Evidence map›Paper›PMID 42050465›Full record

ArticleBMC cancer2026

Computed tomography staging of colon cancer: improved patient selection for neoadjuvant therapy with combined radiologic tumor and nodal staging.

Sonia Lee, Jingjing Yu, Rony Kampalath, Otilio Castillo, Janteshpreet Sandhu, Fatemeh Tajik, Arsha Ostowari, Katharine A Kirby, Farideh H Dehkordi-Vakil, Chanon Chantaduly and 8 more

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Sonia Lee *Department of Radiology, University of California, Irvine, Orange, CA, 92868, USA.
Jingjing Yu *Department of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Rony KampalathDepartment of Radiology, University of California, Irvine, Orange, CA, 92868, USA.
Otilio CastilloDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Janteshpreet SandhuDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Fatemeh TajikDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Arsha OstowariDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Katharine A KirbyCenter for Statistical Consulting, Department of Statistics, University of California, Irvine, Irvine, CA, 92697, USA.
Farideh H Dehkordi-VakilCenter for Statistical Consulting, Department of Statistics, University of California, Irvine, Irvine, CA, 92697, USA.
Chanon ChantadulyDepartment of Radiology, University of California, Irvine, Orange, CA, 92868, USA.
Peter D ChangDepartment of Radiology, University of California, Irvine, Orange, CA, 92868, USA.
Valery VilchezDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Richard J StrakerDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Matthew D WhealonDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Smitha S KrishnamurthiDepartment of Hematology and Oncology, Cleveland Clinic, Cleveland, OH, 44195, USA.
Shishir K MaithelDepartment of Surgery, Northwestern University, Chicago, IL, 60611, USA.
Michael J StamosDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA.
Maheswari SenthilDepartment of Surgery, University of California, Irvine, 3800 Chapman Ave, Suite 7400, Orange, CA, 92868, USA. m.senthil@uci.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient selection for neoadjuvant therapy in colon cancer (CC) needs to be improved as utilizing computed tomography (CT) tumor (T) staging alone is associated with overstaging and overtreatment. Therefore, we sought to identify specific nodal imaging features that can be combined with radiologic T staging to improve patient selection.

methodsPre-operative CTs of stage I-III CC patients treated with upfront resection (2018–2023) were assessed by an expert abdominal radiologist blinded to the histopathologic staging. Radiologic T and node (N) staging based on five imaging features (single lymph node (LN) > 1 cm, ≥ 3 prominent LNs, irregular borders, heterogenous enhancement, and extramural venous invasion) were compared to the pathologic staging, grouped by proficient or deficient mismatch repair status (pMMR vs. dMMR).

resultsOf the 177 patients, 147 and 30 had pMMR and dMMR CC, respectively. The overstaging rate for pathologic T staging was 6.1% pMMR vs. 6.7% dMMR CC (p = 0.91). The overstaging rate for pathologic N disease by any imaging feature was 17.0% pMMR vs. 33.3% dMMR (p = 0.04) but improved to 4.8% pMMR vs. 6.7% dMMR (p = 0.67) with irregular borders and/or heterogenous enhancement alone. Compared to radiologic T staging only, the addition of N staging (any feature) to T staging resulted in decreased overstaging rates of stage I/low-risk stage II to high-risk stage II/III CC from 25.2% to 15.6% for pMMR CC and 60.0% to 33.3% for dMMR CC. Overstaging rates further decreased to 4.8% for pMMR and 16.7% for dMMR CC with the combination of radiologic T and N staging by irregular borders and/or heterogenous enhancement specifically.

conclusionCombining radiologic T and N stage based on any of the five imaging features resulted in lower overstaging rates than radiologic T staging alone, but overstaging rates continued to improve when only irregular borders and heterogenous enhancement were used to assess nodal disease. These results can be used as an initial framework for combining CT T and N staging for CC and improve patient selection for neoadjuvant treatment.

Indexed as

Colonic NeoplasmsLymph NodesNeoadjuvant TherapyPatient SelectionTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansLymphatic MetastasisMaleMiddle AgedNeoplasm StagingRetrospective StudiesColonic neoplasmsComputed tomographyNeoadjuvant therapyNeoplasm stagingOverstaging rate

Identifiers

PMID42050465
PMCPMC13255333

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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.