“Atypical Glandular Cells” on Cervical Cytology: Correlation Between Glandular Cell Component Volume and Histological Follow‐Up

Higher GCC volumes may influence AGC diagnoses, even in cases lacking true cytologic atypia, potentially leading to unnecessary interventions. Greater awareness of this tendency and adherence to established cytologic criteria may improve diagnostic precision within the AGC category.

Authors

Institutions

Publication Details

Journal
Diagnostic Cytopathology
Published
2025-10-20
DOI
https://doi.org/10.1002/dc.70033
Primary Topic
Cervical Cancer and HPV Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

“Atypical Glandular Cells” on Cervical Cytology: Correlation Between Glandular Cell Component Volume and Histological Follow‐Up

Alessa Aragão, Havva Gökce Terzioglu, Julieta E. Barroeta
Diagnostic Cytopathology
Cervical Cancer and HPV Research
article

“Atypical Glandular Cells” on Cervical Cytology: Correlation Between Glandular Cell Component Volume and Histological Follow‐Up

Alessa Aragão, Havva Gökce Terzioglu, Julieta E. Barroeta
article en

Abstract

Higher GCC volumes may influence AGC diagnoses, even in cases lacking true cytologic atypia, potentially leading to unnecessary interventions. Greater awareness of this tendency and adherence to established cytologic criteria may improve diagnostic precision within the AGC category.

Diagnostic CytopathologyVol. 54(2)
Loyola University Medical Center (US), University of Chicago (US)
Openalex Percentile: Top 60%
Cervical Cancer and HPV Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.