83 research outputs found
How I Manage Transplant Ineligible Patients with Myelodysplastic Neoplasms
Myelodysplastic neoplasms, formerly known as myelodysplastic syndromes (MDS), represent a group of clonal disorders characterized by a high degree of clinical and molecular heterogeneity, and an invariable tendency to progress to acute myeloid leukemia. MDS typically present in the elderly with cytopenias of different degrees and bone marrow dysplasia, the hallmarks of the disease. Allogeneic hematopoietic stem cell transplant is the sole curative approach to date. Nonetheless, given the disease's demographics, only a minority of patients can benefit from this procedure. Currently used prognostic schemes such as the Revised International Prognostic Scoring System (R-IPSS), and most recently the molecular IPSS (IPSS-M), guide clinical management by dividing MDS into two big categories: lower- and higher-risk cases, based on a cut-off score of 3.5. The main clinical problem of the lower-risk group is represented by the management of cytopenias, whereas the prevention of secondary leukemia progression is the goal for the latter. Herein, we discuss the non-transplant treatment of MDS, focusing on current practice and available therapeutic options, while also presenting new investigational agents potentially entering the MDS therapeutic arsenal in the near future
Multiple Reaction Monitoring Profiling (MRM-Profiling) of Lipids To Distinguish Strain-Level Differences in Microbial Resistance in Escherichia coli
The worldwide increase in antimicrobial resistance is due to antibiotic overuse in agriculture and overprescription in medicine. For appropriate and timely patient support, faster diagnosis of antimicrobial resistance is required. Current methods for bacterial identification rely on genomics and proteomics and use comparisons with databases of known strains, but the diagnostic value of metabolites and lipids has not been explored significantly. Standard mass spectrometry/chromatography methods involve multiple dilutions during sample preparation and separation. To increase the amount of chemical information acquired and the speed of analysis of lipids, multiple reaction monitoring profiling (MRM-Profiling) has been applied. The MRM-Profiling workflow includes a discovery stage and a screening stage. The discovery stage employs precursor (PREC) ion and neutral loss (NL) scans to screen representative pooled samples for functional groups associated with particular lipid classes. The information from the first stage is organized in precursor/product ion pairs, or MRMs, and the screening stage rapidly interrogates individual samples for these MRMs. In this study, we performed MRM-Profiling of lipid extracts from four different strains of Escherichia coli cultured with amoxicillin or amoxicillin/clavulanate, a Ī²-lactam and Ī²-lactamase inhibitor, respectively. t tests, analysis of variance and receiver operating characteristic (ROC) curves were used to determine the significance of each MRM. Principal component analysis was applied to distinguish different strains cultured under conditions that allowed or disallowed development of bacterial resistance. The results demonstrate that MRM-Profiling distinguishes the lipid profiles of resistant and nonresistant E. coli strains
Toward a more patientācentered drug development process in clinical trials for patients with myelodysplastic syndromes/neoplasms (MDS): Practical considerations from the International Consortium for MDS (icMDS)
Notable treatment advances have been made in recent years for patients with myelodysplastic syndromes/neoplasms (MDS), and several new drugs are under development. For example, the emerging availability of oral MDS therapies holds the promise of improving patients' healthārelated quality of life (HRQoL). Within this rapidly evolving landscape, the inclusion of HRQoL and other patientāreported outcomes (PROs) is critical to inform the benefit/risk assessment of new therapies or to assess whether patients live longer and better, for what will likely remain a largely incurable disease. We provide practical considerations to support investigators in generating highāquality PRO data in future MDS trials. We first describe several challenges that are to be thoughtfully considered when designing an MDSāfocused clinical trial with a PRO endpoint. We then discuss aspects related to the design of the study, including PRO assessment strategies. We also discuss statistical approaches illustrating the potential value of timeātoāevent analyses and their implications within the estimand framework. Finally, based on a literature review of MDS randomized controlled trials with a PRO endpoint, we note the PRO items that deserve special attention when reporting future MDS trial results. We hope these practical considerations will facilitate the generation of rigorous PRO data that can robustly inform MDS patient care and support treatment decisionāmaking for this patient population
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Risk Prediction for Clonal Cytopenia: Multicenter Real-World Evidence.
