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International Journal of General Medicine logoLink to International Journal of General Medicine
. 2021 Dec 10;14:9567–9588. doi: 10.2147/IJGM.S338250

Prognosis and Survival Analysis of 922,317 Lung Cancer Patients from the US Based on the Most Recent Data from the SEER Database (April 15, 2021)

Sheng Hu 1, Wenxiong Zhang 1, Qiang Guo 1, Jiayue Ye 1, Deyuan Zhang 1, Yang Zhang 1, Weibiao Zeng 1, Dongliang Yu 1, Jinhua Peng 1, Yiping Wei 1,✉, Jianjun Xu 1
PMCID: PMC8670860  PMID: 34916838

Abstract

Background

On April 15, 2021, the Surveillance, Epidemiology, and End Results (SEER) database released the latest lung cancer follow-up data. We selected 922,317 lung cancer patients diagnosed from 2000 to 2017 for survival analysis to provide updated data for lung cancer researchers.

Research Question

This study explored the latest trends of survival time in terms of gender, race, nationality, age, income, address, histological type and primary site.

Study Design and Methods

The SEER database covers 27.8% of the US population. We used life table, Kaplan–Meier, log-rank, Breslow and Tarone-Ware tests to calculate survival rate, time, and curve and to compare differences in survival distribution. We performed univariate and multivariate Cox proportional hazards analyses.

Results

The median survival time of all lung cancer patients diagnosed in 2017 increased by 41.72% compared to 2000. Median survival time of female patients diagnosed in 2017 increased by 70.94% compared to 2000. Median survival time of those diagnosed in 2017 for different primary sites was as follows: right middle lobe was the longest, then left lower lobe, right upper lobe, right lower lobe, and left upper lobe. Lung cancer patients older than 75 years had a significantly shorter median survival time. Patients living in metropolitan areas of 250,000 to 1 million had a longer median survival time. Median survival time in the adenocarcinoma group was significantly greater than other patients. Median survival of Asian and other races diagnosed in 2017 was 97.87% higher than those diagnosed in 2000. Survival rate of lung cancer increased gradually with the year of diagnosis.

Interpretation

The rapid improvement of the prognosis of female and young lung cancer patients contributes to the improvement of the overall prognosis. Primary lung cancer in the right middle lobe has the best prognosis.

Keywords: Cox regression analysis, Kaplan Meier survival analysis, lung cancer, prognosis, SEER

Introduction

The Surveillance, Epidemiology, and End Results (SEER) database released the most recent lung cancer follow-up data on 15 April 2021 (https://www.cancer.gov). Although previous articles1–3 analyzed patient survival,4–6 these predated this release and therefore the data were not up to date. Our study therefore aimed to provide lung cancer researchers with accurate and updated survival data.

SEER is an authoritative source of cancer statistics in the United States and the SEER Program provides statistics on the cancer burden among the US population. The SEER database collects and publishes cancer incidence and survival data from population-based cancer registries. These data are collected on every cancer case reported from 18 US geographic areas. Because these areas are representative of the entire US population, SEER can account for diverse populations. SEER also reports mortality data, which are provided by the National Center for Health Statistics.7

Our study analyzed the survival of 922,317 lung cancer patients diagnosed from 2000–2017 in detail. Grouped by gender, race, ethnicity, age, income, address, histologic type, and primary site, respectively, our study found large variations in survival times and conditions among different groups of lung cancer patients by factors, and this variation has further expanded in recent years. And we tabulated the hazard ratios corresponding to each group in each item in detail.

We consider our study meaningful in being able to inform researchers and policy makers on the survival differences of lung cancer patients from different perspectives and to support the latest data in research and policy. It may help public health authorities and policy makers to identify and monitor public health problems and focus interventions to reduce potential excess deaths in these areas.8

Methods

Data Sources

We selected 922,317 lung cancer cases from the latest available data from the SEER database on April 15, 2021. Incidence - SEER Research Data, 18 Registries, Nov 2020 Sub (2000–2018). SEER 18 covers approximately 27.8% of the US population (based on the 2010 census). Geographic areas (registries) covered San Francisco-Oakland SMSA, Connecticut, Detroit (Metropolitan), Hawaii, Iowa, New Mexico, Seattle (Puget Sound), Utah, Atlanta (Metropolitan), San Jose-Monterey, Los Angeles, Alaska Natives, Rural Georgia, California excluding, Kentucky, Louisiana, New Jersey, and Greater Georgia. We selected 13 entries including ID, survival months, status, sex, age, year of diagnosis, race recode (White, Black, American Indian/Alaska Native, Asian or Pacific Islander), origin recode the National Health Insurance Authority (Hispanic, Non-Hispanic), primary site-labeled, laterality, median household income inflation adjusted to 2019, the Rural-Urban Continuum Code, and ICD-O-3 (International Classification of Disease for Oncology-3) histologic type, The specific type of histologic type is shown in Table S1, but all lung tumors designed for this study refer to malignancies of the lung. Epithelial neoplasms including small cell carcinoma. Unless otherwise indicated, all text within the National Cancer Institute (NCI) products is free of copyright and may be reused without permission. Credit the NCI as the source. Each entry is integrated and grouped, and the specific grouping is shown in Table 1.

Table 1.

Basic Characteristics of Patients and Survival Analysis According to Different Factors

