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. Author manuscript; available in PMC: 2013 Jun 1.
Published in final edited form as: Ann Surg Oncol. 2011 Dec 22;19(6):1944–1953. doi: 10.1245/s10434-011-2174-5

Table 2.

Multivariate logistic regression analysis to assess relations with infiltrative growth pattern in colorectal cancer

Variables in the final model
for tumor growth pattern as a binary outcome variable
(infiltrative vs. expansile-intermediate)
Multivariate OR
(95% CI)
P value
MSI-high (vs. MSI-low/MSS) 0.15 (0.07-0.34) <0.0001
Peritumoral lymphocytic reaction (present vs. absent) 0.36 (0.24-0.54) <0.0001
BRAF mutation (vs. wild-type) 2.89 (1.68-4.98) 0.0001
Poor differentiation (vs. well-moderate) 2.27 (1.31-3.92) 0.0035
LINE-1 hypomethylation (for a 30% decrease) 0.55 (0.30-1.00) 0.049
Year of diagnosis (for a 10-year increase) 0.75 (0.55-1.02) 0.065
KRAS mutation (vs. wild-type) 1.31 (0.90-1.92) 0.16

Multivariate logistic regression analysis assessing the relationship with infiltrative growth pattern (as an outcome variable) initially included age, sex, year of diagnosis, body mass index, tumor location, family history of colorectal cancer, microsatellite instability, CpG island methylator phenotype, LINE-1 methylation, KRAS, BRAF, PIK3CA, tumor differentiation, mucinous component, signet ring cell component, and peritumoral lymphocytic reaction. A backward elimination with a threshold of p=0.20 was used to select variables in the final models. Because of multiple hypothesis testing, a p value for significance was adjusted by Bonferroni correction to p=0.0029.

CI, confidence interval; MSI, microsatellite instability; MSS, microsatellite stable; OR, odds ratio.