The accurate preoperative prediction of invasive adenocarcinomas in pulmonary ground-glass nodules (GGNs) is critical for determining the prevention and subsequent treatment of lung cancer. Our goal is to enhance the performance of preoperative prediction through a novel artificial intelligence model to reduce the surgical mismatch rates. We propose a multi-modal hybrid CNN-Transformer fusion network (MMCT-Net) capable of extracting multi-level deep learning features that encompass both local-to-global contextual information and 2D to 3D spatial representations for precise differentiation between preinvasive and invasive lesions. The model also incorporates an adaptive feature integration mechanism to combine these deep learning features synergistically with complementary clinical parameters and radiomics signatures. In this multicenter retrospective study, we analyzed 1-mm thin-section computerized tomography scans and clinicopathological data from 421 patients undergoing GGN surgeries across three centers, all confirmed by histopathology. The experimental results demonstrated that the proposed method achieved an AUC of 92.65

Background:Prolonged air leak (PAL) represents a significant clinical problem after lung resection surgery, frequently causing extended hospital stays. Although several treatments exist, their effectiveness often remains limited. Fibrin sealant has attracted attention as a potential alternative due to its biocompatible properties, but strong evidence from controlled studies supporting its use for bedside pleurodesis remains insufficient. This study was conducted to compare the effectiveness and safety of fibrin sealant vs. 50% glucose solution in managing PAL following pulmonary resection for non-small cell lung cancer (NSCLC). Methods:We performed a retrospective analysis of NSCLC patients who developed PAL (lasting ≥5 days) after surgery between January 2021 and May 2025. Patients received either fibrin sealant or 50% glucose solution for bedside pleurodesis. To address potential selection bias, we employed propensity score matching (1:1 ratio) based on key clinical characteristics. Primary outcomes included success rate after initial intervention and time to chest tube removal. Secondary outcomes focused on complication rates. Results:After matching, 74 pairs were available for analysis. The fibrin sealant group showed significantly better outcomes, with a higher success rate after the first intervention (56.8% vs. 24.3%; OR = 4.08, 95% CI: 2.02-8.24, p < 0.001) and shorter time from intervention to median chest tube duration (6.0 days vs. 9.5 days, p < 0.001). All patients in the fibrin sealant group achieved resolution within three interventions, while some in the glucose group required up to seven procedures. Complication rates were similar between groups (16 cases each, p > 0.05), with no infection-related complications observed in the fibrin sealant group. Conclusion:For patients with PAL after NSCLC resection, bedside pleurodesis using fibrin sealant appears more effective than 50% glucose solution. It offers better initial success rates, significantly reduces air leak duration, and demonstrates a comparable safety profile. These findings support considering fibrin sealant as a primary non-surgical treatment option for this challenging complication.

Brain–heart syndrome (BHS) describes cardiac dysfunction secondary to central nervous system injury, with acute ischemic stroke (AIS) serving as a critical driver that exacerbates myocardial infarction (MI). This study aimed to elucidate the role of Apolipoprotein M (APOM) in stroke-aggravated MI and to explore its underlying systemic and molecular mechanisms. Clinical data were analyzed to evaluate the correlation between stroke and MI. A combined mouse model of middle cerebral artery occlusion (MCAO) and MI was established to assess neurological and cardiac injury. Quantitative proteomics and Weighted Gene Co-expression Network Analysis (WGCNA) were employed to screen key differentially expressed proteins. The role of APOM in myocardial injury was validated using APOM-knockout (KO) mice. Furthermore, nuclear-cytoplasmic fractionation, immunofluorescence, and Western blot were performed to investigate its effects on the Saa1 and NF-κB signaling, NLRP3-related inflammatory signaling pathway, and lipid metabolism pathways. Clinical analysis indicated that stroke is a significant risk factor for MI (OR = 4.5). In the mouse model, MCAO significantly exacerbated post-MI electrocardiographic abnormalities, myocardial inflammatory response, while elevating circulating levels of cTnT and IL-1β. Proteomics identified a significant downregulation of APOM in the heart, brain, and serum post-stroke, a trend consistent with observations in AIS patients. Further experiments revealed that APOM deficiency markedly worsened cardiac conduction disturbances, histological damage, and inflammatory responses in MI mice. Mechanistically, the loss of APOM upregulates the acute-phase protein Saa1, triggers NF-κB phosphorylation and nuclear translocation, and enhances inflammatory signaling related to inflammasomes, while simultaneously mediating cytokine release from cardiomyocytes. Concurrently, APOM deficiency led to a significant decrease in sphingosine-1-phosphate (S1P) and also caused myocardial lipid droplet accumulation and metabolite changes. Additionally, the loss of APOM increased the expression of D-dimer and fibrinogen family proteins. Our findings suggest that APOM is a potential cardioprotective agent post-AIS. Downregulation of APOM may exacerbate myocardial injury after MI by elevating Saa1 expression, activating the NF-κB pathway and the inflammasome-mediated signaling, and inducing lipid metabolic disorders and coagulation-associated alterations. APOM may represent a potential therapeutic target for the intervention of brain–heart syndrome.

