20 datasets found
  1. a

    NCI State Cancer Incidence Rates

    • hub.arcgis.com
    Updated Aug 20, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Cancer Institute (2019). NCI State Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/datasets/NCI::nci-state-cancer-incidence-rates
    Explore at:
    Dataset updated
    Aug 20, 2019
    Dataset authored and provided by
    National Cancer Institute
    License

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

    Area covered
    Description

    This dataset contains Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2012 to 2016.Data is segmented by sex and age, with fields describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.gov Data NotationsState Cancer Registries may provide more current or more local data.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population seer.cancer.gov/stdpopulations/stdpop.19ages.html. 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. [seer.cancer.gov/seerstat]Population counts for denominators are based on Census populations as modified [seer.cancer.gov/popdata] by NCI. The 1969-2016 US Population Data File [seer.cancer.gov/popdata] is used for SEER and NPCR incidence rates.‡ Incidence 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.html.^ All Stages refers to any stage in the Surveillance, Epidemiology, and End Results (SEER) summary stage [seer.cancer.gov/tools/ssm].Healthy People 2020 Objectives [www.healthypeople.gov]provided by the Centers for Disease Control and Prevention [www.cdc.gov]. Michigan Data do not include cases diagnosed in other states for those states in which the data exchange agreement specifically prohibits the release of data to third parties.Trend Data not available for Nevada.Data Source Field Key:(1) Source: CDC's National Program of Cancer Registries Cancer Surveillance System (NPCR-CSS) November 2018 data submission and SEER November 2018 submission as published in United States Cancer Statistics nccd.cdc.gov/uscs Source: State Cancer Registry and the CDC's National Program of Cancer Registries Cancer Surveillance System (NPCR-CSS) November 2018 data submission. State rates include rates from metropolitan areas funded by SEER [seer.cancer.gov/registries].(6) Source: State Cancer Registry and the CDC's National Program of Cancer Registries Cancer Surveillance System (NPCR-CSS) November 2018 data submission.(7) Source: SEER November 2018 submission.8 Source: Incidence data provided by the SEER Program. [seer.cancer.gov] AAPCs are calculated by the Joinpoint Regression Program [surveillance.cancer.gov/joinpoint] and are based on APCs. Data are age-adjusted to the 2000 US standard population www.seer.cancer.gov/stdpopulations/single_age.html. 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 1969-2017 US Population Data [seer.cancer.gov/popdata] File is used with SEER November 2018 data. Please note that the data comes from different sources. Due to different years [statecancerprofiles.cancer.gov/historicaltrend/differences.html] of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. [seer.cancer.gov/seerstat] Please refer to the source for each graph for additional information. Some data are not available [http://statecancerprofiles.cancer.gov/datanotavailable.html] for combinations of geography, cancer site, age, and race/ethnicity.

  2. CPIC California Cancer Registry

    • redivis.com
    application/jsonl +7
    Updated Sep 19, 2016
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Stanford Center for Population Health Sciences (2016). CPIC California Cancer Registry [Dataset]. http://doi.org/10.57761/sq5d-1c97
    Explore at:
    application/jsonl, spss, sas, arrow, stata, parquet, csv, avroAvailable download formats
    Dataset updated
    Sep 19, 2016
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Area covered
    California
    Description

    Abstract

    The Greater Bay Area Cancer Registry (GBACR), in compliance with California state law, gathers information about all cancers diagnosed or treated in a nine-county area (Alameda, Contra Costa, Marin, Monterey, San Benito, San Francisco, San Mateo, Santa...

    Documentation

    PHS does NOT host these data. This listing is information only.

    The Greater Bay Area Cancer Registry (GBACR), in compliance with California state law, gathers information about all cancers diagnosed or treated in a nine-county area (Alameda, Contra Costa, Marin, Monterey, San Benito, San Francisco, San Mateo, Santa Clara and Santa Cruz). This information is obtained from medical records provided by hospitals, doctors\342\200\231 offices, and other related facilities.

    The information, stored under secure conditions with strict regulations that protect confidentiality, helps the GBACR understand cancer occurrence and survival in the Greater Bay Area. For each patient, the information includes basic demographic facts like age, gender, and race/ethnicity, as well as cancer type, extent of disease, treatment and survival. Combined over the diverse Bay Area population, this information gives the GBACR and all users an opportunity to learn how such characteristics may be related to cancer causes, mortality, care and prevention.

