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*Estimated with linear-mixed models under treatment.
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The higher treatment thresholds currently used for risk score models, under-treat individuals in higher risk groups.
Unfortunately, no motor impairment was measured in untreated Surf1 −/− mice, which prevented us from further investigating the clinical features of this model under AICAR treatment.
The number of CD34+ cells in the two models under FGF-Trap treatment was significantly lower than that of vehicle-treated group.
Although both found that patient's preferences were associated with treatment, increasing age remained strongly predictive of under-treatment in models accounting for patient choice (Silliman et al, 1997; Mandelblatt et al, 2000).
Mathematical modeling of viral kinetics under treatment has provided insight into the viral life cycle, treatment effectiveness, and drugs' mechanisms of action.
In a subsequent study, another VE model was also found to perform better than the CE model to fit the viral kinetics under treatment with GS-0938 and sofosbuvir, two nucleotide analogs.
Furthermore "Contact to GP" was included in the model with the independent variable "currently under treatment".
"The real risk is under-treatment".
Another major advantage of our model is its stochastic nature describing the lifetime of cells under treatment.
We also ranked treatments and estimated the cumulative probabilities of being the best treatment using random-effect models under the Bayesian framework (Supplementary Table 6).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com