Number of Patients Percentage of Total Patients (%) 3-Year Survival Rate (%) Probability Density 5-Year Survival Rate (%) Probability Density 10-Year Survival Rate (%) Probability Density Median Survival Time (Months) Standard Error 95.0%, CI Mean Survival Time (Months) Standard Error 95.0%, CI
Lower Upper Lower Upper
Total 9,22,317 100 19 0.003 14 0.002 8 0.001 9 0.021 8.959 9.041 32.793 0.066 32.663 32.922
Sex
Female 4,32,762 46.9 23 0.004 18 0.002 10 0.001 11 0.039 10.923 11.077 38.805 0.107 38.595 39.015
Male 4,89,555 53.1 16 0.003 12 0.002 6 0.001 8 0.025 7.952 8.048 27.522 0.08 27.365 27.68
Age
< 45 years 15,701 1.7 32 0.003 28 0.001 24 0.001 16 0.284 15.443 16.557 67.082 0.763 65.586 68.579
45–54 years 74,518 8.1 24 0.003 20 0.001 15 0.001 12 0.088 11.827 12.173 46.308 0.29 45.74 46.876
55–64 years 1,98,128 21.5 23 0.003 18 0.002 12 0.001 11 0.051 10.9 11.1 41.111 0.165 40.788 41.433
65–74 years 3,00,953 32.6 21 0.004 16 0.002 8 0.001 11 0.041 10.92 11.08 34.554 0.115 34.33 34.779
75–84 years 2,54,341 27.6 15 0.003 10 0.002 3 0.001 7 0.034 6.933 7.067 23.075 0.087 22.904 23.246
≥ 85 years 78,676 8.5 7 0.002 4 0.001 1 0 3 0.034 2.933 3.067 12.349 0.091 12.171 12.527
Race
White 7,65,078 83 19 0.003 14 0.002 8 0.001 9 0.023 8.955 9.045 32.726 0.072 32.585 32.867
Black 1,00,450 10.9 17 0.003 12 0.002 7 0.001 9 0.06 8.882 9.118 29.497 0.191 29.124 29.871
Asian and others (a) 56,789 6.2 23 0.004 17 0.002 11 0.001 12 0.124 11.757 12.243 40.002 0.32 39.375 40.629
Origin recode NHIA
Non-Spanish-Hispanic-Latino 8,72,814 94.6 19 0.003 14 0.002 8 0.001 9 0.021 8.958 9.042 32.686 0.068 32.553 32.818
Spanish-Hispanic-Latino 49,503 5.4 20 0.003 15 0.002 9 0.001 9 0.094 8.816 9.184 35.001 0.321 34.373 35.629
Median household income inflation adj to 2019
< $35,000 19,711 2.1 15 0.003 11 0.001 5 0.001 7 0.111 6.783 7.217 25.872 0.405 25.079 26.665
$35,000-$44,999 76,395 8.3 16 0.003 12 0.002 6 0.001 8 0.064 7.875 8.125 28.092 0.219 27.663 28.521
$45,000-$54,999 1,52,943 16.6 17 0.003 13 0.002 6 0.001 8 0.049 7.905 8.095 28.94 0.151 28.645 29.235
$55,000-$64,999 2,18,082 23.6 18 0.003 14 0.002 8 0.001 9 0.042 8.917 9.083 31.782 0.132 31.522 32.041
$65,000-$74,999 1,95,430 21.2 20 0.003 15 0.002 8 0.001 9 0.05 8.901 9.099 33.927 0.147 33.639 34.215
$75,000+ 2,59,669 28.2 22 0.004 16 0.002 9 0.001 11 0.045 10.911 11.089 36.832 0.133 36.571 37.92
Others (b) 87 0 13 0.01 10 0.002 0 0 14 2.287 9.517 18.483 25.118 3.734 17.799 32.438
Rural-Urban Continuum Code
Counties in metropolitan areas greater than 1 million population 5,24,354 56.9 20 0.003 15 0.002 9 0.001 10 0.031 9.939 10.061 34.716 0.091 34.537 34.895
Counties in metropolitan areas of 250,000 to 1 million population 1,76,075 19.1 19 0.003 14 0.002 8 0.001 9 0.047 8.907 9.093 32.469 0.151 32.172 32.765
Counties in metropolitan areas of less than 250 thousand population 81,081 8.8 18 0.003 13 0.002 7 0.001 9 0.068 8.867 9.133 29.798 0.205 29.396 30.199
Nonmetropolitan counties adjacent to a metropolitan area 80,876 8.8 16 0.003 12 0.002 6 0.001 8 0.064 7.875 8.125 28.298 0.2 27.906 28.689
Nonmetropolitan counties not adjacent to a metropolitan area 58,676 6.4 16 0.003 11 0.002 6 0.001 8 0.07 7.863 8.137 27.212 0.231 26.76 27.664
Others (c) 1255 0.1 14 0.003 11 0.001 5 0 9 0.475 8.069 9.931 25.974 1.478 23.078 28.87
Primary site
Right upper lobe 2,44,392 26.5 23 0.004 17 0.002 10 0.001 12 0.052 11.898 12.102 38.607 0.136 38.341 38.873
Right middle lobe 38,374 4.2 26 0.004 20 0.002 12 0.001 13 0.151 12.705 13.295 43.843 0.381 43.097 44.589
Right lower lobe 1,23,735 13.4 22 0.004 17 0.002 9 0.001 11 0.072 10.859 11.141 37.296 0.191 36.922 37.671
Left upper lobe 1,95,234 21.2 22 0.004 16 0.002 9 0.001 11 0.053 10.896 11.104 36.099 0.149 35.807 36.39
Left lower lobe 99,281 10.8 23 0.004 18 0.002 10 0.001 11 0.078 10.848 11.152 37.904 0.221 37.471 38.337
Main bronchus 43,133 4.7 8 0.002 6 0.001 4 0 5 0.055 4.892 5.108 17.515 0.211 17.102 17.927
Over lapping lesion of lung 10,731 1.2 17 0.003 13 0.001 7 0.001 7 0.164 6.678 7.322 28.642 0.562 27.541 29.743
Lung, NOS 1,64,777 17.9 7 0.002 4 0.001 2 0 4 0.026 3.949 4.051 13.678 0.092 13.497 13.859
Others (d) 2660 0.3 8 0.002 5 0.001 2 0.001 5 0.22 4.569 5.431 15.838 0.668 14.527 17.148
Histologic type (ICD-O-3)
Neoplasia, NAS 67,189 7.3 6 0.002 4 0.001 2 0 2 0.027 1.946 2.054 12.431 0.156 12.126 12.736
Epithelial Neoplasms, NAS 2,94,702 32 9 0.002 6 0.001 3 0 6 0.024 5.954 6.046 17.939 0.074 17.794 18.084
Squamous cell neoplasms 1,79,942 19.5 20 0.004 15 0.002 7 0.001 11 0.055 10.893 11.107 32.733 0.136 32.468 32.999
Adenoma and adenocarcinomas 3,47,366 37.7 28 0.004 22 0.002 13 0.001 15 0.061 14.88 15.12 46.591 0.132 46.333 46.849
Cystic, mucinous and serous neoplasms 12,070 1.3 29 0.004 23 0.002 14 0.001 15 0.377 14.261 15.739 48.995 0.762 47.5 50.489
Acinous cell neoplasm 7044 0.8 67 0.005 55 0.004 34 0.002 86 2.44 81.217 90.783 102.005 1.719 98.636 105.373
Complex epithelial neoplasms 10,523 1.1 26 0.004 20 0.002 11 0.001 14 0.319 13.375 14.625 42.256 0.671 40.94 43.571
Others (e) 3481 0.4 30 0.003 26 0.002 19 0.001 12 0.566 10.891 13.109 56.854 1.541 53.834 59.874
Year of diagnosis
2000 48,893 5.3 15 0.003 11 0.001 6 0.001 8 0.071 7.862 8.138 27.008 0.228 26.56 27.455
2001 49,520 5.37 15 0.003 11 0.001 6 0.001 8 0.07 7.863 8.137 26.954 0.223 26.517 27.391
2002 49,658 5.38 15 0.003 11 0.001 6 0.001 8 0.07 7.863 8.137 26.672 0.216 26.249 27.095
2003 50,123 5.43 16 0.003 12 0.001 7 0.001 8 0.075 7.854 8.146 26.974 0.211 26.56 27.389
2004 49,890 5.41 16 0.003 12 0.002 7 0.001 8 0.076 7.851 8.149 27.146 0.206 26.741 27.55
2005 50,749 5.5 17 0.003 13 0.002 7 0.001 8 0.082 7.839 8.161 27.358 0.2 26.966 27.751
2006 51,223 5.55 18 0.003 13 0.002 7 0.001 9 0.085 8.833 9.167 27.555 0.194 27.175 27.935
2007 51,598 5.59 18 0.003 14 0.002 7 0.001 9 0.089 8.826 9.174 27.275 0.184 26.915 27.636
2008 51,869 5.62 19 0.003 14 0.002 8 0.001 9 0.086 8.831 9.169 26.995 0.175 26.653 27.338
2009 52,587 5.7 19 0.003 14 0.002 N/A N/A 9 0.087 8.829 9.171 26.466 0.164 26.145 26.787
2010 51,355 5.57 20 0.003 15 0.002 N/A N/A 9 0.087 8.829 9.171 25.787 0.155 25.483 26.091
2011 50,918 5.52 21 0.003 15 0.002 N/A N/A 10 0.101 9.803 10.197 25.461 0.145 25.177 25.745
2012 51,591 5.59 20 0.003 15 0.002 N/A N/A 10 0.099 9.806 10.194 23.689 0.129 23.435 23.943
2013 51,787 5.61 21 0.003 16 0.002 N/A N/A 10 0.102 9.8 10.2 22.55 0.115 22.324 22.776
2014 52,469 5.69 23 0.004 N/A N/A N/A N/A 11 0.104 10.796 11.204 21.215 0.1 21.019 21.411
2015 52,702 5.71 24 0.004 N/A N/A N/A N/A 11 0.124 10.757 11.243 19.492 0.083 19.33 19.654
2016 52,642 5.71 N/A N/A N/A N/A N/A N/A 12 0.135 11.736 12.264 16.725 0.064 16.601 16.85
2017 52,743 5.72 N/A N/A N/A N/A N/A N/A 13 0.152 12.703 13.297 12.966 0.042 12.883 13.05
Summary stage
Distant 4,80,617 52.1 5 0.002 3 0.001 2 0 4 0.013 3.974 4.026 12.89. 0.047 12.798 12.982
Localized 1,69,955 18.4 51 0.006 40 0.004 24 0.002 49 0.258 48.494 49.506 78.295 0.22 77.863 78.726
Regional 2,03,809 22.1 28 0.005 21 0.003 11 0.001 18 0.076 17.851 18.149 45.042 0.154 44.739 45.344
Unknown/unstaged 67,936 7.4 10 0.003 7 0.001 3 0 6 0.07 5.863 6.137 19.61 0.186 19.245 19.976
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Notes: (a) included Asian or Pacific Islander and American Indian/Alaska Native. (b) Others included unknown/missing/no match/Not 1990–2018. (c) Others included Unknown/missing/no match (Alaska or Hawaii - Entire State) and Unknown/missing/no match/Not 1990–2018. (d) Others included Only one side - side unspecified, Bilateral, single primary and Paired site, but no information concerning laterality. (e) Others included all the histological types of lung cancer except the above seven types.