    In addition to its local use, information collected by the GBACR becomes part of state and federal population-based registries whose mission is to monitor cancer occurrence at the state and national levels, respectively. Data from the GBACR have contributed to the National Cancer Institute’s Surveillance, Epidemiology and End Results (SEER) program since 1973. The nine counties are also part of the statewide California Cancer Registry (CCR), which conducts essential monitoring of cancer occurrence and survival in California.

    GBACR data are of the highest quality, as recognized by national and international registry standard-setting organizations, including SEER, the National Program for Cancer Registries, and the North American Association for Central Cancer Registries (NAACCR).

    The CPIC has also started collecting data on environmenal factors. These data are available in the The California Neighborhoods Data System. This a new resource for examining the impact of neighborhood characteristics on cancer incidence and outcomes in populations includes a compilation of existing geospatial and other secondary data for characterizing contextual factors

    A summary and description of social and built environment data and measures in the California Neighborhoods Data System (2010) can be found here: Social and Built Environment Data and Measures

    More information about this new data source can be found here: The California Neighborhoods Data System

    Patient characteristics All reported cancer cases in the state of California.

    Data overview Data categories Socioeconomic status Racial/ethnic composition Immigration/acculturation characteristics Racial/ethnic residential segregation Population density Urbanicity (Rural/Urban) Housing Businesses Commuting Street connectivity Parks Farmers Markets Traffic density Crime Tapestry Segmentation

    Notes To apply for these data, you can see instructions here: https://www.ccrcal.org/retrieve-data/data-for-researchers/how-to-request-ccr-data/

  3. a

    NCI State Colorectal Cancer Incidence Rates

    • hub.arcgis.com
    Updated Jan 2, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Cancer Institute (2020). NCI State Colorectal Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/datasets/eb26abf367914e259d618d7ce03cc360
    Explore at:
    Dataset updated
    Jan 2, 2020
    Dataset authored and provided by
    National Cancer Institute
    License

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

    Area covered
    Description

    This dataset contains Cancer Incidence data for Colorectal 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.

  4. NCI State Late Stage Breast Cancer Incidence Rates

    • hub.arcgis.com
    Updated Jan 21, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Cancer Institute (2020). NCI State Late Stage Breast Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/datasets/9dd0d923f8034cc8806173fdc224777d
    Explore at:
    Dataset updated
    Jan 21, 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 Breast Cancer (Late Stage^) 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 for females segmented by 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.^ Late Stage is defined as cases determined to be regional or distant. Due to changes in stage coding, Combined Summary Stage (2004+) is used for data from Surveillance, Epidemiology, and End Results (SEER) databases and Merged Summary Stage is used for data from National Program of Cancer Registries databases. Due to the increased complexity with staging, other staging variables maybe used if necessary.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.

  5. State Cancer Profiles Web site

    • catalog.data.gov
    • healthdata.gov
    • +3more
    Updated Jul 17, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Health & Human Services (2025). State Cancer Profiles Web site [Dataset]. https://catalog.data.gov/dataset/state-cancer-profiles-web-site
    Explore at:
    Dataset updated
    Jul 17, 2025
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Description

    The State Cancer Profiles (SCP) web site provides statistics to help guide and prioritize cancer control activities at the state and local levels. SCP is a collaborative effort using local and national level cancer data from the Centers for Disease Control and Prevention's National Program of Cancer Registries (NPCR) and National Cancer Institute's Surveillance, Epidemiology and End Results Registries (SEER). SCP address select types of cancer and select behavioral risk factors for which there are evidence-based control interventions. The site provides incidence, mortality and prevalence comparison tables as well as interactive graphs and maps and support data. The graphs and maps provide visual support for deciding where to focus cancer control efforts.

  6. NCI State Prostate Cancer Incidence Rates

    • hub.arcgis.com
    Updated Jan 2, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Cancer Institute (2020). NCI State Prostate Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/maps/NCI::nci-state-prostate-cancer-incidence-rates
    Explore at:
    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 Prostate 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 for males segmented 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.

  7. f

    Age-Related Disparity in Immediate Prognosis of Patients with...

