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On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials*
Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement
Factor Xa Generation by Computational Modeling: An Additional Discriminator to Thrombin Generation Evaluation
Factor (f)Xa is a critical enzyme in blood coagulation that is responsible for the initiation and propagation of thrombin generation. Previously we have shown that analysis of computationally generated thrombin profiles is a tool to investigate hemostasis in various populations. In this study, we evaluate the potential of computationally derived time courses of fXa generation as another approach for investigating thrombotic risk. Utilizing the case (n = 473) and control (n = 426) population from the Leiden Thrombophilia Study and each individual's plasma protein factor composition for fII, fV, fVII, fVIII, fIX, fX, antithrombin and tissue factor pathway inhibitor, tissue factor-initiated total active fXa generation was assessed using a mathematical model. FXa generation was evaluated by the area under the curve (AUC), the maximum rate (MaxR) and level (MaxL) and the time to reach these, TMaxR and TMaxL, respectively. FXa generation was analyzed in the entire populations and in defined subgroups (by sex, age, body mass index, oral contraceptive use). The maximum rates and levels of fXa generation occur over a 10- to 12- fold range in both cases and controls. This variation is larger than that observed with thrombin (3–6 fold) in the same population. The greatest risk association was obtained using either MaxR or MaxL of fXa generation; with an ∼2.2 fold increased risk for individuals exceeding the 90th percentile. This risk was similar to that of thrombin generation(MaxR OR 2.6). Grouping defined by oral contraceptive (OC) use in the control population showed the biggest differences in fXa generation; a >60% increase in the MaxR upon OC use. FXa generation can distinguish between a subset of individuals characterized by overlapping thrombin generation profiles. Analysis of fXa generation is a phenotypic characteristic which may prove to be a more sensitive discriminator than thrombin generation among all individuals
Inferred galaxy properties during Cosmic Dawn from early JWST photometry results
Early photometric results from JWST have revealed a number of galaxy
candidates above redshift 10. The initial estimates of inferred stellar masses
and the associated cosmic star formation rates are above most theoretical model
predictions up to a factor of 20 in the most extreme cases, while this has been
moderated after the recalibration of NIRCam and subsequent spectroscopic
detections. Using these recent JWST observations, we use galaxy scaling
relations from cosmological simulations to model the star formation history to
very high redshifts, back to a starting halo mass of 10^7 solar masses, to
infer the intrinsic properties of the JWST galaxies. Here we explore the
contribution of supermassive black holes, stellar binaries, and an excess of
massive stars to the overall luminosity of high-redshift galaxies. Despite the
addition of alternative components to the spectral energy distribution, we find
stellar masses equal to or slightly higher than previous stellar mass
estimates. Most galaxy spectra are dominated by the stellar component, and the
exact choice for the stellar population model does not appear to make a major
difference. We find that four of the 12 high-redshift galaxy candidates are
best fit with a non-negligible active galactic nuclei component, but the
evidence from the continuum alone is insufficient to confirm their existence.
Upcoming spectroscopic observations of z > 10 galaxies will confirm the
presence and nature of high-energy sources in the early universe and will
constrain their exact redshifts.Comment: 20 pages, 13 figures, 5 tables. Accepted by MNRAS. 12 figures, 13
tables in appendice
Anticoagulants and the Propagation Phase of Thrombin Generation
The view that clot time-based assays do not provide a sufficient assessment of an individual's hemostatic competence, especially in the context of anticoagulant therapy, has provoked a search for new metrics, with significant focus directed at techniques that define the propagation phase of thrombin generation. Here we use our deterministic mathematical model of tissue-factor initiated thrombin generation in combination with reconstructions using purified protein components to characterize how the interplay between anticoagulant mechanisms and variable composition of the coagulation proteome result in differential regulation of the propagation phase of thrombin generation. Thrombin parameters were extracted from computationally derived thrombin generation profiles generated using coagulation proteome factor data from warfarin-treated individuals (N = 54) and matching groups of control individuals (N = 37). A computational clot time prolongation value (cINR) was devised that correlated with their actual International Normalized Ratio (INR) values, with differences between individual INR and cINR values shown to derive from the insensitivity of the INR to tissue factor pathway inhibitor (TFPI). The analysis suggests that normal range variation in TFPI levels could be an important contributor to the failure of the INR to adequately reflect the anticoagulated state in some individuals. Warfarin-induced changes in thrombin propagation phase parameters were then compared to those induced by unfractionated heparin, fondaparinux, rivaroxaban, and a reversible thrombin inhibitor. Anticoagulants were assessed at concentrations yielding equivalent cINR values, with each anticoagulant evaluated using 32 unique coagulation proteome compositions. The analyses showed that no anticoagulant recapitulated all features of warfarin propagation phase dynamics; differences in propagation phase effects suggest that anticoagulants that selectively target fXa or thrombin may provoke fewer bleeding episodes. More generally, the study shows that computational modeling of the response of core elements of the coagulation proteome to a physiologically relevant tissue factor stimulus may improve the monitoring of a broad range of anticoagulants
