Evidence map›Paper›PMID 42434286›Full record

ArticleJournal of gastrointestinal oncology2026

Development of a multivariable prediction model for tumor response and treatment tolerance based on body composition dynamics in rectal cancer undergoing neoadjuvant chemoradiotherapy.

Soohyeon Lee, Dong Hyun Kang, Tae Sung Ahn

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Article in Journal of gastrointestinal oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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3 authors.

Soohyeon LeeDepartment of Surgery, College of Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea.ORCID https://orcid.org/0000-0002-6423-4434
Dong Hyun KangDepartment of Surgery, College of Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea.
Tae Sung AhnDepartment of Surgery, College of Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The treatment paradigm for locally advanced rectal cancer (LARC) is evolving toward total neoadjuvant therapy (TNT), emphasizing strategies to maximize tumor regression and enable organ preservation. Identifying host-related biomarkers that predict response to neoadjuvant chemoradiotherapy (CRT) has therefore become increasingly important. Although body composition has been associated with cancer prognosis, the distinct roles of skeletal muscle and adipose tissue dynamics in treatment tolerance and tumor response remain unclear. This study aimed to develop a multivariable prediction model for tumor response and treatment tolerance based on body composition dynamics during CRT. Methods: In this single-center retrospective cohort study conducted at a tertiary referral hospital, 138 patients with LARC who underwent neoadjuvant CRT were analyzed. Baseline and post-CRT body composition parameters (skeletal muscle and adipose indices at the L3 level) and clinicolaboratory variables were evaluated as predictors. The primary outcome was high TRG (tumor regression grade 3-4), and the secondary outcome was CRT-related adverse events (CRT-AEs). A multivariable logistic regression model was developed, with continuous variables standardized. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) and decision curve analysis. Internal validation was performed using 1,000 bootstrap resamples. Results: High TRG was observed in 33.3% of patients. Multivariable analysis demonstrated that the absence of CRT-AEs, higher baseline subcutaneous fat index, and a smaller reduction in visceral fat during CRT were independently associated with high TRG (all P<0.05). In contrast, a greater reduction in skeletal muscle index (ΔSMI) during CRT was significantly associated with CRT-AEs. The prediction model incorporating these variables showed moderate discriminative performance (AUC =0.707; 95% CI: 0.619-0.794). Conclusions: Body composition appears to play compartment-specific roles during neoadjuvant CRT in rectal cancer. Skeletal muscle status primarily reflects treatment tolerance, whereas adipose tissue dynamics are more closely associated with tumor regression. These computed tomography (CT)-based metrics may serve as practical, noninvasive indicators to support risk stratification and personalized treatment strategies in the era of TNT.

Indexed as

body compositionneoadjuvant chemoradiotherapy (neoadjuvant CRT)Rectal cancer (RC)treatment-related adverse eventstumor regression grade (TRG)

Identifiers

PMID42434286
PMCPMC13350587

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.