Using machine learning to personalize treatment for advanced lung cancer
Machine Learning Approaches to Personalized Therapy for Advanced Non-small Cell Lung Cancer With Real-World Data
This study is testing whether using machine learning can help doctors choose the best treatment options for people with advanced lung cancer based on their individual needs.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 144400 (estimated) |
| Sex | All |
| Sponsor | University of Utah Academic / other |
| Drugs / interventions | immunotherapy |
| Locations | 1 site (Salt Lake City, Utah) |
| Trial ID | NCT06934343 on ClinicalTrials.gov |
What this trial studies
This research leverages machine learning and causal inference techniques applied to real-world data to personalize treatment strategies for patients with advanced non-small cell lung cancer (aNSCLC). The study aims to refine treatment selection among existing therapeutic options based on individual patient characteristics, rather than influencing regulatory decisions. By utilizing large-scale electronic health record databases and incorporating patient-reported outcomes, the research seeks to enhance patient-centered outcomes and inform future clinical trial designs. The methodology will also establish a framework for identifying optimal treatment regimes for other complex diseases.
Who should consider this trial
Good fit: Ideal candidates are patients diagnosed with advanced non-small cell lung cancer who have follow-up data available.
Not a fit: Patients with targetable mutations or those receiving specific first-line treatments may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more effective and personalized treatment options for patients with advanced lung cancer.
How similar studies have performed: Other studies have shown promise in using machine learning for personalized medicine, but this specific approach is novel in its application to advanced non-small cell lung cancer.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria Subjects must meet all of the following eligibility criteria: * Diagnosed with advanced NSCLC between January 1, 2011, and June 30, 2024. * Follow-up available until December 31, 2024, with a minimum potential follow-up period of at least six months. Exclusion Criteria Subjects meeting any of the following criteria at baseline will be excluded: * Fewer than one day of follow-up post-initiation of first-line (1L) therapy. * Presence of a targetable mutation, including ALK, BRAF, EGFR, KRAS, or ROS1. * PD-L1 expression \<50% at baseline (restricted to patients with PD-L1 ≥50%). * First-line treatment limited to immunotherapy or chemoimmunotherapy (excluding other treatment regimens). * Patients receiving second-line (2L) treatment, including those enrolled in a clinical study.
Where this trial is running
Salt Lake City, Utah
- Huntsman Cancer Institute at the University of Utah — Salt Lake City, Utah, United States (Recruiting)
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.