Citations

AbstractBackgroundObesity (body mass index [BMI] ≥30 kg/m2) is an important epidemiological risk factor for developing acute myeloid leukemia (AML). Therefore, the authors studied the association of obesity with clinical and genetic phenotype and its impact on outcome in adults with AML.MethodsThe authors analyzed BMI in 1088 adults who were receiving intensive remission induction and consolidation therapy in two prospective, randomized therapeutic clinical trials of the Eastern Cooperative Oncology Group‐American College of Radiology Imaging Network: E1900 (ClinicalTrials.gov identifier NCT00049517; patients younger than 60 years) and E3999 (ClinicalTrials.gov identifier NCT00046930; patients aged 60 years or older).ResultsObesity was prevalent at diagnosis (33%) and, compared with nonobesity, was associated with intermediate‐risk cytogenetics group (p = .008), poorer performance status (p = .01), and a trend toward older age (p = .06). Obesity was not associated with somatic mutations among a selected 18‐gene panel that was tested in a subset of younger patients. Obesity was not associated with clinical outcome (including complete remission, early death, or overall survival), and the authors did not identify any patient subgroup that had inferior outcomes based on BMI. Obese patients were significantly more likely to receive <90% of the intended daunorubicin dose despite protocol specification, particularly in the E1900 high‐dose (90 mg/m2) daunorubicin arm (p = .002); however, this did not correlate with inferior overall survival on multivariate analysis (hazard ratio, 1.39; 95% confidence interval, 0.90–2.13; p = .14).ConclusionsObesity is associated with unique clinical and disease‐related phenotypic features in AML and may influence physician treatment decisions regarding daunorubicin dosing. However, the current study demonstrates that obesity is not a factor in survival, and strict adherence to body surface area‐based dosing is not necessary because dose adjustments do not affect outcomes.

Abstract Objectives Disease flares in the post–coronavirus disease 2019 (COVID-19) vaccination period represent a prominent concern, though risk factors are poorly understood. We studied these flares among patients with idiopathic inflammatory myopathies (IIMs) and other autoimmune rheumatic diseases (AIRDs). Methods The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with &gt;7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models. Results Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7–235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P &lt; 0.001) were associated with disparity between self-reported and IS-denoted flares. Conclusion A diagnosis of IIMs confers an equal risk of flares in the post–COVID-19 vaccination period to AIRDs, with active disease, female gender and comorbidities conferring a higher risk. Disparity between patient- and physician-reported outcomes represents a future avenue for exploration.

Abstract Objective Flares of autoimmune rheumatic diseases (AIRDs) following COVID-19 vaccination are a particular concern in vaccine-hesitant individuals. Therefore, we investigated the incidence, predictors and patterns of flares following vaccination in individuals living with AIRDs, using global COVID-19 Vaccination in Autoimmune Diseases (COVAD) surveys. Methods The COVAD surveys were used to extract data on flare demographics, comorbidities, COVID-19 history, and vaccination details for patients with AIRDs. Flares following vaccination were identified as patient-reported (a), increased immunosuppression (b), clinical exacerbations (c) and worsening of PROMIS scores (d). We studied flare characteristics and used regression models to differentiate flares among various AIRDs. Results Of 15 165 total responses, the incidence of flares in 3453 patients with AIRDs was 11.3%, 14.8%, 9.5% and 26.7% by definitions a–d, respectively. There was moderate agreement between patient-reported and immunosuppression-defined flares (K = 0.403, P = 0.022). Arthritis (61.6%) and fatigue (58.8%) were the most commonly reported symptoms. Self-reported flares were associated with higher comorbidities (P = 0.013), mental health disorders (MHDs) (P &lt; 0.001) and autoimmune disease multimorbidity (AIDm) (P &lt; 0.001). In regression analysis, the presence of AIDm [odds ratio (OR) = 1.4; 95% CI: 1.1, 1.7; P = 0.003), or a MHD (OR = 1.7; 95% CI: 1.1, 2.6; P = 0.007), or being a Moderna vaccine recipient (OR = 1.5; 95% CI: 1.09, 2.2; P = 0.014) were predictors of flares. Use of MMF (OR = 0.5; 95% CI: 0.3, 0.8; P = 0.009) and glucocorticoids (OR = 0.6; 95% CI: 0.5, 0.8; P = 0.003) were protective. A higher frequency of patients with AIRDs reported overall active disease post-vaccination compared with before vaccination (OR = 1.3; 95% CI: 1.1, 1.5; P &lt; 0.001). Conclusion Flares occur in nearly 1 in 10 individuals with AIRDs after COVID vaccination; people with comorbidities (especially AIDm), MHDs and those receiving the Moderna vaccine are particularly vulnerable. Future avenues include exploring flare profiles and optimizing vaccine strategies for this group.