Trial reportThe British journal of radiology2025
CT staging performance in an international trial of neoadjuvant chemotherapy for locally advanced colon cancer.
Trial report in The British journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07255729 (Machine Learning-Based Exosomal microRNA Signature for Preoperative Staging and Chemotherapy Eligibility in Colon Cancer), which is not on this map. Cited by 5 papers.
What it found
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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.
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.
Machine Learning-Based Exosomal microRNA Signature for Preoperative Staging and Chemotherapy Eligibility in Colon Cancer
Who cites it
5 citing papers in PubMed.
- Trial
- CT-derived extracellular volume fraction and AI-assisted body composition for predicting neoadjuvant therapy response and prognosis in colorectal cancer.Abdominal radiology (New York) · 2026Article
- Association between age and surgical resection for patients with stage II or III colorectal cancer: national study.BJS open · 2026Article
- Commentary on "Shifting Paradigm: Utilization and Outcomes with Neoadjuvant Chemotherapy for cT4 and cN2 Colon Cancers".Cancers · 2026Article
- SFTA2 reduced colorectal cancer ferroptosis promoting metastasis through regulating EMT transition by degradation of Nrf2.Food & nutrition research · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectivesIn the Fluorouracil, Oxaliplatin and Targeted Receptor pre-Operative Therapy (FOxTROT) trial, neoadjuvant chemotherapy (NAC) significantly reduced recurrence risk, compared to upfront surgery, in locally advanced colon cancer. This analysis evaluates the correlation between radiological and pathological staging within the trial to support the adoption of CT-based patient selection.
methodsIn this preplanned analysis of prospectively collected data, local radiological and pathological staging were compared in upfront surgery participants. T stage, N stage, and extramural venous invasion (EMVI) status were evaluated using overall agreement, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Subgroup analyses explored the impact of mismatch repair status and tumour side.
resultsA total of 354 participants were included. T stage agreement was 63.0%; T3 and T4 tumours were correctly identified in 78.9% and 41.1% of participants, respectively. The PPV for T3-4 status was 94.5%. N stage agreement was 39.8%; for N status (positive vs. negative), overall agreement, sensitivity, specificity, PPV, and NPV were 54.1%, 81.1%, 26.0%, 53.2%, and 57.1%, respectively. For EMVI, these values were 54.9%, 71.0%, 41.2%, 50.7%, and 62.5%, respectively. Accuracy metrics did not differ significantly by tumour side or mismatch repair status.
conclusionsCT effectively predicted T3-4 status with minimal overstaging, but performed poorly for individual T stage, N stage, and EMVI. We propose radiological T3-4 status should be adopted as the primary biomarker for neoadjuvant patient selection, with molecular biomarkers to guide treatment choice. ADVANCES IN KNOWLEDGE: In this multicentre trial, local radiologists accurately identified T3-4 status to select participants for NAC, indicating utility for future neoadjuvant trials and clinical practice.
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