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Chapter 2.3
68
Table 2. Logistic regression analysis of sustained response. Extension of the baseline model with ontreatment
factors.
cross validated
Week OR 95%CI p-value c-statistics c-statistics
Baseline 0 0.846
HBV DNA log10 4 1.04 (0.61 ; 1.78) 0.881 0.854 0.827
8 1.02 (0.65 ; 1.61) 0.927 0.852 0.828
12 1.07 (0.74 ; 1.56) 0.716 0.852 0.836
16 1.25 (0.92 ; 1.69) 0.147 0.856 0.842
20 1.39 (1.04 ; 1.85) 0.025 0.860 0.846
24 1.39 (1.06 ; 1.82) 0.017 0.857 0.848
28 1.43 (1.09 ; 1.89) 0.010 0.864 0.852
32 1.62 (1.19 ; 2.21) 0.002 0.895 0.888
Overall # 1.33 (1.05 ; 1.68) 0.016
decline 4 1.37 (0.58 ; 3.27) 0.477 0.857 0.839
HBV DNA log10 8 1.16 (0.60 ; 2.25) 0.656 0.854 0.834
12 1.18 (0.74 ; 1.89) 0.488 0.855 0.839
16 1.36 (0.97 ; 1.90) 0.076 0.857 0.845
20 1.49 (1.09 ; 2.03) 0.012 0.864 0.853
24 1.47 (1.10 ; 1.96) 0.010 0.866 0.854
28 1.56 (1.14 ; 2.13) 0.005 0.870 0.859
32 1.72 (1.23 ; 2.41) 0.001 0.898 0.891
Overall # 1.47 (1.13 ; 1.90) 0.004
# Estimated OR by dynamic logistic regression model for fi xed number of treatment weeks
Dynamic logistic regression model of on-treatment factors
Using the dynamic logistic regression model, signifi cant effects were found of crude
HBV DNA levels over time (p=0.016, model A) and of decline in HBV DNA levels over
time (p= 0.004, model B); the latter providing better fi t and discrimination (model A:
QIC = 576.0, mean c-statistics = 0.860; model B: QIC=564.1, mean c-statistics=0.863).
In both models duration of treatment (in weeks) was signifi cantly related to response
(p=0.027 model A and p=0.011 model B). The effects of ALT levels were not signifi cant
(ALT: p=0.406, model C and ln(ALT): p=0.558, model D).
The dynamic logistic regression equation of prediction of SR at a specifi c week, PSR, week ,
is estimated by the crude observed HBV DNA, model A: