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Xu X, Zhang J, Yao T, Zhao X, Wu Q, Lu C, Guo X, Xie S, Qiu L, Bi R, Xue H. Differential prognostic impact and potential molecular mechanisms of PCDHGA12 expression in lung adenocarcinoma and squamous cell carcinoma. Int Immunopharmacol 2024; 139:112727. [PMID: 39067405 DOI: 10.1016/j.intimp.2024.112727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 07/17/2024] [Accepted: 07/17/2024] [Indexed: 07/30/2024]
Abstract
Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), subtypes of non-small cell lung cancer (NSCLC), exhibit distinct characteristics. The expression and prognostic significance of Protocadherin Gamma Subfamily A, 12 (PCDHGA12) in NSCLC remain unexplored. This study analyzed transcriptomic and genomic datasets from TCGA to investigate PCDHGA12 expression and its prognostic relevance in LUAD and LUSC. We found PCDHGA12 mRNA and protein levels were downregulated in both LUAD and LUSC tissues compared to adjacent non-cancerous tissues, with high PCDHGA12 expression correlating with lower overall survival in LUSC but not in LUAD. GSEA revealed a unique enrichment pattern associated with PCDHGA12 low expression in LUSC, especially in the DNA repair pathway. Co-expression analysis showed associations of PCDHGA12 with focal adhesion and the PI3K-AKT pathway in LUAD, and additionally with ECM-receptor interaction in LUSC. Hub gene prognosis analysis identified genes correlated with prognosis only in LUSC, reflecting PCDHGA12's influence. Mutation analysis linked with PCDHGA12 identified differential mutations in SPTA1, KEAP1, and TNR in LUAD, and a notable NAV3 mutation in LUSC. Additionally, immuno-infiltration analysis reveals a positive correlation between PCDHGA12 expression and immune cell infiltration. Specifically, lower PCDHGA12 expression in LUSC is associated with higher levels of CD8 T cells and DCs, lower levels of Tregs and M0 macrophages, and increased expression of HMGB1 and TNFRSF18. These genetic and immunological differences may account for the significant prognostic disparity of PCDHGA12 levels between LUAD and LUSC. Further experimental studies are essential to validate these associations and investigate potential targeted and immunotherapeutic strategies.
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Affiliation(s)
- Xiangqian Xu
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Jun Zhang
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Tangie Yao
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Xiaokai Zhao
- Department of R&D, Zhejiang Yunying Medical Technology Co., Ltd., Jiaxing 314006, China
| | - Qingyuan Wu
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Chenghua Lu
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Xiaoyan Guo
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Shiyun Xie
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Lei Qiu
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Rongrong Bi
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
| | - Honghao Xue
- Department of Pulmonology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China.
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Yuan Y, Liu C, Shi W, Wang Y, Chen L. Trajectory patterns and predictors of cancer-related fatigue in postoperative lung cancer patients receiving chemotherapy. Support Care Cancer 2024; 32:525. [PMID: 39023748 DOI: 10.1007/s00520-024-08715-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 07/04/2024] [Indexed: 07/20/2024]
Abstract
PURPOSE Cancer-related fatigue (CRF) is a chronic symptom that can affect the overall functioning of lung cancer patients throughout the course of the disease. However, there is limited research on the trajectory and predictors of CRF specifically in lung cancer patients. Furthermore, few studies have investigated the predictive role of positive psychological and social factors in relation to CRF. This study aimed to explore the trajectory of CRF and its predictors in postoperative chemotherapy patients with lung cancer. METHODS A total of 202 lung cancer patients who underwent surgery and received adjuvant chemotherapy were recruited for this study. Baseline questionnaires were completed, covering sociodemographic information, disease details, CRF levels, personality traits, psychological resilience, and social support. CRF was assessed at three time points: first chemotherapy (T1), 3 months after chemotherapy (T2), and 6 months after chemotherapy (T3). Latent class growth modeling (LCGM) was used to identify distinct developmental trajectories of CRF. Logistic regression analysis was employed to examine predictors of CRF within different patient groups. RESULTS The LCGM analysis revealed three distinct CRF trajectories: persistent high fatigue group (30.7%), rising fatigue group (30.7%), and no fatigue group (38.6%). Cancer stage (OR = 7.563, 95% CI = 2.468-23.182, P < 0.001), melancholic personality (OR = 6.901, 95% CI = 1.261-37.764, P = 0.026), and high psychological resilience (OR = 0.171, 95% CI = 0.041-0.706, P = 0.015) were associated with the CRF trajectory. On the other hand, sanguine personality (OR = 0.254, 95% CI = 0.071-0.916, P = 0.036) and high social support (OR = 0.168, 95% CI = 0.045-0.627, P = 0.008) were associated with the increasing fatigue trajectory. CONCLUSIONS This study demonstrated that 60% of lung cancer patients experienced persistent fatigue throughout the assessment period. Moreover, it confirmed the heterogeneity of CRF trajectories among lung cancer patients. The severity of CRF was found to be higher in patients with advanced clinical stages, depressive personality traits, and lower psychological resilience.
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Affiliation(s)
- Yaqing Yuan
- School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Cuiping Liu
- School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Wen Shi
- Department of Vascular Surgery, Shandong First Medical University Affiliated Provincial Hospital, Jinan, China
| | - Ying Wang
- School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Liping Chen
- School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China.
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Zhu J, Xia H, Xu X, Zheng R, Liu C, Hong J, Huang Q. FTIR spectroscopy for assessment of hair from lung cancer patients and its application in monitoring the chemotherapy treatment effect. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 314:124185. [PMID: 38565049 DOI: 10.1016/j.saa.2024.124185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/08/2024] [Accepted: 03/22/2024] [Indexed: 04/04/2024]
Abstract
Lung cancer is the most common cancer and the leading cause of death in China. The current gold standard for clinical lung cancer diagnosis is based on histopathological examination of tumors, but it has the limitation for easy operation and convenient applications. Therefore, researchers are still striving to develop other tools and methods for non-invasive and rapid assessment of the health conditions of lung cancer patients. Hair, as a reflection of the metabolism of the body, is closely related to human health conditions. In principle, Fourier-transform infrared (FTIR) spectroscopy can probe the major chemical compositions in the hair. However, as indicated by previous studies, there is still the challenge to make good use of FTIR spectroscopy for achieving reliable analysis of hair from cancer patients. In this study, hair samples from 82 lung cancer patients were collected and subjected to FTIR measurements and analysis, which showed the protein content in the hair is closely related to the protein content in the blood serum of patients, and the contents of protein and lipid are statistically lower in the lung cancer patients. Furthermore, we demonstrated that FTIR spectroscopy could be employed to monitor the hair of lung cancer patients undergoing chemotherapy, and confirmed that the FTIR spectra of the hair may reflect the resultant effect of the chemotherapy. As such, this work validates the way of using FTIR spectroscopy in hair analysis for the assistance of medical diagnosis of lung cancer as well as monitoring the conditions of the patients under the medical treatment.
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Affiliation(s)
- Jianxia Zhu
- School of Nursing, Anhui Medical University, Hefei, Anhui 230032, China; CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China
| | - Haiqian Xia
- School of Nursing, Anhui Medical University, Hefei, Anhui 230032, China; CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China
| | - Xiuzhi Xu
- School of Nursing, Anhui Medical University, Hefei, Anhui 230032, China
| | - Rong Zheng
- School of Nursing, Anhui Medical University, Hefei, Anhui 230032, China
| | - Chao Liu
- CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China; Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, Anhui 230032, China
| | - Jingfang Hong
- School of Nursing, Anhui Medical University, Hefei, Anhui 230032, China.
| | - Qing Huang
- School of Nursing, Anhui Medical University, Hefei, Anhui 230032, China; CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China; Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, Anhui 230032, China.
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Chen Y, Ji Y, Shen L, Li Y, Ren Y, Shi H, Li Y, Wu Y. High core 1β1,3-galactosyltransferase 1 expression is associated with poor prognosis and promotes cellular radioresistance in lung adenocarcinoma. J Cancer Res Clin Oncol 2024; 150:214. [PMID: 38662050 PMCID: PMC11045595 DOI: 10.1007/s00432-024-05745-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 04/07/2024] [Indexed: 04/26/2024]
Abstract
PURPOSE Core 1β1,3-galactosyltransferase 1 (C1GALT1) exhibits elevated expression in multiple cancers. The present study aimed to elucidate the clinical significance of C1GALT1 aberrant expression and its impact on radiosensitivity in lung adenocarcinoma (LUAD). METHODS The C1GALT1 expression and its clinical relevance were investigated through public databases and LUAD tissue microarray analyses. A549 and H1299 cells with either C1GALT1 knockdown or overexpression were further assessed through colony formation, gamma-H2A histone family member X immunofluorescence, 5-ethynyl-2'-deoxyuridine incorporation, and flow cytometry assays. Bioinformatics analysis was used to explore single cell sequencing data, revealing the influence of C1GALT1 on cancer-associated cellular states. Vimentin, N-cadherin, and E-cadherin protein levels were measured through western blotting. RESULTS The expression of C1GALT1 was significantly higher in LUAD tissues than in adjacent non-tumor tissues both at mRNA and protein level. High expression of C1GALT1 was correlated with lymph node metastasis, advanced T stage, and poor survival, and was an independent risk factor for overall survival. Radiation notably upregulated C1GALT1 expression in A549 and H1299 cells, while radiosensitivity was increased following C1GALT1 knockdown and decreased following overexpression. Experiment results showed that overexpression of C1GALT1 conferred radioresistance, promoting DNA repair, cell proliferation, and G2/M phase arrest, while inhibiting apoptosis and decreasing E-cadherin expression, alongside upregulating vimentin and N-cadherin in A549 and H1299 cells. Conversely, C1GALT1 knockdown had opposing effects. CONCLUSION Elevated C1GALT1 expression in LUAD is associated with an unfavorable prognosis and contributes to increased radioresistance potentially by affecting DNA repair, cell proliferation, cell cycle regulation, and epithelial-mesenchymal transition (EMT).
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Affiliation(s)
- Yong Chen
- Department of Medical Oncology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Yanyan Ji
- Department of Medical Oncology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Lin Shen
- Department of Medical Oncology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Ying Li
- Department of Medical Oncology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Yue Ren
- Department of Medical Oncology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Hongcan Shi
- Department of Cardiothoracic Surgery, Medical College of Yangzhou University, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Yue Li
- Department of Medical Oncology, Clinical College of Dalian Medical University, Yangzhou, 225009, Jiangsu, People's Republic of China
| | - Yunjiang Wu
- Department of Thoracic Surgery, Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368 Hanjiang Road, Yangzhou, 225009, Jiangsu, People's Republic of China.
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Cao Y, Liu X, Liu J, Su Z, Liu W, Yang L, Zhang L. Diagnostic value of exosomal noncoding RNA in lung cancer: a meta-analysis. Front Oncol 2024; 14:1357248. [PMID: 38694786 PMCID: PMC11061461 DOI: 10.3389/fonc.2024.1357248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/11/2024] [Indexed: 05/04/2024] Open
Abstract
Background Lung cancer is one of the most dangerous cancers in the world. Most lung cancer patients are diagnosed in the middle and later stages, which can lead to poor survival rates. The development of lung cancer is often accompanied by abnormal expression of exosomal non-coding RNAs, which means that they have the potential to serve as noninvasive novel molecular markers for lung cancer diagnosis. Methods For this study, we conducted a comprehensive literature search in PubMed, Web of science, Science direct, Embase, Cochrane, and Medline databases, and by reviewing published literature, The diagnostic capacity of exosomal microRNAs (miRNAs), long-chain non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) for lung cancer was evaluated. Functional enrichment analysis of miRNA target genes was performed. Results The study included 41 papers, a total of 68 studies. More than 60 miRNAs, 9 lncRNAs and 14 circRNAs were involved. The combined sensitivity and specificity were 0.83(95%CI, 0.80~0.86) and 0.83(95% CI,0.79~0.87); 0.71(95% CI,0.68~0.74) and 0.79(95%CI, 0.75~0.82); 0.79(95%CI,0.67~0.87) and 0.81(95%CI,0.74~0.86), and constructed overall subject operating characteristic curves with the summarized area under the curve values of 0.90, 0.82, and 0.86. Conclusion Our study shows that exosomes miRNAs, lncRNAs and circRNAs are effective in the diagnosis of lung cancer, providing evidence for studies related to novel lung cancer diagnostic markers. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD42023457087.
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Affiliation(s)
- Yuxuan Cao
- Department of Epidemiology and Statistics, Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Xinbo Liu
- Department of Thoracic Surgery, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jiayi Liu
- Department of Epidemiology and Statistics, Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Ziyi Su
- Undergraduate of College of Basic Medicine, Hebei Medical University, Shijiazhuang, China
| | - Wenxuan Liu
- Department of Epidemiology and Statistics, Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Lei Yang
- Department of Epidemiology and Statistics, Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Liwen Zhang
- Department of Epidemiology and Statistics, Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
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Xu J, Zhang Y, Li M, Shao Z, Dong Y, Li Q, Bai H, Duan J, Zhong J, Wan R, Bai J, Yi X, Tang F, Wang J, Wang Z. A single-cell characterised signature integrating heterogeneity and microenvironment of lung adenocarcinoma for prognostic stratification. EBioMedicine 2024; 102:105092. [PMID: 38547579 PMCID: PMC10990706 DOI: 10.1016/j.ebiom.2024.105092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 03/15/2024] [Accepted: 03/15/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND The high heterogeneity of tumour and the complexity of tumour microenvironment (TME) greatly impacted the tumour development and the prognosis of cancer in the era of immunotherapy. In this study, we aimed to portray the single cell-characterised landscape of lung adenocarcinoma (LUAD), and develop an integrated signature incorporating both tumour heterogeneity and TME for prognosis stratification. METHODS Single-cell tagged reverse transcription sequencing (STRT-seq) was performed on tumour tissues and matched normal tissues from 14 patients with LUAD for immune landscape depiction and candidate key genes selection for signature construction. Kaplan-Meier survival analyses and in-vitro cell experiments were conducted to confirm the gene functions. The transcriptomic profile of 1949 patients from 11 independent cohorts including nine public datasets and two in-house cohorts were obtained for validation. FINDINGS We selected 11 key genes closely related to cell-to-cell interaction, tumour development, T cell phenotype transformation, and Ma/Mo cell distribution, including HLA-DPB1, FAM83A, ITGB4, OAS1, FHL2, S100P, FSCN1, SFTPD, SPP1, DBH-AS1, CST3, and established an integrated 11-gene signature, stratifying patients to High-Score or Low-Score group for better or worse prognosis. Moreover, the prognostically-predictive potency of the signature was validated by 11 independent cohorts, and the immunotherapeutic predictive potency was also validated by our in-house cohort treated by immunotherapy. Additionally, the in-vitro cell experiments and drug sensitivity prediction further confirmed the gene function and generalizability of this signature across the entire RNA profile spectrum. INTERPRETATION This single cell-characterised 11-gene signature might offer insights for prognosis stratification and potential guidance for treatment selection. FUNDING Support for the study was provided by National key research and development project (2022YFC2505004, 2022YFC2505000 to Z.W. and J.W.), Beijing Natural Science Foundation (7242114 to J.X.), National Natural Science Foundation of China of China (82102886 to J.X., 81871889 and 82072586 to Z.W.), Beijing Nova Program (20220484119 to J.X.), NSFC general program (82272796 to J.W.), NSFC special program (82241229 to J.W.), CAMS Innovation Fund for Medical Sciences (2021-1-I2M-012, 2022-I2M-1-009 to Z.W. and J.W.), Beijing Natural Science Foundation (7212084 to Z.W.), CAMS Key lab of translational research on lung cancer (2018PT31035 to J.W.), Aiyou Foundation (KY201701 to J.W.). Medical Oncology Key Foundation of Cancer Hospital Chinese Academy of Medical Sciences (CICAMS-MOCP2022003 to J.X.).
