학술논문

Distinguishing optimal candidates for primary tumor resection in patients with metastatic lung adenocarcinoma: A predictive model based on propensity score matching
Document Type
article
Source
Heliyon, Vol 10, Iss 7, Pp e27768- (2024)
Subject
Metastatic lung adenocarcinoma (mLUAD)
Surgery
SEER
Prognosis factor
Risk factor
Nomogram
Science (General)
Q1-390
Social sciences (General)
H1-99
Language
English
ISSN
2405-8440
Abstract
Background: Primary tumor resection is associated with survival benefits in patients with metastatic lung adenocarcinoma (mLUAD). However, there are no established methods to determine which individuals would benefit from surgery. Therefore, we developed a model to predict the patients who are likely to benefit from surgery in terms of survival. Methods: Data on patients with mLUAD were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether surgery was performed on the primary tumor, patients were categorized into two groups: cancer-directed surgery (CDS) and no-cancer-directed surgery (No-CDS). Propensity Score Matching (PSM) was utilized to address bias between the CDS and No-CDS groups. The prognostic impact of CDS was assessed using Kaplan-Meier analysis and Cox proportional hazard models. Subsequently, we constructed a nomogram to predict the potential for surgical benefits based on multivariable logistic regression analysis using preoperative factors. Results: A total of 89,039 eligible patients were identified, including 6.4% (5705) who underwent surgery. Following PSM, the CDS group demonstrated a significantly longer median overall survival (mOS) compared with the No-CDS group (23 [21–25] vs. 7 [7–8] months; P