Deep Learning Model Predicts Pathological Complete Response of Lung Cancer Following Neoadjuvant Immunochemotherapy

Launched by WUHAN UNION HOSPITAL, CHINA · Feb 22, 2024

Keywords

ClinConnect Summary

This clinical trial is studying a new artificial intelligence (AI) system designed to help predict how well patients with non-small cell lung cancer respond to treatment before surgery. Specifically, it aims to see if the AI can accurately identify patients who will have a "pathological complete response," meaning their cancer shows no signs of disease after receiving neoadjuvant immunotherapy combined with chemotherapy. This prediction is based on scans taken before treatment starts.

To be eligible for this trial, participants need to have non-small cell lung cancer that has been confirmed through a biopsy and is classified as stage IB to III. They must also be receiving at least two cycles of the combined immunotherapy and chemotherapy treatment. Patients will undergo scans and evaluations as part of the study, but those with poor-quality scans or those who wait too long to start treatment after their scans won't be included. This trial is still in the planning stages and has not yet started recruiting participants.

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Eligibility criteria

• Inclusion Criteria:
• • 1. Patients' with non-small cell lung cancer, diagnosed through biopsy pathology and clinically classified as stage IB to III;
• • 2. Patients who receive at least two cycles of neoadjuvant immunotherapy combined with chemotherapy induction therapy;
• • 3. According to the IASLC guidelines, postoperative pathological evaluation was performed on the treatment response of the tumor primary lesion and lymph nodes.
• Exclusion Criteria:
• • 1. Missing or inadequate quality of CT;
• • 2. Time interval between CT and start of treatment is greater than 1 month;
• • 3. Incomplete clinicopathologic data.