    • plos.figshare.com
    tiff
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Wenjie Zhu; Edith A. Perez; Ruoxi Hong; Qing Li; Binghe Xu (2023). Age-Related Disparity in Immediate Prognosis of Patients with Triple-Negative Breast Cancer: A Population-Based Study from SEER Cancer Registries [Dataset]. http://doi.org/10.1371/journal.pone.0128345
    Explore at:
    tiffAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wenjie Zhu; Edith A. Perez; Ruoxi Hong; Qing Li; Binghe Xu
    License

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

    Description

    BackgroundTriple-negative breast cancer (TNBC) has been demonstrated to carry poor prognosis, but whether or not there exists any age-related variation in TNBC outcomes has yet to be elucidated. The current population-based study investigated the early survival pattern of elderly women with TNBC and identified outcome-correlated factors.Patients and MethodsWe searched the Surveillance, Epidemiology, and End Results (SEER) database and enrolled female primary non-metastatic TNBC cases. The patients were subdivided into elderly (≥70 years) and young groups (

  8. ☠️ US Cancer Analysis

    • kaggle.com
    Updated May 8, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sheema Zain (2024). ☠️ US Cancer Analysis [Dataset]. https://www.kaggle.com/datasets/sheemazain/us-cancer-analysis/versions/1
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 8, 2024
    Dataset provided by
    Kaggle
    Authors
    Sheema Zain
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    United States
    Description

    As of my last update in January 2022, I don't have access to specific real-time datasets, including a specific "US cancer analysis dataset." However, there are several well-known sources where you might find such datasets:

    1. Surveillance, Epidemiology, and End Results (SEER) Program: SEER is a comprehensive source of cancer statistics in the United States, operated by the National Cancer Institute (NCI). They provide a wide range of cancer-related data including incidence, mortality, survival, and population-based data on cancer cases.

    2. National Program of Cancer Registries (NPCR): This program, also managed by the Centers for Disease Control and Prevention (CDC), collects cancer incidence data at the state level.

    3. CDC WONDER: The CDC's Wide-ranging Online Data for Epidemiologic Research (WONDER) platform provides access to a wide array of public health-related datasets, including cancer statistics.

    4. National Cancer Database (NCDB): This database, jointly sponsored by the American College of Surgeons and the American Cancer Society, contains hospital registry data from over 1,500 Commission on Cancer (CoC)-accredited facilities.

    5. National Health Interview Survey (NHIS): While not specific to cancer, the NHIS collects data on health and health-related behaviors, which may include information on cancer screenings, risk factors, and prevalence.

    6. Behavioral Risk Factor Surveillance System (BRFSS): Similar to NHIS, BRFSS collects state-based, cross-sectional data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services, which may include cancer-related data.

    7. National Health and Nutrition Examination Survey (NHANES): NHANES collects data on the health and nutritional status of a nationally representative sample of the U.S. population through interviews, physical examinations, and laboratory tests, which may include cancer-related information.

    When accessing these datasets, it's essential to review their documentation thoroughly to understand the variables available, the methodology of data collection, any limitations or biases, and the terms of use. Additionally, many of these datasets require approval or registration before access is granted.

  9. NCI State Lung Cancer Incidence Rates

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Jan 2, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Cancer Institute (2020). NCI State Lung Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/maps/NCI::nci-state-lung-cancer-incidence-rates
    Explore at:
    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.

  10. f

    Key Feature interactions from XGBoost Classification Models Older Adults...

    • plos.figshare.com
    xls
    Updated Jul 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi (2025). Key Feature interactions from XGBoost Classification Models Older Adults (Age ≥ 66 Years) with Incident Primary MCC Linked SEER Cancer Registry and Medicare Claims Files, 2008 to 2017. [Dataset]. http://doi.org/10.1371/journal.pone.0327964.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi
    License

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

    Description

    Key Feature interactions from XGBoost Classification Models Older Adults (Age ≥ 66 Years) with Incident Primary MCC Linked SEER Cancer Registry and Medicare Claims Files, 2008 to 2017.

  11. f

    Additional file 1 of Using estimated probability of pre-diagnosis behavior...

    • springernature.figshare.com
    • datasetcatalog.nlm.nih.gov
    xlsx
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Paul P. Fahey; Andrew Page; Glenn Stone; Thomas Astell-Burt (2023). Additional file 1 of Using estimated probability of pre-diagnosis behavior as a predictor of cancer survival time: an example in esophageal cancer [Dataset]. http://doi.org/10.6084/m9.figshare.12082863.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    figshare
    Authors
    Paul P. Fahey; Andrew Page; Glenn Stone; Thomas Astell-Burt
    License

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

    Description

    Additional file 1:Table S1. Disease Characteristics and Outcomes of Eligible SEER Cancer Registry Esophagael Cancer Cases and BRFSS Health Survey Respondents 2001–2015.

