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In addition, our previous work utilizing this in vitro model, with serum collected from CR rats, was done on a similar rat hepatoma cell line (Fao) and we were interested in mimicking those results using human serum on a human hepatoma cell line.
The propensity score was obtained by performing a logistic regression model with serum potassium ≥5.0 mmol/l as an outcome.
A multivariable logistic regression model with serum 25(OH D concentration as an outcome variable was constructed to control for potential confounding variables.
In a multivariate model with serum vitamin D and parathyroid hormone, increasing parathyroid hormone was associated with decreased risk (OR 0.99, 95% CI 0.98-0.9996) (Table 3).
Other approaches reported in the literature include the use of a log-linear model with serum lipids included as a separate term in the regression equation (Moysich et al. 1998).
The independence of hCGβ as a predictor of survival was analyzed by multivariate analysis using the Cox proportional hazard model with serum hCGβ, nuclear grade and stage as input variables.
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We ran linear regression models with serum perfluoroalkyl chemical quartiles as the independent variable to examine the mean change in serum uric acid with increasing categories of perfluoroalkyl chemical, taking the lowest perfluoroalkyl chemical quartile as the referent.
Therefore, we constructed the models combined with serum ferritin.
A generalized linear model was constructed with serum CRP as outcome variable and variables having significant univariate relationship with CRP as independent variables.
In multivariate analysis using the Cox regression model with age, gender, serum hCGβ, nuclear grade and stage as input variables, stage, grade and serum hCGβ concentration were independently associated with the disease specific survival (Table 3-wrap>).
The NRI compared classifications from the model with and without serum adiponectin for changes by incident metabolic syndrome for a net calculation of changes in the right direction.
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