scholarly journals Dose-Response Mixed Models for Repeated Measures – a New Method for Assessment of Dose-Response

2020 ◽  
Vol 37 (8) ◽  
Author(s):  
Gustaf J. Wellhagen ◽  
Bengt Hamrén ◽  
Maria C. Kjellsson ◽  
Magnus Åstrand
Keyword(s):  
Drug Development ◽  
Dose Response ◽  
Mixed Models ◽  
Repeated Measures ◽  
Drug Effect ◽  
Predictive Biomarkers ◽  
New Method ◽  
Measure Data ◽  
Response Analysis ◽  
Response Modeling

Abstract Purpose In this paper we investigated a new method for dose-response analysis of longitudinal data in terms of precision and accuracy using simulations. Methods The new method, called Dose-Response Mixed Models for Repeated Measures (DR-MMRM), combines conventional Mixed Models for Repeated Measures (MMRM) and dose-response modeling. Conventional MMRM can be applied for highly variable repeated measure data and is a way to estimate the drug effect at each visit and dose, however without any assumptions regarding the dose-response shape. Dose-response modeling, on the other hand, utilizes information across dose arms and describes the drug effect as a function of dose. Drug development in chronic kidney disease (CKD) is complicated by many factors, primarily by the slow progression of the disease and lack of predictive biomarkers. Recently, new approaches and biomarkers are being explored to improve efficiency in CKD drug development. Proteinuria, i.e. urinary albumin-to-creatinine ratio (UACR) is increasingly used in dose finding trials in patients with CKD. We use proteinuria to illustrate the benefits of DR-MMRM. Results The DR-MMRM had higher precision than conventional MMRM and less bias than a dose-response model on UACR change from baseline to end-of-study (DR-EOS). Conclusions DR-MMRM is a promising method for dose-response analysis.

scholarly journals Nonlinear Dose–Response Modeling of High-Throughput Screening Data Using an Evolutionary Algorithm

Dose-Response ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 155932582092673
Author(s):  
Jun Ma ◽  
Eric Bair ◽  
Alison Motsinger-Reif
Keyword(s):  
High Throughput ◽  
Dose Response ◽  
High Throughput Screening ◽  
Model Fitting ◽  
Logistic Models ◽  
Toxicity Testing ◽  
Nonlinear Least Squares ◽  
New Method ◽  
Chemical Screening ◽  
Response Modeling

Nonlinear dose–response relationships exist extensively in the cellular, biochemical, and physiologic processes that are affected by varying levels of biological, chemical, or radiation stress. Modeling such responses is a crucial component of toxicity testing and chemical screening. Traditional model fitting methods such as nonlinear least squares (NLS) are very sensitive to initial parameter values and often had convergence failure. The use of evolutionary algorithms (EAs) has been proposed to address many of the limitations of traditional approaches, but previous methods have been limited in the types of models they can fit. Therefore, we propose the use of an EA for dose–response modeling for a range of potential response model functional forms. This new method can not only fit the most commonly used nonlinear dose–response models (eg, exponential models and 3-, 4-, and 5-parameter logistic models) but also select the best model if no model assumption is made, which is especially useful in the case of high-throughput curve fitting. Compared with NLS, the new method provides stable and robust solutions without sensitivity to initial values.

A Dose-Response Analysis of Nicotine Sensitization in Adolescent Rats D2-Primed as Neonates

2010 ◽  
Author(s):  
Elizabeth A. Hanchak ◽  
Meredith L. Smith ◽  
Jessie J. Smith ◽  
Marla K. Perna ◽  
Russell W. Brown
Keyword(s):  
Dose Response ◽  
Response Analysis ◽  
Adolescent Rats

ENCORE: A weight-based exacerbation dose response analysis of mepolizumab in severe asthma with eosinophilic phenotype

Pneumologie ◽  
2017 ◽  
Vol 71 (S 01) ◽  
pp. S1-S125
Author(s):  
I Pouliquen ◽  
D Austin ◽  
N Gunsoy ◽  
SW Yancey
Keyword(s):  
Severe Asthma ◽  
Dose Response ◽  
Response Analysis

Predictive biomarkers for linking disease pathology and drug effect

2016 ◽  
Vol 22 (999) ◽  
pp. 1-1
Author(s):  
Bernd Mayer ◽  
Andreas Heinzel ◽  
Arno Lukas ◽  
Paul Perco
Keyword(s):  
Drug Effect ◽  
Predictive Biomarkers

scholarly journals Clinical characterization of dysautonomia in long COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicolas Barizien ◽  
Morgan Le Guen ◽  
Stéphanie Russel ◽  
Pauline Touche ◽  
Florent Huang ◽  
...  
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Physical Medicine ◽  
Persistent Symptoms ◽  
Index Changes ◽  
Changes Over Time ◽  
And Control ◽  
Testing Group ◽  
Over Time

AbstractIncreasing numbers of COVID-19 patients, continue to experience symptoms months after recovering from mild cases of COVID-19. Amongst these symptoms, several are related to neurological manifestations, including fatigue, anosmia, hypogeusia, headaches and hypoxia. However, the involvement of the autonomic nervous system, expressed by a dysautonomia, which can aggregate all these neurological symptoms has not been prominently reported. Here, we hypothesize that dysautonomia, could occur in secondary COVID-19 infection, also referred to as “long COVID” infection. 39 participants were included from December 2020 to January 2021 for assessment by the Department of physical medicine to enhance their physical capabilities: 12 participants with COVID-19 diagnosis and fatigue, 15 participants with COVID-19 diagnosis without fatigue and 12 control participants without COVID-19 diagnosis and without fatigue. Heart rate variability (HRV) during a change in position is commonly measured to diagnose autonomic dysregulation. In this cohort, to reflect HRV, parasympathetic/sympathetic balance was estimated using the NOL index, a multiparameter artificial intelligence-driven index calculated from extracted physiological signals by the PMD-200 pain monitoring system. Repeated-measures mixed-models testing group effect were performed to analyze NOL index changes over time between groups. A significant NOL index dissociation over time between long COVID-19 participants with fatigue and control participants was observed (p = 0.046). A trend towards significant NOL index dissociation over time was observed between long COVID-19 participants without fatigue and control participants (p = 0.109). No difference over time was observed between the two groups of long COVID-19 participants (p = 0.904). Long COVID-19 participants with fatigue may exhibit a dysautonomia characterized by dysregulation of the HRV, that is reflected by the NOL index measurements, compared to control participants. Dysautonomia may explain the persistent symptoms observed in long COVID-19 patients, such as fatigue and hypoxia. Trial registration: The study was approved by the Foch IRB: IRB00012437 (Approval Number: 20-12-02) on December 16, 2020.

Changes in multiple sclerosis symptoms are associated with changes in work productivity of people living with multiple sclerosis

2021 ◽  
pp. 135245852199455
Author(s):  
Barnabas Bessing ◽  
Mohammad A Hussain ◽  
Suzi B Claflin ◽  
Jing Chen ◽  
Leigh Blizzard ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Mixed Models ◽  
Repeated Measures ◽  
Work Productivity ◽  
Annual Change ◽  
Individual Variations ◽  
Unit Increase ◽  
The Mean ◽  
Employment Rates ◽  
Study Participants

Background: While employment rates have increased in people with multiple sclerosis (PwMS), little is known about the longitudinal trends of work productivity. Objective: To describe the longitudinal patterns of work productivity and examine the factors associated with annual change of work productivity of PwMS. Methods: Study participants were employed participants of the Australian MS Longitudinal Study (AMSLS) followed from 2015 to 2019 with at least two repeated measures ( n = 2121). We used linear mixed models to examine if the within-individual variations in MS symptoms are associated with changes in work productivity. Results: The mean annual change in work productivity between 2015 and 2019 was −0.23% ( SD = 18.68%). Not the actual severity of symptoms but rather the changes in severity of symptoms that are associated with change in work productivity in the same year. In a multivariable model, every unit increase in mean annual change in ‘pain and sensory symptoms’, ‘feelings of anxiety and depression’, and ‘fatigue and cognitive symptoms’ were independently associated with 2.43%, 1.55% and 1.01% annual reductions in work productivity, respectively. Conclusion: Individual changes in work productivity are largely driven by the changes in symptom severity rather than the absolute severity. Stabilising/improving MS symptoms might improve work productivity.

scholarly journals Sleep duration and all-cause mortality in the elderly in China: a population-based cohort study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yanfeng Ren ◽  
Maohua Miao ◽  
Wei Yuan ◽  
Jiangwei Sun
Keyword(s):  
Cohort Study ◽  
Sleep Duration ◽  
Dose Response ◽  
Cox Regression ◽  
Oldest Old ◽  
The Elderly ◽  
Response Analysis ◽  
Short Sleep Duration ◽  
All Cause Mortality

Abstract Background Although a U-shaped association between sleep duration and all-cause mortality has been found in general population, its association in the elderly adults, especially in the oldest-old, is rarely explored. Methods In present cohort study, we prospectively explore the association between sleep duration and all-cause mortality among 15,092 participants enrolled in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2005 to 2019. Sleep duration and death information was collected by using structured questionnaires. Cox regression model with sleep duration as a time-varying exposure was performed to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs). The dose-response association between them was explored via a restricted cubic spline function. Results During an average follow-up of 4.51 (standard deviation, SD: 3.62) years, 10,768 participants died during the follow-up period. The mean (SD) age of the participants was 89.26 (11.56) years old. Compared to individuals with moderate sleep duration (7–8 hours), individuals with long sleep duration (> 8 hours) had a significantly higher risk of all-cause mortality (HR: 1.13, 95%CI: 1.09–1.18), but not among individuals with short sleep duration (≤ 6 hours) (HR: 1.02, 95%CI: 0.96–1.09). Similar results were observed in subgroup analyses based on age and gender. In the dose-response analysis, a J-shaped association was observed. Conclusions Sleep duration was associated with all-cause mortality in a J-shaped pattern in the elderly population in China.

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