Comparison of clinical outcomes and quality of life for robotic versus laparoscopic surgery in elderly patients with mid-low rectal cancer: a multicenter cohort study with inverse probability of treatment weighting analysis

Background: The rising incidence of rectal cancer (RC) in elderly patients contrasts with the scarcity of robust evidence comparing robotic-assisted and laparoscopic resection in this population. This study evaluated clinical outcomes and quality-of-life (QoL) metrics between these approaches in elderly patients with mid-low RC. Methods: Consecutive patients aged 70 years or older with mid-low RC who underwent minimally invasive resection at two tertiary centers from January 2017 to December 2024 were categorized into robotic (n=211) and laparoscopic (n=812) cohorts. Outcomes were analyzed using inverse probability of treatment weighting (IPTW) based on propensity scores. Results: < 0.05). For patients with T4 stage tumors, the robotic approach demonstrated superior cancer-specific survival compared to laparoscopy, a benefit that was maintained after IPTW. Conclusions: Robotic-assisted surgery is a safe and feasible alternative for elderly patients with mid-low RC, offering reduced perioperative complications, superior functional preservation, and potential CSS benefits in T4 disease.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2026-04-21
DOI
https://doi.org/10.3389/fonc.2026.1809161
Primary Topic
Colorectal Cancer Surgical Treatments
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Comparison of clinical outcomes and quality of life for robotic versus laparoscopic surgery in elderly patients with mid-low rectal cancer: a multicenter cohort study with inverse probability of treatment weighting analysis

Chenhao Hu, Junjun She, Zhigang Wu, Feiyu Shi et al.
Frontiers in Oncology
Colorectal Cancer Surgical Treatments
article

Comparison of clinical outcomes and quality of life for robotic versus laparoscopic surgery in elderly patients with mid-low rectal cancer: a multicenter cohort study with inverse probability of treatment weighting analysis

Chenhao Hu, Junjun She, Zhigang Wu, Feiyu Shi, Yujie Li, K X Wang, Guanghui Wang, Lin Wang, Chao Yin, Lei Zhang
article en

Abstract

Background: The rising incidence of rectal cancer (RC) in elderly patients contrasts with the scarcity of robust evidence comparing robotic-assisted and laparoscopic resection in this population. This study evaluated clinical outcomes and quality-of-life (QoL) metrics between these approaches in elderly patients with mid-low RC. Methods: Consecutive patients aged 70 years or older with mid-low RC who underwent minimally invasive resection at two tertiary centers from January 2017 to December 2024 were categorized into robotic (n=211) and laparoscopic (n=812) cohorts. Outcomes were analyzed using inverse probability of treatment weighting (IPTW) based on propensity scores. Results: < 0.05). For patients with T4 stage tumors, the robotic approach demonstrated superior cancer-specific survival compared to laparoscopy, a benefit that was maintained after IPTW. Conclusions: Robotic-assisted surgery is a safe and feasible alternative for elderly patients with mid-low RC, offering reduced perioperative complications, superior functional preservation, and potential CSS benefits in T4 disease.

Frontiers in OncologyVol. 16
First Affiliated Hospital of Xi'an Jiaotong University (CN)
Natural Science Foundation of Shaanxi Province
Openalex Percentile: Top 21%
Colorectal Cancer Surgical Treatments
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.