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Does triage of chest X-rays with artificial intelligence shorten the time to lung cancer diagnosis: a randomised controlled trial

Impact of immediate AI enabled patient triage to chest CT on the lung cancer pathway

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ISRCTN
Registry ID
ISRCTN78987039
Enrollment
150000
Registered
2023-03-21
Start date
2023-08-01
Completion date
Unknown
Last updated
2026-04-14

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

Conditions

Lung cancer Cancer

Interventions

This is a prospective, multi-centre healthcare service delivery study with the primary objective of assessing the effectiveness of AI immediate read and worklist prioritisation for immediate review on

Sponsors

Nottingham University Hospitals NHS Trust
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 120 Years

Inclusion criteria

Inclusion criteria: 1. Chest X-ray referred from primary care 2. Age =18 years 3. Anteroposterior (AP) or Posteroanterior (PA) view

Exclusion criteria

Exclusion criteria: 1. Age <18 years 2. CXR referral not from primary care 3. Lateral X-ray view of the chest

Design outcomes

Primary

MeasureTime frame
1. Time from chest X-ray to lung cancer diagnosis in days from the cancer waiting time database 2. Time from chest X-ray to CT (when performed) in days from the radiology information system

Secondary

MeasureTime frame
1. Time to first respiratory cancer outpatient appointment in days from the cancer waiting time database 2. Time to treatment start for lung cancer patients in days from the cancer waiting time database 3. Agreement between AI (qXR) and human readers for normal/abnormal interpretation of chest X-ray as an agree/disagree decision with discordance review by a thoracic radiologist where required 4. Number of urgent lung cancer referrals from the cancer waiting time database 5. The incidence of lung cancer from the cancer waiting time database 6. The stage of lung cancer diagnosis from the cancer waiting time database 7. Cost-effectiveness of AI support at the time of CXR acquisition and prioritisation for immediate review of CXRs; to be measured by difference in costs per patient diagnosed, per percentage increase in early-stage diagnosis and potentially per QALY subject to the availability of health utilities in the published studies

Countries

England, United Kingdom

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Apr 17, 2026