Citations

Abstract Background: AHCT is a standard of care treatment for eligible patients (pts) with MM. Most consensus guidelines recommend that at the time of first AHCT, enough APBHC should be collected to perform two AHCT. However, recent studies have shown that with each decade after 1990, the use of cryopreserved APBHC for a salvage AHCT has declined and is now in the range of 4.6-15% in the decade between 2010-2018. The collection and storage of APBHC for two AHCT incurs additional costs and a prior single center cost analysis revealed that having had collected for just one AHCT in a cohort of 726 MM pts would have saved 3.8 million USD between 1993 and 2011. 1 Most centers that perform AHCT for MM pts continue to collect and store PBAHC for 2 AHCT. Herein we evaluate utilization trends and costs associated with cryopreserved APBHC in patients with MM. Methods: We retrospectively evaluated the clinicopathologic data from 440 patients with MM who underwent APBHC mobilization and collection at Mayo Clinic Florida between 2010 and 2019. The number of apheresis/collection sessions and APBHC product collection yields were determined for patients who were mobilized by any method. We estimated the costs involved in PBSC collection (apheresis) and cryopreservation storage based on our institution-specific charges as of May 2021. The cost of 1 session of APBHC collection/apheresis was $4,680 and the cost of 1 year of APBHC cryopreservation was $4,790 per patient. Statistical analysis was performed using JMP Pro 15 (SAS). Chi-square and Fischer exact tests were used to carry out univariate analysis for categorical variables and Wilcoxon rank sum/Kruskal Wallis for continuous variables. Results: Patient demographics are shown in Table 1. 440 pts underwent at least one collection session and 347 underwent at least 1 AHCT. The median number of mobilization sessions was 1 (95% CI 1.0-1.03), the median number of collection/apheresis sessions was 2.0 (95% CI 2.39-2.59), 84.3% (n=371) required ≥1 collection session. The median number of CD34 stem cells collected was 7.6 x10 6 (95% CI 7.76-8.19 x10 6), and the median number of infused CD34 cells was 4 x10 6(95% CI 4.13-4.37x10 6). The median cost of total collection sessions (defined as # of apheresis/collection sessions x $4,680) was $9,360 per pt (95% CI $11,181-$12,100). The median cost of cryopreservation (defined as # of years of storage x $4,790) was $19,160 per pt (95% CI $9,682-$22,252). The median number of years of storage was 4 (95% CI 4.11-4.65). 77(17.5%) pts have had APBHC in storage for <2 years, 218 (49.5%) have had APBHC in storage for 2-5 years, and 145 (33%) had have APBHC in storage for >5 years. The median time from MM diagnosis to AHCT was 9.0 months (range 13.8-18.5). 82% of patients collected enough APBHC (≥6x10 6, at least 3x10 6 per AHCT)for 2 AHCT. 8% of patients had all APBHC infused during their first AHCT, 83.5% had half of their APBHC infused during their first AHCT, and 8.1% had a different amount of APBHC infused during their first AHCT thus 91.6% of patients who collected APBHC had cells in storage. The median OS for the entire cohort after AHCT was 94.7 months (95% CI 88.6-100). Out of 347 patients who had stem cells in cryopreservation, 5 (1.4%) underwent a salvage AHCT and 3 (0.9%) underwent a tandem AHCT. 61% percent of patients had ≥1 excess collection sessions for APBHC that ultimately went unused. The median cost of excess collection sessions was $4,680 per pt (range, $4,680-$32,760) and the median total cost for excess collection sessions plus costs for storage was $23,840 per pt (range, $4,680-$85,450). The sum of costs of excess collection sessions was $2,077,920 and the sum of costs of cryopreservation was $5,812,665. Conclusion: The results of this single center analysis show that only 1.4% of patients underwent a salvage AHCT between 2010 and 2019 while 91.6% had APBHC left in storage which confirms the increase in storage of cryopreserved APBHC and declining trend in the use of stored APBHC for salvage AHCT in pts with MM. This is likely due to the advent of next generation novel therapies such as monoclonal antibodies, proteasome inhibitors and immunomodulatory agents. Excess collections, and cryopreservation of unused APBHC incur a cost of nearly $8 million. Institutional policies regarding universal APBHC collection and long-term storage should be reevaluated. 1Phipps C, et al. Bone Marrow Transplantation 2015:50;663-667. Figure 1 Figure 1. Disclosures Murthy: CRISPR Therapeutics: Research Funding. Ailawadhi: Sanofi: Consultancy; Medimmune: Research Funding; Genentech: Consultancy; Ascentage: Research Funding; Pharmacyclics: Consultancy, Research Funding; Xencor: Research Funding; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; AbbVie: Consultancy; Beigene: Consultancy; GSK: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Takeda: Consultancy; Cellectar: Research Funding; Karyopharm: Consultancy.

