DOLCE: Impact of Optellum's Lung Cancer Prediction AI on Health Economics and Patient Outcomes

What this Trial Is About

Researchers are conducting a multi-centre prospective observational study to evaluate patients with solid and part-solid pulmonary nodules detected on routine CT chest scans. The goal is to assess whether the use of an AI-based Lung Cancer Prediction (LCP) tool influences physician decision-making and leads to clinical and health-economic benefits compared to the current standard care for these patients. This study focuses on nodules sized between 5 and 30 mm that meet specific imaging criteria. Participants will be observed without any assigned treatments as this is an observational study. The study involves evaluating baseline CT scans that meet defined quality standards and include nodules with a solid component of at least 80%. Training will be provided on the CT scan requirements. No experimental interventions are administered, but the impact of the AI tool on clinical management, use of scans and procedures, adherence to guidelines, and patient outcomes will be studied over up to one year. During the study, researchers will collect data on patient care and outcomes related to pulmonary nodules, including discharge rates and health economics. Assessments will include reviewing clinical decisions, imaging usage, and adherence to guidelines over a one-year period. Participants will be followed through their routine care with no additional treatments required, and their progress will be monitored to measure the potential effects of the AI tool on service utilization and patient outcomes.

DOLCE: Determining the Impact of Optellum's Lung Cancer Prediction Solution