Identification of low-risk cases of invasive endocervical adenocarcinoma with Silva pattern-based classification: a systematic review and

Nikita Sinha, Olivia D Lara, Kimberly Dessources, Emily P Jones, Leslie H Clark, Russell Broaddus, Benjamin B Albright

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Article in Gynecologic oncology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Nikita SinhaDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.

Olivia D LaraDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.

Kimberly DessourcesDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.

Emily P JonesHealth Sciences Library, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Leslie H ClarkDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.

Russell BroaddusDepartment of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC, USA.

Benjamin B AlbrightDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We aimed to describe the discriminatory ability of the Silva pattern-based classification system for invasive endocervical adenocarcinoma (EAC) in predicting risks of lymph node (LN) metastasis, recurrence, and death. Method: We systematically searched PubMed, Scopus, and Embase through 2024 for manuscripts describing patients with EAC by Silva pattern-based classification. We included studies reporting outcomes of LN metastasis, recurrence, or death by Silva pattern. Random-effects Results: We identified 19 studies including 2998 patients (20.8 % pattern A, 23.1 % pattern B, 54.1 % pattern C). Silva pattern A cases showed a significantly lower risk of LN metastasis (3/509; 0.6 %) than pattern B (6.1 %; OR = 0.33, 95 %CI 0.16-0.67) or pattern C (22.0 %; OR = 0.09; 95 %CI 0.05-0.16). Across 5 studies limited to stage I disease, there were no Silva pattern A cases with LN metastasis, recurrence, or death. Among 11 studies reporting on recurrence and death, Silva pattern A cases had distinctly low risk of 0.3 % for both outcomes, including a significantly lower risk of recurrence (OR = 0.15, 95 %CI 0.06-0.34) and death (OR = 0.21, 95 %CI 0.09-0.50) versus patterns B/C. Silva pattern B cases showed significantly lower risk of all outcomes compared with pattern C. Conclusions: We demonstrate that Silva classification is highly predictive of oncologic outcomes for EAC, with patterns A, B, and C showing distinct low, intermediate, and high risk profiles. The low risk profile of pattern A may justify future prospective study of surgical and adjuvant treatment de-escalation from the current standard of care, while pattern C cases may warrant consideration of adjuvant treatment escalation.

Indexed as

Endocervical adenocarcinomaLymph node metastasisPathologySilva classification systemSilva pattern of invasion

Identifiers

PMID40491861

DOI10.1016/j.gore.2025.101764

PMCPMC12145998

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