100+ datasets found
  1. Number of new lung and bronchus cancer cases in the U.S. in 2025, by state

    • statista.com
    Updated Mar 5, 2025
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    Statista (2025). Number of new lung and bronchus cancer cases in the U.S. in 2025, by state [Dataset]. https://www.statista.com/statistics/1286318/lung-and-bronchus-cancer-cases-us-state/
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    Dataset updated
    Mar 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    United States
    Description

    It is estimated that in 2025 there will be a total of 226,650 new cases of lung and bronchus cancer in the United States. The highest number of these cases are estimated to be in the state of Florida. This statistic presents the estimated number of new lung and bronchus cancer cases in the United States in 2025, by state.

  2. Lung cancer cases rate per 100,000 population in England 1995-2022, by...

    • statista.com
    Updated May 30, 2025
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    Statista (2025). Lung cancer cases rate per 100,000 population in England 1995-2022, by gender [Dataset]. https://www.statista.com/statistics/313112/lung-present-past-cancer-cases-rate-england-age-gender/
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    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom (England), Europe
    Description

    In 2022, 83.2 males and 69.3 females per 100,000 population in England were registered as newly diagnosed with malignant neoplasm of bronchus and lung. Over the analyzed years, the rate of newly diagnosed cases for male individuals has seen a decrease trend. Conversely, the rate of newly diagnosed cases for females has seen a steady increase over the years. This statistic shows the rate of newly diagnosed cases of lung cancer per 100,000 population in England from 1995 to 2022, by gender.

  3. d

    Mortality from lung cancer: crude death rate, by age group, 3-year average,...

    • digital.nhs.uk
    Updated Jul 21, 2021
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    (2021). Mortality from lung cancer: crude death rate, by age group, 3-year average, MFP [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/mortality-from-lung-cancer
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    Dataset updated
    Jul 21, 2021
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Description

    Legacy unique identifier: P00508

  4. Number of new U.S. lung and bronchus cancer cases and deaths in 2025, by...

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Number of new U.S. lung and bronchus cancer cases and deaths in 2025, by gender [Dataset]. https://www.statista.com/statistics/622793/lung-and-bronchus-cancer-cases-and-deaths-us-gender/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    It is estimated that in 2025 there will be a total of ******* new cases of lung and bronchus cancer in the United States. In addition, it is predicted that there will be around ******* deaths from lung and bronchus cancer that year. This statistic presents the estimated number of new lung and bronchus cancer cases and deaths in the United States in 2025, by gender.

  5. NCI State Lung Cancer Incidence Rates

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    Updated Jan 2, 2020
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    National Cancer Institute (2020). NCI State Lung Cancer Incidence Rates [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/NCI::nci-state-lung-cancer-incidence-rates/about
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    Dataset updated
    Jan 2, 2020
    Dataset authored and provided by
    National Cancer Institutehttp://www.cancer.gov/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This dataset contains Cancer Incidence data for Lung Cancer (All Stages^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2016 to 2020.Data are segmented by sex (Both Sexes, Male, and Female) and age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ All Stages refers to any stage in the Surveillance, Epidemiology, and End Results (SEER) summary stage.Data Source Field Key(1) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(5) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(6) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2022 submission).(7) Source: SEER November 2022 submission.(8) Source: Incidence data provided by the SEER Program. AAPCs are calculated by the Joinpoint Regression Program and are based on APCs. Data are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84,85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with SEER November 2022 data.Some data are not available, see Data Not Available for combinations of geography, cancer site, age, and race/ethnicity.Data for the United States does not include data from Nevada.Data for the United States does not include Puerto Rico.

