Table 2.

Logistic regression models of ITE.

	Univariable LR	Multivariable LR	BART
Baseline predictors
BMI z-score	0.872 (0.743, 1.026), P = .098	0.914 (0.770, 1.087), P = .308
Albumin (g/dL)	0.731 (0.531, 1.005), P = .054	0.938 (0.653, 1.347), P = .727
Hemoglobin (g/dL)	0.879 (0.794, 0.973), P = .013	0.924 (0.827, 1.032), P = .161
Monocyte (%)	1.048 (0.996, 1.103), P = .069	1.069 (1.011, 1.129), P = .019
Lymphocyte (%)	0.979 (0.963, 0.995), P = .010	0.975 (0.958, 0.993), P = .008
Platelet count (10^9/L)	1.002 (1.001, 1.004), P = .008	1.002 (1.000, 1.003), P = .029
Model evaluation
AUC		0.667 (0.606, 0.723)	0.696 (0.653, 0.736)
Comparison of AUC			P < .0001
Sensitivity		0.382 (0.276, 0.489)	0.484 (0.351, 0.607)
Specificity		0.802 (0.747, 0.858)	0.769 (0.680, 0.852)
Positive predictive value		0.583 (0.486, 0.680)	0.605 (0.548, 0.667)
Negative predictive value		0.586 (0.642, 0.699)	0.674 (0.636, 0.714)