Computer-aided tool to predict outcomes after simultaneous colorectal and liver surgery

A Multi-Reader Multi-Case Controlled Clinical Trial to Evaluate the Performance Improvement From Computer-aided Tool for the Prognostic Prediction of Colorectal Liver Metastases

Observational Cancer Institute and Hospital, Chinese Academy of Medical Sciences · NCT07027605

This project will test a web-based computer tool that helps doctors predict 1-, 3-, and 5-year recurrence and survival for adults with colorectal cancer who had liver metastases removed at the same time as their primary tumor.

Quick facts

Study typeObservational
Enrollment166 (estimated)
Ages18 Years and up
SexAll
SponsorCancer Institute and Hospital, Chinese Academy of Medical Sciences Academic / other
Locations1 site (Beijing, Beijing Municipality)
Trial IDNCT07027605 on ClinicalTrials.gov

What this trial studies

This multi-reader, multi-case observational study uses 166 retrospective patient cases to compare clinician predictions with and without a web-based Random Forest prognostic tool that integrates demographic, clinical, laboratory, and genetic data. Twelve physicians will independently estimate 1-, 3-, and 5-year recurrence and mortality risks for each case, with the two assessment rounds separated by a washout period. The primary analysis measures whether access to the tool improves accuracy of 3-year postoperative predictions. All cases are from patients who underwent simultaneous colorectal and liver resection at a single tertiary cancer center.

Who should consider this trial

Good fit: Adults (≥18) with histologically confirmed colorectal adenocarcinoma liver metastases who underwent simultaneous resection of the primary tumor and liver lesions with adequate follow-up data are the cases used in this work.

Not a fit: Patients with other active malignancies, insufficient or missing follow-up data, or who did not have simultaneous colorectal and liver resection are unlikely to benefit from this tool.

Why it matters

Potential benefit: If successful, the tool could give doctors more accurate personalized estimates of recurrence and survival after simultaneous resection, helping guide treatment choices and follow-up planning.

How similar studies have performed: Machine-learning prognostic models for CRLM have shown promising accuracy in prior publications, but few prior studies have used a multi-reader, multi-case design to test whether such tools actually improve clinician predictions.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* ≥ 18 years old
* confirmation of histologically diagnosed liver metastases of colorectal adenocarcinoma
* receiving colorectal resection with simultaneous liver resection.

Exclusion Criteria:

* presence of other malignancies
* absence of follow-up data
* patients who were followed up postoperatively for less than 5 years and had no occurrences of death.

Where this trial is running

Beijing, Beijing Municipality

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Colorectal Liver MetastasisMulti-Reader Multi-Case Controlled Clinical TrialPrognostic PredictionColorectal Liver Metastases
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.