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Machine Learning–Based Predictive Model for Immune-Related Pneumonitis After Immunotherapy in Elderly Patients With Lung Cancer

Machine Learning–Based Predictive Model for Immune-Related Pneumonitis After Immunotherapy in Elderly Patients With Lung Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600124424
Enrollment
Unknown
Registered
2026-05-12
Start date
2026-05-12
Completion date
Unknown
Last updated
2026-05-18

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

Conditions

Lung Cancer

Interventions

Sponsors

The Second Xiangya Hospital of Central South University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
60 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age =60 years; pathologically or cytologically confirmed lung cancer; receipt of at least one cycle of immunotherapy, with documented information on drug administration and treatment regimen. Baseline data were also required, including imaging examinations (chest CT and/or PET-CT), baseline complete blood count, liver and renal function tests, inflammatory markers, and records of baseline pulmonary comorbidities (such as COPD or interstitial lung disease) and prior radiotherapy history.

Exclusion criteria

Exclusion criteria: 1.Patients with active pneumonia or an acute exacerbation of interstitial lung disease before immunotherapy;patients in whom CIP could not be reliably determined based on imaging or clinical data;patients with organ transplantation, uncontrolled HIV infection, long-term intensive immunosuppressive therapy, or a history of autoimmune disease;and patients with incomplete clinical data.

Design outcomes

Primary

MeasureTime frame
Occurrence of immune-related pneumonitis;Accuracy;Sensitivity;

Countries

China

Contacts

Public ContactSubo Gong

The Second Xiangya Hospital of Central South University

gsb5l0@csu.edu.cn+86 731 8529 5125

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 22, 2026