Identification of predictors for lymph node metastasis in T2 colorectal cancer: retrospective cohort study from a high-volume hospital

Approximately three-quarters of T2 CRC patients are likely to avoid unnecessary surgery. Female, poorly differentiated tumors, perineural invasion, and lymphovascular invasion are expected to be used as predictors of LNM in T2 CRC.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2025-04-15
DOI
https://doi.org/10.1186/s12885-025-14104-0
Citations
4
Primary Topic
Colorectal Cancer Surgical Treatments
Type
article
Field-Weighted Citation Impact
4.18
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of predictors for lymph node metastasis in T2 colorectal cancer: retrospective cohort study from a high-volume hospital

Xudong Zhao, Xu Sun, Zhiyuan Yu, Rui Li et al.
4 citations
BMC Cancer
Colorectal Cancer Surgical Treatments
4.18
article

Identification of predictors for lymph node metastasis in T2 colorectal cancer: retrospective cohort study from a high-volume hospital

Xudong Zhao, Xu Sun, Zhiyuan Yu, Rui Li, Peiyu Li
article en
4 citations

Abstract

Approximately three-quarters of T2 CRC patients are likely to avoid unnecessary surgery. Female, poorly differentiated tumors, perineural invasion, and lymphovascular invasion are expected to be used as predictors of LNM in T2 CRC.

BMC CancerVol. 25(1)
Nankai University (CN), Chinese PLA General Hospital (CN), PLA Academy of Military Science (CN)
Good health and well-being
Openalex Percentile: Top 6%
Colorectal Cancer Surgical Treatments
4.18
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.