Tracing Metastatic Evolutionary Patterns in Lung Adenocarcinoma: Prognostic Dissection Based on a Multi-state Model

Area of Science:

• Oncology
• Medical Statistics

Background:

• Lung adenocarcinoma recurrence after surgery presents diverse clinical scenarios.
• Understanding recurrence pathways is crucial for effective patient management.

Purpose of the Study:

• To investigate the influence of clinical and pathological factors on tumor recurrence, death, and prognosis.
• To analyze various metastasizing pathways in lung adenocarcinoma post-surgery.

Main Methods:

• Utilized a multi-state model (MSM) on data from 335 lung adenocarcinoma patients with over 10 years of follow-up.
• Defined disease states including operation, local recurrence, metastasis, concurrent local recurrence with metastasis, and death.
• Identified 8 distinct transitions representing tumor progression pathways.

Main Results:

• Approximately 50% of patients experienced recurrence post-surgery.
• Pathological lymph node status was a significant risk factor for metastasis (p=0.001) and concurrent local recurrence with metastasis (p=0.001).
• Different clinical and pathological factors were associated with distinct recurrence transitions.

Conclusions:

• Lung adenocarcinoma recurrence pathways and associated risk factors vary significantly post-surgery.
• The multi-state model aids in predicting intervention timing and type for improved survival.
• Prognosis differs across various recurrence pathways, highlighting the need for tailored treatment strategies.