Data Processing and Statistical Analysis

Because the data volume and analysis items were too large and limited to the length of the paper, the focus was briefly described in the results, and detailed and specific contents are detailed in the tables, figures, and other supplementary materials. We used frequency function statistics, and statistical analysis was performed with SPSS v. 24 (IBM). We used GraphPad Prism 8 to plot the trend of median survival time in different subgroups. We performed life table analysis, Kaplan Meier survival analysis, univariate and multivariate Cox proportional hazards analysis to analyze patient data.

Log rank (Mantel-Cox), Breslow (generalized Wilcoxon) and Tarone-Ware tests were used to compare the distribution of survival data between groups. To explore the factors influencing survival time (survival speed) and predict survival probability, we used univariate and multivariate Cox proportional hazard analysis using the backward Wald method. Taking the first group of each project as the comparison object, the confidence interval of the Hazard Ratio (HR) was 95%, the step probability of entering was 0.05, the step probability of going out was 0.10, and the maximum number of iterations was 20.

Results

The median survival time of all lung cancer patients diagnosed in 2017 (14.030 months) increased by 41.72% compared with 2000 (9.900 months). Table 1 describes the 3-, 5-, and 10-year survival rates, median survival time, and mean survival time according to the variables defined in the Methods section. Table 2 describes the chi square and P values of the three test methods of population comparison and pairwise comparison in Kaplan Meier survival analysis. Figure 2 shows the survival curves according to primary lung cancer site and patient demographics. Table 3 describes the univariate and multivariate Cox proportional HR, for which the first group of each item is taken as the comparison object.

Table 2.

Overall Comparison and Pairwise Comparison of Each Group in Kaplan–Meier Survival Analysis

