Evidence map›Paper›PMID 42143259›Full record

ArticleBMC medical imaging2026

A nomogram based on body composition and the prognostic nutritional index to predict early postoperative complications of colorectal cancer.

Ning Zhu, Yan Liu, Hongqing Yu, Jingya Xu, Yi Wei, Jian Zhai

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Article in BMC medical imaging, 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

Authors and funding

6 authors.

Ning ZhuRadiology Department, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, 241001, China.
Yan LiuRadiology Department, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, 241001, China.
Hongqing YuRadiology Department, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, 241001, China.
Jingya XuRadiology Department, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, 241001, China.
Yi WeiRadiology Department, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, 241001, China.
Jian Zhai *Radiology Department, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, 241001, China. yjszhaij@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to construct a nomogram based on body composition parameters and the prognostic nutritional index (PNI) using quantitative computed tomography (QCT) to predict early postoperative complications in patients with colorectal cancer (CRC). MATERIALS AND

methodsWe retrospectively analyzed the data of 157 patients who underwent radical resection for CRC between January 2019 and April 2024. All patients underwent QCT 1 month prior to surgery. Body composition was assessed at the level of the third lumbar vertebra, including measurements of the visceral fat area, subcutaneous fat area, and intramuscular fat infiltration (MFI) of the posterior vertebral muscles. The visceral-to-subcutaneous fat ratio (VSR) was calculated.

resultsAmong the 157 patients, 31 (19.7%) experienced early postoperative complications. Univariate analysis revealed that the PNI, albumin level, VSR, and MFI were significantly associated with these complications. Multivariate logistic regression analysis identified the PNI (odds ratio [OR] = 0.801; 95% confidence interval (CI): 0.653-0.983), VSR (OR = 3.084; 95% CI: 1.365-6.968), and MFI (OR = 1.074; 95% CI: 1.009-1.145) as independent risk factors for early postoperative complications in CRC. The areas under the receiver operating characteristic curves for the PNI, VSR, MFI, and nomogram model for predicting postoperative complications were 0.796, 0.798, 0.648, and 0.879, respectively. Based on these three independent risk factors, the nomogram demonstrated good discrimination, calibration, goodness of fit, and clinical utility.

conclusionsThe nomogram model utilizing QCT-based body composition metrics and the PNI exhibited strong predictive capability for early postoperative complications in patients with CRC.

Indexed as

Body CompositionColorectal NeoplasmsNomogramsNutrition AssessmentPostoperative ComplicationsAgedColorectal Surgical ProceduresFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorsTomography, X-Ray ComputedColorectal cancerComplicationsNomogramPrognostic nutritional indexQuantitative computed tomography

Identifiers

PMID42143259
PMCPMC13348456

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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.