between January 2018 and May 2020 for R/R NHL or MM as standard-of-care or on a clinical trial. The outcomes of incident VTE and ATE were identified by ICD-10 codes and medical record review. Patient characteristics, pre-existing thrombosis risk factors, laboratory results, medications, and major or clinically relevant non-major bleeding or recurrent thrombotic complications were obtained through chart review. We used descriptive statistics to delineate risk factors, incidence, management and outcomes of thrombotic events. Results: Ninety-one patients who underwent CAR-T therapy were included in the analysis, 37 with NHL and 54 with MM. For NHL, mean age was 63 (range 38-82), and 41% were women. For MM, mean age was 62 (range 33-77), and 50% were women. Patients with NHL were treated with either investigational or Federal Drug Administration-approved CD19-directed therapies, and patients with MM were treated with a variety of investigational B-cell maturation antigen-directed (BCMA) therapies. For thrombotic risk factors, 13% of patients with NHL had a history of VTE, 3% had a history of ATE, 27% had a BMI ≥30, 59% had a recent procedure including central venous catheter (CVC) placement, 14% had an intensive care unit (ICU) stay, and 22% had an infectious complication in the 30 days pre- or post-CAR-T. Forty-one percent of patients with NHL had neurotoxicity of any grade, and 59% had CRS of any grade. At 30 days, 57% had a complete response, 41% had a partial response, 3% had stable disease. For MM, 6% of patients had a pre-existing history of VTE, 2% had a history of ATE, 19% had a BMI ≥30, 96% had a recent procedure, 11% had an ICU stay and 19% had an infection. Seventeen percent had neurotoxicity, and 85% had CRS. Thirty-two percent of patients with NHL and 48% with MM received pharmacologic VTE prophylaxis while undergoing CAR-T. For those who did not receive VTE prophylaxis, thrombocytopenia was the reason for holding prophylaxis, which occurred in 51% and 50% of NHL and MM patients, respectively. In the 60 days post-CAR-T, 4 (11%) patients with NHL were diagnosed with VTE-3 pulmonary embolism (PE) and 1 lower extremity deep vein thrombosis (DVT) associated with a previously placed inferior vena cava filter. Four (7%) patients with MM were diagnosed with VTE-1 PE and 3 upper extremity DVTs associated with CVCs. Five out of these 8 (63%) patients had symptomatic VTE, while the remainder were incidental on PETCT. Mean time from CAR-T infusion to VTE diagnosis was 20 days (range 6-39 days). There were no documented ATEs. Six out of 8 (75%) were treated with therapeutic anticoagulation. Of those who were anticoagulated, 4 patients received direct oral anticoagulants and 2 received low-molecular-weight-heparin. Duration was 3 months in 3 patients, 11 days in 1, 150 days in 1, and indefinitely in 1 with atrial fibrillation. Among all 8 patients with VTE, there were no bleeding events or recurrent thromboses regardless of whether or not they received anticoagulation. Discussion: In this cohort of patients with R/R NHL or MM who received either CD19- or BCMA-directed therapies, almost 1 in 10 developed VTE in the 60 days post-CAR-T. This occurred in the context of a high prevalence of risk factors for thrombosis and low rates of pharmacologic prophylaxis. Among those who developed VTE, the majority were treated with therapeutic anticoagulation for at least 3 months, without documented bleeding or recurrent VTE. Our findings provide crucial information on a common complication that can inform patients, clinicians and researchers and should be expanded upon in larger, prospective studies to identify optimal preventive and therapeutic strategies. Disclosures Fakhri: University of California San Francisco: Current Employment. Andreadis:Jazz Pharmaceuticals: Honoraria; Karyopharm: Honoraria; Incyte: Consultancy; Merck: Research Funding; Gilead/Kite: Consultancy; Novartis: Research Funding; BMS/Celgene/Juno: Honoraria, Research Funding; Genentech: Consultancy, Current equity holder in publicly-traded company. Wong:Janssen: Research Funding; Amgen: Consultancy; Roche: Research Funding; Fortis: Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Research Funding; GSK: Research Funding. Shah:BMS, Janssen, Bluebird Bio, Sutro Biopharma, Teneobio, Poseida, Nektar: Research Funding; GSK, Amgen, Indapta Therapeutics, Sanofi, BMS, CareDx, Kite, Karyopharm: Consultancy.

How I Treat High-risk Multiple Myeloma

Blood ◽  
2021 ◽  
Author(s):  
Elena Zamagni ◽  
Simona Barbato ◽  
Michele Cavo
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Multiple Myeloma ◽  
Clinical Trials ◽  
High Risk ◽  
Tumor Biology ◽  
Treatment Strategies ◽  
Specific Drug ◽  
Improve Quality

Survival of multiple myeloma (MM) has significantly improved over the last decade; however, a composed group of patients (15-20%), named high-risk (HR) MM, still experience reduced survival. Both tumor biology and suboptimal/absent responses to therapy may underlie HR definition and a clear uniform identification of risk factors is crucial for a proper management of these patients. In biologic-HRMM, MRD negativity attainment and sustain, inside and outside BM, should be the primary goal and therapy should be adapted in patients with frailty to reduce toxicity and improve quality of life. MM treatment has traditionally been tailored on age and more recently frailty or comorbidities, but very rarely on the biology of the disease, mainly because of the lack of a clear benefit derived from a specific drug/combination, inhomogeneity in HR definition and lack of data coming from prospective, properly designed clinical trials. Some attempts have been successfully made recently in this direction. In this review, we are discussing the current different definitions of HR and the need for a consensus, the results of available trials in HR patients and the way through risk-adapted treatment strategies. For this purpose, we are proposing several clinical cases of difficult-to-treat patients throughout different treatment phases.

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