Comparison Type Comparative Factor Log Rank (Mantel-Cox) Breslow (Generalized Wilcoxon) Tarone-Ware
Chi Square Sig. Chi Square Sig. Chi Square Sig.
Overall comparison Sex 3,119.588 0.000 2,577.577 0.000 2,934.977 0.000
Age 36,486.760 0.000 33,627.846 0.000 34,681.780 0.000
Race 1,300.355 0.000 1,210.942 0.000 1,311.907 0.000
Origin recode NHIA 10.506 0.001 0.624 0.429 0.323 0.570
Median household income inflation adj to 2019 3,119.588 0.000 2,577.577 0.000 2,934.977 0.000
Rural-Urban Continuum Code 1,952.945 0.000 1,397.391 0.000 1,696.331 0.000
Primary site 56,749.667 0.000 57,432.600 0.000 59,443.510 0.000
Histologic type (ICD-O-3) 82,913.123 0.000 79,928.300 0.000 84,548.100 0.000
Year of diagnosis 7,532.042 0.000 5,692.115 0.000 6,834.910 0.000
Summary stage 240,670.146 0.000 219,186.158 0.000 239,656.003 0.000
Pairwise comparison Sex
Female vs Male 9,473.321 0.000 7,344.132 0.000 8,697.481 0.000
Age
< 45 years vs 45–54 years 658.146 0.000 451.420 0.000 535.237 0.000
< 45 years vs 55–64 years 1,186.997 0.000 755.752 0.000 891.847 0.000
< 45 years vs 65–74 years 2,134.621 0.000 1,209.475 0.000 1,450.388 0.000
< 45 years vs 75–84 years 5,280.355 0.000 3,281.758 0.000 3,847.412 0.000
< 45 years vs ≥ 85 years 9,405.387 0.000 7,374.587 0.000 8,275.701 0.000
45–54 years vs 55–64 years 168.537 0.000 131.890 0.000 125.492 0.000
45–54 years vs 65–74 years 1,135.723 0.000 766.972 0.000 783.114 0.000
45–54 years vs 75–84 years 7,332.664 0.000 5,949.599 0.000 6,199.769 0.000
45–54 years vs≥ 85 years 16,522.957 0.000 16,185.395 0.000 16,484.200 0.000
55–64 years vs 65–74 years 734.202 0.000 495.365 0.000 520.272 0.000
55–64 years vs 75–84 years 9,978.407 0.000 8,503.476 0.000 8,906.353 0.000
55–64 years vs≥ 85 years 21,880.320 0.000 21,656.557 0.000 22,006.761 0.000
65–74 years vs 75–84 years 7,052.078 0.000 6,213.807 0.000 6,581.952 0.000
65–74 years vs≥ 85 years 19,673.925 0.000 19,042.105 0.000 19,640.948 0.000
75–84 years vs ≥ 85 years 6,915.700 0.000 6,358.064 0.000 6,757.770 0.000
Race
White vs Black 278.487 0.000 106.505 0.000 189.853 0.000
White vs Asian and other races 918.554 0.000 1,032.227 0.000 1,028.928 0.000
Black vs Asian and other races 1,325.507 0.000 1,162.642 0.000 1,310.095 0.000
Origin recode NHIA
Non-Spanish-Hispanic-Latino vs Spanish-Hispanic-Latino 10.506 0.001 0.624 0.429 0.323 0.570
Median household income inflation adj to 2019
 < $35,000 vs $35,000-$44,999 42.062 0.000 33.672 0.000 40.737 0.000
 < $35,000 vs $45,000-$54,999 85.564 0.000 68.062 0.000 81.767 0.000
 < $35,000 vs $55,000-$64,999 230.631 0.000 172.090 0.000 206.247 0.000
 < $35,000 vs $65,000-$74,999 431.627 0.000 337.420 0.000 396.074 0.000
 < $35,000 vs $75,000+ 811.362 0.000 684.642 0.000 774.900 0.000
 < $35,000 vs Others 2.197 0.138 4.895 0.027 4.144 0.042
 $35,000-$44,999 vs $45,000-$54,999 16.965 0.000 12.927 0.000 15.542 0.000
 $35,000-$44,999 vs $55,000-$64,999 214.341 0.000 144.686 0.000 176.486 0.000
 $35,000-$44,999 vs $65,000-$74,999 588.760 0.000 440.256 0.000 520.033 0.000
 $35,000-$44,999 vs $75,000+ 1,464.530 0.000 1,219.404 0.000 1,378.889 0.000
 $35,000-$44,999 vs Others 1.005 0.316 3.174 0.075 2.395 0.122
 $45,000-$54,999 vs $55,000-$64,999 176.365 0.000 107.494 0.000 134.260 0.000
 $45,000-$54,999 vs $65,000-$74,999 636.716 0.000 461.262 0.000 549.033 0.000
 $45,000-$54,999 vs $75,000+ 1,882.057 0.000 1,547.162 0.000 1,755.248 0.000
 $45,000-$54,999 vs Others 0.699 0.403 2.703 0.100 1.938 0.164
 $55,000-$64,999 vs $65,000-$74,999 177.901 0.000 155.032 0.000 175.937 0.000
 $55,000-$64,999 vs $75,000+ 1,064.955 0.000 995.599 0.000 1,088.148 0.000
 $55,000-$64,999 vs Others 0.219 0.640 1.752 0.186 1.068 0.301
 $65,000-$74,999 vs $75,000+ 314.574 0.000 308.995 0.000 328.720 0.000
 $65,000-$74,999 vs Others 0.007 0.933 0.987 0.321 0.450 0.502
 $75,000+ vs Others 0.160 0.690 0.267 0.605 0.029 0.864
Rural-Urban Continuum Code
Counties in metropolitan areas greater than 1 million population vs Counties in metropolitan areas of 250,000 to 1 million population 154.789 0.000 89.246 0.000 118.829 0.000
Counties in metropolitan areas greater than 1 million population vs Counties in metropolitan areas of less than 250 thousand population 489.541 0.000 339.405 0.000 414.594 0.000
Counties in metropolitan areas greater than 1 million population vs Nonmetropolitan counties adjacent to a metropolitan area 898.955 0.000 628.695 0.000 771.331 0.000
Counties in metropolitan areas greater than 1 million population vs Nonmetropolitan counties not adjacent to a metropolitan area 1,002.371 0.000 758.392 0.000 899.192 0.000
Counties in metropolitan areas greater than 1 million population vs Others 22.407 0.000 9.820 0.002 15.310 0.000
Counties in metropolitan areas of 250,000 to 1 million population vs Counties in metropolitan areas of less than 250 thousand population 132.516 0.000 103.077 0.000 119.878 0.000
Counties in metropolitan areas of 250,000 to 1 million population vs Nonmetropolitan counties adjacent to a metropolitan area 343.469 0.000 256.190 0.000 307.174 0.000
Counties in metropolitan areas of 250,000 to 1 million population vs Nonmetropolitan counties not adjacent to a metropolitan area 471.405 0.000 381.350 0.000 441.650 0.000
Counties in metropolitan areas of 250,000 to 1 million population vs Others 12.395 0.000 4.685 0.030 7.959 0.005
Counties in metropolitan areas of less than 250 thousand population vs Nonmetropolitan counties adjacent to a metropolitan area 36.154 0.000 24.804 0.000 31.550 0.000
Counties in metropolitan areas of less than 250 thousand population vs Nonmetropolitan counties not adjacent to a metropolitan area 102.205 0.000 84.179 0.000 98.169 0.000
Counties in metropolitan areas of less than 250 thousand population vs Others 3.187 0.074 0.355 0.551 1.314 0.252
Nonmetropolitan counties adjacent to a metropolitan area vs Nonmetropolitan County not adjacent to a metropolitan area 21.335 0.000 21.435 0.000 22.933 0.000
Nonmetropolitan counties adjacent to a metropolitan area vs Others 0.529 0.467 0.090 0.764 0.022 0.882
Nonmetropolitan counties not adjacent to a metropolitan area vs Others 0.031 0.860 1.436 0.231 0.617 0.432
Primary site
Right upper lobe vs Right middle lobe 162.922 0.000 80.685 0.000 116.572 0.000
Right upper lobe vs Right lower lobe 54.723 0.000 68.757 0.000 64.783 0.000
Right upper lobe vs Left upper lobe 168.685 0.000 76.857 0.000 122.258 0.000
Right upper lobe vs Left lower lobe 19.496 0.000 15.767 0.000 19.963 0.000
