Gynecologic Oncology Center, Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Apolinarska 18, Prague 2, 12800, Czech Republic.
Department of Pathology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Studnickova 2, Prague 2, 12800, Czech Republic.
Br J Cancer. 2021 Mar;124(6):1121-1129. doi: 10.1038/s41416-020-01204-w. Epub 2020 Dec 14.
Models predicting recurrence risk (RR) of cervical cancer are used to tailor adjuvant treatment after radical surgery. The goal of our study was to compare available prognostic factors and to develop a prognostic model that would be easy to standardise and use in routine clinical practice.
All consecutive patients with early-stage cervical cancer treated by primary surgery in a single referral centre (01/2007-12/2016) were eligible if assessed by standardised protocols for pre-operative imaging and pathology. Fifteen prognostic markers were evaluated in 379 patients, out of which 320 lymph node (LN)-negative.
The best predictive model for the whole cohort entailed a combination of tumour-free distance (TFD) ≤ 3.5 mm and LN positivity, which separated two subgroups with a substantially distinct RR 36% and 6.5%, respectively. In LN-negative patients, a combination of TFD ≤ 3.5 mm and adenosquamous tumour type separated a group of nine patients with RR 33% from the rest of the group with 6% RR.
A newly identified prognostic marker, TFD, surpassed all traditional tumour-related markers in the RR assessment. Predictive models combining TFD, which can be easily accessed on pre-operative imaging, with LN status or tumour type can be used in daily practice and can help to identify patients with the highest RR.
预测宫颈癌复发风险(RR)的模型用于为根治性手术后的辅助治疗提供依据。我们的研究目的是比较现有的预后因素,并建立一个易于标准化且可在常规临床实践中使用的预后模型。
所有在单一转诊中心接受根治性手术治疗的早期宫颈癌患者(2007 年 1 月至 2016 年 12 月),如果术前影像学和病理学检查符合标准化方案,均符合入选条件。对 379 例患者的 15 个预后标志物进行了评估,其中 320 例为淋巴结(LN)阴性。
整个队列的最佳预测模型是将肿瘤无复发生存距离(TFD)≤3.5mm 和 LN 阳性相结合,这将两个 RR 显著不同的亚组分开,分别为 36%和 6.5%。在 LN 阴性患者中,将 TFD≤3.5mm 和腺鳞癌类型相结合,将 9 例 RR 为 33%的患者与其余 RR 为 6%的患者区分开来。
新发现的 TFD 预后标志物在 RR 评估中超过了所有传统的肿瘤相关标志物。将 TFD 与 LN 状态或肿瘤类型相结合的预测模型可用于日常实践,可以帮助识别 RR 最高的患者。