INTRODUCTION:Limited studies have explored how ferroptosis and Epithelial- Mesenchymal Transition (EMT) jointly affect the prognosis of Esophageal Squamous Cell Carcinoma (ESCC). This study aimed to develop a clinical prognostic model based on the combined impact of ESCC. METHODS:Gene expression levels and clinical data of ESCC patients were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Using Cox regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, we identified nine prognostic genes to build a predictive model. Immune cell infiltration was evaluated using CIBERSORT and single-sample Gene Set Enrichment Analysis methods. Finally, in vitro experiments were conducted to assess the oncogenic effects of ACSL3 and VIM. RESULTS:We developed a Ferroptosis-EMT Integrated Score (FEIS) based on nine key genes. High-FEIS patients had worse survival, increased immune infiltration, and higher expression of immune checkpoints. A nomogram was built for prognosis prediction, and in vitro studies confirmed the tumor-promoting roles of ACSL3 and VIM. DISCUSSION:The FEIS model robustly predicts ESCC prognosis by integrating ferroptosis and EMT, offering novel biomarkers for personalized immunotherapy, though further validation is warranted. CONCLUSION:Our study introduced a novel prognostic tool that integrates ferroptosis and EMT-related biomarkers and offers valuable insights for developing personalized treatment strategies for ESCC patients.

Background: Limited research has been conducted on the interaction between ferroptosis and epithelial-mesenchymal transition (EMT) and their combined effect on esophageal squamous cell carcinoma (ESCC) patient prognosis. The present study aimed to develop a prognostic model based on the impact of ferroptosis and EMT on ESCC prognosis for clinical application. Methods: Gene expression levels and clinical data of ESCC patients were obtained from the GSE53625 dataset in the gene expression omnibus (GEO) database, and the data from the cancer genome atlas (TCGA) were obtained as a validation set. By combining the results of cox regression analysis and least absolute shrinkage and selection operator regression (LASSO) analysis, we selected nine genes associated with prognosis, which were then used to construct a prognostic model. Immune cell infiltration was evaluated using CIBERSORT and single-sample Gene Set Enrichment Analysis methods. Results: Nine key genes were screened to construct ferroptosis and EMT integrated score (FEIS). Compared to the low-FEIS group, the high-FEIS group demonstrated shorter overall survival period. The immune infiltration analysis showed an increase in immune cell infiltration and elevated expression levels of immune checkpoint molecules in the high-FEIS group. A nomogram was constructed to accurately predict patient prognosis. Conclusion: Our study introduced a novel prognostic tool that integrates ferroptosis -and EMT-related biomarker, and offered valuable insights for developing personalized treatment strategies for ESCC patients.

OBJECTIVE:The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant variability, demanding tailored surgical strategies and individualized postoperative adjuvant therapies. This study explored the preoperative assessment of GGN infiltration status using computed tomography (CT) imaging integrated with a neural network to enhance the precision of clinical decision-making in surgical planning and therapeutic interventions. METHODS:This multicenter retrospective study analyzed clinical data to quantify mismatch rates in surgical approaches across varying infiltration statuses. Regions of interest (ROIs) within the CT lung window level were manually delineated using ITK-SNAP software, enabling the extraction of relevant CT imaging features, including morphological descriptors, first-order statistical parameters, texture attributes, and high-order characteristics. Feature selection was performed using the Lasso algorithm to identify the most predictive variables, which were subsequently incorporated into the radiomics-based neural network model. The neural network architecture combined a 3D convolutional neural network (CNN) with random rotations for data augmentation and employed pre-trained parameters to optimize model weights. RESULTS:The radiomics-integrated neural network exhibited high predictive performance, achieving an area under the subject operating characteristic curve (AUC) of 0.85, with validation set AUCs of 0.66 and 0.71. Additionally, the predicted mismatch rate between lobectomy and sublobectomy was 21.48%, representing a 35.57% reduction, while the mismatch rate within sublobectomy decreased by 13.66%, reaching 10.73% CONCLUSION: The neural network-enhanced imaging model provides a robust predictive tool for assessing the preoperative infiltration status of pulmonary GGNs. Its application significantly reduces mismatch rates in surgical decision-making, contributing to more precise and individualized treatment strategies.