Right upper lobe vs Main bronchus 10,216.526 0.000 10,257.262 0.000 10,769.433 0.000
Right upper lobe vs Over lapping lesion of lung 595.338 0.000 829.226 0.000 770.682 0.000
Right upper lobe vs Lung, NOS 37,093.583 0.000 36,323.045 0.000 38,235.231 0.000
Right upper lobe vs Others 699.934 0.000 612.111 0.000 668.653 0.000
Right middle lobe vs Right lower lobe 263.986 0.000 173.472 0.000 217.803 0.000
Right middle lobe vs Left upper lobe 383.715 0.000 183.845 0.000 276.207 0.000
Right middle lobe vs Left lower lobe 203.992 0.000 112.926 0.000 158.356 0.000
Right middle lobe vs Main bronchus 6,517.198 0.000 5,704.728 0.000 6,423.992 0.000
Right middle lobe vs Over lapping lesion of lung 779.740 0.000 877.108 0.000 882.311 0.000
Right middle lobe vs Lung, NOS 13,575.417 0.000 11,318.686 0.000 13,058.521 0.000
Right middle lobe vs Others 827.004 0.000 682.774 0.000 765.542 0.000
Right lower lobe vs Left upper lobe 13.780 0.000 0.580 0.446 2.000 0.157
Right lower lobe vs Left lower lobe 4.529 0.033 10.831 0.001 6.940 0.008
Right lower lobe vs Main bronchus 7,741.953 0.000 7,473.661 0.000 8,027.688 0.000
Right lower lobe vs Over lapping lesion of lung 446.655 0.000 621.232 0.000 581.078 0.000
Right lower lobe vs Lung, NOS 23,928.595 0.000 22,385.509 0.000 24,235.716 0.000
Right lower lobe vs Others 609.686 0.000 513.797 0.000 571.712 0.000
Left upper lobe vs Left lower lobe 33.598 0.000 8.632 0.003 17.905 0.000
Left upper lobe vs Main bronchus 8,554.529 0.000 8,966.598 0.000 9,271.170 0.000
Left upper lobe vs Over lapping lesion of lung 419.865 0.000 684.012 0.000 599.494 0.000
Left upper lobe vs Lung, NOS 30,093.214 0.000 30,515.243 0.000 31,760.602 0.000
Left upper lobe vs Others 604.525 0.000 551.023 0.000 591.460 0.000
Left lower lobe vs Main bronchus 7,605.617 0.000 7,473.549 0.000 7,956.885 0.000
Left lower lobe vs Over lapping lesion of lung 487.337 0.000 692.059 0.000 636.294 0.000
Left lower lobe vs Lung, NOS 21,655.850 0.000 20,479.488 0.000 22,098.264 0.000
Left lower lobe vs Others 639.715 0.000 558.856 0.000 611.053 0.000
Main bronchus vs Over lapping lesion of lung 574.941 0.000 374.213 0.000 491.592 0.000
Main bronchus vs Lung, NOS 482.626 0.000 590.283 0.000 555.427 0.000
Main bronchus vs Others 1.595 0.207 8.097 0.004 5.825 0.016
Over lapping lesion of lung vs Lung, NOS 1,416.129 0.000 1,047.110 0.000 1,270.005 0.000
Over lapping lesion of lung vs Others 122.072 0.000 55.546 0.000 83.040 0.000
Lung, NOS vs Others 52.256 0.000 91.285 0.000 79.609 0.000
Right upper lobe vs Other single lobes 71.499 0.000 53.158 0.000 66.958 0.000
Right middle lobe vs Other single lobes 284.671 0.000 149.788 0.000 212.357 0.000
Right lower lobe vs Other single lobes 21.601 0.000 43.991 0.000 32.919 0.000
Left upper lobe vs Other single lobes 174.418 0.000 57.640 0.000 108.889 0.000
Left lower lobe vs Other single lobes 0.963 0.326 1.070 0.301 1.432 0.231
Main bronchus vs Single lobes 11,026.346 0.000 11,283.718 0.000 11,727.875 0.000
Over lapping lesion of lung vs Single lobes 547.887 0.000 786.542 0.000 722.280 0.000
Lung, NOS vs Single lobes 50,039.338 0.000 51,295.080 0.000 52,602.027 0.000
Histologic type (ICD-O-3)
Neoplasia, NAS vs Epithelial neoplasms, NAS 3,757.214 0.000 7,408.176 0.000 5,986.605 0.000
Neoplasia, NAS vs Squamous cell neoplasms 20,217.196 0.000 27,516.738 0.000 25,146.774 0.000
Neoplasia, NAS vs Adenoma and adenocarcinomas 35,445.959 0.000 40,577.637 0.000 39,259.802 0.000
Neoplasia, NAS vs Cystic, mucinous and serous neoplasms 6,149.905 0.000 6,029.979 0.000 6,450.057 0.000
Neoplasia, NAS vs Acinous cell neoplasm 11,950.640 0.000 10,107.204 0.000 11,760.036 0.000
Neoplasia, NAS vs Complex epithelial neoplasms 4,939.508 0.000 5,491.534 0.000 5,632.441 0.000
Neoplasia, NAS vs Others 1,961.725 0.000 1,547.515 0.000 1,799.985 0.000
Epithelial neoplasms, NAS vs Squamous cell neoplasms 18,051.629 0.000 18,642.122 0.000 19,723.395 0.000
Epithelial neoplasms, NAS vs Adenoma and adenocarcinomas 52,956.139 0.000 43,604.909 0.000 49,887.906 0.000
Epithelial neoplasms, NAS vs Cystic, mucinous and serous neoplasms 3,920.902 0.000 2,832.710 0.000 3,530.938 0.000
Epithelial neoplasms, NAS vs Acinous cell neoplasm 9,902.939 0.000 8,306.628 0.000 9,832.557 0.000
Epithelial neoplasms, NAS vs Complex epithelial neoplasms 2,880.374 0.000 2,512.595 0.000 2,904.016 0.000
Neoplasia, NAS vs Complex epithelial neoplasms 4,939.508 0.000 5,491.534 0.000 5,632.441 0.000
Epithelial neoplasms, NAS vs Others 1,183.182 0.000 575.683 0.000 841.398 0.000
Squamous cell neoplasms vs Adenoma and adenocarcinomas 4,324.050 0.000 2,002.280 0.000 2,974.305 0.000
Squamous cell neoplasms vs Cystic, mucinous and serous neoplasms 526.311 0.000 232.401 0.000 355.225 0.000
Squamous cell neoplasms vs Acinous cell neoplasm 5,171.203 0.000 4,982.770 0.000 5,383.737 0.000
Squamous cell neoplasms vs Complex epithelial neoplasms 246.850 0.000 171.523 0.000 210.048 0.000
Squamous cell neoplasms vs Others 211.562 0.000 15.811 0.000 64.762 0.000
Adenoma and adenocarcinomas vs Cystic, mucinous and serous neoplasms 9.479 0.002 4.511 0.034 6.611 0.010
Adenoma and adenocarcinomas vs Acinous cell neoplasm 3,429.157 0.000 3,748.082 0.000 3,805.019 0.000
Adenoma and adenocarcinomas vs Complex epithelial neoplasms 14.960 0.000 0.000 0.991 2.697 0.101
Adenoma and adenocarcinomas vs Others 10.571 0.001 7.914 0.005 0.424 0.515
Cystic, mucinous and serous neoplasms vs Acinous cell neoplasm 2,508.321 0.000 3,023.062 0.000 2,957.332 0.000
Cystic, mucinous and serous neoplasms vs Complex epithelial neoplasms 24.420 0.000 2.074 0.150 8.732 0.003
Cystic, mucinous and serous neoplasms vs Others 0.961 0.327 12.862 0.000 3.988 0.046
Acinous cell neoplasm vs Complex epithelial neoplasms 2,915.827 0.000 3,292.872 0.000 3,306.154 0.000
Acinous cell neoplasm vs Others 1,432.131 0.000 2,382.199 0.000 2,110.827 0.000
Complex epithelial neoplasms vs Others 20.792 0.000 6.543 0.011 0.027 0.871
Summary stage
Distant vs Localized 189,234.197 0.000 157,689.763 0.000 180,494.909 0.000
Distant vs Regional 95,182.979 0.000 89,552.783 0.000 97,474.996 0.000
Distant vs Unknown/unstaged 2,281.394 0.000 1,319.592 0.000 1,873.692 0.000
Localized vs Regional 22,646.800 0.000 24,779.500 0.000 25,260.467 0.000
Localized vs Unknown/unstaged 54,328.909 0.000 60,221.013 0.000 59,752.077 0.000
Regional vs Unknown/unstaged 15,840.215 0.000 19,402.780 0.000 18,494.477 0.000
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Figure 2.

