Skip to main content
Top
Published in: Indian Journal of Surgical Oncology 2/2023

21-01-2023 | NSCLC | Original Article

Nomogram Predicting the Prognosis of Patients with Surgically Resected Stage IA Non-small Cell Lung Cancer

Authors: Xu-Feng Deng, Yin Dai, Xiao-Qing Liu, Huang-Zhi Qi, Dong Zhou, Hong Zheng, Jiang Li, Quan-Xing Liu

Published in: Indian Journal of Surgical Oncology | Issue 2/2023

Login to get access

Abstract

The American Joint Committee on Cancer (AJCC) 8th stage system was limited in accuracy for predicting prognosis of stage IA non-small cell lung cancer (NSCLC) patients. This study aimed to establish and validate two nomograms that predict overall survival (OS) and lung cancer–specific survival (LCSS) in surgically resected stage IA NSCLC patients. Postoperative patients with stage IA NSCLC in SEER database between 2004 and 2015 were examined. Survival and clinical information according to the inclusion and exclusion criteria were collected. All patients were randomly divided into the training cohort and validation cohort with a ratio of 7:3. Independent prognosis factors were evaluated using univariate and multivariate Cox regression analyses, and predictive nomogram was established based on these factors. Nomogram performance was measured using the C-index, calibration plots, and DCA. Patients were grouped by quartiles of nomogram scores and survival curves were plotted by Kaplan–Meier analysis. In total, 33,533 patients were included in the study. The nomogram contained 12 prognostic factors in OS and 10 prognostic factors in LCSS. In the validation set, the C-index was 0.652 for predicting OS and 0.651 for predicting LCSS. The calibration curves for the nomogram-predicted probability of OS and LCSS showed good agreement between the actual observation and nomogram prediction. DCA indicated that the clinical value of the nomograms were higher than AJCC 8th stage for predicting OS and LCSS. Nomogram scores related risk stratification revealed statistically significant difference which have better discrimination than AJCC 8th stage. The nomogram can accurately predict OS and LCSS in surgically resected patients with stage IA NSCLC.
Appendix
Available only for authorised users
Literature
1.
go back to reference Bray F, Ferlay J, Soerjomataram I et al (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68(6):394–424CrossRefPubMed Bray F, Ferlay J, Soerjomataram I et al (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68(6):394–424CrossRefPubMed
2.
go back to reference Travis WD, Brambilla E, Nicholson AG et al (2015) The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol 10(9):1243–1260CrossRefPubMed Travis WD, Brambilla E, Nicholson AG et al (2015) The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol 10(9):1243–1260CrossRefPubMed
3.
go back to reference Goldstraw P, Chansky K, Crowley J et al (2016) The IASLC lung cancer staging project: proposals for revision of the TNM stage groupings in the forthcoming (Eighth) edition of the TNM classification for lung cancer. J Thorac Oncol 11(1):39–51CrossRefPubMed Goldstraw P, Chansky K, Crowley J et al (2016) The IASLC lung cancer staging project: proposals for revision of the TNM stage groupings in the forthcoming (Eighth) edition of the TNM classification for lung cancer. J Thorac Oncol 11(1):39–51CrossRefPubMed
4.
go back to reference Zhou H, Zhang Y, Qiu Z et al (2018) Nomogram to predict cause-specific mortality in patients with surgically resected stage I non-small-cell lung cancer: a competing risk analysis. Clin Lung Cancer 19(2):e195-203CrossRefPubMed Zhou H, Zhang Y, Qiu Z et al (2018) Nomogram to predict cause-specific mortality in patients with surgically resected stage I non-small-cell lung cancer: a competing risk analysis. Clin Lung Cancer 19(2):e195-203CrossRefPubMed
5.
go back to reference Zeng Y, Mayne N, Yang CJ et al (2019) A nomogram for predicting cancer-specific survival of TNM 8th edition stage I non-small-cell lung cancer. Ann Surg Oncol 26(7):2053–62CrossRefPubMed Zeng Y, Mayne N, Yang CJ et al (2019) A nomogram for predicting cancer-specific survival of TNM 8th edition stage I non-small-cell lung cancer. Ann Surg Oncol 26(7):2053–62CrossRefPubMed
