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Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer

医学 阶段(地层学) 淋巴血管侵犯 宫颈癌 接收机工作特性 放射科 肿瘤科 癌症 内科学 妇科 转移 生物 古生物学
作者
Mari K. Halle,Olivera Bozickovic,David Forsse,Kari S. Wagner‐Larsen,Rose Gold,Njål Lura,Kathrine Woie,Bjørn I. Bertelsen,Ingfrid S. Haldorsen,Camilla Krakstad
出处
期刊:Gynecologic Oncology [Elsevier]
卷期号:181: 110-117 被引量:1
标识
DOI:10.1016/j.ygyno.2023.12.014
摘要

Abstract

Objective

Assess the added prognostic value of the updated International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system, and to identify clinicopathological and radiological biomarkers for improved FIGO 2018 prognostication.

Methods

Patient data were retrieved from a prospectively collected patient cohort including all consenting patients with cervical cancer diagnosed and treated at Haukeland University Hospital during 2001–2022 (n = 948). All patients were staged according to the FIGO 2009 and FIGO 2018 guidelines based on available data for individual patients. MRI-assessed maximum tumor diameter and stromal tumor invasion, as well as histopathologically assessed lymphovascular space invasion were applied to categorize patients according to the Sedlis criteria.

Results

FIGO 2018 stage yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) (0.86 versus 0.81 for FIGO 2009) for predicting disease-specific survival. The most common stage migration in FIGO 2018 versus FIGO 2009 was upstaging from stages IB/II to stage IIIC due to suspicious lymph nodes identified by PET/CT and/or MRI. In FIGO 2018 stage III patients, extent and size of primary tumor (p = 0.04), as well as its histological type (p = 0.003) were highly prognostic. Sedlis criteria were prognostic within FIGO 2018 IB patients (p = 0.04).

Conclusions

Incorporation of cross-sectional imaging increases prognostic precision, as suggested by the FIGO 2018 guidelines. The 2018 FIGO IIIC stage could be refined by including the size and extent of primary tumor and histological type. The FIGO IB risk prediction could be improved by applying MRI-assessed tumor size and stromal invasion.
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