  6. d

    Compendium – Mortality from lung cancer

    • digital.nhs.uk
    csv, xls
    Updated Jul 21, 2022
    + more versions
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    (2022). Compendium – Mortality from lung cancer [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/mortality-from-lung-cancer
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    csv(848.4 kB), xls(180.2 kB)Available download formats
    Dataset updated
    Jul 21, 2022
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 2020 - Dec 31, 2020
    Area covered
    Wales, England
    Description

    Mortality from lung cancer (ICD-10 C33-C34 equivalent to ICD-9 162). To reduce deaths from lung cancer. Legacy unique identifier: P00513

  7. l

    Lung Cancer Mortality

    • data.lacounty.gov
    • ph-lacounty.hub.arcgis.com
    Updated Dec 20, 2023
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    County of Los Angeles (2023). Lung Cancer Mortality [Dataset]. https://data.lacounty.gov/datasets/lung-cancer-mortality/about
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    Dataset updated
    Dec 20, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Death rate has been age-adjusted by the 2000 U.S. standard population. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Lung cancer is a leading cause of cancer-related death in the US. People who smoke have the greatest risk of lung cancer, though lung cancer can also occur in people who have never smoked. Most cases are due to long-term tobacco smoking or exposure to secondhand tobacco smoke. Cities and communities can take an active role in curbing tobacco use and reducing lung cancer by adopting policies to regulate tobacco retail; reducing exposure to secondhand smoke in outdoor public spaces, such as parks, restaurants, or in multi-unit housing; and improving access to tobacco cessation programs and other preventive services.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  8. Number and rates of new cases of primary cancer, by cancer type, age group...

    • www150.statcan.gc.ca
    • datasets.ai
    • +2more
    Updated May 19, 2021
    + more versions
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    Government of Canada, Statistics Canada (2021). Number and rates of new cases of primary cancer, by cancer type, age group and sex [Dataset]. http://doi.org/10.25318/1310011101-eng
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    Dataset updated
    May 19, 2021
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number and rate of new cancer cases diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

  9. w

    Lung cancer: mortality rate

    • data.wu.ac.at
    • data.europa.eu
    html
    Updated Sep 20, 2017
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    NHS Digital (2017). Lung cancer: mortality rate [Dataset]. https://data.wu.ac.at/schema/data_gov_uk/ZDNmMDEwMGQtYjgzOS00YjVkLTlmNDQtZGJkZmIyMmExODFm
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    htmlAvailable download formats
    Dataset updated
    Sep 20, 2017
    Dataset provided by
    NHS Digital
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Deaths from lung cancer - Directly age-Standardised Rates (DSR) per 100,000 population Source: Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Primary Care Trust (PCT), Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2005-07, 2007 Type of data: Administrative data

  10. c

    Lung Cancer Deaths - Datasets - CTData.org

    • data.ctdata.org
    Updated Mar 28, 2016
    + more versions
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    (2016). Lung Cancer Deaths - Datasets - CTData.org [Dataset]. http://data.ctdata.org/dataset/lung-cancer-deaths
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    Dataset updated
    Mar 28, 2016
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Lung Cancer Deaths reports the number, crude rate, and age-adjusted mortality rate (AAMR) of deaths due to lung cancer.

  11. Lung cancer cases in England 2022, by age and gender

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Lung cancer cases in England 2022, by age and gender [Dataset]. https://www.statista.com/statistics/312763/lung-cancer-cases-england-age/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    England
    Description

    This statistic shows the amount of registrations of newly diagnosed cases of lung cancer in England in 2021, by age group and gender. In this year, almost ************* cases were reported among men aged 70 to 74 years. It should be noted that the number of people in England in each age group varies and is therefore not necessarily a reflection of susceptibility to lung cancer.

