Table 5. Random forest importance scores of variables in multivariate treatment failure prediction models for all participants.

Name of Successive Variable	Importance Score of Successive Variable
VAS breathlessness	11.2
VAS sputum purulence	8.3
LAMA	6.5
Number of unscheduled primary care and emergency department visits in previous 12 months	5.6
ICS use	4.9
VAS sputum production	4.2
PPI use	4.2
EuroQol mobility	4.1
Oxygen saturation	3.8
SABA use	3.3
SCS at exacerbation	2.7
Exacerbation associated with increased sputum purulence	1.1
Exacerbation associated with increased sputum production	1.0
EuroQol self care	0.8
Gender	0.6
EuroQol usual activity	-0.5
VAS cough	-1.0

Definition of abbreviations: LAMA = Long-acting muscarinic antagonist; ICS = inhaled corticosteroids; PPI = proton pump inhibitor; SABA = short-acting beta agonist.

Models shown range from those using just a single variable up to those with the full subset which passed the univariate analysis filter of p < 0.1. Variable importance scores were calculated as outlined in S1 Appendix Statistical Methods. To illustrate the interpretation of the variable importance scores, consider the example of VAS breathlessness. The VAS breathlessness random forest importance score of 11.2 indicates that classification accuracy would drop by 11.2% if VAS breathlessness is omitted from the classification model.