Table 2.

Confusion matrices for the three proposed cut-offs for the model predictions regarding the presence of definite radiographic sacroiliitis on the validation dataset

	nr-axSpA	r-axSpA
Cut-off 1, favouring sensitivity over specificity
Model predicts nr-axSpA	15	1	16
Model predicts r-axSpA	64	149	227
	79	150	229
Cohen’s kappa	0.22 (95% CI 0.11–0.33)	Accuracy:	n = 164/229 (71.6%)
Cut-off 2, favouring specificity over sensitivity
Model predicts nr-axSpA	78	38	116
Model predicts r-axSpA	1	112	113
	79	150	229
Cohen’s kappa	0.66 (95% CI 0.57–0.76)	Accuracy:	n = 190/229 (83.0%)
Cut-off 3, optimal relationship between sensitivity and specificity
Model predicts nr-axSpA	75	19	94
Model predicts r-axSpA	4	131	135
	79	150	229
Cohen’s kappa	0.79 (95% CI 0.7–0.87)	Accuracy:	n = 206/229 (90.0%)