ABSTRACT Vacuoles, E1 enzyme, X linked, autoinflammatory, somatic (VEXAS) syndrome is a recently described X-linked autoinflammatory condition associated with somatic mutation of the ubiquitin-like modifier activating enzyme 1 (UBA1) gene. It often coexists with myelodysplastic syndrome, which can occur due to DNA (cytosine-5)-methyltransferase 3A (DNMT3A) mutation. These patients, predominantly males, present after the fifth decade of life with unique systemic inflammatory clinical features and have haematological abnormalities and vacuolated precursor cells on bone marrow pathology. Here we describe a unique case of VEXAS syndrome in a patient harbouring DNMT3A gene mutation with coexisting UBA1 mutation with a review of literature.

Abstract Cycle threshold (CT) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, CT values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presently, the correlation between CT values and clinical outcomes is not well understood. We conducted a systematic review and meta-analysis of published studies through April 19, 2021, that reported an association between CT values and hospitalization, disease severity, and mortality in patients ≥18 years old with SARS-CoV-2. A meta-analysis of 7 studies showed no significant difference in mean CT values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with CT values <25 had a high risk of more severe disease and mortality than patients with CT values >30 (odds ratio [OR], 2.31; 95% CI, 1.70 to 3.13; and OR, 2.95; 95% CI, 2.19 to 3.96; respectively). The odds of increased disease severity and mortality were less pronounced in patients with CT values of 25–30 compared with >30.

Objectives: Clinicians need to identify which patients presenting with S. aureus bacteremia (SAB) have underlying cardiovascular implantable electronic device (CIED) infection and therefore need device extraction. The goal of this study was to identify clinical predictors of CIED infection in patients presenting with SAB. Methods: We retrospectively reviewed all cases of SAB in CIED recipients at Mayo Clinic from Jan 2001 to Dec 2011. CIED infection was defined using clinical, microbiologic and echocardiographic criteria. Patients who presented with clinical signs of CIED pocket infection were excluded. A multivariable model was developed to identify independent predictors of CIED infection. Model discrimination was summarized using the area under a receiver operating characteristics curve (AUC). Results: Among the 131 patients with SAB and CIED, 45 (34%) had underlying CIED infection. Permanent pacemaker (PPM) devices (OR 3.90, 95% CI 1.65-9.23, p=0.002), >1 device-related procedure (OR 3.30, 95% CI 1.23-8.86, p=0.018), and duration of SAB ≥4 days (OR 5.54, 95% CI 3.32-13.23, p <0.001) were independently associated with an increased risk of CIED infection. The AUC for this multivariable model was 0.79 indicating good discriminatory capacity to separate SAB patients with and without CIED infection. Various combinations of these three features and the corresponding predicted probabilities of CIED infection are summarized in Table. Conclusions: An individual patient’s risk of underlying CIED infection can be calculated based on the type of device, number of device-related procedures, and duration of SAB. Patients without any of these high-risk features have very low risk of underlying CIED infection and may be monitored closely without immediate device extraction.

Physical activity (PA) is inversely related with body fat, insulin resistance (IR), and leptin. However, these associations are not clear in patients after gastric bypass surgery (GBS). We hypothesized an inverse relation between PA, BMI, IR, and leptin; and a positive relation between leptin, BMI, and IR in a group of 9 patients after GBS, 8 obese (Ob), and 7 non‐obese (N‐Ob) controls (age=39.0±5.7, 27.7±6.9, 28.0±10.2 yr, respectively). Subjects wore an accelerometer from 6‐7 days, and underwent measurements of height, weight, DEXA, blood glucose, insulin and leptin. IR was estimated using HOMA. Between group differences in PA, BMI, IR, and leptin were determined with ANOVA; and the relation between these variables was determined with simple linear regressions. Between group differences were observed for BMI (Ob=38.7±1.6, GBS=30.4±1.5, N‐Ob=23.8±1.7 kg/m2), IR (Ob=3.0±0.5, GBS=1.1±0.5, N‐Ob=0.7±0.5), and leptin (Ob=55.9, GBS=28.7±4.5, N‐Ob=5.1±5.6 ng/ml). PA was not different between groups. Inverse associations were observed between PA and BMI (r= ‐ 0.55), and leptin (r= ‐ 0.56); and positive associations were observed between leptin and BMI (r= 0.92), and IR (r= 0.63). PA appears to be associated with the control of obesity and IR possibly via reductions in leptin, a mechanism that requires further study. Funded by NIH CTSA UL1‐RR24150, NIH CTSA KL2‐ RR024151