6.
go back to reference Zhang Y, Sun Y, Xiang J et al (2014) A clinicopathologic prediction model for postoperative recurrence in stage Ia non-small cell lung cancer. J Thorac Cardiovasc Surg 148(4):1193–1199CrossRefPubMed Zhang Y, Sun Y, Xiang J et al (2014) A clinicopathologic prediction model for postoperative recurrence in stage Ia non-small cell lung cancer. J Thorac Cardiovasc Surg 148(4):1193–1199CrossRefPubMed
7.
go back to reference Nieder C, Mehta MP, Geinitz H et al (2018) Prognostic and predictive factors in patients with brain metastases from solid tumors: a review of published nomograms. Crit Rev Oncol Hematol 126:13–18CrossRefPubMed Nieder C, Mehta MP, Geinitz H et al (2018) Prognostic and predictive factors in patients with brain metastases from solid tumors: a review of published nomograms. Crit Rev Oncol Hematol 126:13–18CrossRefPubMed
8.
go back to reference Yang J, Chen S, Li Y et al (2020) Incidence rate and risk factors for suicide death in patients with skin malignant melanoma: a Surveillance, Epidemiology, and End Results analysis. Melanoma Res 30(4):402–409CrossRefPubMed Yang J, Chen S, Li Y et al (2020) Incidence rate and risk factors for suicide death in patients with skin malignant melanoma: a Surveillance, Epidemiology, and End Results analysis. Melanoma Res 30(4):402–409CrossRefPubMed
9.
go back to reference He Y, Ong Y, Li X et al (2019) Performance of prediction models on survival outcomes of colorectal cancer with surgical resection: a systematic review and meta-analysis. Surg Oncol 29:196–202CrossRefPubMed He Y, Ong Y, Li X et al (2019) Performance of prediction models on survival outcomes of colorectal cancer with surgical resection: a systematic review and meta-analysis. Surg Oncol 29:196–202CrossRefPubMed
10.
go back to reference Wang Y, Li J, Xia Y et al (2013) Prognostic nomogram for intrahepatic cholangiocarcinoma after partial hepatectomy. J Clin Oncol 31(9):1188–1195CrossRefPubMed Wang Y, Li J, Xia Y et al (2013) Prognostic nomogram for intrahepatic cholangiocarcinoma after partial hepatectomy. J Clin Oncol 31(9):1188–1195CrossRefPubMed
11.
go back to reference Liang W, Zhang L, Jiang G et al (2015) Development and validation of a nomogram for predicting survival in patients with resected non-small-cell lung cancer. J Clin Oncol 33(8):861–869CrossRefPubMed Liang W, Zhang L, Jiang G et al (2015) Development and validation of a nomogram for predicting survival in patients with resected non-small-cell lung cancer. J Clin Oncol 33(8):861–869CrossRefPubMed
12.
go back to reference Nicholson AG, Chansky K, Crowley J et al (2016) The international association for the study of lung cancer lung cancer staging project: proposals for the revision of the clinical and pathologic staging of small cell lung cancer in the forthcoming eighth edition of the TNM classification for lung cancer. J Thorac Oncol 11(3):300–11CrossRefPubMed Nicholson AG, Chansky K, Crowley J et al (2016) The international association for the study of lung cancer lung cancer staging project: proposals for the revision of the clinical and pathologic staging of small cell lung cancer in the forthcoming eighth edition of the TNM classification for lung cancer. J Thorac Oncol 11(3):300–11CrossRefPubMed
13.
go back to reference Heagerty PJ, Zheng Y (2005) Survival model predictive accuracy and ROC curves. Biometrics 61(1):92–105CrossRefPubMed Heagerty PJ, Zheng Y (2005) Survival model predictive accuracy and ROC curves. Biometrics 61(1):92–105CrossRefPubMed
14.
go back to reference Kerr KF, Brown MD, Zhu K et al (2016) Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use. J Clin Oncol 34(21):2534–2540CrossRefPubMedPubMedCentral Kerr KF, Brown MD, Zhu K et al (2016) Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use. J Clin Oncol 34(21):2534–2540CrossRefPubMedPubMedCentral
16.
go back to reference Marcoulides KM, Raykov T (2019) Evaluation of variance inflation factors in regression models using latent variable modeling methods. Educ Psychol Meas 79(5):874–882CrossRefPubMed Marcoulides KM, Raykov T (2019) Evaluation of variance inflation factors in regression models using latent variable modeling methods. Educ Psychol Meas 79(5):874–882CrossRefPubMed
