Artificial Intelligence-Based Early Warning for Distant Metastasis in Malignant Tumors

Status

Not yet recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07616011

Enrollment

10000

Registered

2026-05-29

Start date

2026-06-01

Completion date

2036-12-31

Last updated

2026-05-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Malignant Tumor With Metastasis

Brief summary

Early detection and timely intervention of distant metastasis are essential for improving the prognosis of patients with malignant tumors. However, current clinical methods have notable limitations. Conventional imaging can only detect macroscopic metastatic lesions, failing to seize the optimal intervention window before metastasis occurs or during the micrometastasis stage. Previous research has adopted artificial intelligence to break the constraints of traditional imaging and realized subclinical early warning of distant metastasis based on retrospective data. On this basis, the present study aims to systematically validate the predictive performance and generalizability of the model in real-world clinical settings via a prospective cohort. This study intends to establish an organ-specific, non-invasive and cost-effective pan-cancer tool for early warning of distant metastasis. It can gain critical time for clinical intervention, help reduce the incidence of distant metastasis and ultimately optimize patient prognosis.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to 95 Years

Healthy volunteers

Inclusion criteria

1. Aged ≥ 18 years old; 2. Diagnosed with malignant tumor confirmed by histopathology; 3. No distant metastasis detected at baseline enrollment assessment; 4. Regular imaging examinations for distant metastasis assessment are scheduled in the routine follow-up protocol after enrollment; 5. Complete baseline clinicopathological data are available; 6. Patients provide informed consent and permit researchers to collect and analyze their subsequent imaging and clinicopathological data.

Exclusion criteria

1. Concurrent presence of two or more primary malignant tumors; 2. Presence of any medical or social factors that may interfere with completion of routine imaging follow-up.

Design outcomes

Primary

Measure	Time frame	Description
Incidence of distant metastasis	At each routine follow-up visit (interval: approximately 6 months to 1 year)	Proportion of patients with distant metastasis among malignant tumor cases

Outcome results