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Identifying optimal candidates for primary tumor resection among metastatic non-small cell lung cancer patients: a population-based predictive model
- Source :
- Transl Lung Cancer Res
- Publication Year :
- 2021
-
Abstract
- BACKGROUND: A survival benefit was observed in metastatic non-small cell lung cancer (NSCLC) patients that underwent surgical resection of the primary tumor. We developed a model testing the hypothesis that only certain stage IV patients would benefit from surgery and the potential benefit would vary based on primary tumor characteristics. METHODS: Patients with stage IV NSCLC were identified in the Surveillance, Epidemiology and End Results (SEER) database and then divided into surgery and non-surgery groups. A 1:1 Propensity score matching (PSM) was performed to balance characters. We assumed that patients received primary tumor surgery that lived longer than median cancer specific survival (CSS) time of those who didn’t underwent surgery could benefit from the operation. Multivariable Cox model was used to explore the independent factors of CSS in two groups (beneficial and non-beneficial group). Logistic regression was used to build a nomogram based on the significant predictive factors. RESULTS: A total of 30,342 patients with stage IV NSCLC were identified; 8.03% (2,436) received primary tumor surgery. After PSM, surgical intervention was independently correlated with longer median CSS time (19 vs. 9 months, P
- Subjects :
- Oncology
medicine.medical_specialty
Proportional hazards model
business.industry
Nomogram
medicine.disease
Primary tumor
03 medical and health sciences
0302 clinical medicine
030220 oncology & carcinogenesis
Internal medicine
Propensity score matching
Cohort
Epidemiology
medicine
Original Article
030212 general & internal medicine
Stage (cooking)
business
Lung cancer
Subjects
Details
- ISSN :
- 22186751
- Volume :
- 10
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Translational lung cancer research
- Accession number :
- edsair.doi.dedup.....9a1386386575d8085ff3575bddf4d2b6