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Multivariable prognostic modelling to improve prediction of colorectal cancer recurrence: the PROSPeCT trial.
Goh, Vicky; Mallett, Susan; Boulter, Victor; Glynne-Jones, Robert; Khan, Saif; Lessels, Sarah; Patel, Dominic; Prezzi, Davide; Rodriguez-Justo, Manuel; Taylor, Stuart A; Beable, Richard; Betts, Margaret; Breen, David J; Britton, Ingrid; Brush, John; Correa, Peter; Dodds, Nicholas; Dunlop, Joanna; Gourtsoyianni, Sofia; Griffin, Nyree; Higginson, Antony; Lowe, Andrew; Slater, Andrew; Strugnell, Madeline; Tolan, Damian; Zealley, Ian; Halligan, Steve.
Afiliação
  • Goh V; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK. vicky.goh@kcl.ac.uk.
  • Mallett S; Department of Radiology, Guys and St. Thomas' NHS Foundation Trust, London, UK. vicky.goh@kcl.ac.uk.
  • Boulter V; Centre for Medical Imaging, Division of Medicine, University College London, London, UK.
  • Glynne-Jones R; Patient Representative, Mount Vernon Cancer Centre, Northwood, UK.
  • Khan S; Mount Vernon Cancer Centre, Northwood, UK.
  • Lessels S; Research Department of Pathology, UCL Cancer Institute, University College London, London, UK.
  • Patel D; Scottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK.
  • Prezzi D; Research Department of Pathology, UCL Cancer Institute, University College London, London, UK.
  • Rodriguez-Justo M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Taylor SA; Department of Radiology, Guys and St. Thomas' NHS Foundation Trust, London, UK.
  • Beable R; Research Department of Pathology, UCL Cancer Institute, University College London, London, UK.
  • Betts M; Centre for Medical Imaging, Division of Medicine, University College London, London, UK.
  • Breen DJ; Department of Radiology, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
  • Britton I; Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Brush J; Department of Radiology, University Hospital Southampton NHS Foundation Trust, Southampton, UK.
  • Correa P; Department of Radiology, University Hospitals North Midlands NHS Trust, Stoke-On-Trent, UK.
  • Dodds N; Department of Radiology, Western General Hospital, NHS Lothian, Edinburgh, UK.
  • Dunlop J; Department of Oncology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.
  • Gourtsoyianni S; Department of Radiology, Jersey General Hospital, St. Helier, Jersey.
  • Griffin N; Scottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK.
  • Higginson A; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Lowe A; Department of Radiology, Guys and St. Thomas' NHS Foundation Trust, London, UK.
  • Slater A; Department of Radiology, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
  • Strugnell M; Department of Radiology, Musgrove Park Hospital, Somerset NHS Foundation Trust, Taunton, UK.
  • Tolan D; Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Zealley I; Department of Radiology, Royal Cornwall Hospitals NHS Trust, Truro, UK.
  • Halligan S; Department of Radiology, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Eur Radiol ; 2024 Jun 05.
Article em En | MEDLINE | ID: mdl-38836939
ABSTRACT

OBJECTIVE:

Improving 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

METHODS:

This 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.

RESULTS:

Three 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).

CONCLUSION:

A 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido