Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients

Table 1 Demographic and clinical characteristics of patients in the Surveillance, Epidemiology, and End Results dataset and our hospital

Variables	Training set	Validation set	Test set
	n = 233	n = 53	n = 92
Age, mean (SD)	60.7 (13.5)	61.4 (13.2)	65.62 (8.78)
Sex, n (%)
Female	120 (51.5)	21 (39.6)	17 (18.48)
Male	113 (48.5)	32 (60.4)	75 (81.52)
Marital, n (%)
Unmarried	84 (36.1)	16 (30.2)	0 (0.00)
Married	141 (60.5)	37 (69.8)	92 (100)
Unknown	8 (3.43)	0 (0.00)	0 (0.00)
Race, n (%)
White	41 (17.6)	7 (13.2)	0 (0.00)
Black	167 (71.7)	41 (77.4)	0 (0.00)
Asian and others	25 (10.7)	5 (9.43)	92 (100)
Primary site, n (%)
Upper 1/3	44 (18.9)	13 (24.5)	57 (61.96)
Middle 1/3	89 (38.2)	21 (39.6)	11 (11.96)
Lower 1/3	50 (21.5)	12 (22.6)	18 (19.57)
Overlapping	50 (21.5)	7 (13.2)	6 (6.52)
Histology, n (%)
NET	150 (64.4)	33 (62.3)	6 (6.52)
NEC	71 (30.5)	16 (30.2)	62 (67.39)
MANEC	12 (5.15)	4 (7.55)	24 (26.09)
Size, n (%)
≤ 2	92 (39.5)	19 (35.8)	7 (7.61)
> 2 and ≤ 5	82 (35.2)	21 (39.6)	53 (57.61)
> 5	59 (25.3)	13 (24.5)	32 (34.78)
T stage, n (%)
Tis	3 (1.29)	1 (1.89)	0 (0.00)
T1	41 (17.6)	5 (9.43)	4 (4.35)
T2	77 (33.0)	20 (37.7)	10 (10.87)
T3	67 (28.8)	12 (22.6)	59 (64.13)
T4	45 (19.3)	15 (28.3)	19 (20.65)
N stage, n (%)
N0	111 (47.6)	27 (50.9)	23 (25.00)
N1/N2/N3	122 (52.4)	26 (49.1)	69 (75.00)
M stage, n (%)
M0	196 (84.1)	43 (81.1)	79 (85.87)
M1	37 (15.9)	10 (18.9)	13 (14.13)
LNR, n (%)
0	111 (47.6)	27 (50.9)	24 (26.09)
≤ 0.2	47 (20.2)	11 (20.8)	35 (38.04)
> 0.2	75 (32.2)	15 (28.3)	33 (35.87)
Radiation, n (%)
No	213 (91.4)	48 (90.6)	86 (93.48)
Yes	20 (8.58)	5 (9.43)	6 (6.52)
Chemotherapy, n (%)
No	183 (78.5)	40 (75.5)	41 (44.57)
Yes	50 (21.5)	13 (24.5)	51 (55.43)
Status, n (%)
Alive	168 (72.1)	36 (67.9)	53 (57.61)
Dead	65 (27.9)	17 (32.1)	39 (42.39)
Time, median (range)	51 (1, 189)	40 (1, 186)	23 (1, 148)

NET: Neuroendocrine tumor; NEC: Neuroendocrine carcinoma; MANEC: Mixed adenoneuroendocrine carcinoma; LNR: Lymph node ratio.

Table 2 The performance of the Cox proportional hazards model and the random survival forest model

Model	Dataset	C-index	AUC
			1-year	3-year	5-year
CoxPH	Training	0.834 (0.789-0.879)	0.848 (0.763-0.930)	0.881 (0.831-0.932)	0.875 (0.822-0.927)
	Validation	0.871 (0.802-0.940)	0.843 (0.717-0.969)	0.948 (0.892-1.000)	0.990 (0.969-1.000)
	Test	0.744 (0.665-0.822)	0.786 (0.622-0.889)	0.834 (0.735-0.934)	0.810 (0.688-0.931)
RSF	Training	0.940 (0.924-0.956)	0.962 (0.938-0.989)	0.979 (0.963-0.995)	0.971 (0.951-0.992)
	Validation	0.870 (0.818-0.921)	0.867 (0.761-0.973)	0.955 (0.899-1.000)	0.986 (0.960-1.000)
	Test	0.769 (0.691-0.846)	0.803 (0.608-0.891)	0.895 (0.814-0.976)	0.869 (0.769-0.970)

CoxPH: Cox proportional hazards; RSF: Random survival forest; AUC: Area under receiver operating characteristic curve.