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Predicting Pathological Complete Response in Rectal Cancer Using Machine Learning

NCT07509632 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 320

Last updated 2026-04-03

No results posted yet for this study

Summary

This study aims to develop and validate a robust machine learning-based prediction model utilizing baseline clinical data and magnetic resonance imaging (MRI) features. The objective is to preoperatively predict the probability of achieving a pathological complete response (pCR) in patients with locally advanced rectal cancer (CRC) following neoadjuvant chemoradiotherapy (nCRT).

Conditions

  • Rectal Cancers
  • Pathological Complete Response
  • Neoadjuvant Chemoradiotherapy
  • Machine Learning

Interventions

DIAGNOSTIC_TEST

No interventions

No interventions

Sponsors & Collaborators

  • Peking University People's Hospital

    lead OTHER

Principal Investigators

  • Hong-Peng Jiang, docter · Peking University People's Hospital

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-02-04
Primary Completion
2026-04-25
Completion
2026-05-10

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07509632 on ClinicalTrials.gov