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NCT07408661

Application of Artificial Intelligence and Iron Metabolism Markers in Predicting ICU Outcomes for Critically Ill Cancer Patients

Completed Last updated 13 February 2026
What this trial tests

trial in Cancer in 1,137 participants. Completed in 1 December 2025.

Timeline
1 January 2015
Primary endpoint
1 October 2024
1 December 2025

Quick facts

Lead sponsorTongji University
StatusCompleted
Study typeOBSERVATIONAL
Enrollment1,137
Start date1 January 2015
Primary completion1 October 2024
Estimated completion1 December 2025

Conditions studied

Sponsor

Tongji University

Who can join

Adults 18 to 100, any sex, with Cancer. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This study aimed to develop a more accurate way to predict the 30-day survival of cancer patients admitted to the intensive care unit (ICU). The researchers focused on markers of iron metabolism, as imbalances in iron are common in cancer and severe illness. The study analyzed data from 1,137 critically ill cancer patients. Using artificial intelligence (AI), specifically a model called TabPFN, the study combined these iron markers with other routine clinical data (like blood cell counts and lactate levels) to create a new prediction tool.

Publications & conference data

No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.

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Other recruiting trials for Cancer

Currently open trials in the same condition.

Other Tongji University trials

Trials by the same sponsor.

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Data sources for this page

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/NCT07408661.

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