  12. f

    Selected sample characteristics among Fee-for-Service Medicare beneficiaries...

    • plos.figshare.com
    xls
    Updated Jul 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi (2025). Selected sample characteristics among Fee-for-Service Medicare beneficiaries (age ≥ 66 years at index date) with MCC (n = 1,668), Linked SEER Cancer Registry and Medicare Claims files, 2008-2017. [Dataset]. http://doi.org/10.1371/journal.pone.0327964.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi
    License

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

    Description

    Selected sample characteristics among Fee-for-Service Medicare beneficiaries (age ≥ 66 years at index date) with MCC (n = 1,668), Linked SEER Cancer Registry and Medicare Claims files, 2008-2017.

  13. f

    Type of pre-existing chronic conditions by treatment modality among...

    • plos.figshare.com
    xls
    Updated Jul 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi (2025). Type of pre-existing chronic conditions by treatment modality among Fee-for-Service Medicare beneficiaries (age ≥ 66 years at index date) with MCC (n = 1,668), Linked SEER Cancer Registry and Medicare Claims files, 2008-2017. [Dataset]. http://doi.org/10.1371/journal.pone.0327964.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi
    License

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

    Description

    Type of pre-existing chronic conditions by treatment modality among Fee-for-Service Medicare beneficiaries (age ≥ 66 years at index date) with MCC (n = 1,668), Linked SEER Cancer Registry and Medicare Claims files, 2008-2017.

  14. f

    Associations of chronic conditions with cancer treatment among...

    • plos.figshare.com
    xls
    Updated Jul 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi (2025). Associations of chronic conditions with cancer treatment among Fee-For-Service Medicare beneficiaries (age ≥ 66 years at incident cancer diagnosis) with MCC Linked SEER Cancer Registry and Medicare Claims Files, 2008 to 2017. [Dataset]. http://doi.org/10.1371/journal.pone.0327964.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Yves Paul Vincent Mbous; Zasim Azhar Siddiqui; Murtuza Bharmal; Traci LeMasters; Joanna Kolodney; George A. Kelley; Khalid Kamal; Usha Sambamoorthi
    License

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

    Description

    Associations of chronic conditions with cancer treatment among Fee-For-Service Medicare beneficiaries (age ≥ 66 years at incident cancer diagnosis) with MCC Linked SEER Cancer Registry and Medicare Claims Files, 2008 to 2017.

  15. f

    Linkage disequilibrium between SNPs associated with telomere length.

    • figshare.com
    xls
    Updated Jun 14, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ekaterina Protsenko; David Rehkopf; Aric A. Prather; Elissa Epel; Jue Lin (2023). Linkage disequilibrium between SNPs associated with telomere length. [Dataset]. http://doi.org/10.1371/journal.pone.0240185.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 14, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ekaterina Protsenko; David Rehkopf; Aric A. Prather; Elissa Epel; Jue Lin
    License

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

    Description

    Linkage disequilibrium between SNPs associated with telomere length.

  16. Population health burden associated with telomere length based on Haycock et...

    • plos.figshare.com
    xls
    Updated Jun 14, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ekaterina Protsenko; David Rehkopf; Aric A. Prather; Elissa Epel; Jue Lin (2023). Population health burden associated with telomere length based on Haycock et al 2017 meta-analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0240185.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 14, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ekaterina Protsenko; David Rehkopf; Aric A. Prather; Elissa Epel; Jue Lin
    License

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

    Description

    Population health burden associated with telomere length based on Haycock et al 2017 meta-analysis.

  17. Population health burden associated with telomere length based on Li et al...

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ekaterina Protsenko; David Rehkopf; Aric A. Prather; Elissa Epel; Jue Lin (2023). Population health burden associated with telomere length based on Li et al 2020 meta-analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0240185.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ekaterina Protsenko; David Rehkopf; Aric A. Prather; Elissa Epel; Jue Lin
    License

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

    Description

    Population health burden associated with telomere length based on Li et al 2020 meta-analysis.

  18. f

    Table_1_Long-term survival outcomes of pediatric adrenal malignancies: An...

