Interestingly, a strong association could be observed both by analyzing the TPG (MLLT3) and the breakpoint location of MLL (mainly intron 9), and the multivariate model confirmed that these parameters were dependent on each other.
The multivariate model confirmed that only undergoing HD on MWF-pm shift was independently associated with being an incident case (p = 0.019; RR 10.00 [1.47-68.02]); in fact, 9 out of the 13 incident cases used to have HD in this shift (table 2).
Additional multivariate models confirmed the association between Waddlia IgG seropositivity and miscarriage, with ORs ranging from 4.9 to 6.2.
The multivariate models confirmed age as predictor of urinary 8-oxoGuo (see also Fig. 1) and revealed that active smokers had higher concentrations of urinary 8-oxodGuo than nonsmokers (e.g., Table 5).
Multivariate modeling confirmed the independent contributions of HDL cholesterol, triglyceride levels, and blood pressure to CVD risk, whereas the contribution from waist circumference was substantially explained by other factors.
Univariate analyses of survival showed that abnormally elevated values of both CA125 and TPA were strongly associated with the worst prognosis (P=0.001) and, finally, Cox's multivariate models confirmed their prognostic significance, demonstrating their independence from any other possible survival determinant.
Bivariate and multivariate models confirm that women with at least secondary education were 2.8 times more likely to deliver with TBA and or skilled professional (p < 0.01 in both Panels).
Again, multivariate Cox model confirmed that RAB25 mRNA level was an independent risk factor for PFS and CSS (Table 2).
Multivariate regression model confirmed that higher consumption of meat was associated with higher levels of BMI, while higher consumption of pulses, chocolate, sweets and rotisserie food was associated with lower levels of BMI (Table 4).
Likewise, the multivariate Cox model confirmed that only two factors (residual deficit after the first relapse, and early conversion into secondary progression) were predictive of the duration of Phase 2. In particular, the duration of Phase 2 was not influenced by the duration of Phase 1 (defined as a categorical variable).
Potential bias in baseline characteristics was explored via multivariate analysis, the resultant multivariate Cox model confirming the observed treatment effect with a HR of 0.27 (95% CI 0.09 0.78).
