Department of Research and Development, Netherlands Comprehensive Cancer Organization (IKNL), Utrecht, the Netherlands; Department of Obstetrics and Gynecology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands.
Department of Research and Development, Netherlands Comprehensive Cancer Organization (IKNL), Utrecht, the Netherlands.
Cancer Epidemiol. 2021 Dec;75:102008. doi: 10.1016/j.canep.2021.102008. Epub 2021 Sep 9.
To identify clinicopathologic factors predictive of early relapse (platinum-free interval (PFI) of ≤6 months) in advanced epithelial ovarian cancer (EOC) in first-line treatment, and to develop and internally validate risk prediction models for early relapse.
All consecutive patients diagnosed with advanced stage EOC between 01-01-2008 and 31-12-2015 were identified from the Netherlands Cancer Registry. Patients who underwent cytoreductive surgery and platinum-based chemotherapy as initial EOC treatment were selected. Two prediction models, i.e. pretreatment and postoperative, were developed. Candidate predictors of early relapse were fitted into multivariable logistic regression models. Model performance was assessed on calibration and discrimination. Internal validation was performed through bootstrapping to correct for model optimism.
A total of 4,557 advanced EOC patients were identified, including 1,302 early relapsers and 3,171 late or non-relapsers. Early relapsers were more likely to have FIGO stage IV, mucinous or clear cell type EOC, ascites, >1 cm residual disease, and to have undergone NACT-ICS. The final pretreatment model demonstrated subpar model performance (AUC = 0.64 [95 %-CI 0.62-0.66]). The final postoperative model based on age, FIGO stage, pretreatment CA-125 level, histologic subtype, presence of ascites, treatment approach, and residual disease after debulking, demonstrated adequate model performance (AUC = 0.72 [95 %-CI 0.71-0.74]). Bootstrap validation revealed minimal optimism of the final postoperative model.
A (postoperative) discriminative model has been developed and presented online that predicts the risk of early relapse in advanced EOC patients. Although external validation is still required, this prediction model can support patient counselling in daily clinical practice.
确定预测一线治疗中晚期上皮性卵巢癌(EOC)早期复发(无铂间隔(PFI)≤6 个月)的临床病理因素,并建立和内部验证早期复发的风险预测模型。
从荷兰癌症登记处确定了所有在 2008 年 1 月 1 日至 2015 年 12 月 31 日期间诊断为晚期 EOC 的连续患者。选择接受细胞减灭术和铂类化疗作为初始 EOC 治疗的患者。建立了两种预测模型,即预处理和手术后。将早期复发的候选预测因子拟合到多变量逻辑回归模型中。通过自举法评估模型的校准和区分能力,以纠正模型的乐观性。
共确定了 4557 例晚期 EOC 患者,其中 1302 例为早期复发患者,3171 例为晚期或非复发患者。早期复发者更有可能患有FIGO 分期 IV 期、黏液性或透明细胞型 EOC、腹水、>1cm 残余疾病,并且接受过新辅助化疗-间歇性肿瘤细胞减灭术(NACT-ICS)。最终的预处理模型显示出较差的模型性能(AUC=0.64[95%CI 0.62-0.66])。最终基于年龄、FIGO 分期、预处理 CA-125 水平、组织学亚型、腹水存在、治疗方法和肿瘤减灭术后残余疾病的术后模型显示出较好的模型性能(AUC=0.72[95%CI 0.71-0.74])。自举验证表明最终术后模型的优化程度较低。
已经开发并在线提供了一个(术后)有区分能力的模型,用于预测晚期 EOC 患者早期复发的风险。尽管仍需要外部验证,但该预测模型可以支持日常临床实践中的患者咨询。