Clinical trial · Observational
Clinical Study on the Evaluation of the Efficacy of Cervical Cancer
Study on the Application of Multi-omics in the Assessment of Efficacy and Prediction of Side Effects in Cervical Cancer
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The main objectives of this study are to construct a multi-omics-based prognostic and side-effect prediction model for cervical cancer based on pre-treatment imaging, digital pathology, genomics, proteomics, molecular biology, metabolomics, and intestinal flora characteristics data of cervical cancer patients, combined with patients' clinical information, to guide the precise treatment of cervical cancer patients; and to deeply excavate the characteristics related to recurrent cervical cancer based on time-series multi-omics data. Construct an artificial intelligence auxiliary model for dynamic monitoring of cervical cancer recurrence based on longitudinal multi-omics. To provide a real-time and timely tool for clinical early prediction, early identification, early diagnosis and early intervention of cervical cancer, to prolong the survival time and improve the quality of patients' survival. 1. To realize multi-omics feature extraction of cervical cancer patients before treatment, and build a prognosis and side-effect prediction model of cervical cancer to guide accurate treatment; 2. To make iterative, comprehensive, real-time assessment of the risk of recurrence of cervical cancer based on time-series multi-omics data, and to build an early warning model for early identification and early diagnosis of recurrent cervical cancer; 3. To establish a prognostic and side-effect prediction and risk dynamic assessment model for cervical cancer, to build an intelligent decision support system, to implement the application of prognostic and side-effect prediction and dynamic monitoring model, to further assist in the precise diagnosis and treatment of cervical cancer, and to provide an accurate prognostic tool for identifying, diagnosing, and intervening in cervical cancer during the follow-up process.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Uterine Cervical Neoplasms | Cervical Neoplasm | ALIAS | 0.90 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Observational study | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- label
- training group
- description
- The training group is used to train the model.
- interventionNames
- Other: Observational study
- label
- validation group
- description
- The validation group is used to evaluate model performance.
- interventionNames
- Other: Observational study
Primary outcomes (11)
- measure
- Number of Circulating Tumor Cell Count
- timeFrame
- From data of randomization until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 5 years.
- description
- Number of Circulating Tumor Cell Count (CTC count), cells/mL
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Pathology: patients with pathologically confirmed cervical cancer * Location: primary tumor of the cervix Exclusion Criteria: * Patients with no prior radiation therapy * Patients without treatment * Patients without regular follow-up
References
Publications (0)
Data not yet available