Investigation of mixed model repeated measures analyses and non‐linear random coefficient models in the context of long‐term efficacy data

Delafont, Bruno; Carroll, Kevin; Vilain, Claire; Pham, Emmanuel

doi:10.1002/pst.1868

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…We analyzed repeated measures data 13 and tested the association between creatinine level or protein level with each endothelial/angiogenic markers (sE-Selectin, sEndoglin, sEPCR, angiopoietin-1, angiopoietin-2, VEGF-A, VEGFR2, SDF1-α, basic fibroblast growth factor, c-Kit, and soluble thrombomodulin). For each endothelial/angiogenic, we set up a separated linear mixed model taking into account the mode of C-TAH (manual or autoregulated) and repeated measures over time.…”

Section: Multivariate Analysismentioning

confidence: 99%

Autoregulation of Pulsatile Bioprosthetic Total Artificial Heart is Involved in Endothelial Homeostasis Preservation

et al. 2020

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Pulsatile Carmat bioprosthetic total artificial heart (C-TAH) is designed to be implanted in patients with biventricular end-stage heart failure. Since flow variation might contribute to endothelial dysfunction, we explored circulating endothelial biomarkers after C-TAH implantation in seven patients and compared the manual and autoregulated mode. Markers of endothelial dysfunction and regeneration were compared before and during a 6- to 9-month follow-up after implantation. The follow-up was divided into three periods (< 3, 3–6, and > 6 months) and used to estimate the temporal trends during the study period. A linear mixed model was used to analyze repeated measures and association between tested parameters according to the mode of C-TAH and the time. Relevance of soluble endoglin (sEndoglin) level increase has been tested on differentiation and migration potential of human vasculogenic progenitor cells (endothelial colony forming cells [ECFCs]). Normal sEndoglin and soluble endothelial protein C receptor (sEPCR) levels were found in patients after implantation with autoregulated C-TAH, whereas they significantly increased in the manual mode, as compared with pretransplant values (p = 0.005 and 0.001, respectively). In the autoregulated mode, a significant increase in the mobilization of cytokine stromal cell-derived factor 1 was found (p = 0.03). After adjustment on the mode of C-TAH, creatinine or C-reactive protein level, sEndoglin, and sEPCR, were found significantly associated with plasma total protein levels. Moreover, a significant decrease in pseudotubes formation and migration ability was observed in vitro in ECFCs receiving sEndoglin activation. Our combined analysis of endothelial biomarkers confirms the favorable impact of blood flow variation achieved with autoregulation in patients implanted with the bioprosthetic total artificial heart.

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Section: Multivariate Analysismentioning

confidence: 99%

Autoregulation of Pulsatile Bioprosthetic Total Artificial Heart is Involved in Endothelial Homeostasis Preservation

et al. 2020

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“…7 Also, an expensive GLMM with categorical effects can induce a complicated interpretation. For example, 8 applied a nonlinear mixed-effects model to longitudinal data from two clinical trials in adult patients with upper limb spasticity. The employed model in which the treatment effect varies nonlinearly among the number of treatment cycles was preferred from viewpoint of usefulness for a clinical explanation compared to a standard linear model that includes a categorical effect for the treatment cycles.…”

Section: Introductionmentioning

confidence: 99%

Generalized quasi-linear mixed-effects model

Saigusa

Eguchi

Komori

2022

Stat Methods Med Res

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The generalized linear mixed model (GLMM) is one of the most common method in the analysis of longitudinal and clustered data in biological sciences. However, issues of model complexity and misspecification can occur when applying the GLMM. To address these issues, we extend the standard GLMM to a nonlinear mixed-effects model based on quasi-linear modeling. An estimation algorithm for the proposed model is provided by extending the penalized quasi-likelihood and the restricted maximum likelihood which are known in the GLMM inference. Also, the conditional AIC is formulated for the proposed model. The proposed model should provide a more flexible fit than the GLMM when there is a nonlinear relation between fixed and random effects. Otherwise, the proposed model is reduced to the GLMM. The performance of the proposed model under model misspecification is evaluated in several simulation studies. In the analysis of respiratory illness data from a randomized controlled trial, we observe the proposed model can capture heterogeneity; that is, it can detect a patient subgroup with specific clinical character in which the treatment is effective.

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When can maximal efficacy occur with repeat botulinum toxin injection in upper limb spastic paresis?

Jech

Valkovič

Marqué

et al. 2020

Brain Communications

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Repeated injection cycles with abobotulinumtoxinA, a botulinum toxin type A, are recommended in current clinical guidelines as a treatment option for adults with upper limb spastic paresis. However, the magnitude of the maximal therapeutic effect of repeated abobotulinumtoxinA treatment across different efficacy parameters and the number of injection cycles required to reach maximal effect remain to be elucidated. Here we present a post hoc exploratory analysis of a randomised, double-blind, placebo-controlled trial (12–24 weeks; NCT01313299) and open-label extension study (up to 12 months; NCT0131331), in patients aged 18–80 years with hemiparesis for ≥6 months following stroke/traumatic brain injury. Two inferential methods were used to assess changes in efficacy parameters after repeat abobotulinumtoxinA treatment cycles: Mixed Model Repeated Measures analysis and Non-Linear Random Coefficients analysis. Using the latter model, the expected maximal effect size (not placebo-controlled) and the number of treatment cycles to reach 90% of this maximal effect were estimated. Treatment responses in terms of passive and perceived parameters (i.e. modified Ashworth scale in primary target muscle group, disability assessment scale for principal target for treatment or limb position, and angle of catch at fast speed) were estimated to reach near-maximal effect in 2–3 cycles. Near-maximal treatment effect for active parameters (i.e. active range of motion against the resistance of extrinsic finger flexors and active function, assessed by the Modified Frenchay Scale) was estimated to be reached 1–2 cycles later. In contrast to most parameters, active function showed greater improvements at Week 12 (estimated maximal change from baseline modified Frenchay scale overall score: +0.8 (95% confidence interval [CI] 0.6; 1.0) than at Week 4 (+0.6 [95% CI 0.4; 0.8]). Overall, the analyses suggest that repeated treatment cycles with abobotulinumtoxinA in patients chronically affected with upper limb spastic paresis allow them to relearn how to use the affected arm with now looser antagonists. Future studies should assess active parameters as primary outcome measures over repeated treatment cycles, and assess efficacy at the 12-week time-point of each cycle, as the benefits of abobotulinumtoxinA may be underestimated in studies of insufficient duration.

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Investigation of mixed model repeated measures analyses and non‐linear random coefficient models in the context of long‐term efficacy data

Cited by 3 publications

References 9 publications

Autoregulation of Pulsatile Bioprosthetic Total Artificial Heart is Involved in Endothelial Homeostasis Preservation

Autoregulation of Pulsatile Bioprosthetic Total Artificial Heart is Involved in Endothelial Homeostasis Preservation

Generalized quasi-linear mixed-effects model

When can maximal efficacy occur with repeat botulinum toxin injection in upper limb spastic paresis?

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