ADNEX模型鉴别转移性与原发性卵巢癌的诊断效能研究

doi:10.16150/j.1671-2870.2023.06.010

摘要/Abstract

摘要：

目的： 研究国际卵巢肿瘤分析组织(International Ovarian Tumor Analysis，IOTA)附件多元模型（Assessment of Different NEoplasias in the adneXa, ADNEX）术前鉴别转移性卵巢癌与原发性卵巢癌的临床价值。方法： 收集2016年3月至2021年4月在我院行手术治疗的卵巢恶性肿瘤患者术前予超声检查，并记录模型预判结果，以术后病理结果为金标准，计算ADNEX模型纳入、不纳入CA125时鉴别转移性与原发性卵巢癌的灵敏度、特异度及受试者操作特征（receiver operating characteristic，ROC）曲线下面积。结果： 本研究纳入卵巢恶性肿瘤患者共197例，其中原发性卵巢癌153例（Ⅰ期36例，Ⅱ~Ⅳ期117例），转移性卵巢癌44例。ADNEX模型不纳入CA125时，鉴别转移性与原发性卵巢癌的ROC曲线下面积为0.621（95%置信区间为0.534~0.708），灵敏度为93.2%，特异度为31.4%；ADNEX模型纳入CA125时，鉴别转移性与原发性卵巢癌的ROC曲线下面积为0.810（95%置信区间为0.747~0.872），灵敏度为79.5%，特异度为69.3%。ADNEX模型纳入与不纳入CA125结果间差异有统计学意义（P<0.001）。结论： ADNEX模型对于转移性与原发性卵巢癌的鉴别有较好的临床价值，纳入CA125能提高模型的诊断效能。

关键词: 卵巢癌，转移性, 国际卵巢肿瘤分析, 附件多元模型, 超声诊断

Abstract:

Objective: To study the clinical value of the International Ovarian Tumor Analysis(IOTA) ADNEX(the Assessment of Differential NEopasia in the adneXa) model in differentiating metastatic ovarian cancer from primary ovarian cancer. Methods: Patients who underwent transvaginal ultrasonography and operation in our hospital from March 2016 to April 2021 were selected. Preoperative ultrasound examination was performed, and the model prediction results were recorded. Based on the postoperative pathological results， the sensitivity, specificity and area under receiver operating characteristic (ROC) curve of the ADNEX model with and without CA125 in distinguishing metastatic and primary ovarian cancer was calculated. Results: A total of 197 patients with ovarian cancer were enrolled, including 153 patients with primary ovarian cancer (36 patients with stage Ⅰ ovarian cancer, 117 patients with stage Ⅰ-Ⅳ ovarian cancer) and 44 patients with metastatic ovarian cancer. The area under the ROC curve of ADNEX model without CA125 in differentiating metastatic and primary ovarian cancer was 0.621 (95% confidence interval 0.534-0.708), with a sensitivity of 93.2% and a specificity of 31.4%.The area under the ROC curve of ADNEX model with CA125 was 0.810 (95% confidence interval 0.747-0.872), with a sensitivity of 79.5% and a specificity of 69.3%. The difference between the two was statistically significant (P<0.001). Conclusions: ADNEX model has good clinical value in the differentiation of metastatic and primary ovarian cancer. Use of CA125 in ADNEX can improve the diagnostic efficiency of the model.

Key words: Ovarian cancer, metastatic, IOTA, ADNEX model, Ultrasound diagnosis

中图分类号:

R447
R737.31

倪仲馨, 陈慧. ADNEX模型鉴别转移性与原发性卵巢癌的诊断效能研究[J]. 诊断学理论与实践, 2023, 22(06): 573-578.

NI Zhongxin, CHEN Hui. Study on the diagnostic efficacy of ADNEX model in differentiating metastatic and primary ovarian cancer[J]. Journal of Diagnostics Concepts & Practice, 2023, 22(06): 573-578.

