Comprehensive Assessment of ERα, PR, Ki67, P53 to Predict the Risk of Lymph Node Metastasis in Low-Risk Endometrial Cancer

Figures & data

Table 1. The clinical features of cases which were included in training cohort and validation cohort.

Clinical features	Training cohort (n = 571)		Validation cohort (n = 351)		P
	n	%	n	%
Age(years)
Mean ± SD	52.49 ± 8.90	/	53.46 ± 9.52	/	0.223
Median (Range)	52 (24–81)	/	52(25–83)	/
BMI (kg/m^2)
Mean ± SD	24.90 ± 3.80	/	25.04 ± 3.77	/	0.992
Median (Range)	24.61(16.35–45.72)	/	24.46(17.33–41.87)	/
Grade
1	305	53.4	208	59.3	0.083
2	266	46.6	143	40.7
CA125
>35 U/ml	128	22.4	99	28.2	0.048
≤35 U/ml	443	77.6	252	71.8
Lymphatic vascular invasion (LVSI)
Yes	113	19.8	65	18.5	0.635
No	458	80.2	286	81.5
ERα-positive rate
Median	90	/	85	/	0.821
Range	0–95	/	0–95	/
PR positive rate
Median	90	/	75	/	0.237
Range	0–95	/	0–95	/
Ki67 positive rate
Median	30	/	30	/	0.151
Range	1–90	/	3–90	/
P53 positive rate
Median	20	/	20	/	0.456
Range	0–90	/	0–90	/

Abbreviations: CA125, carbohydrate antigen 125; BMI, body mass index; ERα, estrogen receptor α; PR, progesterone receptor; SD, standard deviation. Additional note: The rates of 4 indicators (ERα, PR, Ki67, P53) mean the percentage of positive cells. The average proportion of positively stained cells in five random microscope fields will be the ultimate result. Captions: The table shows the clinical features of cases which were included in the training (n = 571) and validation (n = 351) cohorts. The results indicated that there was no statistical significance except CA125 between training and validation cohorts.

Table 2. Clinical data of lymph node metastasis and lymph node resection.

Items	Training cohort (n = 571)		Validation cohort (n = 351)		P
	n	%	n	%
Lymph node resection
Patients with only pelvic lymph node dissection	416	72.9	270	76.9	0.169
Patients with pelvic lymph node and para-aortic lymph node dissection	155	27.1	81	23.1
The number of total dissected lymph nodes
Median	32	/	31	/	0.179
Range	5–93	/	5–93	/
The number of dissected pelvic lymph nodes
Median	30	/	29	/	0.450
Range	5–81	/	5–78	/
The number of dissected para-aortic lymph nodes
Median	10	/	8	/	0.199
Range	4-41	/	4-30	/
Lymph node metastasis
Patients without lymph node metastasis	480	84.1	304	86.6	0.036
Patients with pelvic lymph node metastasis	79	13.8	28	10.8
Patients with pelvic lymph node and para-aortic lymph node metastasis	12	2.1	9	2.6

Captions: The table shows the clinical data of lymph node metastasis and lymph node resection. All the cases in training cohort and validation cohort have received lymph node resection. There was no case of only para-aortic lymph node metastasis in this study.

Table 3. Result of univariate and multivariate analysis for risk of lymph node metastasis.

Factor	Univariate analysis			Multivariate analysis
	OR (95%CI)	Wald	P	OR (95%CI)	Wald	P
Age	1.020 (0.995–1.046)	2.383	0.123	/	/	/
BMI	0.974 (0.917–1.035)	0.718	0.397	/	/	/
CA125	2.601 (1.611–4.200)	15.286	<0.001	1.958 (1.002–3.826)	3.866	0.049
Grade	4.830 (2.870–8.128)	35.165	<0.001	2.058 (1.059–4.000)	4.534	0.033
LVSI	6.700 (4.120–10.897)	58.766	<0.001	3.887 (2.022–7.470)	16.588	<0.001
ERα	0.966 (0.959–0.974)	82.708	<0.001	0.970 (0.960–0.981)	30.854	<0.001
PR	0.972 (0.966–0.979)	67.150	<0.001	0.981 (0.971–0.992)	12.742	<0.001
P53	1.028 (1.020–1.036)	51.249	<0.001	1.034 (1.023–1.045)	39.765	<0.001
Ki67	1.036 (1.023–1.049)	30.594	<0.001	1.028 (1.010–1.046)	9.459	0.002

Abbreviations: CA125, carbohydrate antigen 125; OR, odd ratio; LVSI, lymphatic vascular invasion; ERα, estrogen receptor α; PR, progesterone receptor; CI, confidence interval; BMI, body mass index. Additional note: Age, BMI, ER, PR, P53, Ki67 were served as continuous variables. CA125, Grade, LVSI were served as categorical variables. Captions: Logistic regression analysis for risk of lymph node metastasis were performed on these factors. Univariate analysis indicated that Age, BMI show no statistical significance. Therefore, the remaining factors (P < 0.05): CA125, grade, lymphatic vascular invasion (LVSI), ERα, PR, P53 and Ki67 were further analyzed by multivariate analysis.

