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L. Janssen et al.
(mean QoL 6.1 ± 1.3 and 7.8 ± 1.1, respectively; P<0.001). Table 1 shows the univariable and multivariable logistic regression analyses of the predictors of severe fatigue in CML patients. The final multivariable model included: age (OR 0.96, 95% CI: 0.93-0.99; P=0.004), female gender (OR 1.76, 95% CI: 0.92-3.34; P=0.09), CCI (OR 1.91, 95% CI: 1.16-3.13); P=0.011), the use of comedication known to cause fatigue (OR 3.43, 95% CI: 1.58-7.44; P=0.002), and physical activity at different intensities compared to phys- ical inactivity, including moderately active (OR 0.43, 95% CI: 0.12-1.52; P=0.19), vigorously active (OR 0.22, 95% CI:
0.06-0.74; P=0.014), and very vigorously P<0.001). The area under the curve of the final model was 0.79 (95% CI: 0.73-0.85) and the calibration slope was 1.01. The predict- ed severe fatigue and associated observed fatigue are dis- played in Figure 2, showing a positive predictive value of 73%, a negative predictive value of 68%, a sensitivity of 76%, and a specificity of 65%. Our model can be described by the following equation: log-odds = 1.98 – 0.04 * age + 0.56 * gender (male=0, female=1) + 0.65 * CCI + 1.23 * use of comedication known to cause fatigue (no=0, yes=1) – physical activity level (inactivity=0, moderately
Figure 1. Flowchart of the study. CML: chronic myeloid leukemia.
Figure 2. Predicted and observed severe fatigue. The predicted severe fatigue of the multivariable model is plotted against the observed severe fatigue. Each dot represents an individual.
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