Predictors and characteristics of models that predict a positive temporal artery biopsy as well as a model to predict the diagnosis of GCA in those with a negative biopsy
| . | Variables to predict TAB-positive GCA . | Variables to predict TAB-negative GCA . | ||
|---|---|---|---|---|
| . | β (s.e.) . | OR (95% CI) . | β (s.e.) . | OR (95% CI) . |
| N (events) | 174 (33) | 141 (53) | ||
| Intercept | −6.99 (1.16) | – | −4.71 (1.68) | – |
| Jaw claudication | 3.01 (0.69) | 20.29 (5.28, 77.90) | – | – |
| Log CRP | 1.29 (0.56) | 3.63 (1.20, 10.94) | 0.93 (0.34) | 2.54 (1.30, 4.95) |
| TA-MRA | 3.76 (0.88) | 43.02 (7.61, 243.31) | 2.23 (0.48) | 9.29 (3.61, 23.88) |
| TA tenderness | – | – | 0.89 (0.47) | 2.46 (0.98, 6.18) |
| Age | – | – | 0.03 (0.02) | 1.03 (0.99, 1.08) |
| Weight loss | – | – | −1.32 (0.87) | 0.27 (0.05, 1.47) |
| AIC | 77.526 | 156.124 | ||
Spiegelhalter Hosmer-Lemeshow | 0.11/ p=0.74 | 0.006/ p=0.98 | ||
| 38.61/ p<0.01 | 0.92/ p=0.82 | |||
| AUROC | 0.949 (0.898–1.000) | 0.802 (0.728–0.875) | ||
| . | Variables to predict TAB-positive GCA . | Variables to predict TAB-negative GCA . | ||
|---|---|---|---|---|
| . | β (s.e.) . | OR (95% CI) . | β (s.e.) . | OR (95% CI) . |
| N (events) | 174 (33) | 141 (53) | ||
| Intercept | −6.99 (1.16) | – | −4.71 (1.68) | – |
| Jaw claudication | 3.01 (0.69) | 20.29 (5.28, 77.90) | – | – |
| Log CRP | 1.29 (0.56) | 3.63 (1.20, 10.94) | 0.93 (0.34) | 2.54 (1.30, 4.95) |
| TA-MRA | 3.76 (0.88) | 43.02 (7.61, 243.31) | 2.23 (0.48) | 9.29 (3.61, 23.88) |
| TA tenderness | – | – | 0.89 (0.47) | 2.46 (0.98, 6.18) |
| Age | – | – | 0.03 (0.02) | 1.03 (0.99, 1.08) |
| Weight loss | – | – | −1.32 (0.87) | 0.27 (0.05, 1.47) |
| AIC | 77.526 | 156.124 | ||
Spiegelhalter Hosmer-Lemeshow | 0.11/ p=0.74 | 0.006/ p=0.98 | ||
| 38.61/ p<0.01 | 0.92/ p=0.82 | |||
| AUROC | 0.949 (0.898–1.000) | 0.802 (0.728–0.875) | ||
Predictors and characteristics of models that predict a positive temporal artery biopsy as well as a model to predict the diagnosis of GCA in those with a negative biopsy
| . | Variables to predict TAB-positive GCA . | Variables to predict TAB-negative GCA . | ||
|---|---|---|---|---|
| . | β (s.e.) . | OR (95% CI) . | β (s.e.) . | OR (95% CI) . |
| N (events) | 174 (33) | 141 (53) | ||
| Intercept | −6.99 (1.16) | – | −4.71 (1.68) | – |
| Jaw claudication | 3.01 (0.69) | 20.29 (5.28, 77.90) | – | – |
| Log CRP | 1.29 (0.56) | 3.63 (1.20, 10.94) | 0.93 (0.34) | 2.54 (1.30, 4.95) |
| TA-MRA | 3.76 (0.88) | 43.02 (7.61, 243.31) | 2.23 (0.48) | 9.29 (3.61, 23.88) |
| TA tenderness | – | – | 0.89 (0.47) | 2.46 (0.98, 6.18) |
| Age | – | – | 0.03 (0.02) | 1.03 (0.99, 1.08) |
| Weight loss | – | – | −1.32 (0.87) | 0.27 (0.05, 1.47) |
| AIC | 77.526 | 156.124 | ||
Spiegelhalter Hosmer-Lemeshow | 0.11/ p=0.74 | 0.006/ p=0.98 | ||
| 38.61/ p<0.01 | 0.92/ p=0.82 | |||
| AUROC | 0.949 (0.898–1.000) | 0.802 (0.728–0.875) | ||
| . | Variables to predict TAB-positive GCA . | Variables to predict TAB-negative GCA . | ||
|---|---|---|---|---|
| . | β (s.e.) . | OR (95% CI) . | β (s.e.) . | OR (95% CI) . |
| N (events) | 174 (33) | 141 (53) | ||
| Intercept | −6.99 (1.16) | – | −4.71 (1.68) | – |
| Jaw claudication | 3.01 (0.69) | 20.29 (5.28, 77.90) | – | – |
| Log CRP | 1.29 (0.56) | 3.63 (1.20, 10.94) | 0.93 (0.34) | 2.54 (1.30, 4.95) |
| TA-MRA | 3.76 (0.88) | 43.02 (7.61, 243.31) | 2.23 (0.48) | 9.29 (3.61, 23.88) |
| TA tenderness | – | – | 0.89 (0.47) | 2.46 (0.98, 6.18) |
| Age | – | – | 0.03 (0.02) | 1.03 (0.99, 1.08) |
| Weight loss | – | – | −1.32 (0.87) | 0.27 (0.05, 1.47) |
| AIC | 77.526 | 156.124 | ||
Spiegelhalter Hosmer-Lemeshow | 0.11/ p=0.74 | 0.006/ p=0.98 | ||
| 38.61/ p<0.01 | 0.92/ p=0.82 | |||
| AUROC | 0.949 (0.898–1.000) | 0.802 (0.728–0.875) | ||
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