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Moreover, in the multivariate analysis, together with type of surgery, BRCA1 and MMSET levels emerged as significant markers of survival.
Variables found to be significantly prognostic in univariate analyses (P < 0.05) were included in multivariate analysis together with treatment group.
The Cox proportional hazard model was used to calculate the impact of PROX1 expression in the multivariate analysis together with established prognostic factors.
PROX1 emerged as an independent marker for survival in the multivariate analysis, together with established molecular prognostic factors such as LOH 1p/19q and mutated IDH1 R132H protein.
Multivariate analysis together with conventional clinicopathological variables that had been found to be significant by univariate analysis revealed that these two variables were independently prognostic for OS and DFS with higher hazard ratio values (Table 2 and Supplementary Table 4).
In a separate multivariate analysis (together with the same variables as before) (Table 5) the p21 + p53- status versus other combinations of p21p53 status in one group was an independent predictive factor (OR 5.36, 95% C.I. 1.65-17.48, p = 0.005).
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The use of multivariate analysis methods, together with electronic senses, has shown to be very powerful; however, due to the high complexity of food, the employment of just single sensor data is often insufficient.
Bayesian multivariate analysis revealed together six variables to predict clinical outcome (2 months to 16 years) in relation to the national background population, i.e. age, diabetes, left ventricular ejection fraction, BMI, perfusion time during the CABG and peripheral arterial disease.
The amino acid relative percentage contents of the painting samples (reported in Table 6) was subjected to a multivariate statistical analysis together with a data set of 121 reference samples of animal glue, egg and casein, using the principal components analysis (PCA) method [32].
They were then entered in a third multivariate regression analysis together with all (borderline) significant predictors from the univariate analyses and possible confounders.
> Even though, diagnostic biopsy type did not have a significant relation with either DFS or OS in univariate Cox regression analysis it was also tested in multivariate Cox regression analysis together with all significant variables from univariate analysis, to investigate its influence on DFS and OS after correction for the confounding factors.
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