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基于 2018 年 FIGO 分期的同步放化疗加或不加辅助化疗治疗局部晚期宫颈癌的生存预测列线图:一项回顾性分析。

Nomogram for Predicting Survival in Locally Advanced Cervical Cancer with Concurrent Chemoradiotherapy plus or Not Adjuvant Chemotherapy: A Retrospective Analysis Based on 2018 FIGO Staging.

机构信息

Department of Oncology, the Forth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.

出版信息

Cancer Biother Radiopharm. 2024 Nov;39(9):690-705. doi: 10.1089/cbr.2023.0199. Epub 2024 Jun 3.

Abstract

The comprehensive treatment mode of combining concurrent chemoradiotherapy (CCRT) with adjuvant chemotherapy (AC) is a commonly used mainstream model in the clinical practice of locally advanced cervical cancer (LACC). However, the necessity for AC after CCRT lacks sufficient evidence-based medical support. This study constructs a predictive model for the survival time dependence of CCRT ± AC for LACC based on the 2018 International Federation of Gynecology and Obstetrics (FIGO) staging with internal validation, the prognosis was assessed with intensity-modulated radiotherapy (IMRT) and concurrent cisplatin, and provides guidance for future stratified treatment. The retrospective analysis included 482 patients with LACC who CCRT from January 2016 to January 2023. Patients who used the 2009 FIGO staging were all standardized for the 2018 FIGO staging. The 482 patients with LACC were divided into a training set ( = 290) and a validation set ( = 192) at a ratio of 6:4. COX multivariate regression model and LASSO regression were used to screen for independent prognostic factors affecting progression-free survival (PFS) and overall survival (OS), and a nomogram clinical prediction model was constructed based on these factors. Evaluate the effectiveness of the model through the receiver operating characteristic curve, calibration curve, decision curve, risk heat map, and survival curves for risk stratification. The PFS and OS independent prognostic risk factors affecting the 2018 FIGO staging of LACC during CCRT were validated to be similar to the 2009 FIGO staging prediction model reported in previous literature. In the training cohort, area under the curve (AUC) values at 1, 3, and 5 years were 0.941, 0.882, and 0.885 for PFS, and 0.946, 0.946, and 0.969 for OS, respectively. When applied to a test cohort, the model also showed accurate prediction result (AUC at 1, 3, and 5 years were 0.869, 0.891, and 0.899 for PFS, and 0.891, 0.941 and 0.878 for OS, respectively). Subgroup analysis suggests that patients with LACC, adenocarcinoma, stage IVA, pelvic lymph node metastasis, pretreatment hemoglobin ≤100 g/l and residual tumor diameter >2 cm, who received CCRT in the 2018 FIGO stage, may benefit more from adjuvant chemtherapy. Based on the 2018 FIGO staging, a nomogram prediction model for PFS and OS in patients with LACC undergoing CCRT was developed. The model, established by combining weighted clinical and pathological factors, can provide more personalized treatment predictions in clinical practice. For patients with high-risk factors such as residual tumor diameter > 2 cm after CCRT for LACC, AC may bring benefits.

摘要

联合同期放化疗(CCRT)和辅助化疗(AC)的综合治疗模式是局部晚期宫颈癌(LACC)临床实践中常用的主流模式。然而,CCRT 后接受 AC 的必要性缺乏充分的循证医学支持。本研究基于 2018 年国际妇产科联合会(FIGO)分期构建了一个用于预测 LACC 患者接受 CCRT±AC 后生存时间的模型,并进行了内部验证,使用调强放疗(IMRT)和顺铂同步进行预后评估,并为未来的分层治疗提供指导。回顾性分析了 2016 年 1 月至 2023 年 1 月期间接受 CCRT 的 482 例 LACC 患者。所有使用 2009 年 FIGO 分期的患者均按 2018 年 FIGO 分期进行标准化。482 例 LACC 患者按 6:4 的比例分为训练集(=290)和验证集(=192)。使用 COX 多变量回归模型和 LASSO 回归筛选影响无进展生存期(PFS)和总生存期(OS)的独立预后因素,并基于这些因素构建列线图临床预测模型。通过受试者工作特征曲线、校准曲线、决策曲线、风险热图和生存曲线进行风险分层评估模型的有效性。对 2018 年 FIGO 分期 LACC 患者在 CCRT 期间影响 PFS 和 OS 的独立预后风险因素进行验证,结果与之前文献报道的 2009 年 FIGO 分期预测模型相似。在训练队列中,PFS 的 AUC 值在 1、3 和 5 年时分别为 0.941、0.882 和 0.885,OS 的 AUC 值在 1、3 和 5 年时分别为 0.946、0.946 和 0.969。当应用于测试队列时,该模型也表现出准确的预测结果(PFS 的 AUC 值在 1、3 和 5 年时分别为 0.869、0.891 和 0.899,OS 的 AUC 值在 1、3 和 5 年时分别为 0.891、0.941 和 0.878)。亚组分析表明,在 2018 年 FIGO 分期中,接受 CCRT 的 LACC 患者、腺癌、IVA 期、盆腔淋巴结转移、治疗前血红蛋白≤100g/L 和残余肿瘤直径>2cm,可能从辅助化疗中获益更多。基于 2018 年 FIGO 分期,为接受 CCRT 的 LACC 患者建立了一个用于预测 PFS 和 OS 的列线图预测模型。该模型通过结合加权临床和病理因素建立,可以在临床实践中提供更个性化的治疗预测。对于 LACC 患者 CCRT 后残余肿瘤直径>2cm 等高危因素的患者,AC 可能带来获益。

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