Department of Cancer and Surgery, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0HS, UK.
Br J Cancer. 2013 Jun 25;108(12):2448-54. doi: 10.1038/bjc.2013.224. Epub 2013 May 14.
Correct characterisation of ovarian tumours is critical to optimise patient care. The purpose of this study is to evaluate the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) logistic regression model (LR2), ultrasound Simple Rules (SR), the Risk of Malignancy Index (RMI) and subjective assessment (SA) for preoperative characterisation of adnexal masses, when ultrasonography is performed by examiners with different background training and experience.
A 2-year prospective multicentre cross-sectional study. Thirty-five level II ultrasound examiners contributed in three UK hospitals. Transvaginal ultrasonography was performed using a standardised approach. The final outcome was the surgical findings and histological diagnosis. To characterise the adnexal masses, the six-variable prediction model (LR2) with a cutoff of 0.1, the RMI with cutoff of 200, ten SR (five rules for malignancy and five rules for benignity) and SA were applied. The area under the curves (AUCs) for performance of LR2 and RMI were calculated. Diagnostic performance measures for all models assessed were sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and the diagnostic odds ratio (DOR).
Nine-hundred and sixty-two women with adnexal masses underwent transvaginal ultrasonography, whereas 255 had surgery. Prevalence of malignancy was 29% (49 primary invasive epithelial ovarian cancers, 18 borderline ovarian tumours, and 7 metastatic tumours). The AUCs for LR2 and RMI for all masses were 0.94 (95% confidence interval (CI): 0.89-0.97) and 0.90 (95% CI: 0.83-0.94), respectively. In premenopausal women, LR2-RMI difference was 0.09 (95% CI: 0.03-0.15) compared with -0.02 (95% CI: -0.08 to 0.04) in postmenopausal women. For all masses, the DORs for LR2, RMI, SR+SA (using SA when SR inapplicable), SR+MA (assuming malignancy when SR inapplicable), and SA were 62 (95% CI: 27-142), 43 (95% CI: 19-97), 109 (95% CI: 44-274), 66 (95% CI: 27-158), and 70 (95% CI: 30-163), respectively.
Overall, the test performance of IOTA prediction models and rules as well as the RMI was maintained in examiners with varying levels of training and experience.
准确描述卵巢肿瘤对于优化患者护理至关重要。本研究旨在评估国际卵巢肿瘤分析（IOTA）逻辑回归模型（LR2）、超声简单规则（SR）、风险恶性指数（RMI）和主观评估（SA）在不同背景培训和经验的超声医师进行术前附件肿块特征描述时的诊断性能。
这是一项为期 2 年的前瞻性多中心横断面研究。35 名二级超声医师在英国的 3 家医院参与。经阴道超声检查采用标准化方法进行。最终结果是手术发现和组织学诊断。为了描述附件肿块，应用了具有 0.1 截断值的六变量预测模型（LR2）、截断值为 200 的 RMI、10 个 SR（5 个恶性规则和 5 个良性规则）和 SA。计算了 LR2 和 RMI 性能的曲线下面积（AUC）。评估了所有模型的诊断性能指标，包括敏感性、特异性、阳性和阴性似然比（LR+和 LR-）以及诊断比值比（DOR）。
962 名患有附件肿块的女性接受了经阴道超声检查，其中 255 名接受了手术。恶性肿瘤的患病率为 29%（49 例原发性侵袭性上皮性卵巢癌、18 例交界性卵巢肿瘤和 7 例转移性肿瘤）。LR2 和 RMI 对所有肿块的 AUC 分别为 0.94（95%置信区间（CI）：0.89-0.97）和 0.90（95%CI：0.83-0.94）。在绝经前妇女中，LR2-RMI 差异为 0.09（95%CI：0.03-0.15），而绝经后妇女为-0.02（95%CI：-0.08 至 0.04）。对于所有肿块，LR2、RMI、SR+SA（当 SR 不适用时使用 SA）、SR+MA（当 SR 不适用时假设恶性）和 SA 的诊断比值比（DOR）分别为 62（95%CI：27-142）、43（95%CI：19-97）、109（95%CI：44-274）、66（95%CI：27-158）和 70（95%CI：30-163）。
总体而言，在具有不同培训和经验水平的医师中，IOTA 预测模型和规则以及 RMI 的检测性能得以维持。
