Evidence map›Paper›PMID 40379920›Full record

ArticleJournal of cancer research and clinical oncology2025

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer.

Alex Besson, Ke Cao, Ahmed Mardinli, Lara Wirth, Josephine Yeung, Rory Kokelaar, Peter Gibbs, Fiona Reid, Justin M Yeung

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Article in Journal of cancer research and clinical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Alex BessonDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.ORCID https://orcid.org/0000-0001-9134-7509
Ke CaoDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.
Ahmed MardinliDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.
Lara WirthDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.
Josephine YeungDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.
Rory KokelaarDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.
Peter GibbsWalter and Eliza Hall Institute, Parkville, Melbourne, VIC, Australia.
Fiona ReidDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.
Justin M YeungDepartment of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia. justin.yeung@unimelb.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeChemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition plays a crucial role in the pharmacokinetic and pharmacodynamic profile of cytotoxic agents and could inform optimal dosing. This study aims to assess how lumbosacral body composition influences adverse events in patients receiving neoadjuvant chemotherapy for rectal cancer.

methodsA retrospective study (February 2013 to March 2023) examined the impact of body composition on neoadjuvant treatment outcomes for rectal cancer patients. Staging CT scans were analysed using a validated AI model to measure lumbosacral skeletal muscle (SM), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue volume and density. Multivariate analyses explored the relationship between body composition and chemotherapy outcomes.

results242 patients were included (164 males, 78 Females), median age 63.4 years. Chemotherapy dose reductions occurred more frequently in females (26.9% vs. 15.9%, p = 0.042) and in females with greater VAT density (-82.7 vs. -89.1, p = 0.007) and SM: IMAT + VAT volume ratio (1.99 vs. 1.36, p = 0.042). BSA was a poor predictor of dose reduction (AUC 0.397, sensitivity 38%, specificity 60%) for female patients, whereas the SM: IMAT + VAT volume ratio (AUC 0.651, sensitivity 76%, specificity 61%) and VAT density (AUC 0.699, sensitivity 57%, specificity 74%) showed greater predictive ability. Body composition didn't influence dose adjustment of male patients.

conclusionLumbosacral body composition outperformed BSA in predicting adverse events in female patients with rectal cancer undergoing neoadjuvant chemotherapy.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsArtificial IntelligenceBody CompositionNeoadjuvant TherapyRectal NeoplasmsAdultAgedBody Surface AreaFemaleHumansImaging, Three-DimensionalMaleMiddle AgedRetrospective StudiesArtificial intelligenceBody compositionChemotherapyDose modificationRectal cancer

Identifiers

PMID40379920
PMCPMC12084224

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