  12. H

    Air Quality-Lung Cancer Data

    • dataverse.harvard.edu
    Updated Jan 31, 2020
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    Mithun Acharjee; Kumer Pial Das; Young S.Stanley (2020). Air Quality-Lung Cancer Data [Dataset]. http://doi.org/10.7910/DVN/HMOEJO
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 31, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Mithun Acharjee; Kumer Pial Das; Young S.Stanley
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Data comes from two different sources. Population-based lung cancer incidence rates for the period 2010-2014 (most updated data) were abstracted from National Cancer Institute state cancer profiles (Schwartz et al. 1996).This national county-level database of cancer data is collected by state public health surveillance systems. The domain specific county level environmental quality index (EQI) data for the period 2000-2005 were abstracted from United States Environmental Protection Agency (USEPA) profile. Complete descriptions of the datasets used in the EQI are provided in Lobdell’s paper (Lobdell 2011). Data were merged based on the Federal Information Processing Standards (FIPS) code. Out of 3144 counties in United States this study has available information for 2602 counties: Data was not available for four states namely Kansas, Michigan, Minnesota and Nevada due to state legislation and regulations which prohibit the release of county-level data to outside entities, county whose lung cancer mortality information is missing were omitted from the data set, the Union county, Florida is an outlier in terms of mortality information which was deleted from the data set, in the process of local control analysis this study experiences two (cluster 28 and 29) non-informative clusters (non-informative cluster is one for which either treatment or control group information is missing). For analysis, non-informative clusters information was deleted from the data set. Three types of variables are used in this study: (i) lung cancer mortality as an outcome variable (ii) binary treatment indicator is the PM2.5 high (greater than 10.59 mg/m3) vs. low (less than 10.59 mg/m3) (iii) three potential X confounder for clustering namely land EQI, sociodemographic EQI and built EQI. For each index, higher values correspond to poorer environmental quality (Jagai et al. 2017). As PM2.5 is one of the indicators for measuring air EQI, that is why we do not consider the air EQI to avoid confounding effects.

  13. f

    lung cancer data.xlsx

    • figshare.com
    xlsx
    Updated Jan 19, 2025
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    Jehan Al-Musawi; Farah Al-Shadeedi; Nabaa Shakir; Sabreen Ibrahim (2025). lung cancer data.xlsx [Dataset]. http://doi.org/10.6084/m9.figshare.28235576.v1
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    xlsxAvailable download formats
    Dataset updated
    Jan 19, 2025
    Dataset provided by
    figshare
    Authors
    Jehan Al-Musawi; Farah Al-Shadeedi; Nabaa Shakir; Sabreen Ibrahim
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Abstract Objective: To identify the socioepidemiologic and histopathologic patterns of lung cancer patients in the Middle Euphrates region. Patients and Methods: This study analyzed medical information from lung cancer patients at the Middle Euphrates Cancer Center in Iraq from January 2018 to December 2023. Demographic information (age, gender, residency, and education level) as well as clinical details (histopathological categorization) were obtained. The inclusion criteria included all confirmed lung cancer cases, while cases with inadequate data or non-lung cancer diagnosis were omitted. The data were analyzed using IBM SPSS Statistics (version 26). The data summarized using descriptive statistics, and chi-square tests used to identify correlations between categorical variables at a significance level of p < 0.05. Ethical approval was obtained from the relevant institutional review board. Results: A total of 1162 patients were included with mean age at diagnosis(64.47±11.45) years. Majority of patients are over 60 years (64.4%), followed by (40–60 years), 34%, and the least affected group is under 40 years (1.6%). Males account for the majority of cases (68%), while females about 32%, with male:female ratio that fluctuate around 2:1. Illiterate patients and those with low education levels represent the largest proportion accounting for about 87.9% of the study population. Squamous Cell Carcinoma (SCC) is the most frequent subtype (41.7%), followed closely by Adenocarcinoma (AC) at 37%, and Small Cell Lung Cancer (SCLC), 10.5%. Although SCC is the predominant subtype overall, AC incidence is increasing overtime (from 31.7% in 2018 to 41.4% in 2023) with predominance in females, younger and higher educated groups. While the percentage of SCLC and other less common subgroups remained relatively stable over time, there is a significant reduction in NSCLC-NOS diagnoses (from 11.1% in 2018 to 3.2% in 2023). Conclusions: In Iraq, specifically in the Middle Euphrates region, lung cancer is a major public health issue in the elder age groups. The two main subtypes, SCC and AC, are the main contributors, with obvious increment in AC cases in the recent years. The shifting trends indicate the urgent need for improved screening strategies, focused preventative initiatives, and customized treatment plans in view of changing risk profiles.