Clonal cytopenia of undetermined significance (CCUS) represents a distinct disease entity characterized by myeloid-related somatic mutations with a variant allele fraction of ā„2% in individuals with unexplained cytopenia(s) but without a myeloid neoplasm (MN). Notably, CCUS carries a risk of progressing to MN, particularly in cases featuring high-risk mutations. Understanding CCUS requires dedicated studies to elucidate its risk factors and natural history. Our analysis of 357 CCUS patients investigated the interplay between clonality, cytopenia, and prognosis. Multivariate analysis identified 3 key adverse prognostic factors: the presence of splicing mutation(s) (score = 2 points), platelet count <100Ć109/L (score = 2.5), and ā„2 mutations (score = 3). Variable scores were based on the coefficients from the Cox proportional hazards model. This led to the development of the Clonal Cytopenia Risk Score (CCRS), which stratified patients into low- (score <2.5 points), intermediate- (score 2.5-<5), and high-risk (score ā„5) groups. The CCRS effectively predicted 2-year cumulative incidence of MN for low- (6.4%), intermediate- (14.1%), and high- (37.2%) risk groups, respectively, by Gray's test (P <.0001). We further validated the CCRS by applying it to an independent CCUS cohort of 104 patients, demonstrating a c-index of 0.64 (Pā=.005) in stratifying the cumulative incidence of MN. Our study underscores the importance of integrating clinical and molecular data to assess the risk of CCUS progression, making the CCRS a valuable tool that is practical and easily calculable. These findings are clinically relevant, shaping the management strategies for CCUS and informing future clinical trial designs
Assessment of Regional Variability in COVID-19 Outcomes Among Patients With Cancer in the United States.
Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography.
Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer.
Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States.
Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index.
Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time.
Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250āÆ000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58).
Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients
COVID-19 Severity and Cardiovascular Outcomes in SARS-CoV-2-Infected Patients With Cancer and Cardiovascular Disease
BACKGROUND: Data regarding outcomes among patients with cancer and co-morbid cardiovascular disease (CVD)/cardiovascular risk factors (CVRF) after SARS-CoV-2 infection are limited.
OBJECTIVES: To compare Coronavirus disease 2019 (COVID-19) related complications among cancer patients with and without co-morbid CVD/CVRF.
METHODS: Retrospective cohort study of patients with cancer and laboratory-confirmed SARS-CoV-2, reported to the COVID-19 and Cancer Consortium (CCC19) registry from 03/17/2020 to 12/31/2021. CVD/CVRF was defined as established CVD
RESULTS: Among 10,876 SARS-CoV-2 infected patients with cancer (median age 65 [IQR 54-74] years, 53% female, 52% White), 6253 patients (57%) had co-morbid CVD/CVRF. Co-morbid CVD/CVRF was associated with higher COVID-19 severity (adjusted OR: 1.25 [95% CI 1.11-1.40]). Adverse CV events were significantly higher in patients with CVD/CVRF (all
CONCLUSIONS: Co-morbid CVD/CVRF is associated with higher COVID-19 severity among patients with cancer, particularly those not receiving active cancer therapy. While infrequent, COVID-19 related CV complications were higher in patients with comorbid CVD/CVRF. (COVID-19 and Cancer Consortium Registry [CCC19]; NCT04354701)
Accelerating the Throughput of Mass Spectrometry Analysis by Advanced Workflow and Instrumentation
The exploratory profiling and quantitative bioassays of lipids, small metabolites, and peptides have always been challenging tasks. The most popular instrument platform deployed to solve these problems is chromatography coupled with mass spectrometry. However, it requires large amounts of instrument time, intensive labor, and frequent maintenance, and usually produces results with bias. Thus, the pace of exploratory research is one of poor efficacy and low throughput. The work in this dissertation provides two practical tactics to address these problems. The first solution is multiple reaction monitoring profiling (MRM-profiling), a new concept intended to shift the exploratory research from current identification-centered metabolomics and lipidomics to functional group screening by taking advantage of precursor ion scan and product ion scan. It is also demonstrated that MRM-profiling is capable of quantifying the relative amount of lipids within the same subclass. Besides, an application of the whole workflow to investigate the strain-level differences of bacteria is described. The results have zeroed in on several potential lipid biomarkers and corresponding MRM transitions. The second strategy is aimed to increase the throughput of targeted bioassays by conducting induced nanoelectrospray ionization (nESI) in batch mode. A novel prototype instrument named Dip-and-Go system is presented. Characterization of its ability to carry out reaction screening and bioassays exhibits the versatility of the system. The distinct electrophoretic cleaning mechanism contributes to the removal of salt during ionization, which assures the accuracy of measurement
Using Smartwatch and Bluetooth Beacons to Monitor Physical Activity of Older Adults
ObjectiveWe used a novel Sensing At-Risk Population (SARP) system to monitor patientsā physical activity and locations during post-acute rehabilitation; To (1) examine the correlation between SARP measurements and standard physical (PT) and occupational therapists (OT) and nurse (RN) evaluations; (2) examine the effectiveness of SARP to discriminate discharge dispositions.MethodsParticipants were instructed to wear the smartwatch and receive physical and occupational therapy. Spearman correlations were used to determine the associations between SARP measurements and in-person evaluations. Univariate logistic regression was used to identify predictors of discharge dispositions.ļæ½ResultsSARP measurements and PT/OT/RN evaluations were correlated significantly. SARP indicated that participants were active for only 5 minutes/hour during post-acute rehabilitation. SARP significantly predicted hospital readmission (AUC>70%).ConclusionsSARP provides physical activity information during post-acute rehabilitation in real-time. Not only is SARP significantly correlated with PT/OT/RN evaluations, but it also helps to discern discharge dispositions
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