Evidence map›Paper›PMID 38836939›Full record

Trial reportEuropean radiology2024

Multivariable prognostic modelling to improve prediction of colorectal cancer recurrence: the PROSPeCT trial.

Vicky Goh, Susan Mallett, Victor Boulter, Robert Glynne-Jones, Saif Khan, Sarah Lessels, Dominic Patel, Davide Prezzi, Manuel Rodriguez-Justo, Stuart A Taylor and 18 more

Abstract readClinical TrialMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in European radiology, 2024. 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.

  1. Article
  2. Article
  3. Review
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

28 authors.

Vicky GohSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, UK. vicky.goh@kcl.ac.uk.ORCID http://orcid.org/0000-0002-2321-8091
Susan MallettCentre for Medical Imaging, Division of Medicine, University College London, London, UK.
Victor BoulterPatient Representative, Mount Vernon Cancer Centre, Northwood, UK.
Robert Glynne-JonesMount Vernon Cancer Centre, Northwood, UK.
Saif KhanResearch Department of Pathology, UCL Cancer Institute, University College London, London, UK.
Sarah LesselsScottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK.
Dominic PatelResearch Department of Pathology, UCL Cancer Institute, University College London, London, UK.
Davide PrezziSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Manuel Rodriguez-JustoResearch Department of Pathology, UCL Cancer Institute, University College London, London, UK.
Stuart A TaylorCentre for Medical Imaging, Division of Medicine, University College London, London, UK.
Richard BeableDepartment of Radiology, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
Margaret BettsDepartment of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
David J BreenDepartment of Radiology, University Hospital Southampton NHS Foundation Trust, Southampton, UK.
Ingrid BrittonDepartment of Radiology, University Hospitals North Midlands NHS Trust, Stoke-On-Trent, UK.
John BrushDepartment of Radiology, Western General Hospital, NHS Lothian, Edinburgh, UK.
Peter CorreaDepartment of Oncology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.
Nicholas DoddsDepartment of Radiology, Jersey General Hospital, St. Helier, Jersey.
Joanna DunlopScottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK.
Sofia GourtsoyianniSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Nyree GriffinDepartment of Radiology, Guys and St. Thomas' NHS Foundation Trust, London, UK.
Antony HigginsonDepartment of Radiology, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
Andrew LoweDepartment of Radiology, Musgrove Park Hospital, Somerset NHS Foundation Trust, Taunton, UK.
Andrew SlaterDepartment of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Madeline StrugnellDepartment of Radiology, Royal Cornwall Hospitals NHS Trust, Truro, UK.
Damian TolanDepartment of Radiology, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Ian ZealleyDepartment of Radiology, Ninewells Hospital, NHS Tayside, Dundee, UK.
Steve HalliganCentre for Medical Imaging, Division of Medicine, University College London, London, UK.
For PROSPECT investigators

Funding

Health Technology Assessment Programme 09/22/49
6 · The paper itself

Abstract

objectiveImproving prognostication to direct personalised therapy remains an unmet need. This study prospectively investigated promising CT, genetic, and immunohistochemical markers to improve the prediction of colorectal cancer recurrence. MATERIAL AND

methodsThis multicentre trial (ISRCTN 95037515) recruited patients with primary colorectal cancer undergoing CT staging from 13 hospitals. Follow-up identified cancer recurrence and death. A baseline model for cancer recurrence at 3 years was developed from pre-specified clinicopathological variables (age, sex, tumour-node stage, tumour size, location, extramural venous invasion, and treatment). Then, CT perfusion (blood flow, blood volume, transit time and permeability), genetic (RAS, RAF, and DNA mismatch repair), and immunohistochemical markers of angiogenesis and hypoxia (CD105, vascular endothelial growth factor, glucose transporter protein, and hypoxia-inducible factor) were added to assess whether prediction improved over tumour-node staging alone as the main outcome measure.

resultsThree hundred twenty-six of 448 participants formed the final cohort (226 male; mean 66 ± 10 years. 227 (70%) had ≥ T3 stage cancers; 151 (46%) were node-positive; 81 (25%) developed subsequent recurrence. The sensitivity and specificity of staging alone for recurrence were 0.56 [95% CI: 0.44, 0.67] and 0.58 [0.51, 0.64], respectively. The baseline clinicopathologic model improved specificity (0.74 [0.68, 0.79], with equivalent sensitivity of 0.57 [0.45, 0.68] for high vs medium/low-risk participants. The addition of prespecified CT perfusion, genetic, and immunohistochemical markers did not improve prediction over and above the clinicopathologic model (sensitivity, 0.58-0.68; specificity, 0.75-0.76).

conclusionA multivariable clinicopathological model outperformed staging in identifying patients at high risk of recurrence. Promising CT, genetic, and immunohistochemical markers investigated did not further improve prognostication in rigorous prospective evaluation. CLINICAL RELEVANCE STATEMENT: A prognostic model based on clinicopathological variables including age, sex, tumour-node stage, size, location, and extramural venous invasion better identifies colorectal cancer patients at high risk of recurrence for neoadjuvant/adjuvant therapy than stage alone. KEY POINTS: Identification of colorectal cancer patients at high risk of recurrence is an unmet need for treatment personalisation. This model for recurrence, incorporating many patient variables, had higher specificity than staging alone. Continued optimisation of risk stratification schema will help individualise treatment plans and follow-up schedules.

Indexed as

Colorectal NeoplasmsNeoplasm Recurrence, LocalTomography, X-Ray ComputedAgedBiomarkers, TumorFemaleHumansImmunohistochemistryMaleMiddle AgedNeoplasm StagingPrognosisProspective StudiesSensitivity and SpecificityBiomarkers, TumorAngiogenesisCT-perfusionLarge bowelPrognostic model, Neoplasms/primary

Identifiers

PMID38836939
PMCPMC11519198

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.