Complex Oncological Decision-Making Utilizing Fast-and-Frugal Trees in a Community Setting-Role of Academic and...

Area of Science:

• Oncology
• Medical Decision Making
• Bioinformatics

Background:

• Non-small cell lung cancer (NSCLC) treatment is complex due to targeted therapies and molecular testing.
• Existing guidelines are challenging to implement in community oncology practices.
• Molecular testing and appropriate therapy assignment are often lacking in community settings.

Purpose of the Study:

• To develop a simplified decision-making framework for lung adenocarcinoma treatment.
• To utilize case studies and fast-and-frugal tree (FFT) heuristics for this framework.
• To address the complexities of molecular testing and targeted therapy selection in community practice.

Main Methods:

• Retrospective analysis of 11 lung adenocarcinoma patients at a community site.
• Development of fast-and-frugal trees (FFTs) based on patient case studies.
• Condensing multiple FFTs into a single, simplified molecular Stage IV FFT.

Main Results:

• Most patients presented with Stage IV disease (81.8%).
• Common molecular drivers included EGFR (45.5%), KRAS (18.2%), and ALK (18.2%).
• A single, effective FFT was developed for molecular Stage IV lung adenocarcinoma, maintaining accuracy.

Conclusions:

• Fast-and-frugal trees (FFTs) provide a simple yet effective decision-making tool for community oncologists.
• The developed FFT aids in selecting appropriate therapies for lung adenocarcinoma patients.
• This framework can improve treatment decisions in community settings where molecular testing may be limited.