Orthostatic stress such as head‐up tilt (HUT) elicits a wide range of HR and BP responses among healthy individuals. In this study, we evaluated cardiovascular dynamics of subjects with different HR responses to HUT but without autonomic dysfunction. We measured BP (brachial artery) and HR (ECG) during 5 min of 60° HUT in 76 healthy young individuals, while norepinephrine (NE) was assayed during the final 30 s. We then chose 30 individuals based on the extremes of HR responses to HUT: 15 with the highest (ΔHR≥ 20 bpm) and 15 with the lowest response (ΔHR ≤10 bpm). Age and BMI were not different between groups; however, gender distribution was different (high: 5F, 10 M; low: 10F, 5M). Peak HR during HUT was 87.2±10.4 bpm in the high and 69.1±14.1 bpm in the low group (P< 0.05). Baseline HR was not different between groups. High HR responders had lower SBP at baseline (120.9±9.4 vs. 129.4±11.0 mmHg) and during HUT (119.9±9.7 vs. 131.4±13.1 mmHg). High HR responders also had higher plasma NE response to HUT (ΔNE: 156.9±82.1 vs. 89.0±48.0 pg/ml; P< 0.05). Higher HR with lower BP during HUT is consistent with normal baroreflex mechanisms of integration. Although inter‐individual variability appears to be a fundamental part of cardiovascular regulation, the mechanisms of these differences and the gender discrepancy requires further investigation. Supported by K23 RR17520, HL46493, NS32352, KL2 RR024151 ‐01.

The forearm blood flow response to mental stress (MS) is due to circulating epinephrine (Epi), release of nitric oxide, and forearm sympathetic withdrawal. We recently demonstrated that forearm venous Epi predicts the vascular conductance (FVC) and HR response to MS. In a large, ongoing phenotyping study of sympathoexcitation and adrenergic receptor gene variation, we hypothesized that arterial Epi would predict the forearm vasodilator response to MS, while norepinephrine (NE) would predict the pressor response. In 54 healthy, normotensive young adults, FVC (plethysmography), HR (ECG), and blood pressure (brachial artery) were measured in a recumbent chair at rest and during 3 min of a computerized Stroop colored‐word test. During the final 30 sec of stress, arterial Epi and NE were assayed (HPLC). MS increased HR, BP, FVC, Epi, and NE (p < 0.05 for all). Unexpectedly, during MS the arterial Epi levels did not correlate with HR or FVC. However, a robust correlation existed for HR and FVC (r = 0.73, p < 0.001). Further, systolic pressure correlated with FVC (r = 0.36, p < 0.01) and NE (r = 0.46, p < 0.001). We conclude that the HR response to MS is a major contributor to FVC, independent of arterial Epi, suggestive of mechanical effects and potentially flow‐mediated dilation. This also confirms previous work that catecholamine spillover assays are more indicative of sympathoadrenal activation and hemodynamic responses. Support: K23 RR17520, HL 46493.

Resting energy expenditure (REE) equations multiplied by a predetermined physical activity factor (PAF) are commonly used to determine energy requirements However, estimated vs. actual REE and PAF among post‐gastric‐bypass surgery (GBS), obese (Ob) and lean (L) adults have not been compared. We hypothesized that GBS, Ob and L adults will have: 1) actual REE lower than estimated and 2) actual PAF lower than estimated. A group of 13 GB, 15 Ob and 11 L adults completed REE measurements by indirect calorimetry following standard clinical procedures. The Harris‐Benedict equation (HB) and pre‐determined PAF were used to estimate energy requirements. Physical activity energy expenditure (PAEE) was determined with accelerometry and PAF with the equation: (Actual REE + accelerometry PAEE)/Actual REE. Two‐way ANOVAs were used to detect differences by group and method, and agreement between methods using Bland & Altman plots. Group differences in actual REE (1631±174, 1830±290, 1441±151 kcal/day, respectively; P<0.01) and HB REE (1600±131, 1970±274, 1542±225 kcal/day, respectively, P<0.01) were observed, with no differences by method. Actual PAEE (269±70, 365±98, 228±112 kcal/day, respectively, P=0.002) yielded PAF ranging from 1.1 to 1.3, while HB PAF ranged from 1.2 to 1.7; causing higher predicted vs. actual energy requirement in all groups. While HB REE appeared adequate, predetermined PAF are not recommended.