Predicting Local Recurrence in <scp>T3</scp> Laryngeal Squamous Cell Carcinoma: An Analysis of Tumor Volume and Cartilage Invasion Prior to Radiotherapy

The results demonstrate that a larger tumor volume correlates with a reduced treatment response for patients with T3 LSCC treated with RT or CRT.

Authors

Institutions

Publication Details

Journal
Cancer Medicine
Published
2025-12-26
DOI
https://doi.org/10.1002/cam4.71500
Primary Topic
Head and Neck Cancer Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting Local Recurrence in T3 Laryngeal Squamous Cell Carcinoma: An Analysis of Tumor Volume and Cartilage Invasion Prior to Radiotherapy

Lalle Hammarstedt‐Nordenvall, A. Makitie, Sara Jonmarker Jaraj, Rasmus Blomkvist et al.
Cancer Medicine
Head and Neck Cancer Studies
article

Predicting Local Recurrence in T3 Laryngeal Squamous Cell Carcinoma: An Analysis of Tumor Volume and Cartilage Invasion Prior to Radiotherapy

Lalle Hammarstedt‐Nordenvall, A. Makitie, Sara Jonmarker Jaraj, Rasmus Blomkvist, Eivind Gottlieb‐Vedi, Björn Palmgren, Linda Marklund
article en

Abstract

The results demonstrate that a larger tumor volume correlates with a reduced treatment response for patients with T3 LSCC treated with RT or CRT.

Cancer MedicineVol. 15(1)
Uppsala University (SE), Karolinska University Hospital (SE), University of Helsinki (FI), Helsinki University Hospital (FI)
Finska Läkaresällskapet, Stiftelsen Acta Oto-Laryngologica
Good health and well-being
Openalex Percentile: Top 27%
Head and Neck Cancer Studies
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.