Ciccarone Francesca, Biscione Antonella, Robba Eleonora, Pasciuto Tina, Giannarelli Diana, Gui Benedetta, Manfredi Riccardo, Ferrandina Gabriella, Romualdi Daniela, Moro Francesca, Zannoni Gian Franco, Lorusso Domenica, Scambia Giovanni, Testa Antonia Carla
Gynecologic Oncology Unit, Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Ovarian Cancer Center, Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy.
Am J Obstet Gynecol. 2025 Jan;232(1):108.e1-108.e22. doi: 10.1016/j.ajog.2024.07.027. Epub 2024 Jul 30.
Differential diagnosis between benign uterine smooth muscle tumors and malignant counterpart is challenging.
To evaluate the accuracy of a clinical and ultrasound based algorithm in predicting mesenchymal uterine malignancies, including smooth muscle tumors of uncertain malignant potential.
We report the 12-month follow-up of an observational, prospective, single-center study that included women with at least 1 myometrial lesion ≥3 cm on ultrasound examination. These patients were classified according to a 3-class diagnostic algorithm, using symptoms and ultrasound features. "White" patients underwent annual telephone follow-up for 2 years, "Green" patients underwent a clinical and ultrasound follow-up at 6, 12, and 24 months and "Orange" patients underwent surgery. We further developed a risk class system to stratify the malignancy risk.
Two thousand two hundred sixty-eight women were included and target lesion was classified as benign in 2158 (95.1%), as other malignancies in 58 (2.6%) an as mesenchymal uterine malignancies in 52 (2.3%) patients. At multivariable analysis, age (odds ratio 1.05 [95% confidence interval 1.03-1.07]), tumor diameter >8 cm (odds ratio 5.92 [95% confidence interval 2.87-12.24]), irregular margins (odds ratio 2.34 [95% confidence interval 1.09-4.98]), color score=4 (odds ratio 2.73 [95% confidence interval 1.28-5.82]), were identified as independent risk factors for malignancies, whereas acoustic shadow resulted in an independent protective factor (odds ratio 0.39 [95% confidence interval 0.19-0.82[). The model, which included age as a continuous variable and lesion diameter as a dichotomized variable (cut-off 81 mm), provided the best area under the curve (0.87 [95% confidence interval 0.82-0.91]). A risk class system was developed, and patients were classified as low-risk (predictive model value <0.39%: 0/606 malignancies, risk 0%), intermediate risk (predictive model value 0.40%-2.2%: 9/1093 malignancies, risk 0.8%), high risk (predictive model value ≥2.3%: 43/566 malignancies, risk 7.6%).
The preoperative 3-class diagnostic algorithm and risk class system can stratify women according to risk of malignancy. Our findings, if confirmed in a multicenter study, will permit differentiation between benign and mesenchymal uterine malignancies allowing a personalized clinical approach.
鉴别子宫良性平滑肌肿瘤与恶性对应肿瘤具有挑战性。
评估一种基于临床和超声的算法在预测子宫间叶性恶性肿瘤（包括恶性潜能不确定的平滑肌肿瘤）方面的准确性。
我们报告了一项观察性、前瞻性、单中心研究的12个月随访结果，该研究纳入了超声检查发现至少有1个肌层病变≥3 cm的女性。这些患者根据一种三级诊断算法进行分类，采用症状和超声特征。“白色”患者进行为期2年的年度电话随访，“绿色”患者在6个月、12个月和24个月时进行临床和超声随访，“橙色”患者接受手术。我们进一步开发了一个风险分类系统来分层恶性风险。
共纳入2268名女性，目标病变在2158名（95.1%）患者中被分类为良性，在58名（2.6%）患者中被分类为其他恶性肿瘤，在52名（2.3%）患者中被分类为子宫间叶性恶性肿瘤。在多变量分析中，年龄（比值比1.05 [95%置信区间1.03 - 1.07]）、肿瘤直径>8 cm（比值比5.92 [95%置信区间2.87 - 12.24]）、边缘不规则（比值比2.34 [95%置信区间1.09 - 4.98]）、彩色评分 = 4（比值比2.73 [95%置信区间1.28 - 5.82]）被确定为恶性肿瘤的独立危险因素，而声影是一个独立的保护因素（比值比0.39 [95%置信区间0.19 - 0.82]）。该模型将年龄作为连续变量，病变直径作为二分变量（截断值81 mm），提供了最佳的曲线下面积（0.87 [95%置信区间0.82 - 0.91]）。开发了一个风险分类系统，患者被分类为低风险（预测模型值<0.39%：0/606例恶性肿瘤，风险0%）、中度风险（预测模型值0.40% - 2.2%：9/1093例恶性肿瘤，风险0.8%）、高风险（预测模型值≥2.3%：43/566例恶性肿瘤，风险7.6%）。
术前三级诊断算法和风险分类系统可根据恶性风险对女性进行分层。我们的研究结果若在多中心研究中得到证实，将有助于区分子宫良性和间叶性恶性肿瘤，从而实现个性化的临床治疗方法。
