Table 7.
Example table showing results from model validation and subsequent updating161
| Clinical model (n=5677) |
Parma (n=1241) |
Miami (n=821) | Innsbruck (n=668) | Rotterdam (n=471) | |
|---|---|---|---|---|---|
| Prediction model performance | |||||
| C statistic (95% CI) | 0.79 | 0.78 (0.74 to 0.81) | 0.80 (0.74 to 0.85) | 0.78 (0.73 to 0.82) | 0.81 (0.76 to 0.88) |
| Calibration-in-the-large | — | 0.334 (P=0.001) | −0.046 (P=0.76) | 0.113 (P=0.33) | 0.344 (P=0.01) |
| Recalibration slope | — | −0.117 (P=0.14) | 0.046 (P=0.75) | 0.023 (P=0.85) | 0.097 (P=0.48) |
| Model coefficients | |||||
| Intercept | β= −7.539 | δ=1.010 (P=0.14) | δ= −0.292 (P=0.77) | δ= −0.355 (P=0.72) | δ= −0.420 (P=0.72) |
| Age | β=0.062 | δ= −0.003 (P=0.72) | δ= −0.015 (P=0.29) | δ= −0.018 (P=0.18) | δ= −0.013 (P=0.43) |
| Male sex | β=1.332 | δ= −0.015 (P=0.94) | δ=0.199 (P=0.56) | δ= 0.184 (P=0.50) | δ= 0.161 (P=0.59) |
| Atypical chest pain | β=0.633 | δ= −0.470 (P=0.06) | δ= −0.782 (P=0.05) | δ= −0.569 (P=0.17) | δ= −0.311 (P=0.53) |
| Typical chest pain | β=1.998 | δ= −0.615 (P=0.01) | δ= −0.485 (P=0.44) | δ= −0.839 (P=0.14) | δ= −0.194 (P=0.70) |
| Diabetes | β=0.828 | δ=0.241 (P=0.32) | δ=0.088 (P=0.79) | δ= −0.043 (P=0.88) | δ=0.038 (P=0.92) |
| Hypertension | β=0.338 | δ= 0.096 (P=0.59) | δ= −0.433 (P=0.18) | δ= −0.274 (P=0.30) | δ=0.219 (P=0.45) |
| Dyslipidaemia | β=0.422 | δ= −0.131 (P=0.43) | δ=0.008 (P=0.98) | δ= −0.042 (P=0.89) | δ= −0.117 (P=0.70) |
| Smoking | β=0.461 | δ= −0.121 (P=0.57) | δ=0.449 (P=0.77) | δ=0.022 (P=0.93) | δ=0.222 (P=0.50) |
β=estimated regression coefficient; δ=difference between the hospital-specific predictor effects and the predictor effects as estimated in the development data. P values above 0.05 support the validity of the developed prediction model in a specific hospital (Parma, Miami, Innsbruck, or Rotterdam).