Abstract
Lay abstract Aim: We analyzed populations of immune cells in non-small-cell lung cancer (NSCLC). In addition, we also investigated lymph nodes from the same patient that contained or did not contain cancer cells. Patients & methods: We included 71 patients whose cancer did not return within 3 years and 80 patients whose cancer did return within 3 years after they underwent surgery to remove their tumors. We used various statistical methods to identify factors that can predict survival. Results: Sinus histiocytosis (a widening of ducts in the lymph nodes due to an increased number of certain cells) and the density of tumor-infiltrating lymphocytes (immune cells that enter the tumor to destroy it) can predict how long patients can survive after surgery or if their tumor will come back quickly. Discussion: Looking at immune cells can help physicians decide which patients need increased follow-up care due to an increased risk for their tumors to return. Aim: To analyze immune cell populations in non-small-cell lung cancer (NSCLC) tumors and matched tumor-bearing and non-tumor-bearing lymph nodes (ntbLNs) to predict prognosis. Patients & methods: 71 patients with long-term disease-free survival and 80 patients with relapse within 3 years were included in this study. We used Cox regression to identify factors associated with overall survival (OS) and progression-free survival (PFS). Results: Sinus histiocytosis and tumor-infiltrating lymphocyte density in the tumor were positively associated with PFS and OS. CD4 expression in N1 (hazard ratio = 0.72;p = 0.02) and N2 (hazard ratio = 0.91;p = 0.04) ntbLNs were positively correlated with OS and PFS, respectively. Discussion: Immunological markers in ntbLNs could be used to predict survival in NSCLC.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 1479-6694 |
Sprache: | Englisch |
Dokumenten ID: | 102063 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:39 |
Letzte Änderungen: | 17. Okt. 2023, 15:09 |