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Histological type	n (%)
Primary ovarian malignant	153 (77.66)
Serous carcinoma	105 (53.30)
Clear cell carcinoma	15 (7.61)
Ovarian endometrioid carcinoma	15 (7.61)
Carcinosarcoma	3 (1.52)
Mucinous carcinoma	6 (3.05)
Neuroendocrine carcinomas	2 (1.02)
Immature teratomas	2 (1.02)
Granular cell tumor	2 (1.02)
Dysgerminomas	1 (0.51)
Malignant Brenner tumor	1 (0.51)
Ovarian endometrioid carcinoma + clear cell carcinoma	1 (0.51)
Ovarian metastasis	44 (22.34)

Variables	Overall	OC Stages Ⅰ	OC Stages Ⅱ-Ⅳ	Ovarian metastasis	P
Overall [n (%)]	197 (100%)	36 (18.27)	117 (59.39)	44 (22.34)	-
Age [years, median (IQR)]	55.00(48.00-63.00)	56.50(47.00-63.00)	58.00(51.00-64.00)	50.00(38.75-56.50)	<0.001
Menopause [n (%)]					0.014
Yes	126 (63.96)	24 (66.67)	82 (70.09)	20 (45.45)
No	71 (36.04)	12 (33.33)	35 (29.91)	24 (54.55)
CA125 [U/mL, median (IQR)]	210.60(39.10-883.30)	59.30(15.08-311.68)	596.20(122.20-2162.80)	37.95(13.25-102.68)	<0.001
Maximum diameter of lesion, mm, median (IQR)	77.00(51.00-111.00)	91.00(70.00-148.00)	70.00(44.00-100.00)	80.50(57.50-117.75)	0.017
Solid tissue present [n (%)]	195 (98.98)	35 (97.22)	117 (100.00)	43 (97.73)	0.164
Maximum diameter of largest solid component, if present, mm, median (IQR)	56.00(37.00-82.00)	50.00(33.00-63.50)	52.00(34.00-85.00)	68.00(51.50-90.50)	0.038
Papillary projections present [n (%)]					0.260
0	161 (81.73)	26 (72.22)	95 (81.20)	40 (90.91)
1	7 (3.55)	1 (2.78)	5 (4.27)	1 (2.27)
2	3 (1.52)	0 (0.00)	3 (2.56)	0 (0.00)
≥3	26 (13.20)	9 (25.00)	14 (11.97)	3 (6.82)
More than 10 locules [n (%)]	33 (16.75)	7 (19.44)	15 (12.82)	11 (25.00)	0.163
Ascites [n (%)]	48 (24.37)	3 (8.33)	41 (35.04)	4 (9.09)	<0.001

Discrimination	AUC (95%CI)		P
Discrimination	ADNEX model with CA125	ADNEX model without CA125	P
Primary OC vs metastasis	0.810 (0.747-0.872)	0.621 (0.534-0.708)	<0.001
Stage Ⅰ OC vs stages Ⅱ-Ⅳ OC	0.826 (0.745-0.907)	0.771 (0.687-0.854)	0.156
Stage Ⅰ OC vs metastasis	0.620 (0.486-0.754)	0.654 (0.524-0.784)	0.033
Stages Ⅱ-Ⅳ OC vs metastasis	0.890 (0.839-0.940)	0.710 (0.624-0.796)	<0.001

