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NCT07495735
Intelligence System for Predicting Atezolizumab-Bevacizumab Response and Clinical Outcomes in Unresectable Hepatocellular Carcinoma
trial testing No intervention (observational study) in HCC - Hepatocellular Carcinoma in 400 participants. Not yet recruiting.
1 December 2026
Quick facts
| Lead sponsor | First Affiliated Hospital of Wenzhou Medical University |
|---|---|
| Status | Not yet recruiting |
| Study type | OBSERVATIONAL |
| Enrollment | 400 |
| Start date | 22 March 2026 |
| Primary completion | 1 December 2026 |
| Estimated completion | 30 December 2026 |
Drugs / interventions tested
- No intervention (observational study) — full drug profile →
Conditions studied
- HCC - Hepatocellular Carcinoma — all drugs for HCC - Hepatocellular Carcinoma →
- Atezolizumab and Bevacizumab in Hepatocellular Carcinoma — all drugs for Atezolizumab and Bevacizumab in Hepatocellular Carcinoma →
Sponsor
First Affiliated Hospital of Wenzhou Medical University
Who can join
18 and older, any sex, with HCC - Hepatocellular Carcinoma or Atezolizumab and Bevacizumab in Hepatocellular Carcinoma. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
This study is a multicenter retrospective clinical research, led by the First Affiliated Hospital of Wenzhou Medical University, and jointly conducted by other sub-centers. The aim is to develop an non-invasive artificial intelligence system for predicting the response and clinical outcomes of patients with unresectable hepatocellular carcinoma (uHCC) to the treatment with atezolizumab combined with bevacizumab (T+A). In response to the clinical situation where approximately half of uHCC patients do not respond to the standard T+A therapy and traditional invasive biopsy is unable to fully reflect the heterogeneity of the tumor microenvironment, this study plans to retrospectively collect the data of 400 patients who met the inclusion and exclusion criteria from January 2020 to November 2025. The study will systematically summarize multi-dimensional data such as enhanced CT images within one month before treatment, baseline characteristics, serum markers, liver disease factors, and tumor stage. By integrating these clinical features with deep learning imageomics features extracted from images, the research team is dedicated to constructing and validating a safe, non-invasive, and reproducible prediction model, with the aim of achieving precise identification of the benefit population before implementing immunotherapy combined with anti-angiogenic treatment, and providing a powerful intelligent tool support for optimizing clinical treatment decisions and improving patient survival prognosis.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT07495735 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by First Affiliated Hospital of Wenzhou Medical University
- Last refreshed: 27 March 2026
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07495735.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing