Sentence examples for prognostic exposure from inspiring English sources

This includes recent developments in ENP fate modeling that greatly expanded the potential of prognostic exposure assessments.

The aim of this study was to analyze the HP and LWA models using the two matching methods in order to propose the most efficient Method - Model combination to estimate and test the prognostic exposure effect H R t) estimated through the models by exp γ t.

With Method 1, the estimation of HR ¯ t was biased with HP and L W A u, but more with HP; the estimation of HR ¯ a t was biased with L W A a. Whatever the model applied, HR ¯ t (HP, L W A u ) and HR ¯ a t (LWA a ) were underestimated, i.e. a poor prognostic exposure effect tended to be ignored and a no exposure effect tended to become a protective one.

However, even 'perfect' balance of prognostic characteristics among exposure groups can result in confounding (as shown in our examples).

For this reason, generalized additive models (GAMs) were employed to characterize the influence of prognostic factors (including exposure parameters) on sustained virologic response and incidence of anemia in patients with chronic hepatitis C and in HIV-1 infected HIV-1 infectede etravirine patientsinclinical stheietravirine

The difference between the standard Cox model and Fine and Gray model (which accounts for competing risks and aims to estimate the prognostic impact of exposures on outcomes) was apparent only for participants with diabetic nephropathy.

Paired survival data are often used in clinical research to assess the prognostic effect of an exposure.

For this reason, the more general method of GAMs has been used for analyzing clinical endpoints in HIV patients and their relationship with maraviroc exposure and prognostic factors.

Forward-direction prognostic models developed in exposure science can be used to either generate hypotheses or test the validity or the utility of observational studies to represent exposures to larger populations or to evaluate the validity of the measurement results.

Hence, observed balance of important prognostic variables among the exposure groups in a baseline table should not result in omitting such variables from the model to adjust for confounding.

Because the subset of patients with primary breast cancer appeared to have a significantly improved survival outcome compared to patients of other primary tumour types, exploratory analyses of this subset were conducted to evaluate survival with respect to prognostic factors and efaproxiral exposure.