Discrimination	ADNEX model	Sensitivity (95%CI)	Specificity (95%CI)	PPV (95%CI)	NPV (95%CI)	LR+ (95%CI)	LR- (95%CI)	Optimal cutoff value
Primary OC vs metastasis	With CA125	0.795 (0.676-0.915)	0.693 (0.620-0.766)	0.427 (0.320-0.534)	0.922 (0.873-0.971)	2.589 (1.955-3.430)	0.295 (0.163-0.534)	0.140
Primary OC vs metastasis	Without CA125	0.932 (0.857-1.000)	0.314 (0.240- 0.387)	0.281 (0.208- 0.354)	0.941 (0.877-1.006)	1.358 (1.188-1.552)	0.217 (0.071-0.664)	0.110
Stage Ⅰ OC vs stages Ⅱ-Ⅳ OC	With CA125	0.701 (0.618-0.784)	0.833 (0.712- 0.955)	0.932 (0.879-0.984)	0.462 (0.340-0.583)	4.205 (2.006-8.813)	0.359 (0.262-0.491)	0.840
Stage Ⅰ OC vs stages Ⅱ-Ⅳ OC	Without CA125	0.821 (0.751-0.890)	0.639 (0.482-0.796)	0.881 (0.820-0.942)	0.523 (0.375-0.670)	2.272 (1.459-3.538)	0.281 (0.178-0.444)	0.691
Stage Ⅰ OC vs metastasis	With CA125	0.727 (0.596-0.859)	0.639 (0.482-0.796)	0.711 (0.579-0.844)	0.657 (0.500-0.814)	2.014 (1.258-3.225)	0.427 (0.248-0.734)	0.381
Stage Ⅰ OC vs metastasis	Without CA125	0.841 (0.733-0.949)	0.556 (0.393-0.718)	0.698 (0.575-0.822)	0.741 (0.575-0.906)	1.892 (1.285-2.787)	0.286 (0.137-0.600)	0.297
Stages Ⅱ-Ⅳ OC vs metastasis	With CA125	0.841 (0.733-0.949)	0.803 (0.731-0.875)	0.617 (0.494-0.740)	0.931 (0.881-0.980)	4.278 (2.901-6.307)	0.198 (0.100-0.393)	0.239
Stages Ⅱ-Ⅳ OC vs metastasis	Without CA125	0.795 (0.676-0.915)	0.607 (0.518-0.695)	0.432 (0.324-0.540)	0.887 (0.818-0.957)	2.023 (1.544-2.651)	0.337 (0.185-0.615)	0.208

ADNEX model	Cutoff value	Sensitivity (95%CI)	Specificity (95%CI)	PPV(95%CI)	NPV(95%CI)	LR+(95%CI)	LR-(95%CI)
With CA125	0.10	0.886 (0.793-0.980)	0.549 (0.470-0.628)	0.361 (0.271-0.452)	0.944 (0.896-0.992)	1.965 (1.602-2.411)	0.207 (0.090-0.478)
	0.15	0.750 (0.622-0.878)	0.706 (0.634-0.778)	0.423 (0.313-0.533)	0.908 (0.856-0.960)	2.550 (1.891-3.438)	0.354 (0.210-0.597)
	0.20	0.614 (0.470-0.758)	0.810 (0.748-0.873)	0.482 (0.351-0.613)	0.879 (0.826-0.933)	3.237 (2.164-4.844)	0.477 (0.326-0.697)
	0.25	0.477 (0.330-0.625)	0.876 (0.824-0.928)	0.525 (0.370-0.680)	0.854 (0.798-0.909)	3.843 (2.280-6.479)	0.597 (0.447-0.797)
Without CA125	0.10	0.932 (0.857-1.000)	0.288 (0.216-0.359)	0.273 (0.202-0.345)	0.936 (0.866-1.006)	1.308 (1.150-1.487)	0.237 (0.077-0.727)
	0.15	0.727 (0.596-0.859)	0.477 (0.398-0.556)	0.286 (0.202-0.369)	0.859 (0.785-0.933)	1.391 (1.099-1.761)	0.572 (0.343-0.952)
	0.20	0.250 (0.122-0.378)	0.778 (0.712-0.844)	0.244 (0.119-0.370)	0.783 (0.717-0.848)	1.125 (0.623-2.032)	0.964 (0.797-1.167)
	0.25	0.045 (0.000- 0.107)	0.967 (0.939-0.995)	0.286 (0.000-0.620)	0.779 (0.720-0.838)	1.391 (0.279-6.925)	0.987 (0.919-1.059)