Department of Obstetrics and Gynecology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Department of Obstetrics and Gynecology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Gynecol Oncol. 2016 Jan;140(1):22-8. doi: 10.1016/j.ygyno.2015.11.022. Epub 2015 Nov 24.
To test the ability of three prospectively developed computed tomography (CT) models to predict incomplete primary debulking surgery in patients with advanced (International Federation of Gynecology and Obstetrics stages III-IV) ovarian cancer.
Three prediction models to predict incomplete surgery (any tumor residual >1cm in diameter) previously published by Ferrandina (models A and B) and by Gerestein were applied to a validation cohort consisting of 151 patients with advanced epithelial ovarian cancer. All patients were treated with primary debulking surgery in the Eastern part of the Netherlands between 2000 and 2009 and data were retrospectively collected. Three individual readers evaluated the radiographic parameters and gave a subjective assessment. Using the predicted probabilities from the models, the area under the curve (AUC) was calculated which represents the discriminative ability of the model.
The AUC of the Ferrandina models was 0.56, 0.59 and 0.59 in model A, and 0.55, 0.60 and 0.59 in model B for readers 1, 2 and 3, respectively. The AUC of Gerestein's model was 0.69, 0.61 and 0.69 for readers 1, 2 and 3, respectively. AUC values of 0.69 and 0.63 for reader 1 and 3 were found for subjective assessment.
Models to predict incomplete surgery in advanced ovarian cancer have limited predictive ability and their reproducibility is questionable. Subjective assessment seems as successful as applying predictive models. Present prediction models are not reliable enough to be used in clinical decision-making and should be interpreted with caution.
测试三个前瞻性开发的计算机断层扫描（CT）模型预测晚期（国际妇产科联合会分期 III-IV 期）卵巢癌患者不完全肿瘤细胞减灭术的能力。
应用 Ferrandina（模型 A 和模型 B）和 Gerestein 先前发表的三个预测模型来预测不完全手术（任何肿瘤残留直径>1cm），纳入 151 例晚期上皮性卵巢癌患者的验证队列。所有患者均于 2000 年至 2009 年在荷兰东部接受初次肿瘤细胞减灭术治疗，数据为回顾性收集。三位独立读者评估影像学参数并进行主观评估。使用模型预测概率计算曲线下面积（AUC），以代表模型的判别能力。
模型 A 的 AUC 分别为读者 1、2 和 3 的 0.56、0.59 和 0.59，模型 B 的 AUC 分别为读者 1、2 和 3 的 0.55、0.60 和 0.59。Gerestein 模型的 AUC 分别为读者 1、2 和 3 的 0.69、0.61 和 0.69。读者 1 和 3 的主观评估 AUC 值分别为 0.69 和 0.63。
预测晚期卵巢癌不完全手术的模型预测能力有限，其可重复性值得怀疑。主观评估似乎与应用预测模型一样成功。目前的预测模型还不够可靠，不能用于临床决策，应谨慎解释。
