Identifying the Best Marker Combination in CEA, CA125, CY211, NSE, and SCC for Lung Cancer Screening by Combining ROC Curve and Logistic Regression Analyses: Is It Feasible?

Table 2

Value of single-marker detection for screening lung cancer in patients with pneumonia and healthy subjects.

	SEN	SPE	PPV	NPV	+LR	−LR	Yden	Cutoff	AUC
Pneumonia patients
CA125	0.539	0.646	0.597	0.590	1.523	0.714	0.185	21.78	0.618
CEA	0.403	0.883	0.770	0.603	3.444	0.676	0.286	4.81	0.681
CY211	0.633	0.606	0.610	0.629	1.607	0.606	0.240	2.57	0.662
NSE	0.461	0.726	0.621	0.580	1.682	0.742	0.187	14.36	0.634
SCC	—	—	—	—	—	—	—	—	0.456
Healthy subjects
CA125	0.526	0.915	0.834	0.704	6.188	0.518	0.441	22.75	0.756
CEA	0.621	0.867	0.791	0.738	4.669	0.437	0.488	2.74	0.832
CY211	0.539	0.822	0.711	0.687	3.028	0.561	0.360	3.00	0.716
NSE	0.319	0.908	0.738	0.622	3.467	0.750	0.227	16.24	0.620
SCC	0.201	0.956	0.788	0.596	4.568	0.836	0.157	1.60	0.565

SEN: sensitivity; SPE: specificity; PPV: positive predictive value; NPV: negative predictive value; +LR: positive likelihood ratio; −LR: negative likelihood ratio; Yden: Youden index.