Background: Lung cancer is a leading cause of death worldwide, and its incidence shows an upward trend. A study of the long-term changes in the premature death rate in lung cancer in a developed region of China has great exploratory significance to further clarify the effectiveness of intervention measures.
Objective: This study examined long-term changes in premature lung cancer death rates in order to understand the changes in mortality and to design future prevention plans in Pudong New Area (PNA), Shanghai, China.
Methods: Cancer death data were collected from the Mortality Registration System of PNA. We analyzed the crude mortality rate (CMR), age-standardized mortality rate by Segi’s world standard population (ASMRW), and years of life lost (YLL) of patients with lung cancer from 1973 to 2019. Temporal trends in the CMR, ASMRW, and YLL rate were calculated by joinpoint regression expressed as an average annual percentage change (AAPC) with the corresponding 95% CI.
Results: All registered permanent residents in PNA (80,543,137 person-years) from 1973 to 2019 were enrolled in this study. There were 42,229 deaths from lung cancer. The CMR and ASMRW were 52.43/105 and 27.79/105 person-years, respectively. The YLL due to premature death from lung cancer was 481779.14 years, and the YLL rate was 598.16/105 person-years. The CMR and YLL rate showed significantly increasing trends in men, women, and the total population (P<.001). The CMR of the total population increased by 2.86% (95% CI 2.66-3.07, P<.001) per year during the study period. The YLL rate increased with an AAPC of 2.21% (95% CI 1.92-2.51, P<.001) per year. The contribution rates of increased CMR values caused by demographic factors were more evident than those caused by nondemographic factors.
Conclusions: Lung cancer deaths showed an increasing trend in PNA from 1973 to 2019. Demographic factors, such as the aging population, contributed more to an increased CMR. Our research can help us understand the changes in lung cancer mortality and can be used for similar cities in designing future prevention plans.
Lung cancer is the leading cause of cancer-related deaths worldwide, with 2,206,771 new lung cancer cases and 1,796,144 deaths in 2020 . Many studies have made tremendous efforts in the discovery of potential biomarkers for the detection, classification, and progression monitoring of lung cancer. Lung cancer treatment has made great progress over the past decade. Study of the long-term changes in the disease burden of lung cancer has great exploratory significance to further clarify the epidemiological characteristics of lung cancer and improve patient survival times [ ].
In recent decades, China has witnessed rapid economic development, and tremendous changes have occurred in the population and epidemics . Shanghai is an economic, science and technology, industrial, financial, and exhibition center and is 1 of the earliest cities in China to enter an aging society. Shanghai is a representative city for modernization development in China. In the next 20 years, other cities in China and other low- and middle-income countries (LMICs) are likely to follow the development characteristics of Shanghai [ ]. The Shanghai Pudong New Area (PNA) officially began to develop on April 18, 1990. Since then, Pudong has become 1 of the areas with the fastest urbanization and economic growth in China. Economic growth and total scale have highlighted the speed and height of Pudong’s development and opening up. Over the past 30 years, PNA has adhered to reform, expansion, and strengthened innovation. It has developed from a field into a modern urban area with concentrated elements and advanced facilities. It has become the epitome of Shanghai's modernization and the symbol of China's reform and expansion [ , ].
Cancer is a disease that seriously endangers human health. In the past decade, cancer has been the main cause of death in China . The treatment of cancer has become the most important research direction in the world to improve life expectancy [ ]. Years of life lost (YLL) refers to the loss of life caused by early death. It can more accurately reflect the burden on society [ ]. The aging population, progress of treatment, smoking, and environmental pollution may be factors that affect long-term changes in the premature death rate in lung cancer. An epidemiological study of lung cancer mortality trends over time may help quantify its impacts on public health and society, promote the assessment of current protocols for lung cancer, and define high-risk populations that will benefit from early detection programs for lung cancer [ ]. Our study examined long-term changes in the premature death rate in lung cancer from 1973 to 2019 in PNA, Shanghai, China, to improve public health.