  14. Lung Cancer Death Rate (per 100,000), New Jersey, by year: Beginning 2010

    • healthdata.nj.gov
    • data.wu.ac.at
    application/rdfxml +5
    Updated Dec 8, 2020
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    Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health (2020). Lung Cancer Death Rate (per 100,000), New Jersey, by year: Beginning 2010 [Dataset]. https://healthdata.nj.gov/dataset/Lung-Cancer-Death-Rate-per-100-000-New-Jersey-by-y/ia77-ctqr
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    csv, tsv, application/rdfxml, application/rssxml, xml, jsonAvailable download formats
    Dataset updated
    Dec 8, 2020
    Dataset provided by
    New Jersey Department of Healthhttps://www.nj.gov/health/
    Authors
    Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health
    Area covered
    New Jersey
    Description

    Rate: Number of deaths due to cancer of the trachea, bronchus, and lung per 100,000 Population.

    Definition: Number of deaths per 100,000 with malignant neoplasm (cancer) cancer of the trachea, bronchus, and lung as the underlying cause (ICD-10 codes: C33-C34).

    Data Sources:

    (1) Centers for Disease Control and Prevention, National Center for Health Statistics. Compressed Mortality File. CDC WONDER On-line Database accessed at http://wonder.cdc.gov/cmf-icd10.html

    (2) Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health

    (3) Population Estimates, State Data Center, New Jersey Department of Labor and Workforce Development

  15. f

    Table_1_Underlying reasons for post-mortem diagnosed lung cancer cases – A...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 2, 2023
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    Zolta´n Kiss; Krisztina Bogos; Lilla Tamási; Gyula Ostoros; Veronika Müller; Nóra Bittner; Veronika Sárosi; Aladár Vastag; Kata Knollmajer; Máté Várnai; Krisztina Kovács; Andrea Berta; István Köveskuti; Eugenia Karamousouli; György Rokszin; Zsolt Abonyi-Tóth; Zsófia Barcza; István Kenessey; András Weber; Péter Nagy; Petra Freyler-Fadgyas; Miklós Szócska; Péter Szegner; Lászlóné Hilbert; Gabriella Branyiczkiné Géczy; György Surján; Judit Moldvay; Zoltán Vokó; Gabriella Gálffy; Zoltán Polányi (2023). Table_1_Underlying reasons for post-mortem diagnosed lung cancer cases – A robust retrospective comparative study from Hungary (HULC study).xlsx [Dataset]. http://doi.org/10.3389/fonc.2022.1032366.s001
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    xlsxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers
    Authors
    Zolta´n Kiss; Krisztina Bogos; Lilla Tamási; Gyula Ostoros; Veronika Müller; Nóra Bittner; Veronika Sárosi; Aladár Vastag; Kata Knollmajer; Máté Várnai; Krisztina Kovács; Andrea Berta; István Köveskuti; Eugenia Karamousouli; György Rokszin; Zsolt Abonyi-Tóth; Zsófia Barcza; István Kenessey; András Weber; Péter Nagy; Petra Freyler-Fadgyas; Miklós Szócska; Péter Szegner; Lászlóné Hilbert; Gabriella Branyiczkiné Géczy; György Surján; Judit Moldvay; Zoltán Vokó; Gabriella Gálffy; Zoltán Polányi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Hungary
    Description