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Affiliation(s)
- Jiachen Xu
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yundi Zhang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Man Li
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhuo Shao
- Geneplus-Beijing Institute, Changping District, Beijing, China
| | - Yiting Dong
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qingqing Li
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China; Beijing Advanced Innovation Center for Genomics & Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Hua Bai
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianchun Duan
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medical Oncology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Jia Zhong
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Rui Wan
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jing Bai
- Geneplus-Beijing Institute, Changping District, Beijing, China
| | - Xin Yi
- Geneplus-Beijing Institute, Changping District, Beijing, China
| | - Fuchou Tang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China; Beijing Advanced Innovation Center for Genomics & Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jie Wang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Zhijie Wang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Li J, Wang Y, Zhai M, Qin M, Zhao D, Xiang Q, Shao Z, Wang P, Lin Y, Dong Y, Liu Y. Risk factors and a nomogram for predicting cognitive frailty in Chinese patients with lung cancer receiving drug therapy: A single-center cross-sectional study. Thorac Cancer 2024; 15:884-894. [PMID: 38451002 PMCID: PMC11016407 DOI: 10.1111/1759-7714.15256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 02/04/2024] [Accepted: 02/06/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND To identify independent factors of cognitive frailty (CF) and construct a nomogram to predict cognitive frailty risk in patients with lung cancer receiving drug therapy. METHODS In this cross-sectional study, patients with lung cancer undergoing drug therapy from October 2022 to July 2023 were enrolled. The data collected includes general demographic characteristics, clinical data characteristics and assessment of tools for cognitive frailty and other factors. Logistic regression was harnessed to determine the influencing factors, R software was used to establish a nomogram model to predict the risk of cognitive frailty. The enhanced bootstrap method was employed for internal verification of the model. The performance of the nomogram was evaluated by using calibration curves, the area under the receiver operating characteristic curve, and decision curve analysis. RESULTS A total of 372 patients were recruited, with a cognitive frailty prevalence of 56.2%. Age, education background, diabetes mellitus, insomnia, sarcopenia, and nutrition status were identified as independent factors. Then, a nomogram model was constructed and patients were classified into high- and low-risk groups with a cutoff value of 0.552. The internal validation results revealed good concordance, calibration and discrimination. The decision curve analysis presented prominent clinical utility. CONCLUSIONS The prevalence of cognitive frailty was higher in lung cancer patients receiving drug therapy. The nomogram could identify the risk of cognitive frailty intuitively and simply in patients with lung cancer, so as to provide references for early screening and intervention for cognitive frailty at the early phases of drug treatment.
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Affiliation(s)
- Jinping Li
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yan Wang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Minfeng Zhai
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Mengyuan Qin
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Dandi Zhao
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Qian Xiang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Zaoyuan Shao
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Panrong Wang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yan Lin
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yiting Dong
- CAMS Key Laboratory of Translational Research on Lung Cancer, State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
| | - Yan Liu
- Nursing department, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
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Zhou J, Yu B, Guo P, Wang S. The insufficiency of CT examination in early detection of central lung squamous cell carcinoma and squamous epithelial precancerous lesions. BMC Cancer 2024; 24:299. [PMID: 38443800 PMCID: PMC10916110 DOI: 10.1186/s12885-024-12052-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/25/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND CT examination for lung cancer has been carried out for more than 20 years and great achievements have been made in the early detection of lung cancer. However, in the clinical work, a large number of advanced central lung squamous cell carcinoma are still detected through bronchoscopy. Meanwhile, a part of CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions are also accidentally detected through bronchoscopy. METHODS This study retrospectively collects the medical records of patients in the bronchoscopy room of the Endoscopy Department of Zhejiang Cancer Hospital from January 2014 to December 2018. The inclusion criteria for patients includes: 1.Patient medical records completed, 2.Without history of lung cancer before the diagnosis and first pathological diagnosis of primary lung cancer, 3.Have the lung CT data of the same period, 4.Have the bronchoscopy records and related pathological diagnosis, 5.The patients undergoing radical surgical treatment must have a complete postoperative pathological diagnosis. Finally, a total of 10,851 patients with primary lung cancer are included in the study, including 7175 males and 3676 females, aged 22-98 years. Firstly, 130 patients with CT-occult lesions are extracted and their clinical features are analyzed. Then, 604 cases of single central squamous cell carcinoma and 3569 cases of peripheral adenocarcinoma are extracted and compares in postoperative tumor diameter and lymph node metastasis. RESULTS 115 cases of CT-occult central lung squamous cell carcinoma and 15 cases of squamous epithelial precancerous lesions are found. In the total lung cancer, the proportion of CT-occult lesions is 130/10,851 (1.20%). Meanwhile, all these patients are middle-aged and elderly men with a history of heavy smoking. There are statistically significant differences in postoperative median tumor diameter (3.65 cm vs.1.70 cm, P < 0.0001) and lymph node metastasis rate (50.99% vs.13.06%, P < 0.0001) between 604 patients with operable single central lung squamous cell carcinoma and 3569 patients with operable peripheral lung adenocarcinoma. Of the 604 patients with squamous cell carcinoma, 96.52% (583/604) are male with a history of heavy smoking and aged 40-82 years with a median age of 64 years. CONCLUSIONS This study indicates that the current lung CT examination of lung cancer is indeed insufficiency for the early diagnosis of central squamous cell carcinoma and squamous epithelial precancerous lesions. Further bronchoscopy in middle-aged and elderly men with a history of heavy smoking can make up for the lack of routine lung CT examination.
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Affiliation(s)
- Jiaming Zhou
- Department of Endoscopy, Zhejiang Cancer Hospital, Hangzhou, China
| | - Bijun Yu
- Department of Endoscopy, Zhejiang Cancer Hospital, Hangzhou, China
| | - Peng Guo
- Department of Endoscopy, Zhejiang Cancer Hospital, Hangzhou, China
| | - Shi Wang
- Department of Endoscopy, Zhejiang Cancer Hospital, Hangzhou, China.
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Luo X, Zhang N, Guo L, Zhou L, Jiang H, Cui RS. Comprehensive needs, social support, and disease perception in lung cancer patients treated with immune checkpoint inhibitors: a cross-sectional study. Support Care Cancer 2024; 32:166. [PMID: 38372773 DOI: 10.1007/s00520-024-08348-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 01/30/2024] [Indexed: 02/20/2024]
Abstract
PURPOSE The aim of this study was to investigate the comprehensive needs of lung cancer patients treated with immune checkpoint inhibitors and to explore the relationships between comprehensive needs and social support and disease perception, moreover, to analyse associated factors of comprehensive needs. METHODS The study was conducted in a teaching hospital in Jiaxing Province, China. A total of 141 patients with lung cancer completed a battery of self-report questionnaires, including the Comprehensive Needs Assessment Tool in Cancer for Patients (CNAT), Social Supportive Rating Scale (SSRS), Brief Illness Perception Questionnaire (BIPQ), and demographic and clinical characteristics questionnaire. RESULTS The level of comprehensive needs was highest in the domain "medical demand" (42.17 ± 26.57), and the item with the highest level of comprehensive needs was "I need information about the financial support for my medical expenses" (2.00 ± 1.07). Statistically significant correlations were identified between the comprehensive needs score, social support, and disease perception. The multiple regression analysis showed that immunotherapy course, whether irAEs occur, social support, and disease perception were factors influencing patients' comprehensive needs. CONCLUSIONS The most prevalent needs in lung cancer patients were found in the "medical needs" domain. Additionally, immunotherapy course, whether irAEs occur, disease perception, and social support were associated with comprehensive needs among lung cancer patients. It is essential to combine the associated factors to accurately evaluate patient needs. We should pay more attention to proposing the comprehensive measures for these patients and providing more individualized supportive care during the lengthy treatment period.
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Affiliation(s)
- Xiaoyan Luo
- Department of Nursing, Medical College, Jiaxing College, No.899, Guangdome Road, Nanhu District, Jiaxing, Zhejiang Province, China
| | - Ningning Zhang
- Department of Medical Oncology, The First Hospital of Jiaxing, South Zhonghuan Road, Jiaxing, 1882314001, Zhejiang Province, China
| | - Lingru Guo
- Department of Nursing, Medical College, Jiaxing College, No.899, Guangdome Road, Nanhu District, Jiaxing, Zhejiang Province, China
| | - Li Zhou
- Department of Nursing, Medical College, Jiaxing College, No.899, Guangdome Road, Nanhu District, Jiaxing, Zhejiang Province, China
| | - Haiying Jiang
- Department of Nursing, Medical College, Jiaxing College, No.899, Guangdome Road, Nanhu District, Jiaxing, Zhejiang Province, China
| | - Ren-Shan Cui
- Department of Nursing, Medical College, Jiaxing College, No.899, Guangdome Road, Nanhu District, Jiaxing, Zhejiang Province, China.
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10
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Zhao Z, Gu S, Yang Y, Wu W, Du L, Wang G, Dong H. A cost-effectiveness analysis of lung cancer screening with low-dose computed tomography and a polygenic risk score. BMC Cancer 2024; 24:73. [PMID: 38218803 PMCID: PMC10787978 DOI: 10.1186/s12885-023-11800-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/26/2023] [Indexed: 01/15/2024] Open
Abstract
INTRODUCTION Several studies have proved that Polygenic Risk Score (PRS) is a potential candidate for realizing precision screening. The effectiveness of low-dose computed tomography (LDCT) screening for lung cancer has been proved to reduce lung cancer specific and overall mortality, but the cost-effectiveness of diverse screening strategies remained unclear. METHODS The comparative cost-effectiveness analysis used a Markov state-transition model to assess the potential effect and costs of the screening strategies incorporating PRS or not. A hypothetical cohort of 300,000 heavy smokers entered the study at age 50-74 years and were followed up until death or age 79 years. The model was run with a cycle length of 1 year. All the transition probabilities were validated and the performance value of PRS was extracted from published literature. A societal perspective was adopted and cost parameters were derived from databases of local medical insurance bureau. Sensitivity analyses and scenario analyses were conducted. RESULTS The strategy incorporating PRS was estimated to obtain an ICER of CNY 156,691.93 to CNY 221,741.84 per QALY gained compared with non-screening with the initial start age range across 50-74 years. The strategy that screened using LDCT alone from 70-74 years annually could obtain an ICER of CNY 80,880.85 per QALY gained, which was the most cost-effective strategy. The introduction of PRS as an extra eligible criteria was associated with making strategies cost-saving but also lose the capability of gaining more LYs compared with LDCT screening alone. CONCLUSION The PRS-based conjunctive screening strategy for lung cancer screening in China was not cost-effective using the willingness-to-pay threshold of 1 time Gross Domestic Product (GDP) per capita, and the optimal screening strategy for lung cancer still remains to be LDCT screening for now. Further optimization of the screening modality can be useful to consider adoption of PRS and prospective evaluation remains a research priority.
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Affiliation(s)
- Zixuan Zhao
- Department of Public Administration, School of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China
| | - Shuyan Gu
- Center for Health Policy and Management Studies, School of Government, Nanjing University, Nanjing, China
| | - Yi Yang
- Department of Science and Education of the Fourth Affiliated Hospital, and Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Weijia Wu
- Department of Science and Education of the Fourth Affiliated Hospital, and Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Lingbin Du
- Department of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of the University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Gaoling Wang
- Department of Public Administration, School of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Hengjin Dong
- Department of Science and Education of the Fourth Affiliated Hospital, and Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
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Xu R, Chen J, Chen D, Zhang X, Cui W, Deng Y, Sun D, Yuan B, Li J. CT-guided Percutaneous Microwave Ablation Combined with Local Radiotherapy or Chemotherapy of Malignant Pulmonary Tumors. Curr Radiopharm 2024; 17:184-199. [PMID: 38204263 PMCID: PMC11327768 DOI: 10.2174/0118744710261655231214105406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/18/2023] [Accepted: 10/30/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND AND OBJECTIVE The study aimed to investigate the clinical efficacy of CT-guided microwave ablation (MWA) combined with 125I seed implantation or bronchial arterial infusion (BAI) chemotherapy in the treatment of malignant pulmonary tumors. METHODS A total of 56 patients who underwent MWA, MWA combined with 125I particle implantation, or MWA combined with BAI chemotherapy for advanced lung cancer or metastatic lung cancer from January 2015 to June 2021 in Guangdong Provincial People's Hospital were enrolled. Among them, 21 patients were treated with MWA (MWA), 18 with MWA combined with 125I seed implantation (MWA+125I), and 17 with MWA combined with BAI chemotherapy (MWA+BAI). The short-term outcomes, complications, Eastern Cooperative Oncology Group (ECOG) performance score (Zubrod-ECOG-WHO, ZPS), survival, and factors related to survival were compared between the three groups. RESULTS The response rate of the MWA group (9.52%) was significantly lower than that of the MWA+125I group (50.00%) and MWA+BAI chemotherapy group (47.06%), and the differences were statistically significant (p < 0.05). The incidence of complications in the MWA, MWA+125I, and MWA+BAI chemotherapy groups was 47.62%, 55.56%, and 52.94%, respectively, with no significant difference (p > 0.05). Three months after the treatment, the ZPS of the MWA+125I and MWA+BAI chemotherapy groups was significantly lower than before treatment and significantly lower than that of the MWA group in the same period; the differences were statistically significant (p < 0.05). The median survival time of the MWA+125I group was 18 (9.983, 26.017) months and that of the MWA+BAI chemotherapy group was 21 (0.465, 41.535) months, both of which were higher than that of the MWA group [11 (6.686, 15.314) months]; the differences were statistically significant (p < 0.05). Cox regression analysis was performed on the factors related to survival and revealed treatment mode as a protective factor [HR = 0.433, 95% CI = (0.191, 0.984), p = 0.046]. Other factors, such as gender, age, and tumor size, did not independently affect survival. CONCLUSION CT-guided MWA combined with 125I seed implantation and MWA combined with BAI chemotherapy are safe and effective for the treatment of advanced lung cancer and metastatic lung cancer, and can control tumor progression and prolong survival time.
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Affiliation(s)
- Rongde Xu
- Department of Interventional Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China
| | - Jingjing Chen
- Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China
| | - Daohua Chen
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, 510080, China
| | - Xiaobo Zhang
- School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, 510006, China
| | - Wei Cui
- Department of Interventional Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China
| | - Yi Deng
- Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province. The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, 650000, China
- Medical School, Kunming University of Science and Technology, Kunming, Yunnan, 650000, China
| | - Danxiong Sun
- Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province. The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, 650000, China
| | - Bing Yuan
- Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province. The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, 650000, China
| | - Jing Li
- Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China
- Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province. The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, 650000, China
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Bao W, Zhou X, Gu F, Lin J, Li B. Neoadjuvant immune checkpoint inhibitor therapy and chemotherapy improve pulmonary ventilation and diffusion function in patients with lung cancer. Zhejiang Da Xue Xue Bao Yi Xue Ban 2023; 52:588-593. [PMID: 37899399 PMCID: PMC10630051 DOI: 10.3724/zdxbyxb-2023-0290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/08/2023] [Indexed: 10/31/2023]
Abstract
OBJECTIVES To investigate changes of pulmonary ventilation function and diffusion function in lung cancer patients after neoadjuvant immune checkpoint inhibitors (ICIs) therapy combined with chemotherapy treatment. METHODS Patients with newly diagnosed lung cancer (Ⅱa-Ⅲb) admitted to Zhejiang Cancer Hospital from October 2021 to July 2022, who received ICIs combined with chemotherapy for more than two courses were enrolled. Patients underwent pulmonary ventilation function and diffusion function assessments before and after treatment. The demographic information, sizes and locations of cancer lesions, doses and duration of ICIs used, pulmonary function results before and after treatment, and the tumor regression were documented. The changes of pulmonary function parameters before and after the treatment were analyzed with paired t test and Wilcoxon rank-sum test. The factors influencing the pulmonary function changes were analyzed by multiple linear Lasso regression and ridge regression. RESULTS Among the 52 patients, 50 cases were males (96.15%) and 43 cases were squamous carcinoma (82.69%). The medium age of the patients was 67 years. After neoadjuvant therapy, 36 patients (69.23%) showed remission of tumor lesions. After treatment, the parameters of pulmonary ventilation inspiratory vital capacity (IVC) and the area under the expiratory flow-volume curve (AREAex), and the parameter of pulmonary diffusion total lung capacity increased compared with the baseline (all P<0.05). Forced vital capacity (FVC) and forced expiratory volume in first second (FEV1) also showed an increasing trend. Multivariate linear Lasso regression and ridge regression showed that baseline IVC had a significant negative effect on IVC improvement (Beta=-0.435, t=-2.968, P<0.01), baseline TLC had a significant negative effect on the improvement of TLC (Beta=-0.266, t=-2.474, P<0.05), and the remission of obstructive pneumonia favored the improvement of TLC (Beta=0.308, t=2.443, P<0.05). CONCLUSIONS After ICIs neoadjuvant treatment combined with chemotherapy, the lung ventilation and diffusion function can be improved in lung cancer patients, particularly for those with reduced baseline ventilation and diffusion function.