Cancer death data were collected from the Mortality Registration System of PNA, including age, gender, date, and cause of death. The complete population data were provided by the Statistics Bureau and the Public Security Bureau of PNA . Periodic evaluations, data cleaning, and compilation were performed to ensure completeness of the registration system. The per capita gross domestic product (GDP) of Shanghai and PNA were collected from the Shanghai Municipal Bureau of Statistics [ ] and the Shanghai PNA Bureau of Statistics [ ].
Deaths from malignant neoplasm of the trachea (C33) and bronchus and lung (C34) were classified by the underlying cause of lung cancer deaths according to the International Classification of Diseases 10th Revision (ICD-10) . Since the data covered a long time span of 47 years, data before 1975, coded based on ICD-8, and data for 1975-2001, coded based on ICD-9, were converted to ICD-10 codes.
Causes of death were coded by rigorously trained clinicians, and each record was further verified by the Center for Disease Control and Prevention (CDC).
Ethics Approval and Consent to Participate
Our study did not involve any intervention in human participants. The surveillance protocol was approved by the ethical committee of the Shanghai PNA Center CDC. Strict confidentiality of individual data was practiced throughout the study.
The crude mortality rate (CMR) and the age-standardized mortality rate by Segi’s world standard population (ASMRW) of neurological disorders were calculated per 100,000 (/105). The CMR and ASMRW between genders were compared using the Poisson approximation method and the Mantel-Haenszel test, respectively.
The YLL was calculated according to the original method described by Murray and Lopez . The equation used to calculate the YLL is as follows [ ]:
YLL = KCera/(r + β)2｛e–( r + β)(L + a) [–( r + β)(L + a) – 1] – e–(r + β)a[–(r + β)a – 1]} + [(1 – k)/r] × (1 – e–rL),
where a is the age at death, β is the age weighting parameter (β=.04), C is the age weighting fit with constant (C=0.1658), r is the discount rate (r=3%), L is the standard life expectancy at the age of death according to the standard reference life table for the Global Burden of Disease (GBD) study , and e is the Napier constant.
The calculation of the YLL was performed using the World Health Organization (WHO) template .
Temporal trends in the CMR, ASMRW, and YLL rate were calculated using joinpoint Regression 188.8.131.52 (National Cancer Institute, Bethesda, MD, USA) and expressed as an average annual percentage change (AAPC) with a corresponding 95% CI. The Z test was performed to assess whether the AAPC was statistically different from 0. The terms “increase” and “decrease” were used to describe a statistically significant (P<.05) AAPC, while “stable” was used for not statistically significant trends.
Age was classified into 8 groups: 0-4, 5-14, 15-29, 30-44, 45-59, 60-69, 70-79, and 80+ years. Age-specific CMRs were calculated for each age group. Changes in the mortality rates of each period in 5 years from 1973 to 2019 were compared with the period before it or the data from 1973 to 1979, and causes from demographic and nondemographic factors were estimated by the decomposition method, in which mortality rates were calculated and compared for each 5-year age group, from 0-4 to 85+ years . All statistical analyses were conducted using SPSS Statistics version 21.0 (SPSS, Inc, Chicago, IL, USA) and R version 3.4.3 (R Core Team). Statistical significance was set at P<.05.
Baseline Characteristics of Underlying Death from Lung Cancer
From 1973 to 2019, all registered permanent residents in PNA, with a total of 80,543,137 person-years, were enrolled in this study. There were 42,229 deaths from lung cancer. Of these, 30,638 (72.55%) patients were men. The median age at death from lung cancer was 72.10 years, and the average age at death was 70.96±11.21 years. The CMR and ASMRW of lung cancer were 52.43/105 and 27.79/105 person-years, respectively. In addition, the CMR and ASMRW were 77.04/105 and 44.27/105 person-years, respectively, in men, while the corresponding rates were 28.43/105 and 13.77/105 person-years, respectively, in women ().
