Negative Lymph Node Count Predicts Survival of Resected Non-small Cell Lung Cancer
- PDF / 728,035 Bytes
- 8 Pages / 595.276 x 790.866 pts Page_size
- 87 Downloads / 192 Views
LUNG CANCER
Negative Lymph Node Count Predicts Survival of Resected Non‑small Cell Lung Cancer Xinyan Zhou1 · Chunxiao Wu2 · Qi Cheng1 Received: 21 January 2020 / Accepted: 3 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Purpose The purpose of this study was to explore the association between the negative lymph node (NLN) count and survival, as well as compare the prognostic value of the positive lymph node (PLN) count, lymph node ratio (the PLN count/ total lymph nodes examined, LNR), and NLN count in patients with non-small cell lung cancer (NSCLC). Methods We identified patients diagnosed with NSCLC between 2005 and 2011 from the Surveillance, Epidemiology, and End Results database. Outcomes of interest were lung cancer-specific survival (LCSS) and overall survival (OS). Cases were divided into several groups based on the PLN count, NLN count, and LNR. The prognostic significance of the PLN count, NLN count, and LNR models was analyzed with the Kaplan–Meier method and the Cox regression model. Results 39,959 patients with surgical resection for NSCLC were identified. Univariate analysis demonstrated that a greater count of NLNs was associated with better LCSS (P 5) and three subgroups of LNR classification (LNR1, 0%; LNR2, 0%-30%, not including 0%; LNR3, > 30%) were established for our study. The following variables were enrolled in the Cox regression model on the basis of prior evidence and our study objective: (I) sex (male or female); (II) age at diagnosis (continuous); (III) AJCC T stage (T1, T2, or T3, defined by the sixth edition); (IV) AJCC N stage (N0, N1, or N2, defined by the sixth edition); (V) histology (adenocarcinoma, squamous cell carcinoma, or other); (VI) type of resection (lobectomy, pneumonectomy, or other); (VII) radiation treatment (yes or no); (VIII) chemotherapy (yes or no); (IX) PLN count (0, 1–5, or > 5); (X) NLN count (0–2, 3–5, or > 5); and (XI) LNR (0%, 0%-30.0%, or > 30.0%). Survival curves were drawn using the Kaplan–Meier method and compared by the log rank test. The Cox proportional hazards regression model was used to compare the relative risks of groups divided by the PLN count, NLN count, and LNR. Then the Akaike information criterion (AIC) was utilized to compare the relative predictive quality of different Cox proportional hazards models. A smaller AIC value means a more ideal method for prognosis [22, 23]. For all analyses, only P value 5
++ ++ ++ ++ ++++++++++ ++ ++++ +++++++++ ++ ++++++++++ ++++ +++ +++++++++++++ ++++++++++ ++++++++++++++++ ++ +++++ +++++++++++++++++ +++++++++++++++++++++ ++ ++++++ +++++++++++++++++++++++ ++ +++++++ ++++++ +++++++++ ++++ +++++++++++ ++ ++++++++++++++ +++++++ + + + ++++++++++++++++++++ ++++++ + + ++++++++++++++++++++++++++++++++ ++++++++++ +++++++++++++ +++++++++++++++++ +++++++++++++++++++++++++++++++
1.00
0.50 0.25
0
25
50
75
100
Time(months)
NLN
+
0−2
+
3−5
+
125
>5
++++++++ ++ ++ ++ ++ ++ ++ ++ ++ ++++++++ ++ ++ ++ ++ ++ +++ ++++++++ +++ +++ +++ +++ ++ +++ +++ ++ +++ +++
Data Loading...