Thrombin generation profiles in deep venous thrombosis
BACKGROUND: Reliable markers and methods to predict risk for thrombosis are essential to clinical management. OBJECTIVE: Using an integrated approach that defines an individual’s comprehensive coagulation phenotype might prove valuable in identifying individuals at risk for experiencing a thrombotic event. METHODS: Using a numerical simulation model, we generated tissue factor (TF) initiated thrombin curves using coagulation factor levels from the Leiden Thrombophilia Study population and evaluated thrombotic risk, by sex, age, smoking, alcohol consumption, body mass index (BMI) and oral contraceptive (OC) use. We quantitated the initiation, propagation and termination phases of each individuals’ comprehensive TF-initiated thrombin generation curve by the parameters: time to 10nM thrombin, maximum time, level and rate (MaxR) of thrombin generated and total thrombin. RESULTS: The greatest risk association was obtained using MaxR; with a 2.6 fold increased risk at MaxR exceeding the 90(th) percentile. The odds ratio (OR) for MaxR was 3.9 in men, 2.1 in women, and 2.9 in women on OCs. The association of risk with thrombin generation did not differ by age (OR:2.8≤45 years>OR:2.5), BMI (OR:2.9≤26 kg/m(2)>OR:2.3) or alcohol use. In both numerical simulations and empirical synthetic plasma, OC use created extreme shifts in thrombin generation in both control women and women with a prior thrombosis, with a larger shift in thrombin generation in control women. This suggests an interaction of OC use with underlying prothrombotic abnormalities. CONCLUSIONS: Thrombin generation based upon the individual’s blood composition is associated with the risk for thrombosis and may be useful as a predictive marker for evaluating thrombosis on an individual basis
Defining the Boundaries of Normal Thrombin Generation: Investigations into Hemostasis
In terms of its soluble precursors, the coagulation proteome varies quantitatively among apparently healthy individuals. The significance of this variability remains obscure, in part because it is the backdrop against which the hemostatic consequences of more dramatic composition differences are studied. In this study we have defined the consequences of normal range variation of components of the coagulation proteome by using a mechanism-based computational approach that translates coagulation factor concentration data into a representation of an individual's thrombin generation potential. A novel graphical method is used to integrate standard measures that characterize thrombin generation in both empirical and computational models (e.g max rate, max level, total thrombin, time to 2 nM thrombin (“clot time”)) to visualize how normal range variation in coagulation factors results in unique thrombin generation phenotypes. Unique ensembles of the 8 coagulation factors encompassing the limits of normal range variation were used as initial conditions for the computational modeling, each ensemble representing “an individual” in a theoretical healthy population. These “individuals” with unremarkable proteome composition was then compared to actual normal and “abnormal” individuals, i.e. factor ensembles measured in apparently healthy individuals, actual coagulopathic individuals or artificially constructed factor ensembles representing individuals with specific factor deficiencies. A sensitivity analysis was performed to rank either individual factors or all possible pairs of factors in terms of their contribution to the overall distribution of thrombin generation phenotypes. Key findings of these analyses include: normal range variation of coagulation factors yields thrombin generation phenotypes indistinguishable from individuals with some, but not all, coagulopathies examined; coordinate variation of certain pairs of factors within their normal ranges disproportionately results in extreme thrombin generation phenotypes, implying that measurement of a smaller set of factors may be sufficient to identify individuals with aberrant thrombin generation potential despite normal coagulation proteome composition
Measuring creativity in software development
Abstract. Creativity involves choosing to direct resources toward developing novel ideas. Information technology development, including software engineering, requires creative discourse among team members to design and implement a novel, competitive product that meets usability, performance, and functional requirements set by the customer. In this paper, we present results that correlate metrics of creative collaboration with successful software product development in a Senior Software Projects class that is a capstone course in accredited Computer Science programs. An idea management and reward system, called SEREBRO, provides measurement opportunities to develop metrics of fluency, flexibility, originality, elaboration, and overall creativity. These metrics incorporate multiple perspectives and sources of information into the measurement of creativity software design. The idea management portion of SEREBRO is a Web application that allows team members to initiate asynchronous, creative discourse through the use of threads. Participants are rewarded for brainstorming activities that start new threads for creative discourse and spinning new ideas from existing ones
Associations of Low Vitamin D and Elevated Parathyroid Hormone Concentrations With Bone Mineral Density in Perinatally HIV-Infected Children
BACKGROUND:
Perinatally HIV-infected (PHIV) children have, on average, lower bone mineral density (BMD) than perinatally HIV-exposed uninfected (PHEU) and healthy children. Low 25-hydroxy vitamin D [25(OH)D] and elevated parathyroid hormone (PTH) concentrations may lead to suboptimal bone accrual.