Figure 1. The procedure of inclusion and exclusion.

Description: Both training cohort (n = 571) and validation cohort (n = 351) met the same criteria.

Figure 2. ROC curve of combined ratio and other single-factor models.

Description: ROC curve suggests that the area under the curve (AUC) of combined ratio which defined as the value of (ERα + PR)/(Ki67 + P53) is the largest. The values are recorded in Table 4. The area under the curve (AUC) value at the black dot is the highest. And the dot stands for the value here is the best threshold of the combined ratio for predicting lymph node metastasis. The best cutoff value of the combined ratio can be obtained as 1.38 in training cohort, while in validation cohort can be obtained as 1.40. Abbreviations: CA125, carbohydrate antigen 125; LVSI, lymphatic vascular invasion; ERα, estrogen receptor α; PR, progesterone receptor.

Table 4. Area under the ROC curve of models constructed with combined ratio and other single factors in prediction of lymph node metastasis.

	Training cohort		Validation cohort
Factor	AUC value(95%CI)	SE	AUC value(95%CI)	SE
CA125	0.595(0.528–0.663)	0.034	0.493(0.378–0.608)	0.059
LVSI	0.689(0.624–0.755)	0.034	0.691(0.572–0.809)	0.060
Grade	0.680(0.623–0.738)	0.029	0.654(0.546–0.761)	0.055
ERα	0.796(0.744–0.849)	0.027	0.779(0.689–0.868)	0.046
PR	0.771(0.715–0.826)	0.028	0.739(0.646–0.831)	0.047
Ki67	0.694(0.637–0.750)	0.029	0.766(0.674–0.858)	0.047
P53	0.701(0.635–0.767)	0.034	0.655(0.533–0.777)	0.062
Combined ratio	0.876(0.827–0.925)	0.025	0.812(0.728–0.896)	0.043

Abbriviations: CA125, carbohydrate antigen 125; LVSI, lymphatic vascular invasion; ERα, estrogen receptor α; PR, progesterone receptor; CI, confidence interval; AUC, area under the curve. Captions: The AUC value of the combined ratio in training cohort is 0.876, which is greater than the AUC value of other single factors which means it has the best accuracy.

Figure 3. Kaplan-Meier analysis of differences in survival of patients stratified by the cutoff value.

Description: We used the combined ratio which obtained in training cohort to divide patients with a follow-up times at least two years into low-risk group and high-risk group. The training cohort: 314 cases in low-risk group and 75 cases in high-risk group. The validation cohort: 266 cases in low-risk group and 85 cases in high-risk group. (A) RFS curve of cohorts grouped by the combined ratio in training cohort. (B) OS curve of cohorts grouped by the combined ratio in training cohort. (C) RFS curve of cohorts grouped by the combined ratio in validation cohort. (D) OS curve of cohorts grouped by the combined ratio in validation cohort.

Table 5. The survival rates of high-risk and low-risk group in training and validation cohorts.

Cohort	Group	Number of recurrence (n, %)	Three-year RFS (95%CI)	Log-rank P	Number of death (n, %)	Three-year OS (95%CI)	Log-rank P
Training cohort (n = 389)	Low-risk group (n = 314)	14, 4.5	96.7%(94.7%–98.7%)	P < 0.001	8, 2.5	97.3%(96.1%–99.7%)	P < 0.001
	High-risk group (n = 75)	17, 22.7	76.5%(66.7%-86.3%)		10, 13.3	87.5%(79.9%–95.1%)
Validation cohort (n = 351)	Low-risk group (n = 266)	7, 2.6	97.3%(95.3%-99.3%)	P < 0.001	5, 1.9	98.4%(96.8%–99.9%)	P < 0.001
	High-risk group (n = 85)	19, 22.4	78.4%(69.6%-87.4%)		11, 12.9	88.2%(80.8%–95.6%)

Abbriviations: RFS, recurrence-free survival rate; OS, overall survival rate; CI, confidence interval. Captions: The table records different number of ending events in training cohort and validation cohorts. It indicated that there exists a statistical difference in RFS and OS between two groups, which further confirmed the practicability of this model.