    ObjectiveThe Hungarian Undiagnosed Lung Cancer (HULC) study aimed to explore the potential reasons for missed LC (lung cancer) diagnosis by comparing healthcare and socio-economic data among patients with post-mortem diagnosed LC with those who were diagnosed with LC during their lives.MethodsThis nationwide, retrospective study used the databases of the Hungarian Central Statistical Office (HCSO) and National Health Insurance Fund (NHIF) to identify patients who died between January 1, 2019 and December 31, 2019 and were diagnosed with lung cancer post-mortem (population A) or during their lifetime (population B). Patient characteristics, socio-economic factors, and healthcare resource utilization (HCRU) data were compared between the diagnosed and undiagnosed patient population.ResultsDuring the study period, 8,435 patients were identified from the HCSO database with LC as the cause of death, of whom 1,203 (14.24%) had no LC-related ICD (International Classification of Diseases) code records in the NHIF database during their lives (post-mortem diagnosed LC population). Post-mortem diagnosed LC patients were significantly older than patients diagnosed while still alive (mean age 71.20 vs. 68.69 years, p

  16. f

    Risk prediction models for selection of lung cancer screening candidates: A...

    • plos.figshare.com
    docx
    Updated May 31, 2023
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    Kevin ten Haaf; Jihyoun Jeon; Martin C. Tammemägi; Summer S. Han; Chung Yin Kong; Sylvia K. Plevritis; Eric J. Feuer; Harry J. de Koning; Ewout W. Steyerberg; Rafael Meza (2023). Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study [Dataset]. http://doi.org/10.1371/journal.pmed.1002277
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    docxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS Medicine
    Authors
    Kevin ten Haaf; Jihyoun Jeon; Martin C. Tammemägi; Summer S. Han; Chung Yin Kong; Sylvia K. Plevritis; Eric J. Feuer; Harry J. de Koning; Ewout W. Steyerberg; Rafael Meza
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundSelection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years). Nine previously established risk models were assessed for their ability to identify those most likely to develop or die from lung cancer. All models considered age and various aspects of smoking exposure (smoking status, smoking duration, cigarettes per day, pack-years smoked, time since smoking cessation) as risk predictors. In addition, some models considered factors such as gender, race, ethnicity, education, body mass index, chronic obstructive pulmonary disease, emphysema, personal history of cancer, personal history of pneumonia, and family history of lung cancer.Methods and findingsRetrospective analyses were performed on 53,452 National Lung Screening Trial (NLST) participants (1,925 lung cancer cases and 884 lung cancer deaths) and 80,672 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) ever-smoking participants (1,463 lung cancer cases and 915 lung cancer deaths). Six-year lung cancer incidence and mortality risk predictions were assessed for (1) calibration (graphically) by comparing the agreement between the predicted and the observed risks, (2) discrimination (area under the receiver operating characteristic curve [AUC]) between individuals with and without lung cancer (death), and (3) clinical usefulness (net benefit in decision curve analysis) by identifying risk thresholds at which applying risk-based eligibility would improve lung cancer screening efficacy. To further assess performance, risk model sensitivities and specificities in the PLCO were compared to those based on the NLST eligibility criteria. Calibration was satisfactory, but discrimination ranged widely (AUCs from 0.61 to 0.81). The models outperformed the NLST eligibility criteria over a substantial range of risk thresholds in decision curve analysis, with a higher sensitivity for all models and a slightly higher specificity for some models. The PLCOm2012, Bach, and Two-Stage Clonal Expansion incidence models had the best overall performance, with AUCs >0.68 in the NLST and >0.77 in the PLCO. These three models had the highest sensitivity and specificity for predicting 6-y lung cancer incidence in the PLCO chest radiography arm, with sensitivities >79.8% and specificities >62.3%. In contrast, the NLST eligibility criteria yielded a sensitivity of 71.4% and a specificity of 62.2%. Limitations of this study include the lack of identification of optimal risk thresholds, as this requires additional information on the long-term benefits (e.g., life-years gained and mortality reduction) and harms (e.g., overdiagnosis) of risk-based screening strategies using these models. In addition, information on some predictor variables included in the risk prediction models was not available.ConclusionsSelection of individuals for lung cancer screening using individual risk is superior to selection criteria based on age and pack-years alone. The benefits, harms, and feasibility of implementing lung cancer screening policies based on risk prediction models should be assessed and compared with those of current recommendations.