Figure 2

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Kaplan–Meier survival curves of lung cancer patients according to primary site and demographics. (A) All primary site groups. (B) Right upper lobe. (C) Right middle lobe. (D) Right lower lobe. (E) Left upper lobe. (F) Left lower lobe. (G) Main bronchus. (H) Overlapping lesion of lung. (I) Right upper lobe and right middle lobe. (J) Right upper lobe and right lower lobe. (K) Right upper lobe and left upper lobe. (L) Right upper lobe and left lower lobe. (M) Middle lobe and right lower lobe. (N) Right middle lobe and left upper lobe. (O) Middle lobe and left lower lobe. (P) Right lower lobe and left upper lobe. (Q) Right lower lobe and left lower lobe. (R) Left upper lobe and left lower lobe. (S) Address groups. (T) Income groups. (U) Ethnic groups. (V) Age groups. (W) Race groups. (X) Sex groups.

Table 3.

Univariate and Multivariate Cox Proportional Hazards Analysis of Lung Cancer Based on SEER Database

Types of Cox Analysis Comparing Factors B SE Wald df Sig. HR 95.0% HR, CI
Lower Upper
Univariate Primary site 51,359.75 8 0.000
Right middle lobe vs Right upper lobe −0.075 0.006 152.810 1 0.000 0.927 0.916 0.939
Right lower lobe vs Right upper lobe 0.027 0.004 49.306 1 0.000 1.027 1.019 1.035
Left upper lobe vs Right upper lobe 0.041 0.003 151.521 1 0.000 1.042 1.035 1.048
Left lower lobe vs Right upper lobe 0.017 0.004 16.670 1 0.000 1.017 1.009 1.025
Main bronchus vs Right upper lobe 0.528 0.005 9,373.596 1 0.000 1.696 1.678 1.714
Over lapping lesion of lung vs Right upper lobe 0.247 0.010 557.362 1 0.000 1.280 1.254 1.306
Lung, NOS vs Right upper lobe 0.654 0.004 34,847.930 1 0.000 1.923 1.910 1.937
Others (a) vs Right upper lobe 0.511 0.020 626.507 1 0.000 1.666 1.601 1.734
Sex
Male vs Female 0.215 0.002 8,886.971 1 0.000 1.240 1.234 1.245
Age 33,386.410 5 0.000
45–54 years vs < 45 years 0.277 0.010 724.156 1 0.000 1.319 1.293 1.346
55–64 years vs < 45 years 0.343 0.010 1,225.613 1 0.000 1.409 1.382 1.436
65–74 years vs < 45 years 0.426 0.010 1,941.140 1 0.000 1.532 1.503 1.561
75–84 years vs < 45 years 0.658 0.010 4,590.031 1 0.000 1.931 1.894 1.968
85+ years vs < 45 years 1.001 0.010 9,588.206 1 0.000 2.722 2.668 2.777
Race 1,222.947 2 0.000
Black vs White 0.059 0.004 263.022 1 0.000 1.061 1.053 1.068
Others (b) vs White −0.144 0.005 867.837 1 0.000 0.865 0.857 0.874
Origin recode NHIA
Non-Spanish-Hispanic-Latino vs Spanish-Hispanic-Latino 0.016 0.005 9.888 1 0.002 1.016 1.006 1.027
Median household income inflation adj to 2019 2,931.738 6 0.000
$35,000–$44,999 vs <$35,000 −0.054 0.009 38.994 1 0.000 0.948 0.932 0.964
$45,000–$54,999 vs <$35,000 −0.072 0.008 78.900 1 0.000 0.930 0.915 0.945
$55,000–$64,999 vs <$35,000 −0.119 0.008 220.252 1 0.000 0.888 0.874 0.902
$65,000–$74,999 vs <$35,000 −0.163 0.008 407.928 1 0.000 0.850 0.836 0.863
$75,000+ vs <$35,000 −0.219 0.008 756.831 1 0.000 0.803 0.790 0.816
Others (c) vs <$35,000 −0.173 0.123 1.967 1 0.161 0.841 0.661 1.071
Rural-Urban Continuum 1,835.107 5 0.000
Counties in metropolitan areas of 250,000 to 1 million pop vs Counties in metropolitan areas of greater than 1 million pop 0.036 0.003 146.527 1 0.000 1.037 1.031 1.043
Counties in metropolitan areas of less than 250 thousand pop vs Counties in metropolitan areas of greater than 1 million pop 0.087 0.004 462.909 1 0.000 1.091 1.083 1.100
Nonmetropolitan counties adjacent to a metropolitan area vs Counties in metropolitan areas of greater than 1 million pop 0.118 0.004 848.592 1 0.000 1.126 1.117 1.135
Nonmetropolitan counties not adjacent to a metropolitan vs Counties in metropolitan areas of greater than 1 million pop 0.144 0.005 946.941 1 0.000 1.155 1.144 1.166
Others (d) vs Counties in metropolitan areas of greater than 1 million pop 0.139 0.030 21.202 1 0.000 1.149 1.083 1.220
Histologic type (ICD-O-3) 74,262.360 7 0.000
Epithelial neoplasms, NAS vs Neoplasia, NAS −0.296 0.005 3,638.861 1 0.000 0.744 0.737 0.751
Squamous cell neoplasms vs Neoplasia, NAS −0.700 0.005 18,147.780 1 0.000 0.497 0.492 0.502
Adenoma and adenocarcinomas vs Neoplasia, NAS −0.900 0.005 33,303.950 1 0.000 0.406 0.403 0.410
Cystic, mucinous and serous neoplasms vs Neoplasia, NAS −0.933 0.011 6,687.317 1 0.000 0.393 0.385 0.402
Acinous cell neoplasm vs Neoplasia, NAS −2.005 0.021 9,539.132 1 0.000 0.135 0.129 0.140
Complex epithelial neoplasms vs Neoplasia, NAS −0.859 0.012 5,433.430 1 0.000 0.424 0.414 0.433
Others (e) vs Neoplasia, NAS −0.962 0.020 2,265.927 1 0.000 0.382 0.367 0.398
Year of diagnosis 7,025.014 17 0.000
2001 vs 2000 −0.006 0.007 0.709 1 0.400 0.994 0.982 1.007
2002 vs 2000 −0.006 0.007 0.912 1 0.339 0.994 0.981 1.007
2003 vs 2000 −0.022 0.007 11.283 1 0.001 0.978 0.966 0.991
2004 vs 2000 −0.038 0.007 33.250 1 0.000 0.963 0.951 0.975
2005 vs 2000 −0.054 0.007 68.099 1 0.000 0.947 0.935 0.960
2006 vs 2000 −0.077 0.007 136.769 1 0.000 0.926 0.914 0.938
2007 vs 2000 −0.088 0.007 181.709 1 0.000 0.915 0.904 0.927
2008 vs 2000 −0.104 0.007 252.221 1 0.000 0.901 0.889 0.913
2009 vs 2000 −0.117 0.007 315.202 1 0.000 0.890 0.878 0.901
2010 vs 2000 −0.131 0.007 388.059 1 0.000 0.877 0.866 0.889
2011 vs 2000 −0.162 0.007 586.987 1 0.000 0.850 0.839 0.861
2012 vs 2000 −0.156 0.007 540.690 1 0.000 0.855 0.844 0.867
2013 vs 2000 −0.182 0.007 724.595 1 0.000 0.833 0.822 0.844
2014 vs 2000 −0.220 0.007 1,029.316 1 0.000 0.803 0.792 0.814
2015 vs 2000 −0.271 0.007 1,512.721 1 0.000 0.762 0.752 0.773
2016 vs 2000 −0.311 0.007 1,876.193 1 0.000 0.733 0.722 0.743
2017 vs 2000 −0.348 0.008 2,105.528 1 0.000 0.706 0.696 0.717
Summary stage 205,903.400 3 0
Localized vs Distant −1.426 0.004 165,939.800 1 0 0.240 0.239 0.242
Regional vs Distant −0.884 0.003 90,444.560 1 0 0.413 0.411 0.415
Unknown/unstaged vs Distant −0.256 0.005 2,733.579 1 0 0.774 0.767 0.782
Multivariate Primary Site 30,355.820 8 0.000
Right middle lobe vs Right upper lobe −0.045 0.006 55.071 1 0.000 0.956 0.944 0.967
Right lower lobe vs Right upper lobe 0.038 0.004 100.117 1 0.000 1.039 1.031 1.047
Left upper lobe vs Right upper lobe 0.028 0.003 71.195 1 0.000 1.028 1.022 1.035
Left lower lobe vs Right upper lobe 0.031 0.004 55.730 1 0.000 1.031 1.023 1.040
Main bronchus vs Right upper lobe 0.446 0.005 6,583.468 1 0.000 1.562 1.545 1.579
Over lapping lesion of lung vs Right upper lobe 0.257 0.010 603.009 1 0.000 1.293 1.267 1.320
Lung, NOS vs Right upper lobe 0.519 0.004 20,830.791 1 0.000 1.681 1.669 1.693
Others (f) vs Right upper lobe 0.424 0.020 431.055 1 0.000 1.528 1.468 1.590
Sex
Male vs Female 0.197 0.002 7,283.054 1 0.000 1.217 1.212 1.223
Age 29,870.587 5 0.000
45–54 years vs < 45 years 0.261 0.010 639.066 1 0.000 1.299 1.272 1.325
55–64 years vs < 45 years 0.348 0.010 1,254.460 1 0.000 1.417 1.389 1.444
65–74 years vs < 45 years 0.459 0.010 2,223.302 1 0.000 1.582 1.552 1.613
75–84 years vs < 45 years 0.688 0.010 4,960.363 1 0.000 1.990 1.952 2.029
85+ years vs < 45 years 0.960 0.010 8,635.988 1 0.000 2.611 2.559 2.665
Race 849.583 2 0.000
Black vs White 0.095 0.004 642.820 1 0.000 1.099 1.091 1.108
Others (g) vs White −0.062 0.005 153.648 1 0.000 0.939 0.930 0.949
Origin recode NHIA
Non-Spanish-Hispanic-Latino vs Spanish-Hispanic-Latino 0.018 0.005 12.181 1 0.000 1.018 1.008 1.029
Median household income inflation adj to 2019 1,279.382 6 0.000
$35,000–$44,999 vs <$35,000 −0.055 0.009 37.947 1 0.000 0.946 0.930 0.963
$45,000–$54,999 vs <$35,000 −0.082 0.009 87.256 1 0.000 0.921 0.905 0.937
$55,000–$64,999 vs <$35,000 −0.126 0.009 194.220 1 0.000 0.881 0.866 0.897
$65,000–$74,999 vs <$35,000 −0.165 0.009 316.049 1 0.000 0.848 0.833 0.864
$75,000+ vs <$35,000 −0.203 0.009 479.380 1 0.000 0.816 0.802 0.831
Others (h) vs <$35,000 −0.773 0.127 36.796 1 0.000 0.462 0.360 0.593
Rural-Urban Continuum 83.075 5 0.000
Counties in metropolitan areas of 250,000 to 1 million pop vs Counties in metropolitan areas of greater than 1 million pop 0.013 0.003 19.031 1 0.000 1.014 1.007 1.020
Counties in metropolitan areas of less than 250 thousand pop vs Counties in metropolitan areas of greater than 1 million pop 0.001 0.004 0.068 1 0.795 1.001 0.992 1.010
Nonmetropolitan counties adjacent to a metropolitan area vs Counties in metropolitan areas of greater than 1 million pop −0.005 0.005 0.897 1 0.344 0.995 0.986 1.005
Nonmetropolitan counties not adjacent to a metropolitan vs Counties in metropolitan areas of greater than 1 million pop 0.008 0.006 1.923 1 0.166 1.008 0.997 1.020
Others (i) vs Counties in metropolitan areas of greater than 1 million pop 0.243 0.032 59.247 1 0.000 1.275 1.199 1.357
Histologic type ICDO3 42,139.807 7 0.000
Epithelial neoplasms, NAS vs Neoplasia, NAS −0.053 0.005 106.351 1 0.000 0.949 0.939 0.958
Squamous cell neoplasms vs Neoplasia, NAS −0.428 0.005 6,132.065 1 0.000 0.652 0.645 0.659
Adenoma and adenocarcinomas vs Neoplasia, NAS −0.557 0.005 11,534.349 1 0.000 0.573 0.567 0.579
Cystic, mucinous and serous neoplasms vs Neoplasia, NAS −0.578 0.012 2,506.946 1 0.000 0.561 0.549 0.574
Acinous cell neoplasm vs Neoplasia, NAS −1.553 0.021 5,656.729 1 0.000 0.212 0.203 0.220
Complex epithelial neoplasms vs Neoplasia, NAS −0.533 0.012 2,045.116 1 0.000 0.587 0.574 0.601
Others (j) vs Neoplasia, NAS −0.619 0.020 928.675 1 0.000 0.539 0.518 0.560
Year of diagnosis 2,414.036 17 0.000
2001 vs 2000 −0.010 0.007 2.319 1 0.128 0.990 0.977 1.003
2002 vs 2000 −0.014 0.007 4.348 1 0.037 0.986 0.974 0.999
2003 vs 2000 −0.034 0.007 27.497 1 0.000 0.966 0.954 0.979
2004 vs 2000 −0.050 0.007 58.507 1 0.000 0.951 0.939 0.963
2005 vs 2000 −0.061 0.007 86.634 1 0.000 0.941 0.929 0.953
2006 vs 2000 −0.079 0.007 142.858 1 0.000 0.924 0.913 0.936
2007 vs 2000 −0.083 0.007 159.809 1 0.000 0.920 0.908 0.932
2008 vs 2000 −0.092 0.007 193.962 1 0.000 0.912 0.900 0.924
2009 vs 2000 −0.099 0.007 223.976 1 0.000 0.906 0.894 0.918
2010 vs 2000 −0.100 0.007 224.238 1 0.000 0.905 0.893 0.917
2011 vs 2000 −0.110 0.007 267.803 1 0.000 0.896 0.884 0.907
2012 vs 2000 −0.100 0.007 218.197 1 0.000 0.905 0.893 0.917
2013 vs 2000 −0.115 0.007 283.473 1 0.000 0.891 0.880 0.903
2014 vs 2000 −0.141 0.007 418.512 1 0.000 0.868 0.857 0.880
2015 vs 2000 −0.176 0.007 631.345 1 0.000 0.838 0.827 0.850
2016 vs 2000 −0.200 0.007 762.693 1 0.000 0.819 0.808 0.831
2017 vs 2000 −0.231 0.008 918.224 1 0.000 0.794 0.782 0.806
Summary stage 184,737.000 3 0.000
Localized vs Distant −1.385 0.004 149,948.100 1 0.000 0.250 0.248 0.252
Regional vs Distant −0.854 0.003 82,171.650 1 0.000 0.426 0.423 0.428
Unknown/unstaged vs Distant −0.533 0.005 11,191.940 1 0.000 0.587 0.581 0.593
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Notes: (a) Others included Only one side - side unspecified, Bilateral, single primary and Paired site, but no information concerning laterality. (b) Others included Asian or Pacific Islander and American Indian/Alaska Native. (c) Others included unknown/missing/no match/Not 1990–2018. (d) Others included Unknown/missing/no match (Alaska or Hawaii - Entire State) and Unknown/missing/no match/Not 1990–2018. (e) Others included all the histological types of lung cancer except the above seven types. (f) Others included Only one side - side unspecified, Bilateral, single primary and Paired site, but no information concerning laterality. (g) Others included Asian or Pacific Islander and American Indian/Alaska Native (h) Others included unknown/missing/no match/Not 1990–2018 (i) Others included Unknown/missing/no match (Alaska or Hawaii - Entire State) and Unknown/missing/no match/Not 1990–2018. (j) Others included all the histological types of lung cancer except the above seven types.

