Effectiveness of CT radiomic features combined with clinical factors in predicting prognosis in patients with limited-stage small cell lung cancer

Table 2 AUC of predicted models

Characteristic		AUC	95%CI	Sensitivity (%)	Specificity (%)
OS_R	Train(n = 140)	0.66	0.57–0.74	87.13	43.59
OS_R	Test(n = 60)	0.59	0.46–0.72	46.15	80.95
OS_C	Train(n = 140)	0.69	0.60–0.76	68.32	66.67
OS_C	Test(n = 60)	0.61	0.47–0.73	56.41	80.95
OS_RC	Train(n = 140)	0.71	0.62–0.78	68.54	75.00
OS_RC	Test(n = 60)	0.70	0.56–0.81	56.10	85.70
PFS_R	Train(n = 140)	0.73	0.65–0.81	85.84	51.85
PFS_R	Test(n = 60)	0.67	0.54–0.79	41.86	94.12
PFS_C	Train(n = 140)	0.68	0.59–0.75	77.06	54.84
PFS_C	Test(n = 60)	0.64	0.50–0.76	57.45	76.92
PFS_RC	Train(n = 140)	0.74	0.63–0.79	50.52	90.63
PFS_RC	Test(n = 60)	0.72	0.57–0.82	71.74	77.78

Abbreviations: OS_R radiomic model of OS, OS_C clinical model of OS, OS_RC combined model (including radiomic features and clinical factors) of OS, PFS_R radiomic model of PFS, PFS_C clinical model of PFS, PFS_RC combined model (including radiomic features and clinical factors) of PFS

ISSN: 1471-2407