|Characteristic||Deaths, n (%)||Age (years), mean (SD)||Age (years), median||CMRa (/105 person-years)||ASMRWb (/105 person-years)||YLLc (years)||YLL rate (/105 person-years)|
|Male||30,638 (72.55)||70.54 (10.74)||71.56||77.04||44.27||343,728.73||864.30|
|Female||11,591 (27.45)||72.08 (12.30)||73.73||28.43||13.77||138,050.40||338.58|
|1973-1979||929 (2.20)||64.88 (10.31)||66.38||21.57||23.40||12,915.91||299.88|
|1980-1984||969 (2.29)||65.75 (11.14)||67.08||29.29||28.79||13,006.25||393.17|
|1985-1989||969 (2.29)||66.47 (10.98)||67.48||31.51||28.45||12,711.93||413.33|
|1990-1994||1890 (4.48)||67.24 (10.42)||68.18||40.02||31.10||24,095.98||510.23|
|1995-1999||4797 (11.36)||68.32 (10.70)||69.77||43.16||30.70||59,014.12||530.92|
|2000-2004||6363 (15.07)||69.73 (11.10)||71.43||52.98||31.23||74,513.88||620.42|
|2005-2009||7595 (17.99)||71.22 (11.33)||73.46||57.88||27.68||84,179.23||641.55|
|2010-2014||8832 (20.91)||71.66 (11.47)||73.34||63.10||26.28||96,872.05||692.14|
|2015-2019||9885 (23.41)||72.65 (10.85)||72.62||66.40||24.02||104,535.93||702.19|
|Total||42,229 (100.00)||70.96 (11.21)||72.10||52.43||27.79||481,779.14||598.16|
aCMR: crude mortality rate.
bASMRW: age-standardized mortality rate by Segi’s world standard.
cYLL: years of life lost.
Age-specific Mortality in Lung Cancer
The CMRs in the age groups of 0-4, 5-14, 15-29, 30-44, 45-59, 60-69, 70-79, and ≥80 years were 0.09/105, 0.02/105, 0.36/105, 4.26/105, 35.97/105, 132.70/105, 302.76/105, and 372.98/105 person-years, respectively ().
|Group by age (years)||Deaths, n (%)||CMR (/105 person-years)||YLL (years)||YLL rate (/105 person-years)|
aCMR: crude mortality rate.
bYLL: years of life lost.
Burden of Premature Death from Lung Cancer
From 1973 to 2019, the YLL due to premature death from lung cancer was 481779.14 years and the YLL rate was 598.16/105 person-years. The YLL and rate of YLL in men (343,728.73 years and 864.30/105 person-years, respectively) were higher than those in women (138,050.40 years and 338.58/105 person-years, respectively); see. In terms of age, the top 3 YLL were in the age groups of 60-69, 70-79, and 45-59 years, which were 159,523.69, 134,731.32, and 119,690.09 years, respectively. The top 3 YLL rates were in the age groups of 70-79, 80+, and 60-69 years, which were 2785.91/105, 1975.87/105, and 1837.34/105, respectively ( ).
Trends in Mortality and YLL in Lung Cancer
The temporal trends in the CMR, ASMRW, and YLL rate were expressed based on the modeled CMR, ASMRW, and YLL rate, as shown in. The CMR and YLL rate for deaths from lung cancer showed significantly increasing trends in men and women, and the total population during 1973-2019 (all P<.001). The ASMRW decreased in men by 0.72% (95% CI –1.05 to –0.40, P<.001) per year, while the ASMRW in women and the total population during 1973-2019 was not statistically significant (P=.23 and .18, respectively). The CMR in lung cancer in the total population increased by 2.86% (95% CI 2.66-3.07, P<.001) per year during the study period. The YLL rate increased with an AAPC of 2.21% (95% CI 1.92-2.51, P<.001) per year from 1973 to 2019 ( A and 1B).
