Rectal Cancer Neoadjuvant Therapy-Real World Study (RC-NAT-RWS)

Establishing a Strategy for Selecting Watchful Waiting and Determining the Optimal Timing for Surgery Following Neoadjuvant Therapy

This study aims to utilise a real-world data platform to integrate multi-omics data-including radiomics, gut microbiota, pathological quality control and liquid biopsy-to construct a multidimensional predictive model for the efficacy of rectal cancer treatment following neoadjuvant therapy. By integrating multimodal data, the study aims to accurately assess the efficacy of neoadjuvant therapy and identify patients suitable for a 'watch-and-wait' strategy, thereby achieving tumour control and preserving organ function without the need for surgery. Furthermore, it seeks to provide scientific evidence for the efficacy of the 'watch-and-wait' strategy and the selection of optimal timing for surgery, whilst validating the model's effectiveness and assessing its clinical feasibility through prospective clinical trials.

Study Overview

• Status: Recruiting
• Conditions: Rectal Cancer
• Intervention / Treatment: Other: This study is a multicenter, real-world, non-interventional study.

Detailed Description

1. Optimisation and predictive modelling of immunotherapy combined with neoadjuvant chemoradiotherapy Through real-world studies, we will evaluate the efficacy and safety of immunotherapy combined with neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer, focusing on comparing outcomes with traditional chemoradiotherapy regimens to optimise neoadjuvant treatment protocols. By integrating radiomics and molecular subtyping data, we will develop a deep learning model to predict the rate of pathological complete response, thereby accurately forecasting treatment outcomes for patients. This model can further optimise personalised treatment decisions, enhance the effectiveness of organ-preservation strategies, and ultimately reduce surgical trauma for patients.
2. A Treatment Efficacy Assessment System Combining Multi-omics Data with Artificial Intelligence Integrate multi-omics data (such as molecular subtyping, radiomics, and pathological assessment) with artificial intelligence technology to establish a treatment efficacy assessment system. Utilise deep learning models to analyse pre- and post-treatment imaging data and pathological samples, thereby achieving precise efficacy assessment.

• Study Type: Observational
• Enrollment (Estimated): 869

Contacts and Locations

• Study Contact: Name: hongwei Yao, Professor, Doctoral Degree; Phone Number: 63139203; Email: yaohongwei@ccmu.edu.cn

Study Locations

• China
  • Beijing Municipality
    • Beijing, Beijing Municipality, China, 100050
      • Recruiting
      • Beijing Friendship Hospital
      • Contact: hongwei Yao; Email: yaohongwei@ccmu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients with rectal cancer undergoing neoadjuvant therapy.

Description

Inclusion Criteria:

• The patient is informed and has provided written informed consent;

• Rectal adenocarcinoma confirmed by colonoscopic biopsy and pathology, meeting the following criteria:

  1. Clinical stage II/III locally advanced rectal cancer (LARC): cT1-4aN0-2M0;
  2. The distal edge of the tumor is ≤ 10 cm from the anal verge (measured by MRI);
  3. No distant metastasis;
  4. Scheduled to receive neoadjuvant therapy;
• Age ≥ 18 years, male or female。

Exclusion Criteria:

• Presence of distant organ metastasis;
• Multiple primary colorectal cancers;
• History of prior malignancy (except completely cured carcinoma in situ of the cervix, basal cell carcinoma, or squamous cell carcinoma of the skin).

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Neoadjuvant Therapy Cohort for Rectal Cancer; This study is a multicentre, real-world evidence (RWE) study designed to evaluate clinical treatment regimens that offer greater benefits to patients. It will provide evidence-based guidance for clinicians in China regarding the selection of comprehensive treatment regimens for patients with advanced rectal cancer, thereby further refining and optimising clinical practice guidelines for the diagnosis and treatment of rectal cancer; it will also explore new treatment strategies for patients with locally advanced rectal cancer in the era of immunotherapy. Study design: A combination of prospective observational and retrospective cohort studies. The primary endpoint is the complete response rate (pathological complete response and clinical complete response).

Other: This study is a multicenter, real-world, non-interventional study.; non-interventional study

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
To compare the complete response rates across different treatments.	Compare the complete response rates (including pathological complete response [pCR] and clinical complete response [cCR]) between a neoadjuvant regimen combining chemoradiotherapy with immunotherapy and the traditional neoadjuvant chemoradiotherapy regimen, in patients with locally advanced rectal cancer.	Post-neoadjuvant Therapy Efficacy Assessment Time Point (within 8-12 weeks after radiotherapy completion)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Safety profile	Adverse Events (AEs): Type, incidence, severity, and relationship to the study treatment. Severity was graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events, Version 5.0 (NCI-CTCAE v5.0).	20 weeks after the first radiotherapy session
Therapy Tolerability	The proportions of patients with dose interruption, dose reduction, and treatment discontinuation during the neoadjuvant treatment period, all due to treatment-related toxicity.	20 weeks after the first radiotherapy session
Disease-Free Survival (DFS)	Disease-Free Survival (DFS) is a key endpoint (a measure of outcome) used primarily in oncology clinical trials, especially for evaluating adjuvant or curative treatments.	within 5 years after completion of neoadjuvant therapy

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Overall Survival (OS)	Overall Survival (OS) is the primary and most objective endpoint in oncology clinical trials. It measures the time from a defined starting point (e.g., date of diagnosis, randomization in a trial, or start of treatment) until death from any cause.	within 5 years after completion of neoadjuvant therapy

Collaborators and Investigators

• Sponsor: Beijing Friendship Hospital

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2025
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): December 31, 2028

Study Registration Dates

• First Submitted: April 20, 2026
• First Submitted That Met QC Criteria: April 27, 2026
• First Posted (Actual): May 5, 2026

Study Record Updates

• Last Update Posted (Actual): May 5, 2026
• Last Update Submitted That Met QC Criteria: April 27, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Rectal cancer; Neoadjuvant Therapy; Real world study
• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Intestinal Diseases; Gastrointestinal Neoplasms; Digestive System Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colorectal Neoplasms; Intestinal Neoplasms; Rectal Diseases; Rectal Neoplasms
• Other Study ID Numbers: MR-11-26-025202 (Other Identifier: Medical Research Registration Information System)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No