ABSTRACTObjectiveConstruction nomogram was to effectively predict long‐term prognosis in patients with non‐small cell lung cancer (NSCLC).Materials and MethodsThe nomogram is developed by a retrospective study of 347 patients with NSCLC who underwent cardiopulmonary exercise testing (CPET) before surgery from May 2019 to February 2022. Cross‐validation divided the data into a training cohort and validation cohort. The discrimination and accuracy ability of the nomogram were proofed by concordance index (C‐index), calibration curve, receiver operating characteristic (ROC) curve, the area under the curve (AUC), and time‐dependent ROC in validation cohort.ResultsAge, intraoperative blood loss, VO2 peak, and VE/VCO2 slope were included in the model of nomogram. The model demonstrated good discrimination and accuracy with C‐index of 0.770 (95% CI: 0.712–0.822). AUC of 6 (AUC: 0.789, 95% CI: 0.726–0.851) and 12 months (AUC: 0.787, 95% CI: 0.724–0.850) were shown in ROC. Time‐independent ROC maintains a good effect within 12 months.ConclusionWe developed a nomogram based on CPET. This model has a good ability of discrimination and accuracy. It could help clinicians to make treatment decision in clinical decision.

Background Limited research has been conducted on the interaction between ferroptosis and epithelial-mesenchymal transition (EMT) and their combined effect on esophageal squamous cell carcinoma (ESCC) patient prognosis. The present study aimed to develop a prognostic model based on the impact of ferroptosis and EMT on ESCC prognosis for clinical application. Methods Gene expression levels and clinical data of ESCC patients were obtained from the GSE53625 dataset in the Gene Expression Omnibus (GEO) database, and the data from the Cancer Genome Atlas (TCGA) were obtained as a validation set. By combining the results of Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO) analysis, we selected nine genes associated with prognosis, which were then used to construct a prognostic model. Immune cell infiltration was evaluated using CIBERSORT and single-sample Gene Set Enrichment Analysis methods. Finally, in vitro experiments were conducted to assess the oncogenic effects of ACSL3 and VIM. Results Nine key genes were screened to construct ferroptosis and EMT integrated score (FEIS). Compared to the low-FEIS group, the high-FEIS group demonstrated shorter overall survival period. The immune infiltration analysis showed an increase in immune cell infiltration and elevated expression levels of immune checkpoint molecules in the high-FEIS group. A nomogram was constructed to accurately predict patient prognosis. Additionally, our in vitro experiments confirmed the oncogenic effects of ACSL3 and VIM. Conclusion Our study introduced a novel prognostic tool that integrates ferroptosis -and EMT-related biomarker, and offered valuable insights for developing personalized treatment strategies for ESCC patients.

Abstract Objectives The long-term prognosis of patients with coronary artery disease (CAD) with diffuse long lesion underwent coronary artery bypass graft (CABG) or percutaneous coronary intervention (PCI) remains worse. Here, we aimed to identify distinctive genes involved and offer novel insights into the pathogenesis of diffuse long lesion. Materials and methods Whole exome sequencing was performed on peripheral blood samples from 20 CAD patients with diffuse long lesion (CAD-DLL) and from 10 controls with focal lesion (CAD-FL) through a uniform pipeline. Proteomics analysis was conducted on the serum samples from 10 CAD-DLL patients and from 10 controls with CAD-FL by mass spectrometry. Bioinformatics analysis was performed to elucidate the involved genes, including functional annotation and protein–protein interaction analysis. Results A total of 742 shared variant genes were found in CAD-DLL patients but not in controls. Of these, 46 genes were identified as high-frequency variant genes (≥ 4/20) distinctive genes. According to the consensus variant site, 148 shared variant sites were found in the CAD-DLL group. The lysosome and cellular senescence-related pathway may be the most significant pathway in diffuse long lesion. Following the DNA-protein combined analysis, eight genes were screened whose expression levels were altered at both DNA and protein levels. Among these genes, the MAN2A2 gene, the only one that was highly expressed at the protein level, was associated with metabolic and immune-inflammatory dysregulation. Conclusions Compared to individuals with CAD-FL, patients with CAD-DLL show additional variants. These findings contribute to the understanding of the mechanism of CAD-DLL and provide potential targets for the diagnosis and treatment of CAD-DLL.