Regarding age-specific mortality, the YLL, CMR, and ASMRW of the total population were observed from 1973 to 2019 (C and 1D). The increasing trends in the CMR were also observed in the age groups of 70-79 years (P=.01) and 80+ years (P<.001). The 30-44-, 45-59-, and 60-69-year age groups had statistically decreasing trends in the CMR (P<.001). The YLL rate increased by 8.24% (95% CI 2.83-13.94, P=.01) per year in the age group of 80+ years and 0.03% (95% CI –0.44 to 0.50, P=.09) per year in the age group of 70-79 years. However, the YLL rate decreased by 1.51% (95% CI –2.51 to 0.05, P=.001) per year in the age group of 30-44 years, 1.27% (95% CI –1.72 to 0.83, P<.001) per year in the age group of 45-59 years, and 1.46% (95% CI –1.84 to 1.09, P<.001) per year in the age group of 60-69 years ( C and 1D).
Quantitatively Impacts of Demographic and Nondemographic Factors on Increased CMRs
The increasing CMRs caused by nondemographic and demographic factors are shown in. Based on the CMR in lung cancer in 1973-1979, no statistically significant trend was found caused by nondemographic factors in the total population, with an AAPC of 0.17% (95% CI –11.34 to 13.16, P=.97) from 1980 to 2019, but a significant upward trend was observed in the increased CMR caused by demographic factors (AAPC [95% CI]=51.70% [35.48-69.88], P<.001). In men, the increased CMR caused by nondemographic factors decreased by 32.96% (95% CI –51.68 to –6.99, P=.02) during 1980-2019, and the CMR caused by demographic factors increased by 46.42% (95% CI 32.23-62.03, P<.001). In women, the increased CMR caused by nondemographic factors showed an upward trend with an AAPC of 24.24% (95% CI 2.60-50.44, P=.03), and the CMR caused by demographic factors also increased (AAPC [95% CI]=55.63% [38.54-74.83], P<.001); see . B-D shows the proportion of increased CMR values caused by nondemographic and demographic factors. From 1985 to 2019, demographic factors played a decisive role in the contribution of the CMR compared to 1973-1979.
|Comparison periods||CMR of the based period (/105 person-years)||CMR of the other period (/105 person-years)||D value of mortality (/105)||Impact of demographic factors||Impact of nondemographic factors|
|Added value (/105 )||Contribution rate (%)||Added value (/105)||Contribution rate (%)|
|Panel A (based on the first period)|
|1980-1984 vs 1973-1979||21.57||29.29||7.72||2.00||25.68||5.73||74.14|
|1985-1989 vs 1973-1979||21.57||31.51||9.94||4.11||41.38||5.83||58.62|
|1990-1994 vs 1973-1979||21.57||40.02||18.45||10.20||55.28||8.25||44.72|
|1995-1999 vs 1973-1979||21.57||43.16||21.59||12.70||58.83||8.89||41.17|
|2000-2004 vs 1973-1979||21.57||52.98||31.41||19.86||63.21||11.55||36.79|
|2005-2009 vs 1973-1979||21.57||57.88||36.31||27.45||75.58||8.87||24.42|
|2010-2014 vs 1973-1979||21.57||63.10||41.53||34.10||82.11||7.43||17.89|
|2015-2019 vs 1973-1979||21.57||66.40||44.83||40.24||89.76||4.59||10.24|
|Panel B (based on the last period)|
|1980-1984 vs 1973-1979||21.57||29.29||7.72||2.00||25.68||5.73||74.14|
|1985-1989 vs 1980-1984||29.29||31.51||2.22||2.66||114.33||–0.44||-14.33|
|1990-1994 vs 1985-1989||31.51||40.02||8.51||7.61||89.34||0.91||10.66|
|1995-1999 vs 1990-1994||40.02||43.16||3.14||2.72||86.91||0.41||13.09|
|2000-2004 vs 1995-1999||43.16||52.98||9.82||8.13||82.79||1.69||17.21|
|2005-2009 vs 2000-2004||52.98||57.88||4.90||10.12||134.01||–5.21||34.01|
|2010-2014 vs 2005-2009||57.88||63.10||5.22||7.86||125.16||–2.64||25.16|
|2015-2019 vs 2010-2014||63.10||66.40||3.30||7.80||136.61||–4.50||36.61|
aCMR: crude mortality rate.
bPNA: Pudong New Area.
