Maxime Verhoeven

68 Chapter 4 Table 3 Logistic model building in combined datasets: U-Act-Early + tREACH. Model Predictors Log likelihood Chisquare P AUC (95%CI) 1 DAS28 + HAQ -168.68 0.67 (0.61 – 0.74) 2 DAS28 + HAQ + smoking -165.52 6.32 0.01* 0.70 (0.64 – 0.76) 3 DAS28 + HAQ + smoking + BMI -162.98 5.08 0.02* 0.72 (0.66 – 0.78) 4 DAS28 + HAQ + smoking + BMI + erythrocyte folate -160.43 5.11 0.02* 0.73 (0.67 – 0.79) 5 DAS28 + HAQ + smoking + BMI + erythrocyte folate + ABCC3 -158.57 3.71 0.05 0.74 (0.68 – 0.80) 6 DAS28 + HAQ + smoking + BMI + erythrocyte folate + ABCB1 -160.15 0.57 0.45 0.74 (0.68 – 0.80) 7 DAS28 + HAQ + smoking + BMI + erythrocyte folate + ABCC3 + ABCB1 -158.29 4.28 0.12 0.74 (0.68 – 0.80) Each model was compared to the previous model. Model 6 and 7 were compared to model 4. *P-value<0.05 was considered significant. DAS28= DAS28 >5.1; HAQ= HAQ >0.6; smoking= current smoking; BMI= BMI >25kg/m2; erythrocyte folate= erythrocyte folate <750 nmol/L; ABCC3= genotype TC or CC; ABCB1= genotype GG or GA. Table 4 Final prediction model enhanced for clinical implementation. Β OR (95%CI) p Intercept -1.67 0.19 (0.07 – 0.44) <0.001*** Baseline DAS28 > 5.1 1.34 3.81 (2.12 – 6.99) <0.001*** HAQ >0.6 0.44 1.56 (0.58 – 4.33) 0.383 BMI >25 kg/m 2 -0.34 0.71 (0.24 – 2.04) 0.528 Erythrocyte folate <750nmol/L 1.79 5.98 (2.00 – 19.09) 0.002** Smoking (current smoker) 0.81 2.26 (1.25 – 4.16) 0.008** HAQ >0.6 x BMI >25 kg/m 2 1.30 3.68 (1.07 – 13.14) 0.040* HAQ >0.6 x Erythrocyte folate <750nmol/L -1.46 0.23 (0.06 – 0.86) 0.031* AUC 0.75 (95%CI : 0.69 – 0.81) Hosmer – Lemeshow test 0.634 The model was constructed in the combined dataset (tREACH + U-Act-Early, N=264). The multiplication sign indicates that there is an interaction between two predictors. *P-values < 0.05, **P-values < 0.01 and ***P-values<0.001. AUC= area under the curve; β= beta coefficient of the final logistic regression model; OR (95%CI)= odds ratio with 95% confidence interval. Model translation to the clinic In order to apply the model in clinical practice, the prediction model was integrated into an online platform “Evidencio”. 16 Using this tool, clinicians can easily enter DAS28, HAQ, erythrocyte folate, smoking and BMI for individual patients using sliding scales and buttons. The model then automatically calculates and presents a probability of