Metastatic Lymph Node Station Number Predicts Survival in Small Cell Lung Cancer
Han, Z.; Cong, J.; Kaiqi, J.; Jing, Z.; Yan, C.; Yuming, Z.; Gening, J.; Peng, Z.
Show abstract
PurposeAs for pathologic N category, various regrouping strategies have been raised in non-small cell lung cancer (NSCLC) but little was done in small cell lung cancer(SCLC). On the basis of the suggestions discussed in NSCLC, we proposed a novel, metastatic lymph node station number (MNSN) - based pathologic N parameter and compared its efficacy in predicting survival with pN in SCLC. MethodsWe retrospectively analyzed the patients operated and pathologically diagnosed as SCLC in our hospital between 2009 and 2019. Kaplan-Meier method and Cox regression analysis were used to compare survival between groups defined by pN and MNSN. ResultsFrom 2009 to 2019, 566 patients received surgery for SCLC and 530 of them were eligible for subsequent analysis, with a median follow-up time of 21 months. The 5-year overall survival (OS) rates were 58.8%, 38.6%, 27.9% for pN0, pN1, pN2 stages and were 58.8%, 36.8%, 22.1%, 0% for MNSN0, 1-2, 3-5, 6-7 groups, respectively. Analyses of overall and recurrence-free survival (RFS) revealed that pN1 could not be distinguished from pN2 (OS, p = 0.099; RFS, p = 0.254), but the groups in MNSN were well separated from each other (OS, p< 0.001, p = 0.001, p = 0.063; RFS, p< 0.001, p = 0.026, p = 0.01, compared with the former group). When adjusted for sex, age, smoking, tumor purity and T stage, MNSN groups were independent hazard factors for OS and RFS. ConclusionsBased on our cohort study, the MNSN-based N parameter might be a better indicator to predict survival than pN in SCLC and worth considering in the definition of N category in the future.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- DNMT family induced down-regulation of NDRG1 via DNA methylation and clinicopathological significance in gastric cancer 94%
- Prognostic Analysis of Histopathological Images Using Pre-Trained Convolutional Neural Networks 91%
- Construction of competing endogenous RNA interaction networks as prognostic markers in metastatic melanoma 91%
Similar papers in this journal
- Exploring Hypoxia-Related Genes as Prognostic Indicators in Lung Adenocarcinoma 96%
- Insulin-like Growth Factor 1 Receptor Expression Correlates with Programmed Death Ligand 1 Expression and Poor Survival in Non-small Cell Lung Cancer 95%
- Survival benefit of adjuvant therapy following neoadjuvant therapy in patients with resected esophageal cancer: a retrospective cohort study 95%
Similar papers in this journal
- Hepatic resection versus transarterial chemoembolization for the intermediate stage hepatocellular carcinoma: A cohort study 93%
- Patient stratification of clear cell renal cell carcinoma using the global transcription factor activity landscape derived from RNA-seq data 93%
- miR-100-5p downregulates mTOR to suppress the proliferation, migration and invasion of prostate cancer cells 93%
Similar papers in this journal
- Identification of prognostic biomarkers for suppressing tumorigenesis and metastasis of Hepatocellular carcinoma through transcriptome analysis 92%
- Analytical performance of a highly sensitive system to detect gene variants using next-generation sequencing for lung cancer companion diagnostics 91%
- Passive Microwave Radiometry (MWR) for diagnostics of COVID-19 lung complications in Kyrgyzstan 90%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.