BackgroundCardiomyocyte death is an important pathophysiological basis for ischemic cardiomyopathy (ICM). Many studies have suggested that ferroptosis is a key link in the development of ICM. We performed bioinformatics analysis and experiment validation to explore the potential ferroptosis-related genes and immune infiltration of ICM.MethodsWe downloaded the datasets of ICM from the Gene Expression Omnibus database and analyzed the ferroptosis-related differentially expressed genes (DEGs). Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and protein–protein interaction network were performed to analyze ferroptosis-related DEGs. Gene Set Enrichment Analysis was used to evaluate the gene enrichment signaling pathway of ferroptosis-related genes in ICM. Then, we explored the immune landscape of patients with ICM. Finally, the RNA expression of the top five ferroptosis-related DEGs was validated in blood samples from patients with ICM and healthy controls using qRT-PCR.ResultsOverall, 42 ferroptosis-related DEGs (17 upregulated and 25 downregulated genes) were identified. Functional enrichment analysis indicated several enriched terms related to ferroptosis and the immune pathway. Immunological analysis suggested that the immune microenvironment in patients with ICM is altered. The immune checkpoint-related genes (PDCD1LG2, LAG3, and TIGIT) were overexpressed in ICM. The qRT-PCR results showed that the expression levels of IL6, JUN, STAT3, and ATM in patients with ICM and healthy controls were consistent with the bioinformatics analysis results from the mRNA microarray.ConclusionOur study showed significant differences in ferroptosis-related genes and functional pathway between ICM patients and healthy controls. We also provided insight into the landscape of immune cells and the expression of immune checkpoints in patients with ICM. This study provides a new road for future investigation of the pathogenesis and treatment of ICM.

Background: The lymph node ratio (LNR) is useful for predicting survival in patients with small cell lung cancer (SCLC). The present study compared the effectiveness of the N stage, number of positive LNs (NPLNs), LNR, and log odds of positive LNs (LODDS) to predict cancer-specific survival (CSS) in patients with SCLC.Materials and methods: 674 patients were screened using the Surveillance Epidemiology and End Results database. The Kaplan-Meier survival and receiver operating characteristic (ROC) curves were performed to address optimal estimation of the N stage, NPLNs, LNR, and LODDS to predict CSS. The optimal LN status group was incorporated into a nomogram to estimate CSS in SCLC patients. The ROC curve, decision curve analysis, and calibration plots were utilized to test the discriminatory ability and accuracy of this nomogram.Results: The LODDS model showed the highest accuracy compared to the N stage, NPLNs, and LNR in predicting CSS for SCLC patients. LODDS, age, sex, tumor size, and radiotherapy status were included in the nomogram. The results of calibration plots provided evidences of nice consistency. The ROC and DCA plots suggested a better discriminatory ability and clinical applicability of this nomogram than the 8th TNM and SEER staging systems.Conclusions: LODDS demonstrated a better predictive power than other LN schemes in SCLC patients after surgery. A novel LODDS-incorporating nomogram was built to predict CSS in SCLC patients after surgery, proving to be more precise than the 8th TNM and SEER staging.

