1
Return

A Nomogram Combining Body Composition Analysis and Clinical Factors for Predicting the Prognosis of Patients with Resectable Rectal Cancer

delete2026-04-03
delete0
PRE
AI
S
Sun, Mingjie
W
Wei, Longyu
W
Wang, Aoyang
G
Gao, Fei *
DOI:10.1007/s11220-026-00753-3delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
To investigate the value of quantitative computed tomography (QCT) body composition parameters in assessing the prognosis of patients with resectable rectal cancer (RC). A total of 94 patients with colorectal adenocarcinoma from 2016 to 2021 were retrospectively collected. All patients underwent QCT scan before operation. Skeletal muscle cross-sectional area, total fat area, subcutaneous fat area and visceral fat area were measured, and skeletal muscle index (SMI), total fat tissue index (TATI), subcutaneous fat index (SATI) and visceral fat index (VATI) were calculated. TATI, SATI, and VATI truncation values were obtained to predict postoperative outcomes in RC patients, and sarcopenia (SA) was evaluated by SMI. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for recurrence and metastasis. A predictive nomogram was then constructed based on the multivariate regression results. The performance of the nomogram was evaluated using the calibration plots. The cut off values of TATI, SATI, and VATI were 106.39 cm(2)/m(2), 47.33 cm(2)/m(2), and 42.61 cm(2)/m(2). The overall incidence of SA was 30.0% (28/94). Tumor N-stage, SA, and VATI were independent risk factors for postoperative outcomes in RC patients (P < 0.05). The AUC of the nomogram model was 0.844 (95% CI: 0.755-0.911). Tumor N-stage, SA, and VATI correlated with prognosis in RC patients undergoing surgery. The nomogram model established in this study has some value for evaluating the prognosis of patients with resectable RC.
Keywords:
Rectal cancer
Nomogram
Quantitative CT
Body composition analysis
Recurrence and metastasis
Sarcopenia

Journal

S
Sensing and Imaging
IF:
2
Papers:
103
Citations:
618

Organization

S
shanghai jiao tong university
Scholars:
15.1W
Papers: 11.5W
Citations: 159
U
university of science & technology of china, cas
Scholars:
3.2W
Papers: 2.7W
Citations: 74
W
wannan medical college
Scholars:
858
Papers: 254
Citations: 0
C
chinese academy of sciences
Scholars:
54.9W
Papers: 44.5W
Citations: 703
Cited Papers

Cited Papers

Citing Papers

Citing Papers