  17. c

    National Lung Screening Trial

    • dev.cancerimagingarchive.net
    • cancerimagingarchive.net
    dicom, docx, n/a +2
    Updated Sep 24, 2021
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    The Cancer Imaging Archive (2021). National Lung Screening Trial [Dataset]. http://doi.org/10.7937/TCIA.HMQ8-J677
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    sas, zip, and doc, svs, docx, dicom, n/aAvailable download formats
    Dataset updated
    Sep 24, 2021
    Dataset authored and provided by
    The Cancer Imaging Archive
    License

    https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/

    Time period covered
    Sep 24, 2021
    Dataset funded by
    National Cancer Institutehttp://www.cancer.gov/
    Description

    Background: The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer.

    Methods: From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. This dataset includes the low-dose CT scans from 26,254 of these subjects, as well as digitized histopathology images from 451 subjects.

    Results: The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02).

    Conclusions: Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385).

    Data Availability: A summary of the National Lung Screening Trial and its available datasets are provided on the Cancer Data Access System (CDAS). CDAS is maintained by Information Management System (IMS), contracted by the National Cancer Institute (NCI) as keepers and statistical analyzers of the NLST trial data. The full clinical data set from NLST is available through CDAS. Users of TCIA can download without restriction a publicly distributable subset of that clinical data, along with the CT and Histopathology images collected during the trial. (These previously were restricted.)

  18. f

    DataSheet_1_Causes of death and conditional survival estimates of long-term...

    • frontiersin.figshare.com
    bin
    Updated Jun 16, 2023
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    Qun Zhang; Yuan Dai; Hongda Liu; Wenkui Sun; Yuming Huang; Zheng Gong; Shanlin Dai; Hui Kong; Weiping Xie (2023). DataSheet_1_Causes of death and conditional survival estimates of long-term lung cancer survivors.docx [Dataset]. http://doi.org/10.3389/fimmu.2022.1012247.s001
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    binAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    Frontiers
    Authors
    Qun Zhang; Yuan Dai; Hongda Liu; Wenkui Sun; Yuming Huang; Zheng Gong; Shanlin Dai; Hui Kong; Weiping Xie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionLung cancer ranks the leading cause of cancer-related death worldwide. This retrospective cohort study was designed to determine time-dependent death hazards of diverse causes and conditional survival of lung cancer.MethodsWe collected 816,436 lung cancer cases during 2000-2015 in the SEER database, after exclusion, 612,100 cases were enrolled for data analyses. Cancer-specific survival, overall survival and dynamic death hazard were assessed in this study. Additionally, based on the FDA approval time of Nivolumab in 2015, we evaluated the effect of immunotherapy on metastatic patients’ survival by comparing cases in 2016-2018 (immunotherapy era, n=7135) and those in 2013-2016 (non-immunotherapy era, n=42061).ResultsOf the 612,100 patients, 285,705 were women, the mean (SD) age was 68.3 (11.0) years old. 252,558 patients were characterized as lung adenocarcinoma, 133,302 cases were lung squamous cell carcinoma, and only 78,700 cases were small cell lung carcinomas. TNM stage was I in 140,518 cases, II in 38,225 cases, III in 159,095 cases, and IV in 274,262 patients. 164,394 cases underwent surgical intervention. The 5-y overall survival and cancer-specific survival were 54.2% and 73.8%, respectively. The 5-y conditional survival rate of cancer-specific survival is improved in a time-dependent pattern, while conditional overall survival tends to be steady after 5-y follow-up. Except from age, hazard disparities of other risk factors (such as stage and surgery) diminished over time according to the conditional survival curves. After 8 years since diagnosis, mortality hazard from other causes became higher than that from lung cancer. This critical time point was earlier in elder patients while was postponed in patients with advanced stages. Moreover, both cancer-specific survival and overall survival of metastatic patients in immunotherapy era were significantly better than those in non-immunotherapy era (P