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Affiliation(s)
- Wu'an Bao
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310022, China.
| | - Xia Zhou
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310022, China
| | - Feiying Gu
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310022, China
| | - Juan Lin
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310022, China
| | - Bin Li
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310022, China.
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Wang C, Shao J, Song L, Ren P, Liu D, Li W. Persistent increase and improved survival of stage I lung cancer based on a large-scale real-world sample of 26,226 cases. Chin Med J (Engl) 2023; 136:1937-1948. [PMID: 37394562 PMCID: PMC10431578 DOI: 10.1097/cm9.0000000000002729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Indexed: 07/04/2023] Open
Abstract
BACKGROUND Lung cancer prevails and induces high mortality around the world. This study provided real-world information on the evolution of clinicopathological profiles and survival outcomes of lung cancer, and provided survival information within stage I subtypes. METHODS Patients pathologically confirmed with lung cancer between January 2009 and December 2018 were identified with complete clinicopathological information, molecular testing results, and follow-up data. Shifts in clinical characteristics were evaluated using χ2 tests. Overall survival (OS) was calculated through the Kaplan-Meier method. RESULTS A total of 26,226 eligible lung cancer patients were included, among whom 62.55% were male and 52.89% were smokers. Non-smokers and elderly patients took increasingly larger proportions in the whole patient population. The proportion of adenocarcinoma increased from 51.63% to 71.80%, while that of squamous carcinoma decreased from 28.43% to 17.60%. Gene mutations including EGFR (52.14%), KRAS (12.14%), and ALK (8.12%) were observed. Female, younger, non-smoking, adenocarcinoma patients and those with mutated EGFR had better survival prognoses. Importantly, this study validated that early detection of early-stage lung cancer patients had contributed to pronounced survival benefits during the decade. Patients with stage I lung cancer, accounted for an increasingly considerable proportion, increasing from 15.28% to 40.25%, coinciding with the surgery rate increasing from 38.14% to 54.25%. Overall, period survival analyses found that 42.69% of patients survived 5 years, and stage I patients had a 5-year OS of 84.20%. Compared with that in 2009-2013, the prognosis of stage I patients in 2014-2018 was dramatically better, with 5-year OS increasing from 73.26% to 87.68%. Regarding the specific survival benefits among stage I patients, the 5-year survival rates were 95.28%, 93.25%, 82.08%, and 74.50% for stage IA1, IA2, IA3, and IB, respectively, far more promising than previous reports. CONCLUSIONS Crucial clinical and pathological changes have been observed in the past decade. Notably, the increased incidence of stage I lung cancer coincided with an improved prognosis, indicating actual benefits of early detection and management of lung cancer.
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Affiliation(s)
| | | | | | | | | | - Weimin Li
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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Wang H, Zhu H, Ding L, Yang K. A diagnostic classification of lung nodules using multiple-scale residual network. Sci Rep 2023; 13:11322. [PMID: 37443333 PMCID: PMC10345110 DOI: 10.1038/s41598-023-38350-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 07/06/2023] [Indexed: 07/15/2023] Open
Abstract
Computed tomography (CT) scans have been shown to be an effective way of improving diagnostic efficacy and reducing lung cancer mortality. However, distinguishing benign from malignant nodules in CT imaging remains challenging. This study aims to develop a multiple-scale residual network (MResNet) to automatically and precisely extract the general feature of lung nodules, and classify lung nodules based on deep learning. The MResNet aggregates the advantages of residual units and pyramid pooling module (PPM) to learn key features and extract the general feature for lung nodule classification. Specially, the MResNet uses the ResNet as a backbone network to learn contextual information and discriminate feature representation. Meanwhile, the PPM is used to fuse features under four different scales, including the coarse scale and the fine-grained scale to obtain more general lung features of the CT image. MResNet had an accuracy of 99.12%, a sensitivity of 98.64%, a specificity of 97.87%, a positive predictive value (PPV) of 99.92%, and a negative predictive value (NPV) of 97.87% in the training set. Additionally, its area under the receiver operating characteristic curve (AUC) was 0.9998 (0.99976-0.99991). MResNet's accuracy, sensitivity, specificity, PPV, NPV, and AUC in the testing set were 85.23%, 92.79%, 72.89%, 84.56%, 86.34%, and 0.9275 (0.91662-0.93833), respectively. The developed MResNet performed exceptionally well in estimating the malignancy risk of pulmonary nodules found on CT. The model has the potential to provide reliable and reproducible malignancy risk scores for clinicians and radiologists, thereby optimizing lung cancer screening management.
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Affiliation(s)
- Hongfeng Wang
- School of Network Engineering, Zhoukou Normal University, Zhoukou, 466001, China
| | - Hai Zhu
- School of Network Engineering, Zhoukou Normal University, Zhoukou, 466001, China
| | - Lihua Ding
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, China
| | - Kaili Yang
- Henan Provincial People's Hospital, Henan Eye Hospital, Henan Eye Institute, People's Hospital of Zhengzhou University, Henan University People's Hospital, Zhengzhou, 450003, China.
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Wang Y, Nie J, Dai L, Hu W, Han S, Zhang J, Chen X, Ma X, Tian G, Wu D, Zhang Z, Long J, Fang J. Construction of an endoplasmic reticulum stress-related signature in lung adenocarcinoma by comprehensive bioinformatics analysis. BMC Pulm Med 2023; 23:172. [PMID: 37189138 DOI: 10.1186/s12890-023-02443-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND Lung Adenocarcinoma (LUAD) is a major component of lung cancer. Endoplasmic reticulum stress (ERS) has emerged as a new target for some tumor treatments. METHODS The expression and clinical data of LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) database, followed by acquiring ERS-related genes (ERSGs) from the GeneCards database. Differentially expressed endoplasmic reticulum stress-related genes (DE-ERSGs) were screened and used to construct a risk model by Cox regression analysis. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were plotted to determine the risk validity of the model. Moreover, enrichment analysis of differentially expressed genes (DEGs) between the high- and low- risk groups was conducted to investigate the functions related to the risk model. Furthermore, the differences in ERS status, vascular-related genes, tumor mutation burden (TMB), immunotherapy response, chemotherapy drug sensitivity and other indicators between the high- and low- risk groups were studied. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the mRNA expression levels of prognostic model genes. RESULTS A total of 81 DE-ERSGs were identified in the TCGA-LUAD dataset, and a risk model, including HSPD1, PCSK9, GRIA1, MAOB, COL1A1, and CAV1, was constructed by Cox regression analysis. K-M and ROC analyses showed that the high-risk group had a low survival, and the Area Under Curve (AUC) of ROC curves of 1-, 3- and 5-years overall survival was all greater than 0.6. In addition, functional enrichment analysis suggested that the risk model was related to collagen and extracellular matrix. Furthermore, differential analysis showed vascular-related genes FLT1, TMB, neoantigen, PD-L1 protein (CD274), Tumor Immune Dysfunction and Exclusion (TIDE), and T cell exclusion score were significantly different between the high- and low-risk groups. Finally, qRT-PCR results showed that the mRNA expression levels of 6 prognostic genes were consistent with the analysis. CONCLUSION A novel ERS-related risk model, including HSPD1, PCSK9, GRIA1, MAOB, COL1A1, and CAV1, was developed and validated, which provided a theoretical basis and reference value for ERS-related fields in the study and treatment of LUAD.
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Affiliation(s)
- Yang Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
- Clinical Trial Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Jun Nie
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Ling Dai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Weiheng Hu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Sen Han
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Jie Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Xiaoling Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Xiangjuan Ma
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Guangming Tian
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Di Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Ziran Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Jieran Long
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China
| | - Jian Fang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology, Peking University Cancer Hospital & Institute, 52# Fucheng Road, Haidian District, Beijing, 100142, China.
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Ping Y, Huang J, Zhu J, Sun Z, Shang A, Chen C, Liu W, Li D. Comprehensive analyses of molecular features, prognostic values, and regulatory functionalities of m 6A-modified long non-coding RNAs in lung adenocarcinoma. Clin Epigenetics 2023; 15:60. [PMID: 37029420 PMCID: PMC10082542 DOI: 10.1186/s13148-023-01475-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/22/2023] [Indexed: 04/09/2023] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) has a high incidence and recurrence rate. N6-methyladenosine (m6A) modification of RNA has become a promising epigenetic marker in tumors. The dysregulation of both RNA m6A levels and m6A regulator expression levels reportedly affects essential biological processes in various tumors. Long non-coding RNAs (lncRNAs), a subgroup of RNAs over 200 nucleotides in length that do not code for protein, can be modified and regulated by m6A, but the relevant profile in LUAD remains unclear. RESULTS The m6A levels of total RNA were decreased in LUAD tumor tissues and cells. Multiple m6A regulators were abnormally expressed at both the RNA and protein levels, and were related in expression patterns and functionally synergistic. Our microarray revealed 2846 m6A-modified lncRNA transcripts as well as its molecular features, 143 of which were differentially m6A-modified and manifested a negative correlation between expression levels and m6A modification levels. More than half of the differentially m6A-modified lncRNAs associated with dysregulated expression. The 6-MRlncRNA risk signature was a reliable indicator for assessing survival time of LUAD patients. The competitive endogenous regulatory network suggested a potential m6A-induced pathogenicity in LUAD. CONCLUSIONS These data have demonstrated that differential RNA m6A modification and m6A regulator expression levels were identified in LUAD patients. In addition, this study provides evidence increasing the understanding of molecular features, prognostic values, and regulatory functionalities of m6A-modified lncRNAs in LUAD.
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Affiliation(s)
- Yili Ping
- Department of Laboratory Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China
- Department of Laboratory Medicine, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, 310000, China
| | - Jingjuan Huang
- Department of Laboratory Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China
| | - Jichao Zhu
- Department of Laboratory Medicine, Huzhou Central Hospital, Huzhou, 313099, China
| | - Zujun Sun
- Department of Laboratory Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China
| | - Anquan Shang
- Department of Laboratory Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China
| | - Chen Chen
- Department of Laboratory Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China
| | - Wenfang Liu
- Department of General Surgery, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China.
| | - Dong Li
- Department of Laboratory Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine, Shanghai, 200065, China.
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Wang L, Wang Y, Wang F, Gao Y, Fang Z, Gong W, Li H, Zhu C, Chen Y, Shi L, Du L, Li N. Disparity in Lung Cancer Screening Among Smokers and Nonsmokers in China: Prospective Cohort Study. JMIR Public Health Surveill 2023; 9:e43586. [PMID: 36917151 PMCID: PMC10131892 DOI: 10.2196/43586] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 01/17/2023] [Accepted: 02/05/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality in smokers; however, the evidence in nonsmokers is scarce. OBJECTIVE This study aimed to evaluate the participant rate and effectiveness of one-off LDCT screening for lung cancer among smokers and nonsmokers. METHODS A population-based prospective cohort study was performed to enroll participants aged between 40 and 74 years from 2013 to 2019 from 4 cities in Zhejiang Province, China. Participants who were evaluated as having a high risk of lung cancer from an established risk score model were recommended to undergo LDCT screening. Follow-up outcomes were retrieved on June 30, 2020. The uptake rate of LDCT screening for evaluated high-risk participants and the detection rate of early-stage lung cancer (stage 0-I) were calculated. The lung cancer incidence, lung cancer mortality, and all-cause mortality were compared between the screened and nonscreened groups. RESULTS At baseline, 62.56% (18,818/30,079) of smokers and 6% (5483/91,455) of nonsmokers were identified as high risk (P<.001), of whom 41.9% (7885/18,818) and 66.31% (3636/5483) underwent LDCT screening (P<.001), respectively. After a median follow-up of 5.1 years, 1100 lung cancer cases and 456 all-cause death cases (116 lung cancer death cases) were traced. The proportion of early-stage lung cancer among smokers was 60.3% (173/287), which was lower than the proportion of 80.3% (476/593) among nonsmokers (P<.001). Among smokers, a higher proportion was found in the screened group (72/106, 67.9%) than the nonscreened group (56/114, 49.1%; P=.005), whereas no significance was found (42/44, 96% vs 10/12, 83%; P=.20) among nonsmokers. Compared with participants who were not screened, LDCT screening in smokers significantly increased lung cancer incidence (hazard ratio [HR] 1.39, 95% CI 1.09-1.76; P=.007) but reduced lung cancer mortality (HR 0.52, 95% CI 0.28-0.96; P=.04) and all-cause mortality (HR 0.47, 95% CI 0.32-0.69; P<.001). Among nonsmokers, no significant results were found for lung cancer incidence (P=.06), all-cause mortality (P=.89), and lung cancer mortality (P=.17). CONCLUSIONS LDCT screening effectively reduces lung cancer and all-cause mortality among high-risk smokers. Further efforts to define high-risk populations and explore adequate lung cancer screening modalities for nonsmokers are needed.
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Affiliation(s)
- Le Wang
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Youqing Wang
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Key Laboratory of Diagnosis & Treatment Technology on Thoracic Oncology (Lung and Esophagus), Hangzhou, China
| | - Fei Wang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yumeng Gao
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Zhimei Fang
- Kecheng District People's Hospital of Quzhou, Quzhou, China
| | - Weiwei Gong
- Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
| | - Huizhang Li
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Chen Zhu
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Yaoyao Chen
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Lei Shi
- Department of Radiology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Lingbin Du
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Key Laboratory of Diagnosis & Treatment Technology on Thoracic Oncology (Lung and Esophagus), Hangzhou, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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18
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Xiao H, Shi Z, Zou Y, Xu K, Yu X, Wen L, Liu Y, Chen H, Long H, Chen J, Liu Y, Cao S, Li C, Hu Y, Liao X, Yan S. One-off low-dose CT screening of positive nodules in lung cancer: A prospective community-based cohort study. Lung Cancer 2023; 177:1-10. [PMID: 36657367 DOI: 10.1016/j.lungcan.2023.01.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/22/2022] [Accepted: 01/06/2023] [Indexed: 01/09/2023]
Abstract
BACKGROUND To improve the early stage diagnosis and reduce the lung cancer (LC) mortality for positive nodule (PN) population, data on effectiveness of PN detection using one-off low-dose spiral computed tomography (LDCT) screening are needed to improve the PN management protocol. We evaluate the effectiveness of PN detection and developed a nomogram to predict LC risk for PNs. METHODS A prospective, community-based cohort study was conducted. We recruited 292,531 eligible candidates during 2012-2018. Individuals at high risk of LC based on risk assessment underwent LDCT screening and were divided into PN and non-PN groups. The effectiveness of PN detection was evaluated in LC incidence, mortality, and all-cause mortality. We performed subgroup analysis of characteristic variables for the association between PN and LC risk. A competing risk model was used to develop the nomogram. RESULTS Participants (n = 14901) underwent LDCT screening; PNs were detected in 1193 cases (8·0%). After a median follow-up of 6·1 years, 193 were diagnosed with LC (1·3%). Of these, 94 were in the PN group (8·0%). LC incidence, mortality, and all-cause mortality were significantly higher in the PN group (adjusted hazard ratios: 10.60 (7.91-14.20), 7.97 (5.20-12.20), and 1.94 (1.51-2.50), respectively). Additionally, various PN characteristics were associated with an increased probability of developing LC. The C-index value of the nomogram for predicting LC risk of PN individuals was 0·847. CONCLUSIONS The protocol of PNs management for improvement could focus on specific characteristic population and high-risk PN individuals by nomogram assessment.
