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Patient-reported Outcomes and Quality of Life in Anemic and Symptomatic Patients With Myelofibrosis: Results From the MOMENTUM Study.
Myelofibrosis (MF) is a chronic myeloproliferative neoplasm that typically manifests with debilitating symptoms that progressively worsen, negatively impacting patients' quality of life. Fatigue is a multifactorial and burdensome MF-related symptom due to its severity, persistence, and prevalence, with anemia a contributing factor and major unmet need. Clinical trials of the Janus kinase (JAK)1/JAK2/activin A receptor type 1 inhibitor momelotinib have shown consistent anemia benefits, in addition to improvements in MF-related symptoms. The phase 3 MOMENTUM trial in symptomatic and anemic patients met its primary end point, with a greater proportion having a Myelofibrosis Symptom Assessment Form (MFSAF) Total Symptom Score (TSS) reduction ≥50% at week 24 with momelotinib versus danazol. To support the positive primary end point result, we conducted longitudinal, responder, and time-to-event analyses of patient-reported outcomes from MOMENTUM, as measured by the MFSAF, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), and Patient-Reported Outcomes Measurement Information System (PROMIS) assessments. These analyses demonstrated rapid and durable response benefits with momelotinib, with achievement of first TSS response by day 29 and continued improvement over time. Improvements favored momelotinib versus danazol for each MFSAF individual item, and greater improvements were observed for disease- and cancer-related fatigue and physical functioning at week 24, with significant results for multiple items/domains across the 3 assessments. These findings are consistent in demonstrating that momelotinib provides substantial symptom benefit.
Symptomatic benefit of momelotinib in patients with myelofibrosis: Results from the SIMPLIFY phase III studies.
BACKGROUND: Myelofibrosis (MF)-associated constitutional symptoms can severely impact health-related quality of life. Clinical trials in MF traditionally measure symptom response to treatment as a landmark endpoint of total symptom score (TSS) reduction ≥50% from baseline. However, this dichotomous assessment provides a limited view of clinically relevant symptomatic changes. Herein we evaluated longitudinal change from baseline in TSS over the continuous 24-week period and individual symptom scores to obtain a more comprehensive understanding of symptom benefits experienced by patients with MF receiving therapy. METHODS: Longitudinal symptom change was evaluated using mixed-effect model repeated measure (MMRM) methodology with individual item-level analyses to complement the interpretation of the landmark symptom results in the completed phase III SIMPLIFY studies of momelotinib in MF. MMRM compared mean change in TSS from baseline with Week 24 using data from all patient visits. Generalized estimating equations were used to estimate item-level odds ratios using multiple predictive imputations for missing data. RESULTS: Momelotinib and ruxolitinib groups reported similar overall symptom improvements, with a TSS difference of <1.5 points between groups for each post-baseline visit in SIMPLIFY-1. In SIMPLIFY-2, the improvement in TSS observed in momelotinib-treated patients was consistent with that observed in SIMPLIFY-1, whereas progressive TSS deterioration was observed with control. Item-level scores were heterogeneous in both studies. A similar and greater proportion of momelotinib-treated patients were categorized as "improved" or "stable" compared with control in SIMPLIFY-1 and SIMPLIFY-2, respectively. Odds ratios for between-group comparison ranged from 0.75 to 1.21 in SIMPLIFY-1, demonstrating similarity in likelihood of symptom improvement. In SIMPLIFY-2, the likelihood of symptom improvement in each item was higher in the momelotinib arm. CONCLUSIONS: These findings suggest that momelotinib provides clinically relevant symptom benefits in the JAK inhibitor-naïve and JAK inhibitor-exposed settings.
Quantifying inherent predictability and spatial synchrony in the aphid vector Myzus persicae: field-scale patterns of abundance and regional forecasting error in the UK.
BACKGROUND: Sugar beet is threatened by virus yellows, a disease complex vectored by aphids that reduces sugar content. We present an analysis of Myzus persicae population dynamics with and without neonicotinoid seed treatment. We use 6 years' yellow water trap and field-collected aphid data and two decades of 12.2 m suction-trap aphid migration data. We investigate both spatial synchrony and forecasting error to understand the structure and spatial scale of field counts and why forecasting aphid migrants lacks accuracy. Our aim is to derive statistical parameters to inform regionwide pest management strategies. RESULTS: Spatial synchrony, indicating the coincident change in counts across the region over time, is rarely present and is best described as stochastic. Uniquely, early season field populations in 2019 did show spatial synchrony to 90 km compared to the overall average weekly correlation length of 23 km. However, 70% of the time series were spatially heterogenous, indicating patchy between-field dynamics. Field counts lacked the same seasonal trend and did not peak in the same week. Forecasts tended to under-predict mid-season log10 counts. A strongly negative correlation between forecasting error and the proportion of zeros was shown. CONCLUSION: Field populations are unpredictable and stochastic, regardless of neonicotinoid seed treatment. This outcome presents a problem for decision-support that cannot usefully provide a single regionwide solution. Weighted permutation entropy inferred that M. persicae 12.2 m suction-trap time series had moderate to low intrinsic predictability. Early warning using a migration model tended to predict counts at lower levels than observed. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
MARVEL: an integrated alternative splicing analysis platform for single-cell RNA sequencing data.
Alternative splicing is an important source of heterogeneity underlying gene expression between individual cells but remains an understudied area due to the paucity of computational tools to analyze splicing dynamics at single-cell resolution. Here, we present MARVEL, a comprehensive R package for single-cell splicing analysis applicable to RNA sequencing generated from the plate- and droplet-based methods. We performed extensive benchmarking of MARVEL against available tools and demonstrated its utility by analyzing multiple publicly available datasets in diverse cell types, including in disease. MARVEL enables systematic and integrated splicing and gene expression analysis of single cells to characterize the splicing landscape and reveal biological insights.