METHODS:
PHIV and PHEU children in the Pediatric HIV/AIDS Cohort Study had total body (TB) and lumbar spine (LS) BMD and bone mineral content (BMC) measured by dual-energy x-ray absorptiometry; BMD z-scores (BMDz) were calculated for age and sex. Low 25(OH)D was defined as ≤20 ng/mL and high PTH as >65 pg/mL. We fit linear regression models to estimate the average adjusted differences in BMD/BMC by 25(OH)D and PTH status and log binomial models to determine adjusted prevalence ratios of low 25(OH)D and high PTH in PHIV relative to PHEU children.
RESULTS:
PHIV children (n = 412) were older (13.0 vs. 10.8 years) and more often black (76% vs. 64%) than PHEU (n = 207). Among PHIV, children with low 25(OH)D had lower TB-BMDz [SD, -0.38; 95% confidence interval (CI), -0.60 to -0.16] and TB-BMC (SD, -59.1 g; 95% CI, -108.3 to -9.8); high PTH accompanied by low 25(OH)D was associated with lower TB-BMDz. Among PHEU, children with low 25(OH)D had lower TB-BMDz (SD, -0.34; 95% CI, -0.64 to -0.03). Prevalence of low 25(OH)D was similar by HIV status (adjusted prevalence ratio, 1.00; 95% CI, 0.81 to 1.24). High PTH was 3.17 (95% CI, 1.25 to 8.06) times more likely in PHIV children.
CONCLUSIONS:
PHIV and PHEU children with low 25(OH)D may have lower BMD. Vitamin D supplementation trials during critical periods of bone accrual are needed
Distinct Molecular Evolutionary Mechanisms Underlie the Functional Diversification of the Wnt and TGFβ Signaling Pathways
The canonical Wnt pathway is one of the oldest and most functionally diverse of animal intercellular signaling pathways. Though much is known about loss-of-function phenotypes for Wnt pathway components in several model organisms, the question of how this pathway achieved its current repertoire of functions has not been addressed. Our phylogenetic analyses of 11 multigene families from five species belonging to distinct phyla, as well as additional analyses employing the 12 Drosophila genomes, suggest frequent gene duplications affecting ligands and receptors as well as co-evolution of new ligand–receptor pairs likely facilitated the expansion of this pathway’s capabilities. Further, several examples of recent gene loss are visible in Drosophila when compared to family members in other phyla. By comparison the TGFβ signaling pathway is characterized by ancient gene duplications of ligands, receptors, and signal transducers with recent duplication events restricted to the vertebrate lineage. Overall, the data suggest that two distinct molecular evolutionary mechanisms can create a functionally diverse developmental signaling pathway. These are the recent dynamic generation of new genes and ligand–receptor interactions as seen in the Wnt pathway and the conservative adaptation of ancient pre-existing genes to new roles as seen in the TGFβ pathway. From a practical perspective, the former mechanism limits the investigator’s ability to transfer knowledge of specific pathway functions across species while the latter facilitates knowledge transfer
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