BackgroundIn recent years, the incidence rates of rheumatoid arthritis (RA) and heart disease (HD) have noticeably increased worldwide. Previous studies have found that patients with RA are more likely to develop HD, while the cause and effect have still remained elusive. In this study, Mendelian randomization (MR) analysis was used to indicate whether there was a potential association between RA and HD.MethodsData of RA, ischemic heart disease (IHD), myocardial infarction (MI), atrial fibrillation (AF), and arrhythmia were based on the genome-wide association study (GWAS) dataset. No disease group was intersected. Inverse-variance weighted (IVW) method was used to calculate MR estimates, and sensitivity analysis was performed.ResultsThe primary MR analysis showed that genetic susceptibility to RA was significantly associated with the risk of IHD and MI, rather than with AF and arrhythmia. Besides, there was no heterogeneity and horizontal pleiotropy between the primary and replicated analyses. There was a significant correlation between RA and the risk of IHD (odds ratio (OR), 1.0006; 95% confidence interval (CI), 1.000244–1.00104; P = 0.001552), meanwhile, there was a significant correlation between RA and the risk of MI (OR, 1.0458; 95% CI, 1.07061–1.05379; P = 0.001636). The results were similar to those of sensitivity analysis, and the sensitivity analysis also verified the conclusion. Furthermore, sensitivity and reverse MR analyses suggested that no heterogeneity, horizontal pleiotropy or reverse causality was found between RA and cardiovascular comorbidity.ConclusionRA was noted to be causally associated with IHD and MI, rather than with AF and arrhythmia. This MR study might provide a new genetic basis for the causal relationship between RA and the risk of CVD. The findings suggested that the control of RA activity might reduce the risk of cardiovascular disease.

Inflammatory bowel disease (IBD) has become globally intractable. MMPs play a key role in many inflammatory diseases. However, little is known about the role of MMPs in IBD. In this study, IBD expression profiles were screened from public Gene Expression Omnibus datasets. Functional enrichment analysis revealed that IBD-related specific functions were associated with immune pathways. Five MMPS-related disease markers, namely MMP-9, CD160, PTGDS, SLC26A8, and TLR5, were selected by machine learning and the correlation between each marker and immune cells was evaluated. We then induced colitis in C57 mice using sodium dextran sulfate and validated model construction through HE staining of the mouse colon. WB and immunofluorescence experiments confirmed that the expression levels of MMP-9, PTGDS, SLC26A8, and CD160 in colitis were significantly increased, whereas that of TLR5 were decreased. Flow cytometry analysis revealed that MMPs regulate intestinal inflammation and immunity mainly through CD8 in colitis. Our findings reveal that MMPs play a crucial role in the pathogenesis of IBD and are related to the infiltration of immune cells, suggesting that MMPs may promote the development of IBD by activating immune infiltration and the immune response. This study provides insights for further studies on the occurrence and development of IBD.

Introduction: Thymoma is a common mediastinal tumor, but few studies have been performed in thymoma patients 80 years or older. This study aimed to analyze the clinical features, treatment modalities, and survival outcomes of thymoma patients at least 80 years old and compare these features to those of patients younger than 80 years old. Method: Data from thymoma patients in the Surveillance, Epidemiology and End Results database between 2000 and 2019 were selected. Clinical features, treatment modalities of the two age groups were compared. Survival rates were calculated by the Kaplan-Meier method and the log-rank test was used to compare survival rates between two groups. Propensity score matching was used based on whether surgery was performed. Univariate and multivariate Cox proportional-hazards regression analyses were performed to identify independent prognostic factors. Results: Compared with the younger patients, the patients aged 80 years or older had a similar distribution of Masaoka-Koga tumor stage, a higher proportion of type A thymoma, and a lower recurrence rate in the early stage. In elderly patients after propensity score matching, the overall survival and cancer-specific survival were better in the surgery group with complete resection and compared with patients of different ages, elderly patients showed similar benefit from surgery as younger patients were observed. Conclusion: In thymoma patients aged 80 years or older, surgery still plays an important role in survival outcome. Compared with younger patients, older patients have unique clinical features.

Abstract Aims: This study aimed to explore the correlation of 25-hydroxyvitamin D and abdominal aortic calcification.Methods: In this cross-sectional study, the data were collected from NHANES (National Health and Nutrition Examination Survey) 2013–2014. Multivariable logistic regression was performed to determine the association of 25-hydroxyvitamin D and AAC. The non-linear relationship was analyzed using smooth curve fitting. Results: 3,040 participants with compete data were included for data analysis. The fully-adjusted model showed serum calcium and HDL levels were correlated with the severity of AAC, and 25-hydroxyvitamin D was closely correlated with plasma calcium and HDL levels. Furthermore, either a low or high level of 25-hydroxyvitamin D was positively correlated with an increased risk of severe AAC, and a U-shaped dose-response relationship (inflection point: 45.8ng/mL and 146ng/mL) was indicated. Conclusions: Either a high or low level of 25-hydroxyvitamin D was positively associated with an increased risk of severe AAC. It was suggested that clinicians should be cautious when prescribing 25-hydroxyvitamin D supplementation, and the mechanism underlying the correlation of 25-hydroxyvitamin D and AAC remains to be further confirmed.

