Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer.
Adenocarcinoma
Cervical cancer
FIGO 2018
Magnetic resonance imaging
Prognostic markers
Sedlis criteria
Journal
Gynecologic oncology
ISSN: 1095-6859
Titre abrégé: Gynecol Oncol
Pays: United States
ID NLM: 0365304
Informations de publication
Date de publication:
26 Dec 2023
26 Dec 2023
Historique:
received:
01
11
2023
revised:
13
12
2023
accepted:
16
12
2023
medline:
28
12
2023
pubmed:
28
12
2023
entrez:
27
12
2023
Statut:
aheadofprint
Résumé
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. 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. 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). 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.
Identifiants
pubmed: 38150835
pii: S0090-8258(23)01621-9
doi: 10.1016/j.ygyno.2023.12.014
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
110-117Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors report no conflict of interest.