Estimating correlation between multivariate longitudinal data in the presence of heterogeneity

Abstract Background Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Methods Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. Results There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121–0.420) and random slopes (ρ = 0.579, 95% CI: 0.349–0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conclusion Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125)

THE ROLE OF INTERFERON REGULATORY FACTORS IN REGULATING THE EXPRESSION OF NKG2D LIGANDS

Master'sMASTER OF SCIENC

Molecular Motions of the Outer Ring of Charge of the Sodium Channel: Do They Couple to Slow Inactivation?

In contrast to fast inactivation, the molecular basis of sodium (Na) channel slow inactivation is poorly understood. It has been suggested that structural rearrangements in the outer pore mediate slow inactivation of Na channels similar to C-type inactivation in potassium (K) channels. We probed the role of the outer ring of charge in inactivation gating by paired cysteine mutagenesis in the rat skeletal muscle Na channel (rNav1.4). The outer charged ring residues were substituted with cysteine, paired with cysteine mutants at other positions in the external pore, and coexpressed with rat brain β1 in Xenopus oocytes. Dithiolthreitol (DTT) markedly increased the current in E403C+E758C double mutant, indicating the spontaneous formation of a disulfide bond and proximity of the α carbons of these residues of no more than 7 Å. The redox catalyst Cu(II) (1,10-phenanthroline)3 (Cu(phe)3) reduced the peak current of double mutants (E403C+E758C, E403C+D1241C, E403C+D1532C, and D1241C+D1532C) at a rate proportional to the stimulation frequency. Voltage protocols that favored occupancy of slow inactivation states completely prevented Cu(phe)3 modification of outer charged ring paired mutants E403C+E758C, E403C+D1241C, and E403C+D1532C. In contrast, voltage protocols that favored slow inactivation did not prevent Cu(phe)3 modification of other double mutants such as E403C+W756C, E403C+W1239C, and E403C+W1531C. Our data suggest that slow inactivation of the Na channel is associated with a structural rearrangement of the outer ring of charge

The Regener-Pfotzer Maxima during a Total Solar Eclipse

The Regener-Pfotzer (RP) maximum is the altitude at which cosmic radiation intensity is the greatest. A reduction of the altitude of the interaction layer, assumed to be measured by the RP maximum, has been suggested to account for a reduction in the secondary cosmic ray flux measured at the surface of the Earth during a total solar eclipse. To investigate this suggestion, high altitude cosmic radiation was measured using Geiger Mueller (GM) counters carried beneath weather balloons both before and during the total solar eclipse on August 21st, 2017. The pre-eclipse omnidirectional RP maxima occurred at an average altitude of 20.2 km and 20.4 km during the eclipse. The vertical coincidence pre-eclipse RP maxima occurred at an average altitude of 18.3 km and 18.0 km during the eclipse. Our results do not show any reduction in the altitude of neither the omnidirectional nor the vertical coincidence RP maxima outside the range of our observations before the eclipse

Electronic transmission in bent quantum wires

Electronic transmission in bent quantum wires modeled by the tight binding Hamiltonian, and clamped between ideal, semi-infinite leads is studied. The effect of `bending' the chain is simulated by introducing a non-zero hopping between the extremities of the wire. It is seen that the proximity of the two ends gives rise to Falo line shapes in the transmission spectrum. Transmission properties for both an ordered lattice and a Fibonacci quantum wire are discussed. In the quasi-periodic Fibonacci chain, the proximity of the two ends of the chain closes all the gaps in the spectrum and the spectrum loses it's Cantor set character.Comment: 6 pages, 6 figures, Fig.2 replaced by the correct versio

Comparing statistical methods in assessing the prognostic effect of biomarker variability on time-to-event clinical outcomes

BACKGROUND: In recent years there is increasing interest in modeling the effect of early longitudinal biomarker data on future time-to-event or other outcomes. Sometimes investigators are also interested in knowing whether the variability of biomarkers is independently predictive of clinical outcomes. This question in most applications is addressed via a two-stage approach where summary statistics such as variance are calculated in the first stage and then used in models as covariates to predict clinical outcome in the second stage. The objective of this study is to compare the relative performance of various methods in estimating the effect of biomarker variability. METHODS: A joint model and 4 different two-stage approaches (naïve, landmark analysis, time-dependent Cox model, and regression calibration) were illustrated using data from a large multi-center randomized phase III trial, the Ocular Hypertension Treatment Study (OHTS), regarding the association between the variability of intraocular pressure (IOP) and the development of primary open-angle glaucoma (POAG). The model performance was also evaluated in terms of bias using simulated data from the joint model of longitudinal IOP and time to POAG. The parameters for simulation were chosen after OHTS data, and the association between longitudinal and survival data was introduced via underlying, unobserved, and error-free parameters including subject-specific variance. RESULTS: In the OHTS data, joint modeling and two-stage methods reached consistent conclusion that IOP variability showed no significant association with the risk of POAG. In the simulated data with no association between IOP variability and time-to-POAG, all the two-stage methods (except the naïve approach) provided a reliable estimation. When a moderate effect of IOP variability on POAG was imposed, all the two-stage methods underestimated the true association as compared with the joint modeling while the model-based two-stage method (regression calibration) resulted in the least bias. CONCLUSION: Regression calibration and joint modelling are the preferred methods in assessing the effect of biomarker variability. Two-stage methods with sample-based measures should be used with caution unless there exists a relatively long series of longitudinal measurements and/or strong effect size (NCT00000125)