Sex

The median survival time of female patients increased faster than in males (Figure 1A and B). The median survival time of female patients diagnosed in 2017 (18.000 months, Table S2) increased by 70.94% (Table S3) compared with 2000 (10.530 months, Table S1). In males, the trend was similar although the increase was smaller: from 9.450 months in 2000 to 11.540 months in 2017 (Table S2), an increase of 22.12% (Table S3). Surprisingly, the difference in median survival time between female and male patients increased from 1.08 months to 6.46 months (Table S2). The 3-, 5-, and 10-year survival rates for female patients were 23%, 18%, and 10%, respectively; and for male patients these were 16%, 12%, and 6%, respectively (Table 1). The log rank (Mantel-Cox) for the overall comparison of females with males was 3,119.588, Breslow (generalized Wilcoxon) was 2,577.577, and Tarone-Ware was 2934.977. For the pairwise comparison, the log rank (Mantel-Cox) was 9,473.321, Breslow (generalized Wilcoxon) was 7,344.132, and Tarone-Ware was 8697.481. All had P < 0.001 (Table 2). The HR for univariate Cox analyses of male:female was 1.240 (1.234–1.246), P < 0.001. The HR for multivariate Cox analyses of male:female was 1.217 (1.212–1.223), P < 0.001 (Table 3).

Figure 1.

Figure 1

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Median survival time. Survival and its growth rate in lung cancer patients from 2000 to 2017. (A and B) According to sex. (C and D) According to primary site. (E and F) According to age. (G and H) According to median household income (inflation adjusted to 2019). (I and J) According to address. (K and L) According to histologic type. (M and N) According to race. (O and P) According to ethnic group.

Primary Site

The median survival time when the primary site was in one lobe was greater than in patients whose primary site was in the main bronchus with an overlapping lesion in the lung (Figure 1C and D). Patients diagnosed in 2017 with a primary site in the right middle lobe had the longest median survival time (20.370 months), then in the left lower lobe (19.000 months), right upper lobe (17.930 months), right lower lobe (17.690 months), and left upper lobe (17.120 months, Table S4). The survival time of patients with single-lobe cancer increased markedly since 2000: the number of patients diagnosed in 2017 at the primary site of the right middle lobe, left lower lobe, right lower lobe, right upper lobe, and left upper lobe increased by 85.35%, 78.91%, 66.89, 65.56%, and 55.92%, respectively (Table S5). The specific values of the 3-year, 5-year, and 10-year survival rates of lung cancer patients of different primary sites were shown in Table 1.

The log rank (Mantel-Cox) for the overall comparison was 56,749.667, the Breslow (generalized Wilcoxon) was 57,432.600, and Tarone-Ware was 59,443.510, with P < 0.001 for all (Table 2). The specific values of univariate and multivariate hazard ratios (HRs) for different primary sites were shown in Table 3.

Age

Younger patients had a longer median survival time (Figure 1E and F), but survival time was almost equal between the 55–64 and 65–74 age groups, and the changes were synchronous (Tables S6 and S7). The sudden decrease in the median survival time of patients with lung cancer diagnosed in 2016 and 2017 in the group less than or equal to 44 years may be related to the small number of patients at onset and cannot be counted in the changing trend that the median survival time of patients with lung cancer diagnosed in the group less than or equal to 44 years increased overall. The specific values of the 3-year, 5-year, and 10-year survival rates of lung cancer patients of different ages were shown in Table 1. The log rank (Mantel-Cox) for the overall comparison was 36,486.760, the Breslow (generalized Wilcoxon) was 33,627.846, and Tarone-Ware was 34,681.780, P < 0.001 for all (Table 2). The specific values of univariate and multivariate hazard ratios (HRs) for different ages were shown in Table 3.

Median Household Income

A longer median survival time was seen in patients with higher incomes (Figure 1G and H) and Table S8). The median survival time of the $75,000 + group (18.24 months) was 7.740 months longer than the $35,000 group (10.500 months). The median survival times of the $35,000–$44,999, $45,000–$54,999, $55,000–$64,999 and $65,000–$74,999 groups were 10.890 months, 11.490 months, 12.260 months, and 15.730 months, respectively. The fastest increase in median survival time was 78.30% and 60.35% for the $75,000+ and $65,000–$74,999 groups, respectively (Table S9). The specific values of the 3-year, 5-year, and 10-year survival rates of lung cancer patients of different incomes were shown in Table 1. The log rank (Mantel-Cox) for the overall comparison was 3,119.588, the Breslow (generalized Wilcoxon) was 2,577.577, and Tarone-Ware was 2,934.977, P < 0.001 for all (Table 2). The specific values of univariate and multivariate hazard ratios (HRs) for different median household incomes were shown in Table 3.

Address

A longer survival time was seen in a metropolitan population (Figure 1I and J) and Table S9). Survival in metropolitan areas of 1 million (15.970 months) exceeded 14.030 months (all lung cancer patients), while in metropolitan areas of 1 million this was 13.720 months. Times in other areas were: metropolitan areas of 250,000 (11.700 months), nonmetropolitan counties adjacent to a metropolitan area (11.520 months), and the nonmetropolitan counties not adjacent to a metropolitan area group (10.990 months) had less survival time than 14.030 months (Table S10). As can be seen from Table S10, the fastest increases in median survival time were 60.34% and 38.03% for metropolitan areas of 1 million and metropolitan areas of 1 million, respectively (Table S11). The specific values of the 3-year, 5-year, and 10-year survival rates of lung cancer patients of different addresses were shown in Table 1. The log rank (Mantel-Cox) for the overall comparison was 1,952.945, the Breslow (generalized Wilcoxon) was 1,397.391, and Tarone-Ware was 1,696.331, all P < 0.001 (Table 2). The specific values of univariate and multivariate hazard ratios (HRs) for different addresses were shown in Table 3.

Histologic Type ICD-O-3

Median survival time of lung cancer patients in the adenocarcinoma group (Diagnosed 2017) was significantly higher than all other patients, followed by the complex epithelial neoplasms and squamous cell neoplasms groups. (Figure 1K and L) and Table S12). The number of patients in the Adenoma and adenocarcinomas group diagnosed in 2017 increased by 87.35% compared to 2000. Survival time in the Squamous cell neoplasms group (15.270 months) was longer than 14.030 months (Figure 1K and L) and Table S12), and the number of patients diagnosed in 2017 increased by 38.44% compared to 2000. Median survival time in the other groups was as follows: Neoplasia, NAS (8.100 months), Epithelial neoplasms, NAS (9.200 months) and Cystic, mucinous and serous neoplasms (12.000 months). Each was shorter than 14.030 months (Table S12 and S13). The specific values of the 3-year, 5-year, and 10-year survival rates of lung cancer patients of different histologic types were shown in Table 1.

The log rank (Mantel-Cox) for the overall comparison was 82,913.123, the Breslow (generalized Wilcoxon) was 79,928.300, and Tarone-Ware was 84,548.100, all P < 0.001 (Table 2). The specific values of univariate and multivariate hazard ratios (HRs) for different histologic types were shown in Table 3.

Race

Median survival time of Asian and other races diagnosed in 2017 was 97.87% higher than in 2000 (Figure 1M and N), and median survival time of White patients increased by 38.61%. In contrast, Black patients only had a 24.77% increase, which is below average (Table S15). Among lung cancer patients diagnosed in 2017, median survival was 13.750 months for White patients, 11.890 months for Black patients, and 20.420 months for Asian and other patients (Table S14). The 3 -, 5 -, and 10-year survival rates for White, Black, Asian and other races were, in order: 19.00%, 14.00%, 8.00%; 17.00%, 12.00%, 7.00%; 23.00%, 17.00%, 11.00% (Table 1).

