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AI-Assisted Comprehensive Management for Cancer Patients With Comorbidities (GCOG-CG001)

NCT07136727 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 5000

Last updated 2025-08-22

No results posted yet for this study

Summary

Combined with the digital whole process management data pool, a multi-modal data fusion framework is developed, and an AI model is established to realize risk stratification and personalized treatment Recommendation and dynamic prognosis prediction; validation of whole-process management based on multimodal digital fusion AI-aided decision support system through prospective non-randomized controlled interventional study The effect on survival, complication control and utilization of medical resources in patients with comorbid malignant tumors.

Conditions

  • Oncological Comorbidities (e. g. Hypertension, Diabetes, Malnutrition)

Interventions

OTHER

AI-assisted comprehensive management system

Precision Risk Stratification and personalized treatment recommendation through AI models may improve the suitability of treatment regimens and thus reduce the incidence of antineoplastic therapy-related adverse effects (e.g. , reduction of chemotherapy toxicity through nutritional intervention) , and improve the efficacy of chemotherapy, and prolonged progression-free survival (PFS) and overall survival (OS)

Sponsors & Collaborators

  • The First Affiliated Hospital of Xinxiang Medical College

    lead OTHER

Principal Investigators

  • Wei Shen Wei Shen, MD, Doctor of Medicine · First Affiliated Hospital of Xinjiang Medical University

Study Design

Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-08-15
Primary Completion
2027-05-01
Completion
2031-05-01

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 NCT07136727 on ClinicalTrials.gov