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Updated: May 29, 2025

Acellular and Cellular Lung Model to Study Tumor Metastasis
Published on: August 19, 2018
Tracing Metastatic Evolutionary Patterns in Lung Adenocarcinoma: Prognostic Dissection Based on a Multi-state Model
Geewon Lee1,2, Yang-Jin Kim3, Insuk Sohn4
1Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Purpose:
After surgery for lung adenocarcinoma, a patient may experience various states of recurrence, with multiple factors potentially influencing the transitions between these states. Our purpose was to investigate the effects of clinical and pathological factors on tumor recurrence, death, and prognosis across various metastasizing pathways.
Materials And Methods:
Our study group included 335 patients with all demographic and pathologic data available who underwent surgical resection for lung adenocarcinoma for more than 10 years. The following states of disease were defined: initial state, operation (OP); three intermediate states of local recurrence (LR), metastasis (Meta), and concurrent LR with metastasis (LR+Meta); and a terminal state, death. We identified eight transitions representing various pathways of tumor progression. We employed a multi-state model (MSM) to separate the impacts of multiple prognostic factors on the transitions following surgery.
Results:
After surgery, approximately half of patients experienced recurrence. Specifically, 142 (42.4%), 54 (16.1%), and seven (2.1%) patients developed Meta, LR+Meta, and LR, respectively. Clinical and pathological factors associated with the transitions were different. Impact of pathological lymph node remained a risk factor for both OP to Meta (λ02, p=0.001) and OP to LR+Meta (λ03, p=0.001).
Conclusion:
Lung adenocarcinoma displays a broad spectrum of clinical scenarios even after curative surgery. Incidence, risk factors, and prognosis varied across different pathways of recurrence in lung adenocarcinoma patients. The greatest implication of this MSM is its ability to predict the timing and type of clinical intervention that will have the greatest impact on survival.
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