Cancer Research on Prevention and Treatment    2022, Vol. 49 Issue (03) : 197-204     DOI: 10.3971/j.issn.1000-8578.2022.21.0623
Construction and Validation of A Nomogram Prognostic Model for Patients with Lung Adenocarcinoma
LUO Wenqing1, LI Yuanqi2, YE Fei1, LI Qiangming1, ZHANG Guoqing1, LI Xiangnan1
1. Department of Thoracic Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; 2. Xiangya School of Public Health, Central South University, Changsha 410012, China
Download: PDF(5263 KB)   ( 82 )   HTML ()
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract Objective To construct a nomogram prognostic model for predicting the survival of patients with lung adenocarcinoma based on the large sample data from the SEER database. Methods We retrospectively analyzed the clinical data of patients who were diagnosed with lung adenocarcinoma from 2010 to 2015 in the SEER database. A nomogram model was created based on independent parameters influencing the prognosis of patients with lung adenocarcinoma using Lasso Cox regression analysis. The C-index and calibration curve were utilized to assess the ability to distinguish and calibrate the nomogram. NRI and DCA curves were used to evaluate the prediction ability and net benefit of the nomogram. Results A total of 15 independent risk factors affecting the prognosis of lung adenocarcinoma were identified and integrated into the nomogram model. The C-index of the prediction model was 0.819 in the training cohort and 0.810 in the validation cohort. The predicted specific survival rate of the 1-, 3- and 5-year calibration curves of the training cohort and the validation cohort were consistent with the actual specific survival rate. In comparison to the 7th edition of the AJCC TNM staging system, the NRI and DCA curves demonstrated a considerable boost to the predictive capacity and net benefits achieved by the nomogram model. The risk stratification model constructed with this nomogram model was able to distinguish the patients with different risks well (P<0.0001). Conclusion A nomogram prognostic model is successfully developed and validated, which provides asimple and reliable tool for the survival prediction of the patients with lung adenocarcinoma. Meanwhile, therisk stratification model constructed by the prediction model can conveniently screen patients with different risks, which is important for the individualized treatment of lung adenocarcinoma patients.
Keywords SEER database      Lung adenocarcinoma      Nomogram      Prognostic model     
ZTFLH:  R734.2  
Fund:National Natural Science Foundation of China (No. 32070623); Key Discipline Construction Project of Zhengzhou University (No. XKZDQY202006)
Issue Date: 17 March 2022
 Cite this article:   
LUO Wenqing,LI Yuanqi,YE Fei, et al. Construction and Validation of A Nomogram Prognostic Model for Patients with Lung Adenocarcinoma[J]. Cancer Research on Prevention and Treatment, 2022, 49(03): 197-204.
E-mail this article
E-mail Alert
Articles by authors
LUO Wenqing
LI Yuanqi
YE Fei
LI Qiangming
ZHANG Guoqing
LI Xiangnan
[1] Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020:
GLOBOCAN Estimates of Incidence and Mortality Worldwide
for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2021,
71(3): 209-249.
[2] Avelino CUR, Cardoso RM, de Aguiar SS, et al. Assessment
of quality of life in patients with advanced non-small cell
lung carcinoma treated with a combination of carboplatin and
paclitaxel[J]. J Bras Pneumol, 2015, 41(2): 133-142.
[3] Shi J, Hua X, Zhu B, et al. Somatic Genomics and Clinical
Features of Lung Adenocarcinoma: A Retrospective Study[J].
PLoS Med, 2016, 13(12): e1002162.
[4] Lin JJ, Cardarella S, Lydon CA, et al. Five-Year Survival in
EGFR-Mutant Metastatic Lung Adenocarcinoma Treated with
EGFR-TKIs[J]. J Thorac Oncol, 2016, 11(4): 556-565.
[5] Qi L, Li Y, Qin Y, et al. An individualised signature for
predicting response with concordant survival benefit for
lung adenocarcinoma patients receiving platinum-based
chemotherapy[J]. Br J Cancer, 2016, 115(12): 1513-1519.
[6] Zhang Y, Zheng D, Xie J, et al. Development and Validation of
Web-Based Nomograms to Precisely Predict Conditional Risk of
Site-Specific Recurrence for Patients With Completely Resected
Non-small Cell Lung Cancer: A Multiinstitutional Study[J]. Chest,
2018, 154(3): 501-511.
[7] Wo Y, Yang H, Zhang Y, et al. Development and External
Validation of a Nomogram for Predicting Survival in Patients
With Stage IA Non-small Cell Lung Cancer ≤2 cm Undergoing
Sublobectomy[J]. Front Oncol, 2019, 9: 1385.
[8] Duggan MA, Anderson WF, Altekruse S, et al. The Surveillance,
Epidemiology, and End Results (SEER) Program and Pathology:
Toward Strengthening the Critical Relationship[J]. Am J Surg
Pathol, 2016, 40(12): e94-e102.