17.
go back to reference Janssen-Heijnen M, van Erning FN, De Ruysscher DK et al (2015) Variation in causes of death in patients with non-small cell lung cancer according to stage and time since diagnosis. Ann Oncol 26(5):902–907CrossRefPubMed Janssen-Heijnen M, van Erning FN, De Ruysscher DK et al (2015) Variation in causes of death in patients with non-small cell lung cancer according to stage and time since diagnosis. Ann Oncol 26(5):902–907CrossRefPubMed
18.
go back to reference Wang BY, Huang JY, Cheng CY et al (2013) Lung cancer and prognosis in Taiwan: a population-based cancer registry. J Thorac Oncol 8(9):1128–1135CrossRefPubMed Wang BY, Huang JY, Cheng CY et al (2013) Lung cancer and prognosis in Taiwan: a population-based cancer registry. J Thorac Oncol 8(9):1128–1135CrossRefPubMed
19.
go back to reference Galvin A, Delva F, Helmer C et al (2018) Sociodemographic, socioeconomic, and clinical determinants of survival in patients with cancer: a systematic review of the literature focused on the elderly. J Geriatr Oncol 9(1):6–14CrossRefPubMed Galvin A, Delva F, Helmer C et al (2018) Sociodemographic, socioeconomic, and clinical determinants of survival in patients with cancer: a systematic review of the literature focused on the elderly. J Geriatr Oncol 9(1):6–14CrossRefPubMed
20.
go back to reference Dziedzic D, Rudzinski P, Langfort R et al (2016) Results of surgical treatment and impact on T staging of non-small-cell lung cancer adjacent lobe invasion. Eur J Cardiothorac Surg 50(3):423–427CrossRefPubMed Dziedzic D, Rudzinski P, Langfort R et al (2016) Results of surgical treatment and impact on T staging of non-small-cell lung cancer adjacent lobe invasion. Eur J Cardiothorac Surg 50(3):423–427CrossRefPubMed
21.
go back to reference Zheng YZ, Zhai WY, Zhao J et al (2020) Oncologic outcomes of lobectomy vs. Segmentectomy in non-small cell lung cancer with clinical T1N0M0 stage: a literature review and meta-analysis. J Thorac Dis 12(6):3178–87CrossRefPubMedPubMedCentral Zheng YZ, Zhai WY, Zhao J et al (2020) Oncologic outcomes of lobectomy vs. Segmentectomy in non-small cell lung cancer with clinical T1N0M0 stage: a literature review and meta-analysis. J Thorac Dis 12(6):3178–87CrossRefPubMedPubMedCentral
22.
go back to reference Liang W, He J, Shen Y et al (2017) Impact of examined lymph node count on precise staging and long-term survival of resected non-small-cell lung cancer: a population study of the US SEER database and a Chinese multi-institutional registry. J Clin Oncol 35(11):1162–1170CrossRefPubMed Liang W, He J, Shen Y et al (2017) Impact of examined lymph node count on precise staging and long-term survival of resected non-small-cell lung cancer: a population study of the US SEER database and a Chinese multi-institutional registry. J Clin Oncol 35(11):1162–1170CrossRefPubMed
23.
go back to reference Wu YL, Tsuboi M, He J et al (2020) Osimertinib in resected EGFR-mutated non-small-cell lung cancer. N Engl J Med 383(18):1711–1723CrossRefPubMed Wu YL, Tsuboi M, He J et al (2020) Osimertinib in resected EGFR-mutated non-small-cell lung cancer. N Engl J Med 383(18):1711–1723CrossRefPubMed
Metadata
Title
Nomogram Predicting the Prognosis of Patients with Surgically Resected Stage IA Non-small Cell Lung Cancer
Authors
Xu-Feng Deng
Yin Dai
Xiao-Qing Liu
Huang-Zhi Qi
Dong Zhou
Hong Zheng
Jiang Li
Quan-Xing Liu
Publication date
21-01-2023
Publisher
Springer India
Published in
Indian Journal of Surgical Oncology / Issue 2/2023
Print ISSN: 0975-7651
Electronic ISSN: 0976-6952
DOI
https://doi.org/10.1007/s13193-022-01700-w

Other articles of this Issue 2/2023

Indian Journal of Surgical Oncology 2/2023 Go to the issue
Webinar | 06-02-2024 | 20:00 (CET)

Mastering chronic pancreatitis pain: A multidisciplinary approach and practical solutions

Severe pain is the most common symptom of chronic pancreatitis. In this webinar, experts share the latest insights in pain management for chronic pancreatitis patients. Experts from a range of disciplines discuss pertinent cases and provide practical suggestions for use within clinical practice.

Sponsored by: Viatris

Developed by: Springer Healthcare