Optimizing Surgery Strategies in Stage IB Lung Squamous Cell Carcinoma: Insights from Interpretable Machine Learning

Key Points

• The central aim is to provide personalized survival estimates for patients with stage IB lung squamous cell carcinoma.
• Utilized interpretable machine learning techniques
• Identified high-risk subgroups
• Evaluated the effectiveness of postoperative chemotherapy
• High-risk subgroups derived no significant benefit from additional chemotherapy
• Supported a risk-adapted conservative approach to adjuvant treatment
• Facilitated integration of precision medicine into treatment decision-making