The log rank (Mantel-Cox) for the overall comparison was 1,300.355, the Breslow (generalized Wilcoxon) was 1,210.942, and Tarone-Ware was 1,311.907, all P < 0.001 (Table 2). Univariate HRs compared with White for Black, Asian and other races were, in order: 1.061 (1.053–1.068) and 0.865 (0.857–0.874), P < 0.001. Multivariate HRs were, in order: 1.099 (1.091–1.108), 0.939 (0.930–0.949), all P < 0.001 (Table 3). The specific values of univariate and multivariate hazard ratios (HRs) for different races were shown in Table 3.

Origin Recode the National Health Insurance Authority

Median survival time was 14.110 months for Non-Spanish-Hispanic-Latino patients diagnosed in 2017 and 12.860 months for Spanish-Hispanic-Latino patients (Figure 1O and P) and Table S16). Compared to patients diagnosed in 2000, survival in Non-Spanish-Hispanic-Latinos increased by 42.67% and in Spanish-Hispanic-Latinos by 28.60% (Table S17). The 3 -, 5 -, and 10-year survival rates for Non-Spanish-Hispanic-Latinos and Spanish-Hispanic-Latinos were, in order: 19.00%, 14.00%, 8.00%; 20.00%, 15.00%, 9.00% (Table 1).

The log rank (Mantel-Cox) for the pairwise and overall comparisons was 10.506, the Breslow (generalized Wilcoxon) was 0.624, and Tarone-Ware was 0.323. P values were < 0.001, 0.429, and 0.570, respectively (Table 2). Univariate HR compared with Spanish-Hispanic-Latino for Non-Spanish-Hispanic-Latino was 1.016 (1.006–1.027), P = 0.002. Multivariate HR was 1.018 (1.008–1.029), P < 0.001 (Table 3).

Summary Stage

The survival rates of lung cancer patients at different summary stages vary considerably, as detailed in Table 1. The survival difference of lung cancer patients with different summary stages was statistically significant (Table 2). The hrs of lung cancer patients with different summary stages differed significantly (Table 3). The survival curves and median survival times of lung cancer patients with different summary stages are shown in Figure 3.

Figure 3.

Figure 3

Open in a new tab

Survival curves of different summary stages and changes in median survival time of lung cancer patients from 2000 to 2017. (A) Median survival time of lung cancer patients at different summary stages from 2000 to 2017. (B) Increase in median survival time of lung cancer patients at different summary stages from 2000 to 2017. (C) Kaplan–Meier survival curves for different summary stages.

Discussion

According to Howlader and Forjaz,1 lung cancer mortality rate in the US has decreased significantly recently. Although lung cancer incidence has been described in multiple papers,9–12 studies with large samples, multiple sub items, multiple statistical analysis methods, and statistical details by year of diagnosis are not common13 and the data are mostly outdated.14–17 Therefore, we took advantage of the new data published by SEER on April 15, 2021, which allowed a detailed analysis of the survival of lung cancer patients in the US. After an in-depth study of 922,317 patients, we have several novel findings. The median survival time of all lung cancer patients diagnosed in 2017 (14.030 months) increased by 41.72% compared with 2000 (9.900 months).

Women’s median survival time and 3-year, 5-year, and 10-year survival rates were more significant and growing faster than men’s. Pilleron et al18 also found that gender was one of the most important factors influencing lung cancer survival time. The prognosis of female patients undergoing lobectomy/segmentectomy was significantly better than in male patients.19 Part of the reason may be that men have a higher smoking rate,20 and the pathobiology of adenocarcinoma in women may differ from that in men.21

The median survival time of patients with a single lobe primary site was the longest where this was in the right middle lobe, followed by the left upper lobe, right upper lobe, right lower lobe, and the shortest in left lower lobe. The rapidly increasing survival time may be due to the increase in early diagnosis of lung cancer22 and improved thoracoscopic lobectomy and segmentectomy techniques.23 In contrast, median survival rates where the primary site was in the main bronchus and over lapping lung did not significantly increase. These are independent predictors of lung cancer metastasis and worse outcomes.24

Although younger patients had a longer median survival time, interestingly, median survival time was almost the same in the 55–64 and 65–74 groups. This may be because there is little difference in the physical condition25 between the two age groups. The median survival time in those over 75 was significantly reduced, which may be related to the decline of the patient’s physical fitness or the increased likelihood of severe complications, which are associated with poor survival.26

Median survival time was longer for patients with higher incomes and there was also an association between family disposable income and survival.27 Low-income patients with lung cancer may have delays in diagnosis and treatment, requiring social intervention and care.28 Increased healthcare costs in the public sector were associated with lower cancer mortality.29

The farther the patient’s address is from a metropolitan area, the shorter the median survival time. In metropolitan areas with a population of more than 1 million, median survival time exceeded that of all other lung cancer patients, which may be related to the availability and timeliness of access to good medical care in these areas. The HR was highest in nonmetropolitan counties not adjacent to metropolitan areas. Singh and Siahpush found a widening life expectancy gap between urban and rural areas for lung cancer patients in the US between 1969–2009,30 and our results found that this gap has widened even further over the last decade. Routine tracking of lung cancer excess deaths through urban-rural county classification may help public health authorities and policy makers identify and monitor public health concerns and focus interventions to reduce potential excess deaths in these areas.8

Median survival time of lung cancer patients in the adenocarcinoma group (Diagnosed 2017) was significantly higher than all other patients, followed by the complex epithelial neoplasms and squamous cell neoplasms groups. Median survival time in the adenocarcinoma group was 6.35 months longer than in squamous cell carcinoma. This may be related to the improvement of minimally invasive surgery,31 chemotherapy,32 immunotherapy,33,34 molecular targeted therapy34 or other treatments for lung adenocarcinoma. The Epithelial neoplasms, NAS group was one of the worst groups, containing mainly large and small cell lung cancer. Although there are some new treatments,35–38 survival time has not improved significantly. The acinous cell neoplasm group had the longest median survival of lung cancer histology.

The median survival times and rates of Asian, Pacific Islanders and Native American Indians/Alaskans were significantly higher than of White and Black people, and the fastest growth rate was about 97.87%. In contrast, the growth rate in White people was only about 38.61% and in Black people was only about 24.76%. This may be due to different access to health care and the provision of recommended treatment.39 Efforts to ensure that all patients with lung cancer receive timely and appropriate treatment should reduce differences in survival between races.40 Median survival time was 14.110 months for Non-Spanish-Hispanic-Latino lung cancer patients (an increase of 42.67%) and 12.860 months for Spanish-Hispanic-Latino (an increase of only 28.60%). The univariate HR of non-Hispanic Latinos was higher than in Hispanic Latinos, which is contrary to a previous study41 but may be due to a difference in sample size. According to Soneji et al42 narrowing racial differences in lung cancer survival rates depends not only on equal opportunities for surgical resection, but also on better management and treatment of smoking-related complications and diseases.42

The later the year of diagnosis, the longer the median survival time and the lower the risk ratio. This showed that in the past 20 years, the treatment effect in the US has improved. The reason for the survival time of localized lung cancer patients is greater than that of Distant patients. This fully shows that early detection and early treatment are very important in the treatment of lung cancer.

Our study provides detailed insight into the relationship between patients’ sex, primary site, age, income, residential address, histological type, race, ethnicity, and survival thanks to the large sample size. However, we acknowledge that if patient data from other countries can be integrated, our study would be more representative. Incidence of lung cancer was not analyzed in detail so this could be further studied in subsequent papers. The SEER database still has some shortcomings, such as not collecting information on “smoking”.

Conclusions

After analyzing the data of 922,317 patients with lung cancer in the recently-published SEER database, we found large differences in survival time by gender, race and ethnicity, age, income, address, histological type, primary site and summary stage. This difference has grown in recent years. Government and society need to further strengthen policies to improve trends. We should increase the frequency and precision of lung cancer screening in the future.

Acknowledgments

Acknowledgment

We hereby thank the staff of the Department of Thoracic Surgery of the Second Affiliated Hospital of Nanchang University for their strong support for this study.

Abbreviations

HR, Hazard Ratio; ICD-O-3, International Classification of Disease for Oncology-3; NCI, The National Cancer Institute; SEER, The surveillance, epidemiology, and end results.

Ethics Approval and Informed Consent

Since SEER is an open database and all the data extracted from SEER are nonhuman studies, there is no need to obtain ethical approval from the Ethics Committee of the Second Affiliated Hospital of Nanchang University. Data published by the SEER database is publicly available and identifiable and therefore does not require patient informed consent.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

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