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Affiliation(s)
- Haifan Xiao
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China.
| | - Zhaohui Shi
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Yanhua Zou
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Kekui Xu
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Xiaoping Yu
- The Department of Diagnostic Radiology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Lu Wen
- The Department of Diagnostic Radiology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Yang Liu
- Kaifu District Center for Disease Control and Prevention, 1440 Xifeng Road, Changsha 410005, China
| | - Haiyan Chen
- Fufong District Center for Disease Control and Prevention, 8 Huojuzhong Road, Changsha 410001, China
| | - Huajun Long
- Yuhua District Center for Disease Control and Prevention, 772 Zhongyiyi Road, Changsha 410007, China
| | - Jihuai Chen
- Yuelu District Center for Disease Control and Prevention, 1060 Dujuan Road, Changsha 410006, China
| | - Yanling Liu
- Tianxin District Center for Disease Control and Prevention, 86 Lianhua Road, Changsha 410000, China
| | - Shiyu Cao
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Can Li
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Yingyun Hu
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China
| | - Xianzhen Liao
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China.
| | - Shipeng Yan
- The Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha 410013, China.
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Shi Y, Zhou J, Zhao Y, Zhu B, Zhang L, Li X, Fang J, Shi J, Zhuang Z, Yang S, Wang D, Yu H, Zhang L, Zheng R, Greco M, Wang T. Results of the phase IIa study to evaluate the efficacy and safety of rezivertinib (BPI-7711) for the first-line treatment of locally advanced or metastatic/recurrent NSCLC patients with EGFR mutation from a phase I/IIa study. BMC Med 2023; 21:11. [PMID: 36617560 PMCID: PMC9827694 DOI: 10.1186/s12916-022-02692-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 12/01/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Rezivertinib (BPI-7711) is a novel third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI). This phase IIa study was part of a phase I/IIa study (NCT03386955), aimed to evaluate the efficacy and safety of rezivertinib as the first-line treatment for patients with locally advanced or metastatic/recurrent EGFR mutated non-small cell lung cancer (NSCLC). METHODS Patients received the first-line treatment of 180 mg rezivertinib orally once daily until disease progression, unacceptable toxicity, or withdrawal of consent. The primary endpoint was the objective response rate (ORR) assessed by blinded independent central review (BICR). Secondary endpoints included disease control rate (DCR), duration of response (DoR), progression-free survival (PFS), overall survival (OS), and safety. RESULTS From Jun 12, 2019, to Oct 17, 2019, 43 patients were enrolled. At the data cutoff date on Dec 23, 2021, the ORR by BICR was 83.7% (95% CI: 69.3-93.2%). The median DoR was 19.3 (95% CI: 15.8-25.0) months. The median PFS by BICR was 20.7 (95% CI: 13.8-24.8) months and 22.0 (95% CI: 16.8-26.3) months by investigators. Data on OS was immature. Totally, 40 (93.0%) patients had at least one treatment-related adverse event while 4 (9.3%) of them were grade ≥ 3. CONCLUSIONS Rezivertinib (BPI-7711) showed promising efficacy and a favorable safety profile for the treatment among the locally advanced or metastatic/recurrent NSCLC patients with EGFR mutation in the first-line setting. TRIAL REGISTRATION ClinicalTrials.gov, NCT03386955.
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Affiliation(s)
- Yuankai Shi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
| | - Jianying Zhou
- Department of Respiratory Medicine, The First Affiliated Hospital, Zhejiang University, School of Medicine, Hangzhou, China
| | - Yanqiu Zhao
- Department of Respiratory Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Bo Zhu
- Department of Oncology, Institute of Cancer, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Liangming Zhang
- Department of Medical Oncology, Yantai Yuhuangding Hospital, Yantai, China
| | - Xingya Li
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jian Fang
- Department of Thoracic Oncology, Beijing Cancer Hospital, Beijing, China
| | - Jianhua Shi
- Department of Medical Oncology, Linyi Cancer Hospital, Linyi, China
| | - Zhixiang Zhuang
- Department of Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Sheng Yang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Donglin Wang
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Huiqing Yu
- Department of Palliative Care, Department of Geriatric Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Longzhen Zhang
- Department of Radiotherapy, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Rongsheng Zheng
- Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Michael Greco
- Department of Drug Discovery, Beta Pharma Inc., Princeton, NJ, USA
| | - Tingting Wang
- Department of Clinical Development, Beta Pharma (Shanghai) Co., Ltd, Shanghai, China
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20
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Guo L, Meng Q, Zheng L, Chen Q, Liu Y, Xu H, Kang R, Zhang L, Liu S, Sun X, Zhang S. Lung Cancer Risk Prediction Nomogram in Nonsmoking Chinese Women: Retrospective Cross-sectional Cohort Study. JMIR Public Health Surveill 2023; 9:e41640. [PMID: 36607729 PMCID: PMC9862335 DOI: 10.2196/41640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/04/2022] [Accepted: 11/25/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND It is believed that smoking is not the cause of approximately 53% of lung cancers diagnosed in women globally. OBJECTIVE The study aimed to develop and validate a simple and noninvasive model that could assess and stratify lung cancer risk in nonsmoking Chinese women. METHODS Based on the population-based Cancer Screening Program in Urban China, this retrospective, cross-sectional cohort study was carried out with a vast population base and an immense number of participants. The training set and the validation set were both constructed using a random distribution of the data. Following the identification of associated risk factors by multivariable Cox regression analysis, a predictive nomogram was developed. Discrimination (area under the curve) and calibration were further performed to assess the validation of risk prediction nomogram in the training set, which was then validated in the validation set. RESULTS In sum, 151,834 individuals signed up to take part in the survey. Both the training set (n=75,917) and the validation set (n=75,917) were comprised of randomly selected participants. Potential predictors for lung cancer included age, history of chronic respiratory disease, first-degree family history of lung cancer, menopause, and history of benign breast disease. We displayed 1-year, 3-year, and 5-year lung cancer risk-predicting nomograms using these 5 factors. In the training set, the 1-year, 3-year, and 5-year lung cancer risk areas under the curve were 0.762, 0.718, and 0.703, respectively. In the validation set, the model showed a moderate predictive discrimination. CONCLUSIONS We designed and validated a simple and noninvasive lung cancer risk model for nonsmoking women. This model can be applied to identify and triage people at high risk for developing lung cancers among nonsmoking women.
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Affiliation(s)
- Lanwei Guo
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Qingcheng Meng
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Liyang Zheng
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Qiong Chen
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Yin Liu
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Huifang Xu
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Ruihua Kang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Luyao Zhang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Shuzheng Liu
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Xibin Sun
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
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Shi Y. Landscape of the clinical development of China innovative anti-lung cancer drugs. CANCER PATHOGENESIS AND THERAPY 2023; 1:67-75. [PMID: 38328605 PMCID: PMC10846302 DOI: 10.1016/j.cpt.2022.10.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/18/2022] [Accepted: 10/08/2022] [Indexed: 02/09/2024]
Abstract
Even today, lung cancer remains one of the most frequently diagnosed cancers and the leading cause of cancer-related deaths worldwide. Throughout the past decades, remarkable advances have been made in the research and development of anti-lung cancer drugs in China. Since the first registered Chinese clinical trial on May 2, 2006, many potent anti-lung cancer drugs have been developed and approved by the China Food and Drug Administration and the National Medical Product Administration of China. Among them, the most advance were observed in the development of targeted agents and immunotherapeutic agents such as epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) icotinib, aumolertinib, and furmonertinib, anaplastic lymphoma kinase (ALK)-TKI ensartinib, programmed cell death-1 (PD-1) monoclonal antibodies (mAbs) camrelizumab, sintilimab, and tislelizumab, and programmed cell death-ligand 1 (PD-L1) mAb sugemalimab, which have made huge breakthrough in recent years. Some other investigational innovative drug also demonstrated promising efficacy and acceptable safety profiles. Results from clinical studies on these China innovative drugs have led to changes in clinical practice guidelines and considerably improved the outcomes for patients with lung cancer. Thus, in this review, we aim to provide further insight into the clinical development and achievement of China innovative anti-lung cancer drugs.
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Affiliation(s)
- Yuankai Shi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, Beijing 100021, China
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22
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Wang M, Lin S, He N, Yang C, Zhang R, Liu X, Suo C, Lin T, Chen H, Xu W. The Introduction of Low-Dose CT Imaging and Lung Cancer Overdiagnosis in Chinese Women. Chest 2023; 163:239-250. [PMID: 35998705 DOI: 10.1016/j.chest.2022.08.2207] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 06/27/2022] [Accepted: 08/03/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Overdiagnosis of lung cancer by low-dose CT (LDCT) screening has raised concerns globally. LDCT screening has been used widely in employee health examinations in China since 2011. RESEARCH QUESTION Has the increasing use of LDCT in low-risk populations in China led to lung cancer overdiagnosis? STUDY DESIGN AND METHODS A total of 34,152 incident cases of and 27,208 deaths resulting from lung cancer in a population of approximately 3 million were derived from the Cancer Surveillance of Shanghai between 2002 and 2017. Changes in stage-specific and histologic type-specific incidence and mortality and incidence rate ratio (IRR) relative to the base year 2002 or to the period 2002 through 2005 were calculated by sex and were used to evaluate potential overdiagnosisve of lung cancer. RESULTS In men, both age-adjusted incidence of and mortality as a result of lung cancer decreased significantly up to 2008 and thereafter remained stable; in women, the incidence increased rapidly from 2011 (annual percentage change, 11.98%; 95% CI, 9.57%-14.45%), whereas the mortality declined persistently. The upward trend of incidence mainly was observed in lung adenocarcinoma in both sexes, with a sharper increase from 2012 through 2017. In men, the incidence of early-stage cancer increased 6.9 per 100,000 (95% CI, 5.1-8.7 per 100,000) and was accompanied by 5.5 per 100,000 (95% CI, -9.2 to -1.7 per 100,000) decline in late-stagecancer from 2002 through 2017. In women, early-stage incidence rose 16.1 per 100,000 (95% CI, 14.0-18.3 per 100,000), but no significant decline in late-stage cancer was found (absolute difference, -0.6 per 100,000; 95% CI, -2.8 to 1.7 per 100,000). The IRR was highest in most recent period and increased most in young women, mainly for early-stage cancer or lung adenocarcinoma. INTERPRETATION The results provide evidence at a population level for lung cancer overdiagnosis in Chinese women resulting from increasing LDCT screening in the low-risk populations. Criteria for LDCT screening and management of screening-detected nodules need to be addressed fully for expanded application of LDCT screening in China.
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Affiliation(s)
- Mengyan Wang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Yiwu Research Institute, Fudan University, Yiwu, China
| | - Shangqun Lin
- Centers for Disease Control and Prevention of Pudong New Area, Shanghai, China
| | - Na He
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Yiwu Research Institute, Fudan University, Yiwu, China
| | - Chen Yang
- Centers for Disease Control and Prevention of Pudong New Area, Shanghai, China
| | - Ruoxin Zhang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Yiwu Research Institute, Fudan University, Yiwu, China
| | - Xing Liu
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Yiwu Research Institute, Fudan University, Yiwu, China
| | - Chen Suo
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Yiwu Research Institute, Fudan University, Yiwu, China
| | - Tao Lin
- Centers for Disease Control and Prevention of Pudong New Area, Shanghai, China
| | - Haiquan Chen
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Wanghong Xu
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Yiwu Research Institute, Fudan University, Yiwu, China.
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Wang H, Zhu H, Ding L. Accurate classification of lung nodules on CT images using the TransUnet. Front Public Health 2022; 10:1060798. [PMID: 36544802 PMCID: PMC9760709 DOI: 10.3389/fpubh.2022.1060798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 11/11/2022] [Indexed: 12/12/2022] Open
Abstract
Background Computed tomography (CT) is an effective way to scan for lung cancer. The classification of lung nodules in CT screening is completely doctor dependent, which has drawbacks, including difficulty classifying tiny nodules, subjectivity, and high false-positive rates. In recent years, deep convolutional neural networks, a deep learning technology, have been shown to be effective in medical imaging diagnosis. Herein, we propose a deep convolutional neural network technique (TransUnet) to automatically classify lung nodules accurately. Methods TransUnet consists of three parts: the transformer, the Unet, and global average pooling (GAP). The transformer encodes discriminative features via global self-attention modeling on CT image patches. The Unet, which collects context by constricting route, enables exact lunge nodule localization. The GAP categorizes CT images, assigning each sample a score. Python was employed to pre-process all CT images in the LIDI-IDRI, and the obtained 8,474 images (3,259 benign and 5,215 lung nodules) were used to evaluate the method's performance. Results The accuracies of TransUnet in the training and testing sets were 87.90 and 84.62%. The sensitivity, specificity, and AUC of the proposed TransUnet on the testing dataset were 70.92, 93.17, and 0.862%, respectively (0.844-0.879). We also compared TransUnet to three well-known methods, which outperformed these methods. Conclusion The experimental results on LIDI-IDRI demonstrated that the proposed TransUnet has a great performance in classifying lung nodules and has a great potential application in diagnosing lung cancer.
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Affiliation(s)
- Hongfeng Wang
- School of Network Engineering, Zhoukou Normal University, Zhoukou, China
| | - Hai Zhu
- School of Network Engineering, Zhoukou Normal University, Zhoukou, China
| | - Lihua Ding
- College of Public Health, Zhengzhou University, Zhengzhou, China,*Correspondence: Lihua Ding
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Liu T, Li N, Liu C, Miao X. A Qualitative Exploration of Medication Experience and Factors Contributing to Adherence to Oral-Targeted Therapy Among Lung Cancer Survivors. Semin Oncol Nurs 2022; 38:151352. [PMID: 36253304 DOI: 10.1016/j.soncn.2022.151352] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/14/2022] [Accepted: 09/16/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVES The introduction of oral-targeted therapy for cancer improves survival while adherence also presents as a challenge to patients. Current studies on oral anticancer agents are primarily limited to patients from developed countries with breast cancer and chronic myeloid leukemia receiving oral chemotherapy and hormonal therapy. This study explored experience of oral-targeted therapy adherence among Chinese patients with nonsmall cell lung cancer and its contributing factors by using a qualitative research. DATA SOURCES Semi-structured interviews with 16 patients and 7 family caregivers at a tertiary tumor hospital in China were conducted to understand their experience and perceptions of oral-targeted therapy. Thematic analysis was applied to generate the themes and to identify underlying factors associated with the adherence. CONCLUSION The lung cancer survivors struggled with ambivalence between survival and relief during taking targeted anticancer medication and showed diverse models of nonadherence, including intentionally or unintentionally intermittent medication and overadherence. Three main themes were identified: (1) cancer-related distresses, (2) inadequate social support, and (3) forgetfulness, together with seven subthemes, representing factors impeding patients' medication adherence. The themes demonstrate complicated and interrelated factors from personal, interpersonal, sociocultural, and structural forces contributing to patients' poor adherence. IMPLICATIONS FOR NURSING PRACTICE The findings suggest the imperativeness of reinforcing community- or home-based oral-targeted medication management in which nurses play a principal role to implement strategies of patient education, symptom management, reminder prompts, and monitoring to improve adherence.
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Affiliation(s)
- Ting Liu
- School of Nursing, Qingdao University, Qingdao, Shandong, China
| | - Ning Li
- Department of Thoracic Surgery, Linyi Cancer Hospital, Linyi, Shandong, China
| | - Cuiping Liu
- School of Nursing, Shandong First Medical University, Shandong Academy of Medical Sciences, Qingdao, Shandong, China
| | - Xiuxin Miao
- School of Nursing, Qingdao University, Qingdao, Shandong, China.
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Identification and Validation of a Novel Necroptosis-Related Long Noncoding RNA Prognostic Signature for Lung Adenocarcinoma. BIOMED RESEARCH INTERNATIONAL 2022; 2022:9710540. [PMID: 36330457 PMCID: PMC9626207 DOI: 10.1155/2022/9710540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 07/24/2022] [Accepted: 10/07/2022] [Indexed: 11/17/2022]
Abstract
Background Several cancers, including lung adenocarcinoma (LUAD), are caused by genes related to necroptosis. However, it is still unknown how necroptosis-related long noncoding RNAs (lncRNAs) may be involved in LUAD. In order to predict the prognosis of LUAD patients and personalize immunotherapy, this study set out to construct a necroptosis-related lncRNA prognostic signature (NLPS). Methods The Cancer Genome Atlas (TCGA) database was used to download the LUAD transcriptome data and the associated clinical data. lncRNAs associated with necroptosis were screened using coexpression analysis. An NLPS was built using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The Gene Expression Omnibus (GEO) database's GSE30219 was used to validate the NLPS. The prognostic value of the risk score was assessed using Kaplan-Meier survival, receiver operating characteristic (ROC) Cox regression, multivariate Cox regression, and nomogram analyses. Then, we looked into the differences between the low- and high-risk groups in the tumor immune microenvironment, immunotherapy response, and half-maximal inhibitory concentration (IC50). Results The 14 lncRNAs in a novel NLPS were created. With further validation in the GSE30219 dataset, the risk score according to the NLPS was an independent prognostic indicator for LUAD patients. Patients with better overall survival (OS) in the low-risk group, who were characterized by increased immune cell infiltration, tumor mutational burden (TMB), and immunophenoscore (IPS), may have hot tumors and higher immunotherapy response rates. In addition, the risk score was also closely linked to sensitivity to various anticancer medications. Conclusions We constructed a novel NLPS that could predict OS and sensitivity to immunotherapy in LUAD patients.
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Yuan J, Sun Y, Xu F, Li M, Fan M, Zhang C, Wang K, Li H, Bu X, Yan X, Wang J, Ma J, Zhang G, Chen M, Ren H. Cost-effectiveness of lung cancer screening combined with nurse-led smoking cessation intervention: A population-based microsimulation study. Int J Nurs Stud 2022; 134:104319. [DOI: 10.1016/j.ijnurstu.2022.104319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 05/17/2022] [Accepted: 06/25/2022] [Indexed: 10/17/2022]
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Zhang M, He X, Wu J, Wang X, Jiang Q, Xie F. How Do Treatment Preferences of Patients With Cancer Compare With Those of Oncologists and Family Members? Evidence From a Discrete Choice Experiment in China. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2022; 25:1768-1777. [PMID: 35710892 DOI: 10.1016/j.jval.2022.05.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 03/29/2022] [Accepted: 05/02/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES This study aimed to compare the treatment preference among oncologists, patients with lung cancer, and their family members in China. METHODS A face-to-face discrete choice experiment survey was conducted among oncologists, patients, and their family members. Participants completed 13 choice sets describing 6 key attributes, namely, overall survival time, risk of severe adverse effect, severity of pain, appetite, physical functioning status, and monthly cost. Mixed logit model and latent class analysis were used to estimate attribute level preference weights and the relative importance (RI) for attributes. The willingness to pay (WTP) and maximum acceptable risk (MAR) were also estimated. The RI, WTP, and MAR of oncologists, patients, and family members were compared. RESULTS A total of 121 oncologists and 161 dyads of patients and family members completed the survey. Overall survival time, physical functioning status, and pain were the 3 most important attributes across all 3 groups. Oncologists and family members had higher RI on overall survival time than patients (48% and 51% vs 38%). Patients had higher RI on physical functioning status and pain (23% and 14%) than oncologists (13% and 12%) and family members (16% and 11%). For extending survival, patients had the least WTP, and family members had the highest MAR. The latent class analysis identified 2 classes in the patient group and 3 classes in oncologist and family member groups. CONCLUSIONS There were differences in preferences for survival, risk, quality of life, and costs associated with cancer treatments among patients, oncologists, and family members. This finding highlights the need of involving patients in treatment decision making in China.
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Affiliation(s)
- Mengqian Zhang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China; Center for Social Science Survey and Data, Tianjin University, Tianjin, China
| | - Xiaoning He
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China; Center for Social Science Survey and Data, Tianjin University, Tianjin, China.
| | - Jing Wu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China; Center for Social Science Survey and Data, Tianjin University, Tianjin, China.
| | - Xinyue Wang
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China; Department of Thoracic Oncology, Tianjin Lung Cancer Center, Tianjin Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Qian Jiang
- Department of Clinical Pharmacy, Sichuan Cancer Hospital & Institute, Sichuan Cancer Centre, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Xie
- Department of Health Research Methods, Evidence and Impact and Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, ON, Canada
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Chen H, Xu S, Hu Z, Wei Y, Zhu Y, Fang S, Pan Q, Liu K, Li N, Zhu L, Xu G. Bioinformatics algorithm for lung adenocarcinoma based on macropinocytosis-related long noncoding RNAs as a reliable indicator for predicting survival outcomes and selecting suitable anti-tumor drugs. Medicine (Baltimore) 2022; 101:e30543. [PMID: 36197217 PMCID: PMC9509037 DOI: 10.1097/md.0000000000030543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
As a highly conserved endocytic mechanism during evolution, macropinocytosis is enhanced in several malignant tumors, which promotes tumor growth by ingesting extracellular nutrients. Recent research has emphasized the crucial role of macropinocytosis in tumor immunity. In the present study, we established a new macropinocytosis-related algorithm comprising molecular subtypes and a prognostic signature, in which patients with lung adenocarcinoma (LUAD) were classified into different clusters and risk groups based on the expression of 16 macropinocytosis-related long noncoding RNAs. According to the molecular subtypes, we discovered that patients with LUAD in cluster1 had a higher content of stromal cells and immune cells, stronger intensity of immune activities, higher expression of PD1, PDL1, and HAVCR2, and a higher tumor mutational burden, while patients in cluster2 exhibited better survival advantages. Furthermore, the constructed prognostic signature revealed that low-risk patients showed better survival outcomes, earlier tumor stage, higher abundance of stromal cells and immune cells, higher immune activities, higher expression of PD1, PDL1, CTLA4, and HAVCR2, and more sensitivity to Paclitaxel and Erlotinib. By contrast, patients with high scores were more suitable for Gefitinib treatment. In conclusion, the novel algorithm that divided patients with LUAD into different groups according to their clusters and risk groups, which could provide theoretical support for predicting their survival outcomes and selecting drugs for chemotherapy, targeted therapy, and immunotherapy.
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Affiliation(s)
- Hang Chen
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Shuguang Xu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Zeyang Hu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Yiqing Wei
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Youjie Zhu
- Department of Respiratory Medicine, Ningbo Huamei Hospital, Chinese Academy of Sciences, Ningbo, Zhejiang, China
| | - Shenzhe Fang
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Qiaoling Pan
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Kaitai Liu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Ni Li
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Linwen Zhu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Guodong Xu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China
- *Correspondence: Guodong Xu, Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China (e-mail: )
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Li R, Luo L, Tao W, Huang W, Bao T. Level of knowledge on low-dose CT lung cancer screening in Sichuan province, China: a cross-sectional study. BMJ Open 2022; 12:e061987. [PMID: 36127104 PMCID: PMC9490565 DOI: 10.1136/bmjopen-2022-061987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVES Low-dose CT (LDCT) can help determine the early stage of lung cancer and reduce mortality. However, knowledge of lung cancer and lung cancer screening among community residents and medical workers, and potential factors that may affect medical institutions to set up LDCT are limited. DESIGN A cross-sectional study was conducted in Sichuan province, China, in 2021. Community residents, medical workers and medical institutions were randomly selected, and participants responded to related questionnaires. Knowledge of lung cancer and LDCT lung cancer screening was evaluated. Data analyses were performed using SAS V.9.4. RESULTS A total of 35 692 residents, 6350 medical workers and 81 medical institutions were recruited; 4.05% of the residents were very familiar with lung cancer and 37.89% were (completely) unfamiliar. Characteristics, such as age and level of education, were significantly related to residents who were very familiar with lung cancer. Furthermore, 22.87% of the residents knew that LDCT can effectively screen for early-stage lung cancer, which was correlated with smoking (OR 1.1300; 95% CI 1.0540 to 1.2110; p=0.006) and family history of cancer (OR 1.2210; 95% CI 1.1400 to 1.3080; p<0.0001); 66.06% of medical workers believed that LDCT can detect early-stage lung cancer. Technicians and nurses were less knowledgeable than doctors about whether LDCT can effectively screen for early-stage lung cancer (OR 0.6976; 95% CI 0.5399 to 0.9015; p=0.0059 and OR 0.6970; 95% CI 0.5718 to 0.8496; p=0.0004, respectively). Setting up LDCT in medical institutions was related to grade, administrative rank, number of hospital beds that opened and total number of medical workers. CONCLUSIONS The knowledge of lung cancer in residents is relatively low, and the knowledge of LDCT in screening (early-stage) lung cancer needs to be improved both in residents and medical workers. Possible factors that affect medical institutions to set up LDCT may need to be incorporated.
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Affiliation(s)
- Ruicen Li
- Department of Industrial Engineering and Engineering Management, Sichuan University, Chengdu, Sichuan, China
- Health Management Center, West China Hospital, Sichuan University, Chengdu, China
| | - Li Luo
- Department of Industrial Engineering and Engineering Management, Sichuan University, Chengdu, Sichuan, China
| | - Wenjuan Tao
- Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, China
| | - Wenxia Huang
- Department of Healthcare, West China Hospital, Sichuan University, Chengdu, China
| | - Ting Bao
- Health Management Center, West China Hospital, Sichuan University, Chengdu, China
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30
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Wang C, Yu Q, Song T, Wang Z, Song L, Yang Y, Shao J, Li J, Ni Y, Chao N, Zhang L, Li W. The heterogeneous immune landscape between lung adenocarcinoma and squamous carcinoma revealed by single-cell RNA sequencing. Signal Transduct Target Ther 2022; 7:289. [PMID: 36008393 PMCID: PMC9411197 DOI: 10.1038/s41392-022-01130-8] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 05/23/2022] [Accepted: 07/25/2022] [Indexed: 11/30/2022] Open
Abstract
A thorough interrogation of the immune landscape is crucial for immunotherapy strategy selection and prediction of clinical responses in non-small-cell lung cancer (NSCLC) patients. Single-cell RNA sequencing (scRNA-seq) techniques have prompted the opportunity to dissect the distinct immune signatures between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), the two major subtypes of NSCLC. Here, we performed scRNA-seq on 72,475 immune cells from 40 samples of tumor and matched adjacent normal tissues spanning 19 NSCLC patients, and drew a systematic immune cell transcriptome atlas. Joint analyses of the distinct cellular compositions, differentially expressed genes (DEGs), cell–cell interactions, pseudotime trajectory, transcriptomic factors and prognostic factors based on The Cancer Genome Atlas (TCGA), revealed the central roles of cytotoxic and effector T and NK cells and the distinct functional macrophages (Mφ) subtypes in the immune microenvironment heterogeneity between LUAD and LUSC. The dominant subtype of Mφ was FABP4-Mφ in LUAD and SPP1-Mφ in LUSC. Importantly, we identified a novel lymphocyte-related Mφ cluster, which we named SELENOP-Mφ, and further established its antitumor role in both types, especially in LUAD. Our comprehensive depiction of the immune heterogeneity and definition of Mφ clusters could help design personalized treatment for lung cancer patients in clinical practice.
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Affiliation(s)
- Chengdi Wang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China.
| | - Qiuxiao Yu
- National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 518116, Shenzhen, China
| | - Tingting Song
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Zhoufeng Wang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Lujia Song
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Ying Yang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Jun Shao
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Jingwei Li
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Yinyun Ni
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Ningning Chao
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China
| | - Li Zhang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China.
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Center of Precision Medicine, Precision Medicine Key Laboratory of Sichuan Province, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, 610041, Chengdu, China.
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Yan Q, Hu B, Chen H, Zhu L, Lyu Y, Qian D, Shao G. A novel algorithm for lung adenocarcinoma based on N6 methyladenosine-related immune long noncoding RNAs as a reliable biomarker for predicting survival outcomes and selecting sensitive anti-tumor therapies. J Clin Lab Anal 2022; 36:e24636. [PMID: 35949000 PMCID: PMC9459339 DOI: 10.1002/jcla.24636] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Revised: 07/19/2022] [Accepted: 07/20/2022] [Indexed: 11/25/2022] Open
Abstract
Background Lung cancer is a highly heterogeneous malignant tumor with high incidence and mortality. Recently, increasing evidence has demonstrated that N6‐methyladenosine (m6A) methylation and the tumor microenvironment (TME) play important roles in the occurrence and development of lung adenocarcinoma (LUAD). Methods In this study, we constructed a novel and reliable algorithm based on m6A‐related immune lncRNAs (mrilncRNAs), consisting of molecular subtypes and a prognostic signature. Results According to the analyses of molecular subtypes, patients in cluster 1 were in a more advanced stage, showed poor prognosis, were sensitive to immunotherapy (anti‐programmed cell death 1 Ligand 1 (PD‐L1) and anti‐lymphocyte activating 3 (LAG‐3)), and had a highest tumor mutational burden (TMB), while anti‐cytotoxic T‐lymphocyte‐associated protein 4 (CTLA‐4) therapy seemed to be a good choice for patients in cluster 3. Subsequently, the results of the risk assessment model indicated that the low‐risk patients exhibited a survival advantage, had an earlier stage, and showed a higher response to common anti‐cancer drugs, including chemotherapy (Docetaxel, Paclitaxel), molecular targeted therapy (Erlotinib), and immunotherapy (anti‐CTLA‐4 therapy), while Gefitinib could be a good choice for patients with high‐risk scores. Conclusion In conclusion, the constructed algorithm exhibits promising practical prospects, and allows the selection of suitable and sensitive anti‐cancer drugs, which could provide theoretical support to predict the survival outcomes of patients with LUAD.
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Affiliation(s)
- Qiuwen Yan
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
| | - Bingchuan Hu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
| | - Hang Chen
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
| | - Linwen Zhu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
| | - Yao Lyu
- Department of Pharmacy, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
| | - Dingding Qian
- Department of Cardiology, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
| | - Guofeng Shao
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, People's Republic of China
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Xu G, Chen H, Wu S, Chen J, Zhang S, Shao G, Sun L, Mu Y, Liu K, Pan Q, Li N, An X, Lin S, Chen W. Eukaryotic initiation factor 5A2 mediates hypoxia-induced autophagy and cisplatin resistance. Cell Death Dis 2022; 13:683. [PMID: 35931669 PMCID: PMC9356061 DOI: 10.1038/s41419-022-05033-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 06/16/2022] [Accepted: 06/17/2022] [Indexed: 01/21/2023]
Abstract
Hypoxia-induced cisplatin resistance is a major challenge during non-small cell lung cancer (NSCLC) treatment. Based on previous studies, we further explored the effect of eukaryotic initiation factor 5A2 (eIF5A2) in hypoxia-induced cisplatin resistance. In this study, we found that autophagy and cisplatin resistance were increased under hypoxic conditions in three different NSCLC cell lines. Compared with that under normoxic conditions, dramatic upregulation of eIF5A2 and hypoxia inducible factor 1 subunit alpha (HIF-1α) levels were detected under hypoxia exposure. Small interfering RNA silencing of HIF-1α resulted in decreased expression of eIF5A2, indicating that eIF5A2 acts downstream of HIF-1α. In addition, the expression of eIF5A2 was significantly higher in NSCLC tumors compared with that in normal tissues. RNA silencing-mediated downregulation of eIF5A2 decreased hypoxia-induced autophagy, thereby reducing hypoxia-induced cisplatin resistance in NSCLC cells. The roles of eIF5A2 in cisplatin resistance were further validated in vivo. Combined treatment using eIF5A2-targeted downregulation together with cisplatin significantly inhibited tumor growth compared with cisplatin alone in the subcutaneous mouse model. In conclusions, eIF5A2 overexpression is involved in hypoxia-induced autophagy during cisplatin resistance. We suggest that a combination of eIF5A2 targeted therapy and cisplatin chemotherapy is probably an effective strategy to reverse hypoxia-induced cisplatin resistance and inhibit NSCLC development.
