Table 4.
Dosing algorithm for African Americans and Caucasians in the multivariate linear regression model (outcome variable is log warfarin maintenance dose per day).*
| Variable† | N | Regression coefficient
(95% CI) |
|---|---|---|
| Intercept | 259 | 2.81 (2.45 to 3.17) |
| Race (African Americans=1) | 112 | −0.08 (−0.22 to 0.06) |
| Age | 259 | −0.01 (−0.01 to −0.01) |
| VKORC1 1173 (CT=1) | 90 | −0.39 (−0.50 to −0.27) |
| VKORC1 1173 (TT=1) | 14 | −0.82 (−1.04 to −0.59) |
| Factor 7 −401 (GT=1) | 81 | −0.11 (−0.22 to 0.00) |
| Factor 7 −401 (TT=1) | 14 | −0.19 (−0.42 to 0.03) |
| CYP2C9 (any*2=1) | 52 | −0.16 (−0.29 to −0.03) |
| CYP2C9 (any*3=1) | 18 | −0.30 (−0.50 to −0.10) |
| BMI (less than 25=1) | 82 | −0.18 (−0.30 to −0.06) |
| BMI (25 to 30=1) | 89 | −0.23 (−0.35 to −0.10) |
| Number of medications that potentiate warfarin | 259 | −0.08 (−0.12 to −0.04) |
| Most drinks on one occasion | 259 | 0.06 (0.01 to 0.11) |
| History of deep vein thrombosis (yes=1) | 38 | 0.58 (0.12 to 1.03) |
| Gender (female=1) | 89 | −0.10 (−0.20 to 0.01) |
| Race x history of deep vein thrombosis (yes and African American=1) | 237 | −0.33 (−0.61 to −0.05) |
| Race x most drinks on one occasion | 147 | −0.03 (−0.06 to 0.00) |
Dose (mg/day) = exp[2.81 −(0.08 X African American) −(0.01 X age) −(0.39 X VKORC1 1173CT) −(0.82 X VKORC1 1173TT) −(0.11X Factor 7 −401GT) −(0.19X Factor 7 −401TT) −(0.16 X CYP2C9 any*2) −(0.30 X CYP2C9 any*3) −(0.18 X BMI <25) −(0.23 X BMI 25 to 30) –(0.08 X number of medications that potentiate warfarin) −(0.10 X female) +(0.06 X most alcoholic drinks on one occasion) −(0.03 X African American x most drinks on one occasion) +(0.58 X history of deep vein thrombosis) −(0.33 X African American x history of deep vein thrombosis)]
Age, number of medications that potentiate warfarin, and most drinks on one occasion were entered as linear terms in the model and dummy variables (0=absent, 1=present) for the other variables.