Table 3.

Sensitivity (95% CI) of prediction models from split-sample and entire sample estimation approaches in the development dataset and prospective validation dataset

	Split-sample prediction model		Entire-sample prediction model
Risk percentile cutpoint	Testing set, Development	Prospective validation	5-fold cross-validation, Development	Bootstrap optimism correction, Development	Prospective validation
≥ 99%	12.2% (7.5%, 17.8%)	19.9% (10.9%, 30.1%)	11.6% (8.4%, 15.2%)	17.5% (8.8%, 24.6%)	15.1% (7.5%, 24.2%)
≥ 95%	42.1% (32.6%, 51.0%)	40.1% (30.1%, 50.2%)	33.9% (27.1%, 40.5%)	47.2% (40.1%, 52.9%)	39.2% (28.7%, 50.5%)
≥ 90%	54.0% (45.4%, 62.1%)	52.0% (41.7%, 61.1%)	50.5% (43.3%, 57.2%)	63.2% (56.3%, 67.8%)	53.0% (43.0%, 62.3%)
≥ 75%	78.5% (72.9%, 83.4%)	75.1% (67.0%, 82.3%)	75.1% (70.4%, 79.8%)	84.4% (81.0%, 86.9%)	72.1% (63.8%, 79.7%)