Multivariable prognostic modelling to improve prediction of colorectal cancer recurrence: the PROSPeCT trial
Authors: 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 ,   For PROSPECT investigators, Breen David J. , Brush John , Correa Peter , Dodds Nicholas , Griffin Nyree , Lowe Andrew , Mallett Susan , McDermaid Michelle , Mohammad Amjad , Oliver Colin , Strugnell Madeline , Taylor Stuart A. , Tolan Damian , Thomas Biju , Zealley Ian 
Published: June 2024

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.