It is crucial to understand the long-term changes in the rate of premature death from lung cancer for medical treatment research to formulate future preventive measures. The goal of “Healthy China 2030” has been to reduce the premature death rate of noncommunicable diseases by 30% . Since 2000, many cities in China have gradually entered an aging society, and Shanghai is the first to do so. In recent years, the aging in Shanghai has not been alleviated but has gradually increased. Since 2018, PNA as a miniature Shanghai has already entered a superaging society, with a proportion of over 20% ( ). We concluded that the increasing trends in the CMR were seen in the age groups of 70-79 years (P=.01) and 80+ years (P<.001) in terms of age-specific mortality and burden. The YLL rate increased by 8.24% (95% CI 2.83-13.94, P=.01) per year in the age group of 80+ years and 0.03% (95% CI –0.44 to 0.50, P=.09) per year in the age group of 70-79 years. The proportion of individuals aged 70-79 years ( ) was almost the largest since 1995. The age groups under 70 years had statistically decreasing trends in lung cancer CMR (P<.001). It is evident that aging has contributed to an increase in lung cancer mortality.
Economic development, such as an increased GDP, improves public health. However, some factors related to the developed economy, such as lifestyle factors and environmental and medical levels, may also influence the mortality rate. Globally, smoking-attributable deaths have increased by 20.1% (15.3-25.2) since 1990, with most deaths occurring in China . In China, smoking has either peaked or continued to increase [ ]. According to our statistics over the past 50 years, the YLL rate increased with an AAPC of 2.21% per year from 1973 to 2019, and this may be associated with the increased smoking rate. The YLL rate of men is higher than that of women ( ), which is consistent with the difference in the smoking proportion between men and women.
Outdoor air pollution exposure is a clear carcinogen to humans . For decades, after rapid industrialization and urbanization, air pollution in China has worsened [ ]. Air pollution has significantly affected the health of Chinese people as 1 of the top 10 risk factors for death [ ]. Several large cohorts confirmed that the particulate matter (PM2.5) concentration in the environment is associated with the risk of lung adenocarcinoma in nonsmokers and lung cancer mortality in lifelong nonsmokers [ , ]. When the development of PNA started in 1990, the secondary industry accounted for more than 75% and the tertiary industry accounted for only 20% of the GDP of PNA. In 2018, the status of the secondary and tertiary industries was reversed, and the proportion of the tertiary industry exceeded 75% of the PNA GDP. However, the development of secondary industries cannot prevent air and environmental pollution. A long-period comparative analysis of air pollution in Shanghai analyzed the continuous Morlet wavelet transform on the time series of a 5274-day air pollution index from 2000. The monthly variation in air pollution in Shanghai was not significant, and air pollution in Shanghai showed an increasing trend, but the situation has reversed since 2015 [ ]. It is evident that in the past 50 years, especially before 2015, air pollution in PNA has led to an increasing trend in the YLL due to premature death in people with lung cancer in Shanghai.
The initial treatment of lung cancer is relatively simple, including surgery, chemotherapy, and radiotherapy. In the early 2000s, the key genes for lung cancer were identified. In this field, molecular detection is the basic method for guiding and individualizing treatment selection tools. Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are small molecule–targeted drugs widely used in advanced non-small-cell lung cancer (NSCLC). Its effectiveness can be shown in symptom improvement, lesion control, and prolongation of progression-free survival (PFS). Women and nonsmoking patients were the dominant groups in TKI treatment . The introduction of immune checkpoint inhibitors in 2015 was an important milestone in the treatment of lung cancer. Immunotherapy has been proven to have a long-lasting positive effect on patients with NSCLC and has been rapidly upgraded to first-line treatment after the success of second-line and backline treatments [ , ]. Since 2003, lung cancer–targeting drugs have entered the scope of Shanghai medical insurance and are widely used in lung cancer treatment. Furthermore, immunotherapy and antiangiogenic drugs have also been gradually introduced in Shanghai. The diversity of drug selection and the individualization and accuracy of treatment schemes directly affect the survival of patients with lung cancer. This may explain why the YLL rate showed a downward trend with an AAPC of the total population after 2005 compared with that before 2005. We found that, except for patients over 80 years old, the CMRs and YLL rate decreased after 2000 in almost all age groups. The changes in these data are related to the rapid development of tumor-targeted therapy and immunotherapy over the past 20 years.
Lung cancer is the leading cause of cancer-related deaths worldwide, with 2,206,771 new lung cancer cases and 1,796,144 deaths in 2020. Lung cancer has a high incidence rate and contributes to 30% of all cancer-related deaths in China. The mortality trends in lung cancer in the United States have gradually decreased . Mortality rates increased from 1990 by 3.91% per year and decreased from 2004 by 1.95% in Montenegro [ ]. Some studies have observed a sharp increase in the lung cancer mortality rate since 2000 in China [ ]. The lung cancer mortality rate increased from 30.18% in 2004 to 36.10% in 2010 [ ]. In 2018, the mortality rate of Chinese men was 68% higher than their US counterparts, while that of Chinese women was similar to that of US women. The difference in men may be related to smoking [ ]. Lung cancer mortality in China may increase by 40% between 2015 and 2030 [ ]. Our study also found that mortality increased significantly in both genders in PNA. In addition to reducing the proportion of smokers, the widespread application of chest computerized tomography (CT) screening will impact lung cancer mortality in China [ ].
Strengths and Limitations
This study has major strengths, including a large population size (over 8 million) and a relatively long time span (47 years). However, there are several limitations to the study. First, all our data were from a single district, although this district is the largest in Shanghai. Second, there were no data on lifestyle, histological typing, and disease history in our study, so it was impossible to determine the role of each risk factor that may lead to changes in lung cancer mortality . Nonetheless, our study was based on complete and accurate public data over 4 decades from the government surveillance system, and high data quality was ensured.
This population-based study found increasing trends in the mortality and burden of lung cancer in men and women, and the total population in a developed region of China from 1973 to 2019. Demographic factors, particularly aging, contributed to an increase in mortality. Our study can contribute to a better understanding of lung cancer and can be used in similar cities to design future prevention plans.
The authors thank all the staff in the vital statistics system of Pudong New Area (PNA) from 1973 to 2019 for their great work in data collection and ensuring high data quality.
This work was supported by the General Program of Health Bureau of Shanghai PNA (PW2021A-68), the Shanghai Specialized Research Fund for Integrated Chinese and Western Medicine in General Hospitals (ZHYY-ZXYJHZX-201914), the General Program of the National Natural Science Foundation of China (81673250), key disciplines of public health in Shanghai (GWV-10.1-XK17), the National Science and Technology Major Project of the Ministry of Science and Technology of China (2017ZX10201201-006-001), the Shanghai Public Health System Construction Three-year Action Plan Outstanding Youth Talent Training Program (GWV-10.2-YQ43), and the Reserve Academic Leaders Training Program of the Pudong New Area Center for Disease Control and Prevention (PDCDC-HBXD2020-05).
The data that support the findings of this study are available from the Center for Disease Control and Prevention (CDC) of Pudong New Area (PNA), Shanghai, but restrictions apply to the availability of these data, which were used under license for this study; therefore, they are not publicly available. However, data are available from the authors upon reasonable request and with permission from the CDC of PNA.
WY, WL, and XL drafted the manuscript. XL, WY, ZL, and YC participated in the collection, analysis, and interpretation of data. YC, ZL, WY, GZ, LW, CX, and XL contributed to the data collection and suggestions for analysis. CJ, LY, YC, and ZL conceived the study, participated in its design, and coordination and critically revised the manuscript. All authors read and approved the final manuscript.
