Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug;11(8):1591-1605.
doi: 10.21037/tlcr-22-240.

Survival of 7,311 lung cancer patients by pathological stage and histological classification: a multicenter hospital-based study in China

Siyi He  1 , He Li  1 , Maomao Cao  1 , Dianqin Sun  1 , Fan Yang  1 , Xinxin Yan  1 , Shaoli Zhang  1 , Yutong He  2 , Lingbin Du  3 , Xibin Sun  4 , Ning Wang  5 , Min Zhang  6 , Kuangrong Wei  7 , Lin Lei  8 , Changfa Xia  1 , Ji Peng  8 , Wanqing Chen  1
Affiliations

Survival of 7,311 lung cancer patients by pathological stage and histological classification: a multicenter hospital-based study in China

Siyi He et al. Transl Lung Cancer Res. 2022 Aug.

Abstract

Background: Representative prognostic data by clinical characteristics for lung cancer is not yet available in China. This study aimed to calculate the survival of lung cancer patients with different pathological evaluations, explore their predictive effects and provide information for prognosis improvement.

Methods: In this multicenter cohort study, primary lung cancer patients diagnosed in 17 hospitals at three distinct levels in China between 2011-2013 were enrolled and followed up till 2020. Overall survival and lung cancer specific survival were calculated by Kaplan-Meier method. Cox proportional hazards model was applied to assess the effects of predictors of lung cancer survival.

Results: Of all the 7,311 patients, the 5-year overall and lung cancer specific survival rates were 37.0% and 41.6%, respectively. For lung cancer patients at stages I, II, III, and IV, the 5-year overall survival rates were 76.9%, 56.1%, 32.6%, and 21.4%, respectively; the lung cancer specific survival rates were 82.3%, 59.7%, 37.2%, and 26.4%, respectively. Differences of survival for each stage remained significant between histological classifications (P<0.01). The 5-year overall survival rates for patients with squamous cell carcinoma, adenocarcinoma (AC), and small cell carcinoma were 36.9%, 43.3% and 27.9%, respectively; the corresponding disease-specific rates were 41.5%, 48.6% and 31.0%, respectively. Such differences were non-statistically significant at advanced stages (P=0.09). After multivariate adjustments, stage and classification remained independent predictors for the survival of lung cancer.

Conclusions: The prognosis of lung cancer varied with the pathological stages and histological classifications, and had room for improvement. Stage was the strongest predictor, so efforts on early detection and treatment are needed.

Keywords: Lung neoplasms; histological classification; multicenter study; neoplasm staging; survival analysis.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-22-240/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Flowchart of the study population.
Figure 2
Figure 2
Survival curves of lung cancer patients with specific diagnosis of pathological stage/histological classification. (A) Overall survival curves of patients by pathological stage. (B) Lung cancer specific survival curves of patients by pathological stage. (C) Overall survival curves of patients by histological classification. (D) Lung cancer specific survival curves of patients by histological classification. AC, adenocarcinoma; SCC, squamous cell carcinoma; SCLC, small cell lung carcinoma.
Figure 3
Figure 3
Cox regression analysis on associations between clinical characteristics and the survival of enrolled lung cancer patients. [Notes: The forest plot refers to the HRs in the cox regression analysis adjusted by all the considered variables (adjusted HR2). Adjusted HR1: Cox proportional hazards models were adjusted by age at diagnosis, sex, smoking, alcohol assumption, history of respiratory diseases, family history of lung cancer, and BMI. Adjusted HR2: Cox proportional hazards models were further adjusted by pathological stage (for histological classification)/histological classification (for pathological stage), lesion site, treatment, grade of the hospital and location of the hospital. LCSS, lung cancer specific survival; OS, overall survival; HR, hazard ratio.
See this image and copyright information in PMC

References

    1. Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015. CA Cancer J Clin 2016;66:115-32. 10.3322/caac.21338 - DOI - PubMed
    1. Zhou M, Wang H, Zeng X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2019;394:1145-58. 10.1016/S0140-6736(19)30427-1 - DOI - PMC - PubMed
    1. Cai Y, Chen W, Wang X, et al. Contemporary trends on expenditure of hospital care on total cancer and its subtypes in China during 2008-2017. Chin J Cancer Res 2021;33:627-36. 10.21147/j.issn.1000-9604.2021.05.09 - DOI - PMC - PubMed
    1. Office for National Statistics. Cancer survival in England: adult, stage at diagnosis and childhood - patients followed up to 2018. Available online: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/..., based on 12 August 2019 data submission.
    1. Howlader N, Noone AM, Krapcho M, et al. editors. SEER Cancer Statistics Review, 1975-2018, National Cancer Institute. Bethesda, MD. Available online: https://seer.cancer.gov/csr/1975_2018/, based on November 2020 SEER data submission, posted to the SEER web site, April 2021.