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Exploratory integrated Analysis to buIld a Pathologic finding, REcurrence,survival preDicting algorithm using artificial Intelligence from Clinical facTors andImage finding On thin section computed tomographyin patients with clinical stage IA Non-small cell lung cancer

Exploratory integrated Analysis to buIld a Pathologic finding, REcurrence,survival preDicting algorithm using artificial Intelligence from Clinical facTors andImage finding On thin section computed tomographyin patients with clinical stage IA Non-small cell lung cancer - AI PREDICTION

Status
Active, not recruiting
Phases
Unknown
Study type
Unknown
Source
JPRN
Registry ID
JPRN-UMIN000057915
Enrollment
2509
Registered
2025-05-20
Start date
2022-09-01
Completion date
Unknown
Last updated
2026-09-14

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

Interventions

None listed

Sponsors

National cancer center
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Cohort 1 Meet any of the following criteria. 1) Registered and eligible in JCOG0802/WJOG4607L from a JCOG participating institution. 2) Registered and eligible in JCOG0804/WJOG4507L from a JCOG participating institution. 3) Registered and eligible in JCOG1211. Cohort 2 Meet all of the following criteria. 1) Non-small cell lung cancer (excluding low-grade tumors) operated on at the Department of Thoracic Surgery of the National Cancer Center Hospital East between January 2003 and December 2014. 2) Performance status (PS) is 0 or 1 according to the ECOG criteria. 3) Patients who have undergone pathological complete resection. 4) Age 80 years or younger at the time of surgery. 5) Clinical stage 0-IB. 6) Thin-section CT scans taken before surgery (with or without contrast, slice thickness: 10 mm or less) will be available to the study office. 7) Written informed consent to participate in this supplementary study has been obtained from surviving patients.

Exclusion criteria

Exclusion criteria: Cohort 1 1) CT images submitted for central image review did not include thin-section CT images of the main lesion. Cohort 2 1) Patients had a history of other cancers at the time of surgery. 2) Multiple lung cancers were identified at the time of surgery. 3) Preoperative treatment had been performed. 4) The purpose of surgery was for biopsy or passive limited surgery. 5) The medical records did not contain sufficient data required for this supplementary study.

Design outcomes

Primary

MeasureTime frame
Transfer learning of pathology prediction AI algorithms to construct prognosis and recurrence prediction algorithms

Countries

Japan

Contacts

Public ContactKeiju Aokage

National Cancer Center Hospital East Division of Thoracic Surgery

kaokage@east.ncc.go.jp0471331111

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Sep 19, 2026