Conflicts of Interest
Trends in the proportion of the ≥65-year age group in the total and female population in Shanghai PNA and the capital per GDP in Shanghai and Shanghai PNA from 1995 to 2018. GDP: gross domestic product; PNA: Pudong New Area.PNG File , 24 KB
Age composition of the population in Shanghai PNA from 1973 to 2019. PNA: Pudong New Area.PNG File , 20 KB
- World Health Organization International Agency for Research on Cancer. GLOBOCAN: Lung Cancer Fact Sheet 2020. URL: https://gco.iarc.fr/today/data/factsheets/cancers/15-Lung-fact-sheet.pdf [accessed 2020-12-01]
- Osmani L, Askin F, Gabrielson E, Li QK. Current WHO guidelines and the critical role of immunohistochemical markers in the subclassification of non-small cell lung carcinoma (NSCLC): moving from targeted therapy to immunotherapy. Semin Cancer Biol 2018 Oct;52(Pt 1):103-109 [FREE Full text] [CrossRef] [Medline]
- Wang J, Gao S, Wang Y, Zhou J, Lin J, Wang L, et al. Cancer incidence and mortality patterns in Luwan district of Shanghai during 2002-2011. Drug Discov Ther 2018 May 13;12(2):77-87 [FREE Full text] [CrossRef] [Medline]
- Li X, Deng Y, Tang W, Sun Q, Chen Y, Yang C, et al. Urban-rural disparity in cancer incidence, mortality, and survivals in Shanghai, China, during 2002 and 2015. Front Oncol 2018 Dec 3;8:579-579 [FREE Full text] [CrossRef] [Medline]
- Chen H, Hao L, Yang C, Yan B, Sun Q, Sun L, et al. Understanding the rapid increase in life expectancy in Shanghai, China: a population-based retrospective analysis. BMC Public Health 2018 Feb 14;18(1):256-256 [FREE Full text] [CrossRef] [Medline]
- Li X, Qian M, Zhao G, Yang C, Bao P, Chen Y, et al. The performance of a community-based colorectal cancer screening program: evidence from Shanghai Pudong New Area, China. Prev Med 2019 Jan;118:243-250. [CrossRef] [Medline]
- Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018 Nov 12;68(6):394-424 [FREE Full text] [CrossRef] [Medline]
- GBD 2016 Causes of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017 Sep;390(10100):1151-1210. [CrossRef]
- People's Government of Pudong New Area. Shanghai Statistical Yearbook. URL: http://www.pudong.gov.cn/shpd/InfoOpen/newTongJiList.aspx?CategoryNum=014004002002
- Shanghai Government. Annual Report of Finance Bureau. URL: https://www.shanghai.gov.cn/2021ndbg/index.html
- People's Government of Pudong New Area. Information disclosure of Finance Bureau. URL: https://www.pudong.gov.cn/zwgkzfxxgknbzfbm_czj/index.html
- Paoin W, Yuenyongsuwan M, Yokobori Y, Endo H, Kim S. Development of the ICD-10 simplified version and field test. Health Inf Manag 2018 May 06;47(2):77-84. [CrossRef] [Medline]
- Murray CJ, Lopez AD, World Health Organization , World B, Harvard School of Public Health. The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020. Summary. Geneva, Switzerland: World Health Organization; 1996:1-41.
- World Health Organization. Health Statistics and Information Systems, Disease Burden and Mortality Estimates. URL: https://www.who.int/healthinfo/global_burden_disease/estimates/en/index1.html [accessed 2020-07-31]
- World Health Organization. Global Health Estimates 2016: Disease Burden by Cause, Age, Sex, by Country and by Region, 2000-2016. Geneva: World Health Organization; 2018.
