RESUMO
BACKGROUND: Extramedullary multiple myeloma (MM) (EMM) is a rare and aggressive subentity of MM that can be present at diagnosis or develop anytime during the disease course. There is a paucity of data on the clinical characteristics and overall epidemiology of EMM. Furthermore, there is a scarcity of data on how the interaction of age and gender influences the survival of EMM. AIM: To evaluate the clinical characteristics of patients with EMM over the past 2 decades and to identify epidemiologic characteristics that may impact overall prognosis. METHODS: A total of 858 patients diagnosed with EMM, between 2000 and 2017, were ultimately enrolled in our study by retrieving the Surveillance, Epidemiology, and End Results database. We analyzed demographics, clinical characteristics, and overall mortality (OM) as well as cancer-specific mortality (CSM) of EMM. Variables with a P value < 0.1 in the univariate Cox regression were incorporated into the multivariate Cox model to determine the independent prognostic factors, with a hazard ratio (HR) of greater than 1 representing adverse prognostic factors. RESULTS: From a sample of 858 EMM, the male gender (63.25%), age range 60-79 years (51.05%), and non-Hispanic whites (66.78%) were the most represented. Central Nervous System and the vertebral column was the most affected site (33.10%). Crude analysis revealed higher OM in the age group 80+ [HR = 6.951, 95% confidence interval (95%CI): 3.299-14.647, P = 0], Non-Hispanic Black population (HR = 1.339, 95%CI: 1.02-1.759, P = 0.036), Bones not otherwise specified (NOS) (HR = 1.74, 95%CI: 1.043-2.902, P = 0.034), and widowed individuals (HR = 2.107, 95%CI: 1.511-2.938, P = 0). Skin involvement (HR = 0.241, 95%CI: 0.06-0.974, P = 0.046) and a yearly income of $75000+ (HR = 0.259, 95%CI: 0.125-0.538, P = 0) had the lowest OM in the crude analysis. Crude analysis revealed higher CSM in the age group 80+, Non-Hispanic Black, Bones NOS, and widowed. Multivariate cox proportional hazard regression analyses only revealed higher OM in the age group 80+ (HR = 9.792, 95%CI: 4.403-21.774, P = 0) and widowed individuals (HR = 1.609, 95%CI: 1.101-2.35, P = 0.014). Multivariate cox proportional hazard regression analyses of CSM also revealed higher mortality of the same groups. Eyes, mouth, and ENT involvement had the lowest CSM in the multivariate analysis. There was no interaction between age and gender in the adjusted analysis for OM and CSM. CONCLUSION: EMM is a rare entity. To our knowledge, there is a scarcity of data on the clinical characteristics and prognosis factors of patients with extramedullary multiple myeloma. In this retrospective cohort, using a United States-based population, we found that age, marital status, and tumor site were independent prognostic factors. Furthermore, we found that age and gender did not interact to influence the mortality of patients with EMM.
RESUMO
BACKGROUND: Patients with type 2 diabetes mellitus (T2DM) have a prolonged QT interval and are at high risk of sudden cardiac death. A prolonged QT interval, indicative of impaired ventricular repolarization, is a risk factor for lethal ventricular arrhythmias, such as torsades-de-pointes (TdP). AIMS: To identify key clinical and biochemical covariates associated with Fridericia's corrected QT interval (QTcF) among euthyroid patients with T2DM, and to describe the temporal relationship between these factors and QTcF. METHODS: We performed prospective, clinical, biochemical and electrocardiographic measurements among patients with T2DM enrolled in the DIACART study at Pitié-Salpêtrière Hospital, at T1 (baseline) and T2 (follow-up), with a median interval of 2.55 years. RESULTS: Mean age (63.9±8.5 years), sex (22.35% women), drugs with known risk of TdP according to the CredibleMeds website (Cred-drugsTdP) and serum thyroid-stimulating hormone (TSH) concentrations correlated with QTcF in univariate analysis at both T1 and T2. In multivariable analysis, all these covariates except age were significantly associated with QTcF at both T1 (women: standardized ß=0.24±0.07, P=0.001; Cred-drugsTdP: ß=0.19±0.07, P=0.007; TSH concentration: ß=0.18±0.07, P=0.01) and T2 (women: ß=0.25±0.08, P=0.002; Cred-drugsTdP: ß=0.25±0.08, P=0.001; TSH concentration: ß=0.19±0.08, P=0.01). Furthermore, variation in QTcF over the years was associated with variation in TSH concentration (r=0.24, P=0.007) and changes in use of Cred-drugsTdP (r=0.2, P=0.02). CONCLUSIONS: Serum TSH concentration and its variation were associated with QTcF and its variation, even after correcting for the main determinants of QTcF. Interventional optimization of TSH concentration in T2DM warrants further investigation to establish its impact on the risk of TdP and sudden cardiac death.