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Affiliation(s)
- Guodong Xu
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Hang Chen
- grid.203507.30000 0000 8950 5267Medical School, Ningbo University, Ningbo, PR China
| | - Shibo Wu
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Jiabin Chen
- grid.417168.d0000 0004 4666 9789Department of Oncology, Tongde Hospital of Zhejiang Province, Hangzhou, PR China
| | - Shufen Zhang
- Cancer Institute of Integrated Traditional Chinese and Western Medicine, Zhejiang Academy of Traditional Chinese Medicine, Tongde Hospital of Zhejiang Province, Hangzhou, PR China
| | - Guofeng Shao
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Lebo Sun
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Yinyu Mu
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Kaitai Liu
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Qiaoling Pan
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Ni Li
- grid.203507.30000 0000 8950 5267Department of Cardiothoracic Surgery, the Affiliated Lihuili Hospital, Ningbo University, Ningbo, PR China
| | - Xiaoxia An
- grid.452661.20000 0004 1803 6319Department of Anesthesiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang China
| | - Shuang Lin
- grid.452661.20000 0004 1803 6319Department of Thoracic Surgery, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang China
| | - Wei Chen
- Cancer Institute of Integrated Traditional Chinese and Western Medicine, Zhejiang Academy of Traditional Chinese Medicine, Tongde Hospital of Zhejiang Province, Hangzhou, PR China
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Chen T, Xie R, Zhao Q, Cai H, Yang L. Cost-Utility Analysis of Camrelizumab Plus Chemotherapy Versus Chemotherapy Alone as a First-Line Treatment for Advanced Nonsquamous Non-Small Cell Lung Cancer in China. Front Oncol 2022; 12:746526. [PMID: 35936702 PMCID: PMC9353739 DOI: 10.3389/fonc.2022.746526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 06/06/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose To evaluate the cost utility of camrelizumab plus standard chemotherapy versus standard chemotherapy alone as a first-line treatment for advanced nonsquamous non-small cell lung cancer (NSCLC) from the perspective of the Chinese health care system and to provide a reference for health decision-making. Methods A Markov model consisting of three health states was designed to evaluate the cost utility of these two treatment regimens for NSCLC patients with the incremental cost-effectiveness ratio (ICER) as the primary output indicator. Clinical data were derived from a published phase III clinical trial (CameL; ClinicalTrials.gov; NCT03134872). One-way sensitivity analysis and probabilistic sensitivity analysis were performed to assess the model uncertainty. Results Base case analysis showed that the ICER of camrelizumab plus chemotherapy compared with chemotherapy alone was $43,275.43 per QALY. It was higher than the willingness-to-pay (WTP) threshold of $31,510.57 per QALY in China, which has a standard of three times the GDP per capita recommended by the WHO. One-way sensitivity analysis showed that the utility value of PFS had the greatest influence on the results, and the other sensitive parameters were the cost of subsequent second-line therapy in the two group, the pemetrexed price, the cost of adverse event management and the utility value of PD. The probability sensitivity analysis showed that the probabilities of the cost-effectiveness of camrelizumab plus standard chemotherapy were 27.1%, 66.7% and 88.0% when the WTP values were $40,000, $50,000 and $60,000 per QALY, respectively. Conclusions Taking three times the GDP per capita in China as the WTP threshold, the camrelizumab plus standard chemotherapy regimen does not have a cost-effectiveness advantage compared with the standard chemotherapy regimen alone as a first-line treatment for advanced NSCLC.
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Affiliation(s)
- Ting Chen
- Department of Pharmacy, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China
| | - Ruixiang Xie
- Department of Pharmacy, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China
| | - Qiuling Zhao
- Department of Pharmacy, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China
| | - Hongfu Cai
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China
| | - Lin Yang
- Department of Pharmacy, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China
- *Correspondence: Lin Yang,
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Shi Y, Zhang X, Wu G, Xu J, He Y, Wang D, Huang C, Chen M, Yu P, Yu Y, Li W, Li Q, Hu X, Xia J, Bu L, Yin A, Zhou Y. Treatment strategy, overall survival and associated risk factors among patients with unresectable stage IIIB/IV non-small cell lung cancer in China (2015-2017): A multicentre prospective study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 23:100452. [PMID: 35465042 PMCID: PMC9019386 DOI: 10.1016/j.lanwpc.2022.100452] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
BACKGROUND There are limited studies on treatment and survival analysis among patients with unresectable Stage IIIB or IV non-small cell lung cancer (NSCLC) in routine practice in China. To address this gap, we conducted a prospective observational study in a cohort of patients treated at 11 hospitals in China. METHODS This was a multicentre, prospective cohort study including patients with newly diagnosed unresectable Stage IIIB or IV NSCLC from June 26th, 2015 to April 28th, 2017. Patient baseline characteristics, disease characteristics, and anti-cancer treatments were obtained by medical chart review. The overall survival (OS) from the initiation of first-line treatment was analysed by the Kaplan-Meier method. Factors associated with survival were analysed by univariate and multivariate Cox regression models. FINDINGS Among 1324 patients enrolled with median follow-up duration of 15·0 (range: 0·0-42·1) months, 83·5% (1105/1324) of them received first-line chemotherapy of which platinum-based compounds were the dominated agents. Overall, 30·9% (409/1324) of patients received targeted therapy as 1st-line treatment including 65·0% (266/409) EGFR-TKIs and 5·1% (21/409) ALK-TKIs. Of all eligible patients, gene testing rates were 44·0% (583/1324) for EGFR mutations, 17·0% (225/1324) for EML4-ALK gene fusions, and 8·3% (110/1324) for ROS1 gene fusions. The EGFR-TKIs were administered to 63·9% (179/280) of EGFR mutated patients as first-line treatment. The overall median OS was 23·2 (95%CI 19·5-25·5) months, and patients treated at tier 1 cities had better OS than that of tier 2 cities. Also, the OS in patients with EGFR mutation was longer than those with EGFR wild type. Multivariate Cox regression models suggested that male, education below high school, tier 2 cities, smoking history, and multiple metastases were associated with poor survival. INTERPRETATION The gene test coverage was relatively low among the studied population, and over half of EGFR mutated patients received EGFR-TKIs, suggesting that the result of genetic tests in real-world settings may not always indicate the selection of treatment. The OS benefit observed from patients treated in tier 1 cities and those with EGFR mutation may indicate a need for broader gene test coverage, providing NSCLC patients with personalized treatment according to the results of genetic tests. FUNDING Roche Holding AG.TRANSLATED ABSTRACT: This translation in Chinese was submitted by the authors and we reproduce it as supplied. It has not been peer reviewed. Our editorial processes have only been applied to the original abstract in English, which should serve as reference for this manuscript.:IIIBIV(NSCLC)., ,, 11.:,, 20156262017428IIIBIVNSCLC.,.Kaplan-Meier(OS), Cox.:1324, 15.0(:0.0-42.1), 83.5%(1105/1324), ., 30.9%(409/1324), 65.0%(266/409)EGFR-TKI5.1%(21/409)ALK-TKI., EGFR,EML4-ALKROS144.0%(583/1324),17.0%(225/1324)8.3%(110/1324).63.9%(179/280)EGFREGFR-TKI.23.2 (95% 19·5-25·5) , ., EGFREGFR.Cox, ,,,.:, EGFREGFR-TKI, , .EGFR, , NSCLC.
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Affiliation(s)
- Yuankai Shi
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
- Corresponding author.
| | - Xin Zhang
- Respiratory Diseases Department, Zhongshan Hospital Fudan University, Shanghai, China
| | - Gang Wu
- Cancer Center, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianping Xu
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Yong He
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Dong Wang
- Cancer Center, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Cheng Huang
- Department of Medical Oncology, Fujian Cancer Hospital, Fuzhou, China
| | - Mingwei Chen
- Department of Respiratory and Critical Care Medicine, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ping Yu
- Department of Thoracic Oncology, Sichuan Cancer Hospital, Chengdu, China
| | - Yan Yu
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Wei Li
- Cancer Center, The First Hospital of Jilin University, Changchun, China
| | - Qi Li
- Department of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaohua Hu
- Department of Medical Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jinjing Xia
- Department of Medical Science Oncology, Shanghai Roche Pharmaceuticals Ltd., Shanghai, China
| | - Lilian Bu
- Department of Medical Science Oncology, Shanghai Roche Pharmaceuticals Ltd., Shanghai, China
| | - Angela Yin
- Real World Solutions, IQVIA, Beijing, China
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Xu Y, Chai B, Wang X, Wu Z, Gu Z, Liu X, Zhao Y, Chen T, Ma Z, Sun Q. miRNA-199a-5p/SLC2A1 axis regulates glucose metabolism in non-small cell lung cancer. J Cancer 2022; 13:2352-2361. [PMID: 35517408 PMCID: PMC9066207 DOI: 10.7150/jca.67990] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 03/06/2022] [Indexed: 12/22/2022] Open
Abstract
Lung cancer is acknowledged as a common cancer with high morbidity and mortality. MicroRNAs (miRNAs), kind of non-coding single-stranded RNA molecules, can be used in cancer clinical treatments. In this research, miR-199a-5p was seen lowly expressed in NSCLC sera samples. miR-199a-5p suppressed the cell proliferation, migration and arrested cell cycle in NSCLC cell lines. The results showed that SLC2A1 (glucose transporter 1, GLUT1) was a direct target of miR-199a-5p. Downregulation of SLC2A1 could not only inhibit cell proliferation, migration and cell cycle, but also promote cell apoptosis. The data suggests that miR-199a-5p can inhibit glucose metabolism in NSCLC by targeting SLC2A1.This study proves that miR-199a-5p / SLC2A1 can play an essential role in the development of NSCLC by targeting SLC2A1. It puts forward a new approach for clinical treatments of NSCLC.
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Affiliation(s)
- Yikun Xu
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China
| | - Binshu Chai
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China
| | - Xianyi Wang
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China
| | - Zong Wu
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China
| | - Zhitao Gu
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Xiaomin Liu
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China.,Shanghai New Tobacco Product Research Institute, Shanghai, 201315, China
| | - Yiqi Zhao
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China
| | - Tangbing Chen
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Zhongliang Ma
- Lab for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, 200444, China
| | - Qiangling Sun
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.,Thoracic Cancer institute, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China
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Zhao Z, Wang Y, Wu W, Yang Y, Du L, Dong H. Cost-effectiveness of Low-Dose Computed Tomography With a Plasma-Based Biomarker for Lung Cancer Screening in China. JAMA Netw Open 2022; 5:e2213634. [PMID: 35608858 PMCID: PMC9131747 DOI: 10.1001/jamanetworkopen.2022.13634] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
IMPORTANCE China, which has one-third of the worldwide smoking population, has a substantial cancer burden, with lung cancer being the leading cause of cancer-related death. The effectiveness of lung cancer screening for mortality reduction has been confirmed, but the cost-effectiveness of diverse screening modalities remains unclear. OBJECTIVE To compare the cost-effectiveness of low-dose computed tomography (LDCT) with a biomarker (micro-RNA signature classifier [MSC]) with that of LDCT alone by screening interval and cumulative smoking exposure. DESIGN, SETTING, AND PARTICIPANTS In this economic evaluation, a comparative cost-effectiveness analysis used Markov state transition models that simulated the 1947 to 1971 China birth cohort. Simulated individuals in 8 cohorts of 10 000 entered the study between ages 50 and 74 years and were followed up until death or age 79 years, corresponding to a study period from January 1, 2021, to December 31, 2050. The model was run with a cycle length of 1 year. All the transition probabilities were validated, and health utility values were extracted from published literature. Cost parameters were derived from the databases of local medical insurance bureaus. MAIN OUTCOMES AND MEASURES Primary outcomes included life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) with future costs and outcomes discounted by 5%. Screening strategies with a mean ICER less than Chinese yuan (CNY) 212 676 per QALY gained were deemed to be cost-effective. The cost-effectiveness of 7 alternative screening strategies with a screening starting age of 50 years, minimum cumulative smoking exposure of 20 vs 30 pack-years, and screening interval of annual vs 1 time was estimated, including the 2021 China guideline-recommended strategy (LDCT, annual, 30 pack-years) and the 2018 China guideline-recommended strategy (LDCT, annual, 20 pack-years). RESULTS In a simulated population of 80 000 individuals, the conjunctive LDCT and MSC screening strategy was estimated to obtain an ICER of CNY -793 995.17 to 254 417.46 (minimum cumulative smoking exposure, 20-30 pack-years) per QALY gained compared with LDCT screening alone. China's 2021 guideline-recommended strategy was not cost-effective compared with the 2018 guideline-recommended strategy, with higher costs and fewer QALYs gained; the QALY loss ranged from 0.02 to 0.15 per person and the increase in cost ranged from CNY 945.89 to CNY 5131.29 per person. LDCT and MSC screening beginning at age 70 to 74 years in individuals with a 20 pack-year smoking history was the most cost-effective strategy, with an ICER of CNY -793 995.17 per QALY gained. Lowering the minimum cumulative smoking exposure for screening from 30 to 20 pack-years and maintaining annual screening were associated with greater cost savings regardless of the screening tool. CONCLUSIONS AND RELEVANCE This economic evaluation found that China's 2018 recommendation for lung cancer screening was more cost-effective than the 2021 recommendation. Moreover, the cost-effectiveness of lung cancer screening was improved when MSC was included with LDCT. These findings may be useful for the modification of guidelines for lung cancer screening.
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Affiliation(s)
- Zixuan Zhao
- Center for Health Policy Studies, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China
| | - Youqing Wang
- Department of Cancer Prevention, Cancer Hospital of the University of the Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Weijia Wu
- Center for Health Policy Studies, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Yang
- Center for Health Policy Studies, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China
| | - Lingbin Du
- Department of Cancer Prevention, Cancer Hospital of the University of the Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Hengjin Dong
- Center for Health Policy Studies, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China
- The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
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Chen H, Zhou C, Hu Z, Sang M, Ni S, Wu J, Pan Q, Tong J, Liu K, Li N, Zhu L, Xu G. Construction of an algorithm based on oncosis-related LncRNAs comprising the molecular subtypes and a risk assessment model in lung adenocarcinoma. J Clin Lab Anal 2022; 36:e24461. [PMID: 35476781 PMCID: PMC9169186 DOI: 10.1002/jcla.24461] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 12/12/2022] Open
Abstract
Background As an important non‐apoptotic cell death method, oncosis has been reported to be closely associated with tumors in recent years. However, few research reported the relationship between oncosis and lung cancer. Methods In this study, we established an oncosis‐based algorithm comprised of cluster grouping and a risk assessment model to predict the survival outcomes and related tumor immunity of patients with lung adenocarcinomas (LUAD). We selected 11 oncosis‐related lncRNAs associated with the prognosis (CARD8‐AS1, LINC00941, LINC01137, LINC01116, AC010980.2, LINC00324, AL365203.2, AL606489.1, AC004687.1, HLA‐DQB1‐AS1, and AL590226.1) to divide the LUAD patients into different clusters and different risk groups. Compared with patients in clsuter1, patients in cluster2 had a survival advantage and had a relatively more active tumor immunity. Subsequently, we constructed a risk assessment model to distinguish between patients into different risk groups, in which low‐risk patients tend to have a better prognosis. GO enrichment analysis revealed that the risk assessment model was closely related to immune activities. In addition, low‐risk patients tended to have a higher content of immune cells and stromal cells in tumor microenvironment, higher expression of PD‐1, CTLA‐4, HAVCR2, and were more sensitive to immune checkpoint inhibitors (ICIs), including PD‐1/CTLA‐4 inhibitors. The risk score had a significantly positive correlation with tumor mutation burden (TMB). The survival curve of the novel oncosis‐based algorithm suggested that low‐risk patients in cluster2 have the most obvious survival advantage. Conclusion The novel oncosis‐based algorithm investigated the prognosis and the related tumor immunity of patients with LUAD, which could provide theoretical support for customized individual treatment for LUAD patients.
