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The multivariate stepwise analysis confirmed that two of these four factors (anthracycline sensitivity and the number of organs involved) were significantly correlated with the TTP (Table 3-wrap>).
Multivariate stepwise analysis including T staging, EGFR and p53 revealed that T staging and EGFR were independent predictors of survival; relative risks were 3.68 for T staging and 2.65 for EGFR.
In order to confirm an independent role of SNPs in NSCLC survival, we further performed a multivariate stepwise analysis with selected demographic characteristics and clinical features in different genetic models of TNFRSF1B +676 T>G (rs1061622) on NSCLC survival.
Finally, this latter result was confirmed in a multivariate stepwise analysis conducted in the sub-group of patients with wt KRas tumors (p values were 0.021, 0.036 and 0.058 for CCND1, FCGR3A and bevacizumab pre-treatment, respectively).
A multivariate stepwise analysis conducted on the entire population, including both gene polymorphisms considered as ternary variables along with bevacizumab pre-treatment (yes/no), revealed that CCND1 A870G (p = 0.044) and FCGR3A F158V (p = 0.006) polymorphisms were significant independent survival predictors (p = 0.014 for bevacizumab pre-treatment).
This latter statistic became significant (CCND1 p = 0.035, EGFR not retained in the analysis) in a multivariate stepwise analysis conducted on patients with KRas wt tumors (relative risk of progression in GG patients relative to AA patients was 5.59, 95% CI 1.36-22.95; risktive risk of progression in AG patients relative to AA patients was 2.32, 95% CI 0.66-8.17).
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For the definition of the regional models a multivariate stepwise regression analysis was used, while a jack-knife procedure in the validation phase was performed.
A multivariate stepwise logistic analysis showed that age, self-estimated degree of stress, reported number of additional poor health conditions, and less alcohol consumption were independently correlated with having headaches.
A multivariate stepwise regression analysis (regression, SPSS) was performed to determine the correlation between the structural and/or numerical abnormalities found for both iFISH, SNP-array techniques and their relationship with the expression of those genes analyzed by RQ-PCR.
Effects of covariates were assessed by multivariate stepwise logistic analysis.
Multivariate stepwise regression analysis was used to study predictors for change.
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