Table 4.

Multiple linear regression analysis of predictor for O⁶-EtGua level^a

	Never-smokers				Ever-smokers
	Multivariate			r² variance explained^f	Multivariate
Covariates	β^c	P^d	P^e		β^c	P^d	P^e	r² variance explained^f
GSTT1 (0, wild-type; 1, null)	−2.36	0.009	0.045	8.7%	−1.26	0.20		1.8%
GSTP1 I¹⁰⁵V (0, I/I; 1, any V)	−1.77	0.02		8.9%	−0.50	0.53		2.1%
MGMT I¹⁴³V (0, I/I; 1, any V)	−0.69	0.37		1.0%	1.64	0.05		4.3%
XPD D³¹²N (0, D/D; 1, any N)	−1.46	0.05		2.9%	0.91	0.25		12.3%
XRCC3 T²⁴¹M (0, T/T; 1, any M)	−1.75	0.02		7.0%	2.22	0.007	0.035	8.5%
No. years of smoked	NA^b			NA^b	−0.08	0.005	0.025	9.4%
Age	−0.03	0.24		1.7%	−0.04	0.35		0.9%
Sex (0, women; 1, men)	0.68	0.34		1.1%	0.09	0.91		0.0%
Alcohol (0, never, 1, quit, 2 current)	0.22	0.57		0.4%	−0.32	0.47		0.6%
r²	27.3% ^g				25.3%^g

The square-root transformed value is the dependent variable. Age, sex, alcohol consumption are covariates.

For never-smoker stratum, the regression model did not include covariate ‘No. years of smoked’.

β coefficient: the unit change of dependent variable caused by 1 unit change of variable. For genotype covariates, β is the difference of the mean of each genotype coded as 0 or 1.

P value for the term in the multiple linear regression.

Bonferroni multiplicity adjusted P value = (listed P value x 5), assuming 5 independent hypothesis testing in each stratum.

Bolded indicates multiplicity adjust P value ≤ 0.05.

The difference of the r² of the full model and the r² of the reduced model without that variable.

r², percentage of variation of the dependent variable that the model can explain.