[9] Shin S, Kang D, Cho JH, et al. Prognostic impact of lymph node
ratio in patients with pT1-2N1M0 non-small cell lung cancer[J]. J
Thorac Dis, 2020, 12(10): 5552-5560.
[10] Nakamura H, Saji H. Worldwide trend of increasing primary
adenocarcinoma of the lung[J]. Surg Today, 2014, 44(6):
[11] 王高祥, 熊燃, 吴汉然, 等. 中性粒细胞/淋巴细胞比值预测
根治性切除肺腺癌患者预后分析[J]. 中国肺癌杂志, 2018,
21(8): 588-593. [Wang GX, Xiong R, Wu HR, et al. Prognostic
Value of Neutrophil-to-lymphocyte Ratio in Patients with Lung
Adenocarcinoma Treated with Radical Dissection[J]. Zhongguo
Fei Ai Za Zhi, 2018, 21(8): 588-593.]
[12] Liao F, Guo X, Lu X, et al. A validated survival nomogram for
early-onset diffuse gastric cancer[J]. Aging (Albany NY), 2020,
12(13): 13160-13171.
[13] Lin JL, Lin JX, Li P, et al. Dynamic prediction of long-term survival in patients with primary gastric diffuse large B-cell
lymphoma: a SEER population-based study[J]. BMC Cancer,
2019, 19(1): 873.
[14] Campos-Balea B, de Castro Carpe?o J, Massutí B, et al.
Prognostic factors for survival in patients with metastatic lung
adenocarcinoma: An analysis of the SEER database[J]. Thorac
Cancer, 2020, 11(11): 3357-3364.
[15] Yang H, Li X, Shi J, et al. A nomogram to predict prognosis in
patients undergoing sublobar resection for stageⅠA non-smallcell
lung cancer[J]. Cancer Manag Res, 2018, 10: 6611-6626.
[16] Zhou HQ, Zhang YX, Qiu ZT, et al. Nomogram to Predict Cause-
Specific Mortality in Patients With Surgically Resected Stage Ⅰ
Non-Small-Cell Lung Cancer: A Competing Risk Analysis[J].
Clin Lung Cancer, 2018, 19(2): e195-e203.
[17] Pitz MW, Musto G, Navaratnam S. Sex as an independent
prognostic factor in a population-based non-small cell lung cancer
cohort[J]. Can Respir J, 2013, 20(1): 30-34.
[18] Varlotto JM, Voland R, Mckie K, et al. Population-based
differences in the outcome and presentation of lung cancer
patients based upon racial, histologic, and economic factors in all
lung patients and those with metastatic disease[J]. Cancer Med,
2018, 7(14): 1211-1220.
[19] Zuo Z, Zhang G, Song P, et al. Survival Nomogram for Stage
IB Non-Small-Cell Lung Cancer Patients, Based on the SEER
Database and an External Validation Cohort[J]. Ann Surg Oncol,
2021, 28(7): 3941-3950.
[20] 田希贵, 刘德森, 汪元玉, 等. 腺癌与其他类型非小细胞肺癌术
后临床特点的差异及预后因素分析[J]. 中国癌症杂志, 2017,
27(3): 227-232. [Tian XG, Liu DS, Wang YY, et al. Postoperative
differences in clinical characteristics between adenocarcinoma
and other types of non-small cell lung cancer and analysis of
prognostic factors of adenocarcinoma treated with surgery[J].
Zhongguo Ai Zheng Za Zhi, 2017, 27(3): 227-232.]
[21] 彭红, 马美丽, 韩宝惠. 1742例Ⅳ期非小细胞肺癌的预后分
析[C]. 上海市肺科学会和美国ACCP联合会议论文集, 2011:
142-148. [Peng H, Ma ML, Han BH. Survival analysis of 1742
cases of Ⅳ non-small cell lung cancer[C]. Proceedings of the
Joint Conference of the Shanghai Pulmonary Society and ACCP,
2011: 142-148.]
[22] 冯悦. 168例肺腺癌患者预后因素分析[D]. 承德医学院, 2016.
[Feng Y. Analysis of prognostic factors in 168 cases of lung
adenocarcinoma patients[D]. Chengde Medical College, 2016.]
[23] Shi M, Zhan C, Shi J, et al. Prediction of Overall Survival of
Patients with Completely Resected Non-Small Cell Lung Cancer:
Analyses of Preoperative Spirometry, Preoperative Blood Tests,
and Other Clinicopathological Data[J]. Cancer Manag Res, 2019,
11: 10487-10497.
[24] Sun F, Ma K, Yang X, et al. A nomogram to predict prognosis
after surgery in early stage non-small cell lung cancer in elderly
patients[J]. Int J Surg, 2017, 42: 11-16.
