Evidence map›Paper›PMID 40230305›Full record

Observational studyHealth technology assessment (Winchester, England)2025

Evaluation of prognostic models to improve prediction of metastasis in patients following potentially curative treatment for primary colorectal cancer: the PROSPECT trial.

Vicky Goh, Susan Mallett, Manuel Rodriguez-Justo, Victor Boulter, Rob Glynne-Jones, Saif Khan, Sarah Lessels, Dominic Patel, Davide Prezzi, Stuart Taylor and 2 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Health technology assessment (Winchester, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Construction and validation of a prognostic model for 1 year all-cause mortality risk in patients with colorectal cancer liver metastases after HIFU treatment.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  2. Article
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

12 authors.

Vicky GohSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID 0000-0002-2321-8091
Susan MallettUCL Centre for Medical Imaging, London, UK.ORCID 0000-0002-0596-8200
Manuel Rodriguez-JustoResearch Department of Pathology, UCL Cancer Institute, London, UK.ORCID 0000-0001-5007-1761
Victor BoulterPatient Representative.
Rob Glynne-JonesMount Vernon Centre for Cancer Treatment, Northwood, UK.ORCID 0000-0002-6742-222X
Saif KhanDepartment of Pathology, London, UK.ORCID 0000-0002-5957-328X
Sarah LesselsScottish Clinical Trials Research Unit (SCTRU), NHS National Services Scotland, Edinburgh, Scotland.ORCID 0000-0002-7373-3067
Dominic PatelResearch Department of Pathology, UCL Cancer Institute, London, UK.ORCID 0000-0001-9223-6632
Davide PrezziSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID 0000-0002-0878-2196
Stuart TaylorUCL Centre for Medical Imaging, London, UK.ORCID 0000-0002-6765-8806
Steve HalliganUCL Centre for Medical Imaging, London, UK.ORCID 0000-0003-0632-5108
all the PROSPECT investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Despite apparently curative treatment, many patients with colorectal cancer develop subsequent metastatic disease. Current prognostic models are criticised because they are based on standard staging and omit novel biomarkers. Improved prognostication is an unmet need. Objectives: To improve prognostication for colorectal cancer by developing a baseline multivariable model of standard clinicopathological predictors, and to then improve prediction via addition of promising novel imaging, genetic and immunohistochemical biomarkers. Design: Prospective multicentre cohort. Setting: Thirteen National Health Service hospitals. Participants: Consecutive adult patients with colorectal cancer. Interventions: Collection of prespecified standard clinicopathological variables and more novel imaging, genetic and immunohistochemical biomarkers, followed by 3-year follow-up to identify postoperative metastasis. Main outcome: Best multivariable prognostic model including perfusion computed tomography compared with tumour/node staging. Secondary outcomes: Additive benefit of perfusion computed tomography and other biomarkers to best baseline model comprising standard clinicopathological predictors; measurement variability between local and central review; biological relationships between perfusion computed tomography and pathology variables. Results: Between 2011 and 2016, 448 participants were recruited; 122 (27%) were withdrawn, leaving 326 (226 male, 100 female; mean ± standard deviation 66 ± 10.7 years); 183 (56%) had rectal cancer. Most cancers were locally advanced [≥ T3 stage, 227 (70%)]; 151 (46%) were node-positive (≥ N1 stage); 306 (94%) had surgery; 79 (24%) had neoadjuvant therapy. The resection margin was positive in 15 (5%); 93 (28%) had venous invasion; 125 (38%) had postoperative adjuvant chemotherapy; 81 (25%, 57 male) developed recurrent disease. Prediction of recurrent disease by the baseline clinicopathological time-to-event Weibull multivariable model (age, sex, tumour/node stage, tumour size and location, treatment, venous invasion) was superior to tumour/node staging: sensitivity: 0.57 (95% confidence interval 0.45 to 0.68), specificity 0.74 (95% confidence interval 0.68 to 0.79) versus sensitivity 0.56 (95% confidence interval 0.44 to 0.67), specificity 0.58 (95% confidence interval 0.51 to 0.64), respectively. Addition of perfusion computed tomography variables did not improve prediction significantly: Limitations: The number of patients developing metastasis was lower than expected from historical data. Our findings should not be overinterpreted. While the baseline model was superior to tumour/node staging, any clinical utility needs definition in daily practice. Conclusions: A prognostic model of standard clinicopathological variables outperformed tumour/node staging, but novel biomarkers did not improve prediction significantly. Biomarkers that appear promising in small single-centre studies may contribute nothing substantial to prognostication when evaluated rigorously. Future work: It would be desirable for other researchers to externally evaluate the baseline model. Trial registration: This trial is registered as ISRCTN95037515. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 09/22/49) and is published in full in

Indexed as

Colorectal NeoplasmsNeoplasm MetastasisAgedBiomarkers, TumorFemaleHumansMaleMiddle AgedNeoplasm StagingPrognosisProspective StudiesTomography, X-Ray ComputedBiomarkers, TumorCLINICAL TRIALSCOLORECTAL NEOPLASMSDIAGNOSTIC IMAGINGGENETICSIMMUNOLOGYMODELNEOVASCULARISATIONNON-RANDOMISEDPATHOLOGICPATHOLOGYPROGNOSISPROGNOSTIC FACTOR(S)STATISTICALTOMOGRAPHYX-RAY COMPUTED

Identifiers

PMID40230305
PMCPMC12010235

What OpenQuestion holds

Textmetadata
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.