- Cheng X, Yang Y, Schwebel DC, Liu Z, Li L, Cheng P, et al. Population ageing and mortality during 1990-2017: a global decomposition analysis. PLoS Med 2020 Jun 8;17(6):e1003138-e1003138 [FREE Full text] [CrossRef] [Medline]
- Tan X, Zhang Y, Shao H. Healthy China 2030, a breakthrough for improving health. Glob Health Promot 2019 Dec 03;26(4):96-99. [CrossRef] [Medline]
- GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017 Sep;390(10100):1345-1422. [CrossRef]
- Jha P. Avoidable global cancer deaths and total deaths from smoking. Nat Rev Cancer 2009 Sep 20;9(9):655-664. [CrossRef] [Medline]
- Gharibvand L, Lawrence Beeson W, Shavlik D, Knutsen R, Ghamsary M, Soret S, et al. The association between ambient fine particulate matter and incident adenocarcinoma subtype of lung cancer. Environ Health 2017 Jun 24;16(1):71-71 [FREE Full text] [CrossRef] [Medline]
- Su T, Chen S, Chan C. Progress of ambient air pollution and cardiovascular disease research in Asia. Prog Cardiovasc Dis 2011 Mar;53(5):369-378. [CrossRef] [Medline]
- Turner MC, Krewski D, Pope CA, Chen Y, Gapstur SM, Thun MJ. Long-term ambient fine particulate matter air pollution and lung cancer in a large cohort of never-smokers. Am J Respir Crit Care Med 2011 Dec 15;184(12):1374-1381. [CrossRef]
- Su Y, Sha Y, Zhai G, Zong S, Jia J. Comparison of air pollution in Shanghai and Lanzhou based on wavelet transform. Environ Sci Pollut Res Int 2019 Jun 21;26(17):16825-16834 [FREE Full text] [CrossRef] [Medline]
- Duma N, Santana-Davila R, Molina JR. Non-small cell lung cancer: epidemiology, screening, diagnosis, and treatment. Mayo Clin Proc 2019 Aug;94(8):1623-1640. [CrossRef] [Medline]
- Reck M, Rodríguez-Abreu D, Robinson AG, Hui R, Csőszi T, Fülöp A, et al. Pembrolizumab versus chemotherapy for PD-L1–positive non–small-cell lung cancer. N Engl J Med 2016 Nov 10;375(19):1823-1833. [CrossRef]
- Borghaei H, Paz-Ares L, Horn L, Spigel DR, Steins M, Ready NE, et al. Nivolumab versus docetaxel in advanced nonsquamous non–small-cell lung cancer. N Engl J Med 2015 Oct 22;373(17):1627-1639. [CrossRef]
- Yang D, Liu Y, Bai C, Wang X, Powell CA. Epidemiology of lung cancer and lung cancer screening programs in China and the United States. Cancer Lett 2020 Jan 01;468:82-87. [CrossRef] [Medline]
- Nedović-Vuković M, Laušević D, Ljaljević A, Golubović M, Trajković G. Lung cancer mortality in Montenegro, 1990 to 2015. Croat Med J 2019 Feb;60(1):26-32. [CrossRef]
- Chen W, Zhang S, Zou X, Zhao P. An analysis of lung cancer mortality in China, 2004 - 2005. Zhonghua Yu Fang Yi Xue Za Zhi 2010 May;44(5):378-382. [Medline]
- Martín-Sánchez JC, Lunet N, González-Marrón A, Lidón-Moyano C, Matilla-Santander N, Clèries R, et al. Projections in breast and lung cancer mortality among women: a Bayesian analysis of 52 countries worldwide. Cancer Res 2018 Jul 31;78(15):4436-4442. [CrossRef]
- Global Burden of Disease Cancer Collaboration. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2017: a systematic analysis for the Global Burden of Disease Study. JAMA Oncol 2019 Dec 01;5(12):1749-1768 [FREE Full text] [CrossRef] [Medline]
|AAPC: average annual percentage change|
|ASMRW: age-standardized mortality rate by Segi’s world standard population|
|CMR: crude mortality rate|
|GDP: gross domestic product|
|ICD-10: International Classification of Diseases 10th Revision|
|NSCLC: non-small-cell lung cancer|
|PNA: Pudong New Area|
|TKI: tyrosine kinase inhibitor|
|YLL: years of life lost|
Edited by H Bradley; submitted 18.09.21; peer-reviewed by Y Deng, A Reyna Sevilla; comments to author 08.11.21; revised version received 20.11.21; accepted 24.02.22; published 20.04.22Copyright
©Wenjing Ye, Weiwei Lu, Xiaopan Li, Yichen Chen, Lin Wang, Guangwang Zeng, Cheng Xu, Chen Ji, Yuyang Cai, Ling Yang, Zheng Luo. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 20.04.2022.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.