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Affiliation(s)
- Hang Chen
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Chongchang Zhou
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Zeyang Hu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Menglu Sang
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Saiqi Ni
- Department of Urology, Ningbo City First Hospital, Ningbo, China
| | - Jiacheng Wu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Qiaoling Pan
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Jingtao Tong
- Department of Radiation Oncology, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Kaitai Liu
- Department of Radiation Oncology, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Ni Li
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Linwen Zhu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Guodong Xu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
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Cancer Burden in China during 1990–2019: Analysis of the Global Burden of Disease. BIOMED RESEARCH INTERNATIONAL 2022; 2022:3918045. [PMID: 35463971 PMCID: PMC9023157 DOI: 10.1155/2022/3918045] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Accepted: 04/01/2022] [Indexed: 02/08/2023]
Abstract
This study reports the risk factors, trends, and burden of cancer in China from 1990 to 2019 from the Global Burden of Diseases. The incidence, mortality, and DALY of all cancers in China for the past 30 years were analyzed. In 2019, the age-standardized rates (ASRs) of cancer incidence, mortality, and DALY in China were 232.42/100 000, 136.72/100 000, and 3288.22/100 000, respectively. The five cancers with the highest age-standardized incidence rates were lung, stomach, colorectal, breast, and prostate cancers. From 1990 to 2019, the number of new cancer cases, deaths, and DALY increased by 168.78%, 86.89%, and 51.20%, respectively. The ASR increased by 22.21% for incidence and decreased by 19.01% and 27.19% for mortality and DALY, respectively, and their corresponding average annual percent change values were 0.71, -0.80, and -1.26, respectively. The main risk factors for cancer in China were smoking, air pollution, dietary factors, and alcohol use. From 1990 to 2019, the cancer incidence rate was on the rise, and cancer mortality and DALY rates were declining; however, these characteristics vary by cancer site. Therefore, current prevention strategies should be reoriented, and specific strategies for cancers in different sites should be established to prevent the increase in cancer cases.
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Shen W, Tong D, Chen J, Li H, Hu Z, Xu S, He S, Ge Z, Zhang J, Mao Q, Chen H, Xu G. Silencing oncogene cell division cycle associated 5 induces apoptosis and G1 phase arrest of non‐small cell lung cancer cells via p53‐p21 signaling pathway. J Clin Lab Anal 2022; 36:e24396. [PMID: 35373420 PMCID: PMC9102649 DOI: 10.1002/jcla.24396] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 03/17/2022] [Accepted: 03/18/2022] [Indexed: 11/06/2022] Open
Affiliation(s)
- Wei Shen
- Department of Pulmonary and Critical Care Medicine The Third People’s Hospital of Cixi Ningbo Zhejiang China
| | - Dimin Tong
- Department of Pulmonary and Critical Care Medicine The Third People’s Hospital of Cixi Ningbo Zhejiang China
| | - Jie Chen
- Department of Pulmonary and Critical Care Medicine The Third People’s Hospital of Cixi Ningbo Zhejiang China
| | - Hongxiang Li
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Zeyang Hu
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Shuguang Xu
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Sufang He
- Department of Pulmonary and Critical Care Medicine Guangdong Provincial People's Hospital Ganzhou Hospital Ganzhou Jiangxi China
| | - Zhen Ge
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Jianan Zhang
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Qiqi Mao
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Hang Chen
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
| | - Guodong Xu
- Department of Cardiothoracic Surgery The Affiliated Lihuili Hospital Ningbo University Ningbo Zhejiang China
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Li N, Tan F, Chen W, Dai M, Wang F, Shen S, Tang W, Li J, Yu Y, Cao W, Xu Y, Qin C, Zhao L, Zhu M, Guo L, Wu Z, Yang Z, Zheng Y, Chen H, Liu Y, Wei D, Dong D, Cao J, Zhang S, Yan S, Wang N, Du L, Shen H, Wu N, He J. One-off low-dose CT for lung cancer screening in China: a multicentre, population-based, prospective cohort study. THE LANCET. RESPIRATORY MEDICINE 2022; 10:378-391. [PMID: 35276087 DOI: 10.1016/s2213-2600(21)00560-9] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 09/10/2021] [Accepted: 12/09/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Lung cancer is the leading cause of cancer death worldwide. Data on the effectiveness of one-off low-dose CT (LDCT) in reducing lung cancer mortality and all-cause mortality are needed to inform screening programmes in countries with limited medical resources. We aimed to evaluate the effectiveness of one-off LDCT screening in the early detection of lung cancer in China. METHODS A multicentre, population-based, prospective cohort study was done in 12 cities of eight provinces across China, recruiting individuals aged 40-74 years who were asymptomatic for lung cancer with no lung cancer history. Participants were classified as at high risk or low risk of lung cancer using a sex-specific risk score that incorporated cigarette smoking, level of physical activity, occupational exposures, history of chronic respiratory diseases, family history of lung cancer, diet, and passive smoking (women only). Participants at high risk were invited for a one-off LDCT scan and were classified into screened and non-screened groups on the basis of whether or not they had the scan. Lung cancer incidence density, lung cancer mortality, and all-cause mortality were calculated for the screened and non-screened groups. The effectiveness of a one-off LDCT scan was evaluated by a comparison of the screened and non-screened groups in terms of lung cancer mortality and all-cause mortality in the period from cohort entry until administrative censoring (June 20, 2020). Inverse probability weighting was adopted to account for potential imbalanced factors between the two groups and Cox proportional hazards model was used to estimate the weighted associations between mortality and one-off LDCT scans. FINDINGS Between Feb 19, 2013, and Oct 31, 2018, 1 032 639 individuals were assessed for eligibility. 1 016 740 participants were enrolled in the study, of whom 3581 had a lung cancer diagnosis after a median follow-up of 3·6 years (IQR 2·8-5·1). Among the 223 302 participants at high risk, 79 581 (35·6%) had an LDCT scan (screened group) and 143 721 (64·4%) did not (non-screened group). After inverse probability weighting, lung cancer incidence density was 47·0% higher (hazard ratio 1·47 [95% CI 1·27-1·70]; p<0·0001), lung cancer mortality was 31·0% lower (0·69 [95% CI 0·53-0·92]; p=0·010) and all-cause mortality was 32·0% lower (0·68 [0·57-0·82]; p<0·0001) for participants in the screened group compared with those in the non-screened group. INTERPRETATION One-off LDCT screening was associated with significantly lower lung cancer mortality and all-cause mortality in a large population in China. Our results point to the promise of one-off LDCT screening in countries with limited medical resources. Further studies are needed to explore interactions by subgroup-including sex, age, smoking status, and economic status-to develop population-specific screening strategies. FUNDING Ministry of Finance and National Health Commission of the People's Republic of China. TRANSLATION For the Chinese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cancer Data Science, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fengwei Tan
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wanqing Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cancer Data Science, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Min Dai
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fei Wang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Sipeng Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Wei Tang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiang Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cancer Data Science, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yiwen Yu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Cao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yongjie Xu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chao Qin
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Liang Zhao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Lanwei Guo
- Henan Office for Cancer Control and Research, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Zheng Wu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhuoyu Yang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yadi Zheng
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongda Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yunyong Liu
- Liaoning Office for Cancer Control and Research, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, China
| | - Donghua Wei
- Office for Cancer Prevention and Control, Anhui Provincial Cancer Hospital, Hefei, China
| | - Dong Dong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou, China
| | - Ji Cao
- Cancer Prevention and Control Office, Cancer Hospital, Guangxi Medical University, Nanning, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Shipeng Yan
- Department of Cancer Prevention and Control, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Ning Wang
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education Beijing, Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital and Institute, Beijing, China
| | - Lingbin Du
- Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Ning Wu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; PET-CT Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Du Y, Li Y, Sidorenkov G, Vliegenthart R, Heuvelmans MA, Dorrius MD, Groen HJ, Liu S, Fan L, Ye Z, Greuter MJ, de Bock GH. Cost-effectiveness of lung cancer screening by low-dose CT in China: a micro-simulation study. JOURNAL OF THE NATIONAL CANCER CENTER 2022; 2:18-24. [PMID: 39035210 PMCID: PMC11256619 DOI: 10.1016/j.jncc.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 10/29/2021] [Accepted: 11/02/2021] [Indexed: 10/19/2022] Open
Abstract
Background The effectiveness of lung cancer screening with low-dose computed tomography (LDCT) has been established. The current study evaluates the cost-effectiveness of lung cancer screening with LDCT in a general population in China. Methods A previously validated micro-simulation model was used to simulate a cohort of men and women on a lifetime horizon in the presence and absence of LDCT screening. The modeling data were collected from numerous national and international sources. Simulated screening scenarios included different combinations of screening intervals and start and stop ages. Additional costs (valued in Chinese Yuan, CNY; 1 USD = 6.8976 CNY, 1 EUR = 7.8755 CNY in 2020), life-years gained (LYG) and mortality reduction due to screening were also determined. The costs and life-years were discounted by 3%. All results were scaled to 1,000 individuals. The average cost-effectiveness ratio (ACER) was calculated. A willingness-to-pay threshold of CNY 217.3k / LYG was considered. A healthcare system perspective was adopted. Results Compared to no screening, lung cancer screening by LDCT in a general Chinese population yielded 21.0 - 36.7 LYG in men and 9.2 - 16.6 LYG in women across the scenarios. For men, biennial LDCT screening yielded an ACER of CNY 171.4k - 306.3k / LYG relative to no screening. Biennial screening performed between 55 and 75 years of age was optimal at the defined threshold; it resulted in CNY 174.6k / LYG and a lung cancer mortality reduction of 9.1%, and this scenario had a 75% probability of being cost-effective. For women, the ACER ranged from CNY 364.2k to 1193.3k / LYG. Conclusions In China, lung cancer screening with LDCT in the general population including never smokers could be cost-effective for men with 75% probability, but not for women. The optimal strategy for men would be performing biennial screening between 55 and 75 years of age.
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Affiliation(s)
- Yihui Du
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Yanju Li
- Department of Radiology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Centre for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Grigory Sidorenkov
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Marjolein A. Heuvelmans
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Monique D. Dorrius
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Harry J.M. Groen
- Department of Pulmonary Diseases, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Shiyuan Liu
- Department of Radiology, Shanghai Changzheng Hospital, the Second Military Medical University, Shanghai, China
| | - Li Fan
- Department of Radiology, Shanghai Changzheng Hospital, the Second Military Medical University, Shanghai, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Centre for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Marcel J.W. Greuter
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Geertruida H. de Bock
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
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Wang C, Ma J, Shao J, Zhang S, Liu Z, Yu Y, Li W. Predicting EGFR and PD-L1 Status in NSCLC Patients Using Multitask AI System Based on CT Images. Front Immunol 2022; 13:813072. [PMID: 35250988 PMCID: PMC8895233 DOI: 10.3389/fimmu.2022.813072] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/17/2022] [Indexed: 12/23/2022] Open
Abstract
Background Epidermal growth factor receptor (EGFR) genotyping and programmed death ligand-1 (PD-L1) expressions are of paramount importance for treatment guidelines such as the use of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) in lung cancer. Conventional identification of EGFR or PD-L1 status requires surgical or biopsied tumor specimens, which are obtained through invasive procedures associated with risk of morbidities and may be unavailable to access tissue samples. Here, we developed an artificial intelligence (AI) system that can predict EGFR and PD-L1 status in using non-invasive computed tomography (CT) images. Methods A multitask AI system including deep learning (DL) module, radiomics (RA) module, and joint (JO) module combining the DL, RA, and clinical features was developed, trained, and optimized with CT images to predict the EGFR and PD-L1 status. We used feature selectors and feature fusion methods to find the best model among combinations of module types. The models were evaluated using the areas under the receiver operating characteristic curves (AUCs). Results Our multitask AI system yielded promising performance for gene expression status, subtype classification, and joint prediction. The AUCs of DL module achieved 0.842 (95% CI, 0.825–0.855) in the EGFR mutated status and 0.805 (95% CI, 0.779–0.829) in the mutated-EGFR subtypes discrimination (19Del, L858R, other mutations). DL module also demonstrated the AUCs of 0.799 (95% CI, 0.762–0.854) in the PD-L1 expression status and 0.837 (95% CI, 0.775–0.911) in the positive-PD-L1 subtypes (PD-L1 tumor proportion score, 1%–49% and ≥50%). Furthermore, the JO module of our AI system performed well in the EGFR and PD-L1 joint cohort, with an AUC of 0.928 (95% CI, 0.909–0.946) for distinguishing EGFR mutated status and 0.905 (95% CI, 0.886–0.930) for discriminating PD-L1 expression status. Conclusion Our AI system has demonstrated the encouraging results for identifying gene status and further assessing the genotypes. Both clinical indicators and radiomics features showed a complementary role in prediction and provided accurate estimates to predict EGFR and PD-L1 status. Furthermore, this non-invasive, high-throughput, and interpretable AI system can be used as an assistive tool in conjunction with or in lieu of ancillary tests and extensive diagnostic workups to facilitate early intervention.
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Affiliation(s)
- Chengdi Wang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Jiechao Ma
- AI Lab, Deepwise Healthcare, Beijing, China
| | - Jun Shao
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Shu Zhang
- AI Lab, Deepwise Healthcare, Beijing, China
| | | | - Yizhou Yu
- AI Lab, Deepwise Healthcare, Beijing, China
- Faculty of Engineering, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
- *Correspondence: Weimin Li, ; Yizhou Yu,
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
- *Correspondence: Weimin Li, ; Yizhou Yu,
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Li Y, Chen D, Wu X, Yang W, Chen Y. A narrative review of artificial intelligence-assisted histopathologic diagnosis and decision-making for non-small cell lung cancer: achievements and limitations. J Thorac Dis 2022; 13:7006-7020. [PMID: 35070383 PMCID: PMC8743410 DOI: 10.21037/jtd-21-806] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 12/01/2021] [Indexed: 12/12/2022]
Abstract
Objective To summarize the current evidence regarding the applications, workflow, and limitations of artificial intelligence (AI) in the management of patients pathologically-diagnosed with lung cancer. Background Lung cancer is one of the most common cancers and the leading cause of cancer-related deaths worldwide. AI technologies have been applied to daily medical workflow and have achieved an excellent performance in predicting histopathologic subtypes, analyzing gene mutation profiles, and assisting in clinical decision-making for lung cancer treatment. More advanced deep learning for classifying pathologic images with minimal human interactions has been developed in addition to the conventional machine learning scheme. Methods Studies were identified by searching databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, up to February 2021 without language restrictions. Conclusions A number of studies have evaluated AI pipelines and confirmed that AI is robust and efficacious in lung cancer diagnosis and decision-making, demonstrating that AI models are a useful tool for assisting oncologists in health management. Although several limitations that pose an obstacle for the widespread use of AI schemes persist, the unceasing refinement of AI techniques is poised to overcome such problems. Thus, AI technology is a promising tool for use in diagnosing and managing lung cancer.