  19. d

    Data from: Cancer Rates

    • catalog.data.gov
    • hub.arcgis.com
    • +2more
    Updated Nov 22, 2024
    + more versions
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    Lake County Illinois GIS (2024). Cancer Rates [Dataset]. https://catalog.data.gov/dataset/cancer-rates-5cf0c
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    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Lake County Illinois GIS
    Description

    Cancer Rates for Lake County Illinois. Explanation of field attributes: Colorectal Cancer - Cancer that develops in the colon (the longest part of the large intestine) and/or the rectum (the last several inches of the large intestine). This is a rate per 100,000. Lung Cancer – Cancer that forms in tissues of the lung, usually in the cells lining air passages. This is a rate per 100,000. Breast Cancer – Cancer that forms in tissues of the breast. This is a rate per 100,000. Prostate Cancer – Cancer that forms in tissues of the prostate. This is a rate per 100,000. Urinary System Cancer – Cancer that forms in the organs of the body that produce and discharge urine. These include the kidneys, ureters, bladder, and urethra. This is a rate per 100,000. All Cancer – All cancers including, but not limited to: colorectal cancer, lung cancer, breast cancer, prostate cancer, and cancer of the urinary system. This is a rate per 100,000.

  20. f

    Trend analysis of major cancer statistics according to sex and severity...

    • plos.figshare.com
    docx
    Updated Jun 1, 2023
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    Minsu Ock; Woong Jae Choi; Min-Woo Jo (2023). Trend analysis of major cancer statistics according to sex and severity levels in Korea [Dataset]. http://doi.org/10.1371/journal.pone.0203110
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Minsu Ock; Woong Jae Choi; Min-Woo Jo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    South Korea
    Description

    Existing epidemiologic reports or studies of cancer statistics in Korea lack sufficient data on cancer severity distributions and observed survival rates. This study analyzed trends in major cancer statistics according to sex and severity levels in Korea from 2006 to 2013. We included eight cancers (hepatocellular carcinoma, and thyroid, colorectal, gastric, lung, prostate, breast, and cervical cancer), using Korea Central Cancer Registry data. Severity level was classified by Surveillance, Epidemiology, and End Results (SEER) stage as follows: localized, regional, distant, or unknown. Numbers of incident cancer cases from 2006 to 2013 were described by sex and SEER stage. We estimated up to 8-year observed survival rates of major cancers by sex and SEER stage, and provided prevalence rates by sex and SEER stage in 2011, 2012, and 2013. Although increases in new cancer cases are slowing and the total number of incident cancer cases in 2013 decreased for the first time since 2006, the number of prevalent cancer cases was 663,530 in 2013, an increase of 13.3% compared to 2011. Among the five cancers affecting both sexes, sex-related differences in 5-year observed survival rates for lung cancer were greatest in the localized stage (men, 31.9%; women, 48.1%), regional stage (men, 20.0%; women, 31.3%), and unknown stage (men, 24.3%; women, 37.5%). The sum of the proportions of localized and regional stages for thyroid and breast cancer was over 90% in 2013, while the sum of the proportions of localized and regional stages for lung cancer was only 56.7% in 2013. Differences in observed survival rates between men and women were prominent in lung cancer for all SEER stages. The reported epidemiologic data from this study can be used to obtain a more valid measure of cancer burden using a summary measure of population health.

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Statista (2025). Number of new lung and bronchus cancer cases in the U.S. in 2025, by state [Dataset]. https://www.statista.com/statistics/1286318/lung-and-bronchus-cancer-cases-us-state/
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Number of new lung and bronchus cancer cases in the U.S. in 2025, by state

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Dataset updated
Mar 5, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2025
Area covered
United States
Description

It is estimated that in 2025 there will be a total of 226,650 new cases of lung and bronchus cancer in the United States. The highest number of these cases are estimated to be in the state of Florida. This statistic presents the estimated number of new lung and bronchus cancer cases in the United States in 2025, by state.

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