NDLI: Using Silva pattern system to predict prognosis and plan treatment of invasive endocervical adenocarcinoma: a single-center retrospective analysis

Content Provider	Springer Nature : BioMed Central
Author	Li, Xiao Pang, Shujie Shen, Yan Qu, Pengpeng
Abstract	Background This study evaluated the prognostic value of the Silva pattern system for invasive endocervical adenocarcinoma (EAC) by analysing its association with clinical and pathological features to provide more appropriate clinical management. Methods A retrospective analysis including 63 patients with pathological diagnosis of invasive EAC was performed from March 2011 to December 2016 at our hospital. All pathological slides were reviewed by three senior pathologists, and cases were stratified into patterns A, B, or C by consensus according to the Silva pattern system criteria. Clinicopathological characteristics and follow-up of the three Silva subgroups were analysed. Results Silva A, B, and C EAC patients were compared based on tumour size, clinical stage, lymphovascular invasion (LVI), and depth of invasion (DOI). The differences were found to be statistically significant (p < 0.01). There was no statistically significant difference in the proportion of lymph node metastasis among the three groups (p > 0.05) or in the recurrence and mortality rates of patients with Silva A, B, and C EAC (p > 0.05). Single factor analysis showed that tumour size, clinical stage, lymph node metastasis, LVI, and DOI were related to postoperative recurrence, whereas age, Silva classification, and postoperative recurrence were not correlated. Conclusion The Silva classification system can predict lymph node status and prognosis of invasive EAC, but it cannot be used as an independent indicator. Individualized treatment plans should be adopted for patients with EAC.
Related Links	https://bmcwomenshealth.biomedcentral.com/counter/pdf/10.1186/s12905-022-02090-5.pdf
Ending Page	9
Page Count	9
Starting Page	1
File Format	HTM / HTML
ISSN	14726874
DOI	10.1186/s12905-022-02090-5
Journal	BMC Women's Health
Issue Number	1
Volume Number	22
Language	English
Publisher	BioMed Central
Publisher Date	2022-12-02
Access Restriction	Open
Subject Keyword	Gynecology Maternal and Child Health Reproductive Medicine Classification system Invasive endocervical adenocarcinoma Lymph node metastasis Pattern-based Risk stratification
Content Type	Text
Resource Type	Article
Subject	Obstetrics and Gynecology Reproductive Medicine
Journal Impact Factor	2.4/2023
5-Year Journal Impact Factor	2.9/2023

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