Background Numerous studies have demonstrated that rheumatoid arthritis (RA) is related to increased incidence of heart failure (HF), but the underlying association remains unclear. In this study, the potential association of RA and HF was clarified using Mendelian randomization analysis. Methods Genetic tools for RA, HF, autoimmune disease (AD), and NT-proBNP were acquired from genome-wide studies without population overlap. The inverse variance weighting method was employed for MR analysis. Meanwhile, the results were verified in terms of reliability by using a series of analyses and assessments. Results According to MR analysis, its genetic susceptibility to RA may lead to increased risk of heart failure (OR=1.02226, 95%CI [1.005495-1.039304], P =0.009067), but RA was not associated with NT-proBNP. In addition, RA was a type of AD, and the genetic susceptibility of AD had a close relation to increased risk of heart failure (OR=1.045157, 95%CI [1.010249-1.081272], P =0.010825), while AD was not associated with NT-proBNP. In addition, the MR Steiger test revealed that RA was causal for HF and not the opposite (P = 0.000). Conclusion The causal role of RA in HF was explored to recognize the underlying mechanisms of RA and facilitate comprehensive HF evaluation and treatment of RA.

Oxidative stress is crucial to the biology of tumors. Oxidative stress' potential predictive significance in colorectal cancer (CRC) has not been studied; nevertheless here, we developed a forecasting model based on oxidative stress to forecast the result of CRC survival and enhance clinical judgment. The training set was chosen from the transcriptomes of 177 CRC patients in GSE17536. For validation, 65 samples of colon cancer from GSE29621 were utilized. For the purpose of choosing prognostic genes, the expression of oxidative stress-related genes (OXEGs) was found. Prognostic risk models were built using multivariate Cox regression analysis, univariate Cox regression analysis, and LASSO regression analysis. The outcomes of the western blot and transcriptome sequencing tests were finally confirmed. ATF4, CARS2, CRP, GPX1, IL1B, MAPK8, MRPL44, MTFMT, NOS1, OSGIN2, SOD2, AARS2, and FOXO3 were among the 14 OXEGs used to build prognostic characteristics. Patients with CRC were categorized into low-risk and high-risk groups according on their median risk scores. Cox regression analysis using single and multiple variables revealed that OXEG-related signals were independent risk factors for CRC. Additionally, the validation outcomes from western blotting and transcriptome sequencing demonstrated that OXEGs were differently expressed. Using 14 OXEGs, our work creates a predictive signature that may be applied to the creation of new prognostic models and the identification of possible medication candidates for the treatment of CRC.

Background:As the population ages, there will be an increasing number of octogenarian patients with non-small cell lung cancer (NSCLC). In carefully selected elderly patients, surgery can improve long-term survival. To identify candidates who would benefit from surgery, we performed this study and built a predictive model.Materials and methods:Data from NSCLC patients over 80 years old were obtained from the Surveillance, Epidemiology and End Results database. A 1:1 propensity score matching was performed to balance the clinicopathological features between the surgery and non-surgery groups. Kaplan-Meier analyses and log-rank tests were used to assess the significance of surgery to outcome, and Cox proportional-hazards regression and competing risk model were conducted to determine the independent prognostic factors for these patients. A nomogram was built using multivariable logistic analyses to predict candidates for surgery based on preoperative factors.Results:The final study population of 31,462 patients were divided into surgery and non-surgery groups. The median cancer-specific survival time respectively was 53 vs. 13 months. The patients' age, sex, race, Tumor, Node, Metastasis score, stage, chemotherapy use, tumor histology and nuclear grade were independent prognostic factors. Apart from race and chemotherapy, other variates were included in the predictive model to distinguish the optimal surgical octogenarian candidates with NSCLC. Internal and external validation confirmed the efficacy of this model.Conclusion:Surgery improved the survival time of octogenarian NSCLC patients. A novel nomogram was built to help clinicians make the decision to perform surgery on elderly patients with NSCLC.