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Affiliation(s)
- Yongzhong Li
- Department of Thoracic Surgery, the Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Donglai Chen
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, School of Medicine, Shanghai, China
| | - Xuejie Wu
- Department of Thoracic Surgery, the Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Wentao Yang
- Department of Thoracic Surgery, the Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yongbing Chen
- Department of Thoracic Surgery, the Second Affiliated Hospital of Soochow University, Suzhou, China
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Zhao Z, Du L, Li Y, Wang L, Wang Y, Yang Y, Dong H. Cost-Effectiveness of Lung Cancer Screening using Low-dose Computed Tomography in China: Policy Guidance Based on Start Age and Interval (Preprint). JMIR Public Health Surveill 2022; 8:e36425. [PMID: 35793127 PMCID: PMC9301557 DOI: 10.2196/36425] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 05/21/2022] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Background Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death in China. The effectiveness of screening for lung cancer has been reported to reduce lung cancer–specific and overall mortality, although the cost-effectiveness, optimal start age, and screening interval remain unclear. Objective This study aimed to assess the cost-effectiveness of lung cancer screening among heavy smokers in China by incorporating start age and screening interval. Methods A Markov state-transition model was used to assess the cost-effectiveness of a lung cancer screening program in China. The evaluated screening strategies were based on a screening start age of 50-74 years and a screening interval of once or annually. Transition probabilities were obtained from the literature and validated, while cost parameters were derived from databases of local medical insurance bureaus. A societal perspective was adopted. The outputs of the model included costs, quality-adjusted life years (QALYs), and lung cancer–specific mortality, with future costs and outcomes discounted by 5%. A currency exchange rate of 1 CNY=0.1557 USD is applicable. The incremental cost-effectiveness ratio (ICER) was calculated for different screening strategies relative to nonscreening. Results The proposed model suggested that screening led to a gain of 0.001-0.042 QALYs per person as compared with the findings in the nonscreening cohort. Meanwhile, one-time and annual screenings were associated with reductions in lung cancer–related mortality of 0.004%-1.171% and 6.189%-15.819%, respectively. The ICER ranged from 119,974.08 to 614,167.75 CNY per QALY gained relative to nonscreening. Using the World Health Organization threshold of 212,676 CNY per QALY gained, annual screening from a start age of 55 years and one-time screening from the age of 65 years can be considered as cost-effective in China. Deterministic and probabilistic sensitivity analyses were conducted. Conclusions This economic evaluation revealed that a population-based lung cancer screening program in China for heavy smokers using low-dose computed tomography was cost-effective for annual screening of smokers aged 55-74 years and one-time screening of those aged 65-74 years. Moreover, annual lung cancer screening should be promoted in China to realize the benefits of a guideline-recommended screening program.
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Affiliation(s)
- Zixuan Zhao
- Department of Science and Education of the Fourth Affiliated Hospital, Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Lingbin Du
- Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yuanyuan Li
- Department for Science and Education, Hangzhou Ninth People's Hospital, Hangzhou, China
| | - Le Wang
- Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Youqing Wang
- Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yi Yang
- Department of Science and Education of the Fourth Affiliated Hospital, Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Hengjin Dong
- Department of Science and Education of the Fourth Affiliated Hospital, Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
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Integrated single-cell RNA sequencing analysis reveals distinct cellular and transcriptional modules associated with survival in lung cancer. Signal Transduct Target Ther 2022; 7:9. [PMID: 35027529 PMCID: PMC8758688 DOI: 10.1038/s41392-021-00824-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 08/11/2021] [Accepted: 11/04/2021] [Indexed: 02/05/2023] Open
Abstract
Lung adenocarcinoma (LUAD) and squamous carcinoma (LUSC) are two major subtypes of non-small cell lung cancer with distinct pathologic features and treatment paradigms. The heterogeneity can be attributed to genetic, transcriptional, and epigenetic parameters. Here, we established a multi-omics atlas, integrating 52 single-cell RNA sequencing and 2342 public bulk RNA sequencing. We investigated their differences in genetic amplification, cellular compositions, and expression modules. We revealed that LUAD and LUSC contained amplifications occurring selectively in subclusters of AT2 and basal cells, and had distinct cellular composition modules associated with poor survival of lung cancer. Malignant and stage-specific gene analyses further uncovered critical transcription factors and genes in tumor progression. Moreover, we identified subclusters with proliferating and differentiating properties in AT2 and basal cells. Overexpression assays of ten genes, including sub-cluster markers AQP5 and KPNA2, further indicated their functional roles, providing potential targets for early diagnosis and treatment in lung cancer.
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Guo LW, Lyu ZY, Meng QC, Zheng LY, Chen Q, Liu Y, Xu HF, Kang RH, Zhang LY, Cao XQ, Liu SZ, Sun XB, Zhang JG, Zhang SK. Construction and Validation of a Lung Cancer Risk Prediction Model for Non-Smokers in China. Front Oncol 2022; 11:766939. [PMID: 35059311 PMCID: PMC8764453 DOI: 10.3389/fonc.2021.766939] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 12/13/2021] [Indexed: 11/13/2022] Open
Abstract
Background About 15% of lung cancers in men and 53% in women are not attributable to smoking worldwide. The aim was to develop and validate a simple and non-invasive model which could assess and stratify lung cancer risk in non-smokers in China. Methods A large-sample size, population-based study was conducted under the framework of the Cancer Screening Program in Urban China (CanSPUC). Data on the lung cancer screening in Henan province, China, from October 2013 to October 2019 were used and randomly divided into the training and validation sets. Related risk factors were identified through multivariable Cox regression analysis, followed by establishment of risk prediction nomogram. Discrimination [area under the curve (AUC)] and calibration were further performed to assess the validation of risk prediction nomogram in the training set, and then validated by the validation set. Results A total of 214,764 eligible subjects were included, with a mean age of 55.19 years. Subjects were randomly divided into the training (107,382) and validation (107,382) sets. Elder age, being male, a low education level, family history of lung cancer, history of tuberculosis, and without a history of hyperlipidemia were the independent risk factors for lung cancer. Using these six variables, we plotted 1-year, 3-year, and 5-year lung cancer risk prediction nomogram. The AUC was 0.753, 0.752, and 0.755 for the 1-, 3- and 5-year lung cancer risk in the training set, respectively. In the validation set, the model showed a moderate predictive discrimination, with the AUC was 0.668, 0.678, and 0.685 for the 1-, 3- and 5-year lung cancer risk. Conclusions We developed and validated a simple and non-invasive lung cancer risk model in non-smokers. This model can be applied to identify and triage patients at high risk for developing lung cancers in non-smokers.
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Affiliation(s)
- Lan-Wei Guo
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhang-Yan Lyu
- Department of Cancer Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy of the Ministry of Education, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Qing-Cheng Meng
- Department of Radiology, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Li-Yang Zheng
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Qiong Chen
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Yin Liu
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Hui-Fang Xu
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Rui-Hua Kang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Lu-Yao Zhang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiao-Qin Cao
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Shu-Zheng Liu
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Xi-Bin Sun
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Jian-Gong Zhang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Shao-Kai Zhang
- Department of Cancer Epidemiology and Prevention, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Henan Cancer Hospital, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Shao-Kai Zhang,
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Chen H, Hu Z, Sang M, Ni S, Lin Y, Wu C, Mu Y, Liu K, Wu S, Li N, Xu G. Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma. Front Genet 2021; 12:767694. [PMID: 34956321 PMCID: PMC8692741 DOI: 10.3389/fgene.2021.767694] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/26/2021] [Indexed: 12/25/2022] Open
Abstract
Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature on the basis of long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of patients with LUAD. We selected ARlncRNAs associated with prognosis to construct a model and divided each sample into different groups on the basis of risk score. The ARlncRNA signature could be recognized as an independent prognostic factor for patients with LUAD, and patients in the low-risk group had a greater survival advantage. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden. Low-risk patients had a higher PD-1, CTLA-4, and HAVCR2 expression and had a better efficacy of immune checkpoint inhibitors, including PD-1/CTLA-4 inhibitor. A reliable signature on the basis of ARlncRNAs was constructed to explore the TIME and prognosis of patients with LUAD, which could provide valuable information for individualized LUAD treatment.
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Affiliation(s)
- Hang Chen
- Medical School, Ningbo University, Ningbo, China
| | - Zeyang Hu
- Medical School, Ningbo University, Ningbo, China
| | - Menglu Sang
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Saiqi Ni
- Department of Urology, Ningbo City First Hospital, Ningbo, China
| | - Yao Lin
- Medical School, Ningbo University, Ningbo, China
| | - Chengfang Wu
- Medical School, Ningbo University, Ningbo, China
| | - Yinyu Mu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Kaitai Liu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Shibo Wu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Ni Li
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Guodong Xu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
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Yang Z, Wang F, Tan F, Cao W, Xu Y, Qin C, Yu Y, Zhao L, Wen Y, Wu Z, Zheng Y, Liu Y, Yu L, Wei D, Dong D, Cao J, Zhang S, Yan S, Wang N, Liao X, Du L, Li J, Li N, Chen W, He J. Menstrual factors, reproductive history, and risk of lung cancer: a multi-center population-based cohort study in Chinese females. Transl Lung Cancer Res 2021; 10:3912-3928. [PMID: 34858781 PMCID: PMC8577983 DOI: 10.21037/tlcr-21-552] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 09/16/2021] [Indexed: 12/24/2022]
Abstract
Background Female menstrual and reproductive factors, as remarkable indicators of hormone effect, were hypothesized to be associated with lung cancer risk, whereas the existed epidemiological evidence was inconsistent. Our study aims to investigate the association between menstrual and reproductive factors and lung cancer risk based on the Chinese Lung Cancer Screening Program. Methods This study was based on a large-scale multi-center population cohort across China recruiting individuals aged 40–74 years old between 2013–2018. Cox regression model was applied to estimate the HRs and 95% CIs. Restricted cubic spline (RCS) analysis was used to estimate dose-response relationships and test for nonlinear associations. Results Among 553,434 female participants, 1,529 incident lung cancer cases were identified with a median follow-up of 3.61 years. With adjustment for multiple covariates and all significant hormonal factors, elevated lung cancer risk was associated with later age (15, or ≥16 years) at menarche (HR =1.27, 95% CI: 1.04–1.56; HR =1.45, 95% CI: 1.19–1.76), later age (25–29, or ≥30 years) at first live birth (HR =1.27, 95% CI: 1.13–1.43; HR =1.23, 95% CI: 1.00–1.51), and benign breast disease history (HR =1.25, 95% CI: 1.10-1.41). For postmenopausal females specifically, surgical menopause (HR =1.62; 95% CI: 1.29–2.05) and other surgeries on the reproductive system (HR =1.19; 95% CI: 1.01–1.40) both appeared to be predictive of elevated lung cancer risk. Concerning age at menopause, a nonlinear association was observed (P-nonlinear =0.0126). Increased lung cancer risk was observed among females with age at menopause especially above 50. Although we observed no significant associations between longer time (≥13 months) of breastfeeding and lung cancer risk among all participants (HR =0.86; 95% CI: 0.71–1.04), significant decreased adenocarcinoma risk (HR =0.65; 95% CI: 0.53–0.81) was noted among nonsmoking females. Conclusions Our findings add some support for the role of menstrual and reproductive factors in lung carcinogenesis. However, these relationships were complex, and required further investigations addressing the biological mechanisms.
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Affiliation(s)
- Zhuoyu Yang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fei Wang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fengwei Tan
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Cao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yongjie Xu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chao Qin
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yiwen Yu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Liang Zhao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yan Wen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zheng Wu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yadi Zheng
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yunyong Liu
- Department for Cancer Prevention and Treatment of Liaoning Province/Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China.,Division of Pneumoconiosis School of Public Health, China Medical University, Shenyang, China
| | - Lianzheng Yu
- Department of Noncommunicable Chronic Disease Prevention, Liaoning Center for Disease Control and Prevention, Shenyang, China
| | - Donghua Wei
- Cancer Department of Physical Examination, Anhui Provincial Cancer Hospital, Hefei, China
| | - Dong Dong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou, China
| | - Ji Cao
- Department of Experimental Pathology, Tumor Hospital of Guangxi Medical University, Nanning, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China
| | - Shipeng Yan
- Department of Cancer Prevention and Control, Hunan Cancer Hospital & The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Ning Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xianzhen Liao
- Department of Cancer Prevention and Control, Hunan Cancer Hospital & The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Lingbin Du
- Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)/IBMC, Chinese Academy of Sciences, Hangzhou, China
| | - Jiang Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Wanqing Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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49
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Mao G, Mu Z, Wu D. Exosomal lncRNA FOXD3-AS1 upregulates ELAVL1 expression and activates PI3K/Akt pathway to enhance lung cancer cell proliferation, invasion, and 5-fluorouracil resistance. Acta Biochim Biophys Sin (Shanghai) 2021; 53:1484-1494. [PMID: 34605863 DOI: 10.1093/abbs/gmab129] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Indexed: 12/20/2022] Open
Abstract
Long non-coding RNA (lncRNA) FOXD3-AS1 expression is upregulated in lung cancer; however, its effect and mechanism on 5-fluorouracil (5-FU) resistance remain unclear. In this study, we determined the effects of FOXD3-AS1-enriched exosomes derived from lung cancer cells on the proliferation, invasion, and 5-FU resistance of lung cancer cells. Online bioinformatics database analysis showed that FOXD3-AS1 was upregulated in lung cancer progression. Real-time quantitative PCR results confirmed that FOXD3-AS1 expression was upregulated in lung cancer tissues and cell lines, and FOXD3-AS1 was greatly enriched in lung cancer cell-derived exosomes. ELAV-like RNA-binding protein 1 (ELAVL1) was identified as an RNA-binding protein of FOXD3-AS1. The lung cancer cell-derived exosomes promoted A549 cell proliferation and invasion and inhibited apoptosis caused by 5-FU, and transfection of si-FOXD3-AS1 or si-ELAVL1 in exosome-incubated A549 cells reversed these effects. Moreover, exosome-incubated A549 cells were co-transfected with si-FOXD3-AS1 and pcDNA-ELAVL1, showing the same cell proliferation, invasion, and 5-FU resistance as those of A549 cells treated with lung cancer cell-derived exosomes alone. Mechanistic studies identified that lung cancer cell-derived exosomes activated the PI3K/Akt pathway, and transfection of si-FOXD3-AS1 or treatment with the PI3K inhibitor LY294002 reversed the activation of the PI3K/Akt axis induced by exosomes. In conclusion, our study revealed that lung cancer cell-derived exosomal FOXD3-AS1 upregulated ELAVL1 expression and activated the PI3K/Akt pathway to promote lung cancer progression. Our findings provide a new strategy for lung cancer treatment.
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Affiliation(s)
- Guangxian Mao
- Department of Thoracic Surgery, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - Zhimin Mu
- Department of Thoracic Surgery, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - Da Wu
- Department of Thoracic Surgery, Peking University Shenzhen Hospital, Shenzhen 518036, China
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50
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Fan Y, Su Z, Wei M, Liang H, Jiang Y, Li X, Meng Z, Wang Y, Wu H, Song J, Qiao Y, Zhou Q. Lung cancer risk following previous abnormal chest radiographs: A 27-year follow-up study of a Chinese lung screening cohort. Thorac Cancer 2021; 12:3387-3395. [PMID: 34751511 PMCID: PMC8671899 DOI: 10.1111/1759-7714.14213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 10/16/2021] [Indexed: 02/05/2023] Open
Abstract
Background Chest radiograph (CXR) is still one of the most commonly used diagnostic tools for chest diseases. In this cohort study, we attempted to investigate the magnitude and temporal pattern of lung cancer risk following abnormal CXR findings. Methods We conducted an extended follow‐up of an occupational screening cohort in Yunnan, China. The associations between abnormal CXR results from baseline screening, the first four consecutive rounds of CXR screening, all previous rounds of screening and lung cancer risk were analyzed using time‐varying coefficient Cox regression model. The associations of lung cancer risk and previous CXR‐screening results according to histology were also considered. Sensitivity analyses were conducted to assess the robustness of the previous abnormal CXR findings on subsequent lung cancer risk. Results Abnormal CXR findings were associated with a significantly increased lung cancer risk. This relative hazard significantly decreased over time. Compared to negative screening results, the adjusted hazard ratios (HR) of baseline abnormal CXR results, and at least one abnormal result in the first four consecutive screening rounds during the first 5 years of follow‐up were 17.06 (95% CI: 11.74–24.79) and 13.77 (95%: 9.58–17.79), respectively. This significantly increased lung cancer risk continued over the next 5 years. These associations were stronger for persistent abnormal findings, and abnormal findings identified in recent screening rounds. Conclusions The increased risk was significant for both squamous cell carcinoma and adenocarcinoma. Although decreased over time, an increased lung cancer risk relative to abnormal CXR findings can continue for 10 years.
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Affiliation(s)
- Yaguang Fan
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Zheng Su
- Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mengna Wei
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Liang
- Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Yong Jiang
- Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuebing Li
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhaowei Meng
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Ying Wang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Heng Wu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Jinzhao Song
- Department of Mechanical Engineering & Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Youlin Qiao
- Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Center of Global Health, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qinghua Zhou
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China.,Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, China
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