Related articles from Frontiers Journals
[1] LI Jinzhou, WANG Wenjie, YAO Yalong, MU Yanxi, CHEN Kang, SHEN Yimin, WANG Zhou, HUANG Zeping, CHEN Xiao. Development and Validation of Prognostic Nomogram Based on Negative Lymph Node Count for Patients with Gastric Signet Ring Cell Carcinoma#br#[J]. Cancer Research on Prevention and Treatment, 2022, 49(09): 923-930.
[2] SUI Daxing, WANG Xueying, ZHANG Jiaxin. A New N-staging System for Predicting Postoperative Survival of M0 Stage Inflammatory Breast Cancer[J]. Cancer Research on Prevention and Treatment, 2022, 49(08): 799-805.
[3] WANG Lin, HUANG Zixian, YOU Chengcheng, TAN Shunzi, HUANG Liming, HUANG Yiling. Screening of Molecular Markers of Cisplatin Resistance in Lung Adenocarcinoma and Functional Verification Based on TCGA Database[J]. Cancer Research on Prevention and Treatment, 2022, 49(06): 569-574.
[4] . Expression of MAD2L1 in Lung Adenocarcinoma and Its Effect on Immune Microenvironment[J]. Cancer Research on Prevention and Treatment, 2022, 49(06): 586-592.
[5] LIU Changjian, WANG Jian, LIU Shaoyan. Pyroptosis-related lncRNAs Predict Prognosis of Laryngeal Cancer[J]. Cancer Research on Prevention and Treatment, 2022, 49(04): 335-339.
[6] XIA Qisheng, DENG Tingting, XU Yaping, LIU Honglin, LIU Haoyuan. Inhibitory Effect of Loropetalum Chinense on Proliferation of Lung Adenocarcinoma A549 Cells[J]. Cancer Research on Prevention and Treatment, 2022, 49(03): 182-186.
[7] FAN Bingjie, CHANG Yu, LIU Xiyang, ZHANG Mingzhi, ZHANG Lei. Effects of Chemoradiotherapy Versus Chemotherapy Alone on Survival of Patients with Primary Mediastinal Large B-cell Lymphoma[J]. Cancer Research on Prevention and Treatment, 2022, 49(03): 205-212.
[8] YANG Hao, MEI Tonghua. Effect of Lymph Node Metastasis on Prognosis of Small Cell Lung Cancer with M1a Disease: A Study Based on SEER database[J]. Cancer Research on Prevention and Treatment, 2022, 49(02): 116-122.
[9] YUE Jing, KANG Jing, LI Guoyin. Influence of SLC16A Family on Clinical Features and Biological Behaviours of Lung Adenocarcinoma and Squamous Cell Carcinoma[J]. Cancer Research on Prevention and Treatment, 2022, 49(01): 24-31.
[10] LIU Ying, XIE Bin, WANG Meng, LI Yiran, YAN Wenjin, XU Xingxiang, MIN Lingfeng. A Survival Prediction Model of Pulmonary Sarcomatoid Carcinoma Based on SEER Database[J]. Cancer Research on Prevention and Treatment, 2021, 48(09): 853-858.
[11] Chen Guangying, Ma Junxun, Hu Yi. Value of DNA Repair Gene and TP53 Co-mutation in Predicting Effect of Immunotherapy on Lung Adenocarcinoma[J]. Cancer Research on Prevention and Treatment, 2021, 48(07): 704-708.
[12] QI Chunyan, WU Tao, QI Xiaoguang. Identification of Drug-resistance Core Genes and Drug Targets in Lung Adenocarcinoma Patients Harboring ALK Fusion Gene[J]. Cancer Research on Prevention and Treatment, 2021, 48(05): 451-456.
[13] SONG Wenjing, LIU Shuting, HE Xin, GONG Pengju, YANG Yan, WEI Lei, ZHANG Jingwei. Expression Level of VSIG4 in Breast Cancer and Its Correlation with Immune Infiltration and Prognosis[J]. Cancer Research on Prevention and Treatment, 2021, 48(05): 489-496.
[14] ZHU Di, ZHANG Yushan, ZHENG Shoujuan, WANG Xia. Establishment and Validation of A Prognostic Nomogram for Pediatric Ependymoma Based on SEER Database[J]. Cancer Research on Prevention and Treatment, 2021, 48(04): 358-364.
[15] REN Ke, YAO Nan, WU Sujia, SHI Xin, LI Chao, LU Jun. Prognostic Analysis and Risk Prediction Model Establishment of Extremity Osteosarcoma Based on Vasculogenic Mimicry-related Molecule MIG-7[J]. Cancer Research on Prevention and Treatment, 2021, 48(01): 31-37.
Full text