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Construction of an Artificial Intelligence System for Predicting the Efficacy of Lung Cancer Immunotherapy and Early Warning of Immune-Related Adverse Reactions Based on Multi-Modal Data

Construction of an Artificial Intelligence System for Predicting the Efficacy of Lung Cancer Immunotherapy and Early Warning of Immune-Related Adverse Reactions Based on Multi-Modal Data

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600118816
Enrollment
Unknown
Registered
2026-02-11
Start date
2026-03-01
Completion date
Unknown
Last updated
2026-02-16

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

Conditions

Non-small Cell Lung Cancer (NSCLC)

Interventions

Responder group vs. Non-responder group:NA

Sponsors

The First Affiliated Hospital of Wenzhou Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age >= 18 years, any gender, with complete clinical data; 2. Stage ?B-?C or ? NSCLC not suitable for surgery and local therapy; 3. No EGFR or ALK mutations; 4. ECOG PS 0-1; 5. Presence of measurable lesions per RECIST 1.1 criteria, with baseline imaging completed within 1 month prior to treatment initiation and follow-up imaging evaluated every 6-8 weeks.

Exclusion criteria

Exclusion criteria: 1. Autoimmune Disease; 2. Severe cardiopulmonary insufficiency and other comorbidities; 3. Incomplete clinical data; 4. Patients without measurable lesions per RECIST 1.1 criteria at baseline.

Design outcomes

Primary

MeasureTime frame
Accuracy;

Secondary

MeasureTime frame
Sensitivity ;Specificity;Positive Predictive Value;Negative Predictive Value;

Countries

China

Contacts

Public ContactChengye Li

The First Affiliated Hospital of Wenzhou Medical University

lichengye41@126.com+86 577 8806 9354

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 19, 2026