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The covariates eligible for inclusion in the model as potential confounders were gender, age as a continuous variable, and comorbidity level.
Factors will be considered for inclusion in the model as potentially associated with DDC and OS if the univariate p-value is ≤ 0.1.
Continuous prognostic variables were also considered for inclusion in the model as dichotomous variables using various cutoff points only if they attained a P-value of ⩽0.1 in the univariate analysis.
Factors considered for inclusion in the model as predictors were respondents' age and gender, lifestyle behaviours (currently smoking; vegetarian or macrobiotic diet; physical activity during the last year), and professional characteristics (postgraduate specialisation; any certificated CAM training, completed or in progress; number of inhabitants in the area of medical practice).
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The fractional polynomial terms selected for inclusion in the model were as follows.
A stepwise procedure in which markers are considered for inclusion in the model one at a time was used, as applied by Habier et al. [ 13].
For regression models, covariates for inclusion in the model were identified from bivariate analyses.
The criterion for inclusion in the model was p ≤ 0.05.
Main effects were chosen as described above, using a significance criterion of p ≤ 0.05 for inclusion in the model.
Each marker that is not already in the model is tested for inclusion in the model.
27 Variables eligible for inclusion in the models were conceptually associated with the procedure, as well as statistically associated (P < 0.20) with the procedure in bivariable analysis.
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