Subgroup identification for treatment selection in biomarker adaptive design

Table 1 Predictive performance of the five classifiers for eight scenarios (A-H). Each value is the average of 1,000 trials

Scenario	A	B	C	D	E	F	G	H
Predictive biomarkers	10	15	20	10	10	10	10	15
Significances	7.025	9.27	11.761	7.432	12.426	5.274	12.313	17.039
True positives	4.147	6.443	8.865	4.487	9.495	2.202	9.267	14.002
DLDA Sensitivity	0.598	0.651	0.694	0.626	0.979	0.507	0.985	0.99
Specificity	0.991	0.993	0.993	0.995	0.999	0.94	0.983	0.99
PPV	0.745	0.788	0.809	0.791	0.993	0.475	0.97	0.981
NPV	0.958	0.963	0.968	0.96	0.998	0.946	0.992	0.995
Accuracy	0.952	0.959	0.964	0.958	0.997	0.897	0.984	0.99
ASD (1,1) Sensitivity	0.784	0.808	0.841	0.943	0.991	0.953	0.989	0.991
Specificity	0.691	0.689	0.686	0.142	0.644	0.083	0.551	0.533
PPV	0.253	0.256	0.268	0.112	0.283	0.104	0.51	0.5
NPV	0.967	0.97	0.976	0.824	0.999	0.849	0.992	0.994
Accuracy	0.7	0.7	0.702	0.222	0.679	0.169	0.682	0.671
ASD (1,2) Sensitivity	0.635	0.683	0.723	0.831	0.982	0.807	0.977	0.982
Specificity	0.931	0.927	0.923	0.357	0.899	0.284	0.853	0.838
PPV	0.537	0.56	0.579	0.148	0.647	0.117	0.774	0.762
NPV	0.959	0.964	0.97	0.903	0.998	0.904	0.991	0.993
Accuracy	0.902	0.903	0.903	0.404	0.907	0.336	0.89	0.882
ASD (2,1) Sensitivity	0.464	0.533	0.573	0.766	0.953	0.654	0.581	0.649
Specificity	0.982	0.982	0.982	0.767	0.976	0.754	0.973	0.972
PPV	0.623	0.656	0.685	0.32	0.839	0.27	0.846	0.868
NPV	0.944	0.951	0.956	0.968	0.995	0.952	0.86	0.882
Accuracy	0.93	0.937	0.941	0.767	0.974	0.744	0.856	0.875
ASD (2,2) Sensitivity	0.331	0.408	0.453	0.64	0.926	0.445	0.424	0.511
Specificity	1	1	1	0.95	0.999	0.951	0.999	0.999
PPV	0.673	0.719	0.761	0.635	0.987	0.509	0.864	0.904
NPV	0.932	0.939	0.945	0.96	0.993	0.941	0.816	0.843
Accuracy	0.933	0.941	0.945	0.919	0.992	0.901	0.827	0.853

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