    • frontiersin.figshare.com
    pdf
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zemin Lv; Yunyun Yu; Yangmei Luo; Song Lin; Xuang Xiang; Xiaowen Mao; Shigang Cheng (2023). Table_1_Long-term survival outcomes of pediatric adrenal malignancies: An analysis with the upstaged SEER registry during 2000-2019.pdf [Dataset]. http://doi.org/10.3389/fendo.2022.977105.s001
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Frontiers
    Authors
    Zemin Lv; Yunyun Yu; Yangmei Luo; Song Lin; Xuang Xiang; Xiaowen Mao; Shigang Cheng
    License

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

    Description

    ObjectiveTo investigate the clinicopathological characteristics and long-term survival outcomes of pediatric adrenal malignancies.MethodThis study retrospectively analyzed children with pathologically confirmed pediatric adrenal malignancies from Surveillance, Epidemiology, and End Results Database from 2000 to 2019. Kaplan-Meier curve was used to assess the overall survival (OS) and cancer-special survival (CSS), and the Log-Rank method was used to calculate statistical differences. Cox proportional hazards model and Fine-and-Grey model were used to calculate the hazard ratio (HR) of all-cause mortality risk and the sub-distribution HR (sHR) of disease-specific mortality risk, respectively, and their corresponding 95% confidence intervals (CI).Results1601 children were included in the study in which 1335 (83.4%) neuroblastoma, 151 (9.4%) ganglioneuroblastoma, 89 (5.6%) adrenocortical carcinoma, and 26 (1.6%) were diagnosed with other types malignancies. Metastatic disease accounted for the largest proportion (69.3%), and the proportion of metastases diagnosed by neuroblastoma was higher than that of adrenocortical carcinoma and ganglioneuroblastoma (73.9% vs. 45.7% vs. 47.2%). The 5-year OS and CSS of all cohort were 69.5% and 70.5%, respectively. Adrenal cortical carcinoma had the worst prognosis, with 5-year OS and CSS of 52.5% and 53.1%, respectively. Patients in recent years had no better OS and CSS than in previous years at diagnosis. The tumor stage remained the main prognostic predictor. Compared to metastatic adrenal tumors, the risk of all-cause mortality (adjusted HR: 0.12, 95% CI: 0.06-0.25, P < 0.001) and the risk of disease-specific mortality (adjusted sHR: 0.11, 95% CI: 0.05-0.25, P

  19. f

    12, 36-, and 60-month cancer-specific and overall survival rates in prostate...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 27, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Xinxing Zhang; Yuxuan Wang (2025). 12, 36-, and 60-month cancer-specific and overall survival rates in prostate cancer patients with bone metastasis, 17 SEER registries, 2010–2021. [Dataset]. http://doi.org/10.1371/journal.pone.0326429.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Xinxing Zhang; Yuxuan Wang
    License

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

    Description

    12, 36-, and 60-month cancer-specific and overall survival rates in prostate cancer patients with bone metastasis, 17 SEER registries, 2010–2021.

  20. f

    Baseline characteristics of prostate cancer patients with bone metastases,...

    • plos.figshare.com
    xls
    Updated Jun 27, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Xinxing Zhang; Yuxuan Wang (2025). Baseline characteristics of prostate cancer patients with bone metastases, 17 SEER registries, 2010-2021. [Dataset]. http://doi.org/10.1371/journal.pone.0326429.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Xinxing Zhang; Yuxuan Wang
    License

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

    Description

    Baseline characteristics of prostate cancer patients with bone metastases, 17 SEER registries, 2010-2021.

  21. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
National Cancer Institute (2019). NCI State Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/datasets/NCI::nci-state-cancer-incidence-rates

NCI State Cancer Incidence Rates

Explore at:
Dataset updated
Aug 20, 2019
Dataset authored and provided by
National Cancer Institute
License

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

Area covered
Description

This dataset contains Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2012 to 2016.Data is segmented by sex and age, with fields describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.gov Data NotationsState Cancer Registries may provide more current or more local data.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population seer.cancer.gov/stdpopulations/stdpop.19ages.html. 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. [seer.cancer.gov/seerstat]Population counts for denominators are based on Census populations as modified [seer.cancer.gov/popdata] by NCI. The 1969-2016 US Population Data File [seer.cancer.gov/popdata] is used for SEER and NPCR incidence rates.‡ Incidence 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.html.^ All Stages refers to any stage in the Surveillance, Epidemiology, and End Results (SEER) summary stage [seer.cancer.gov/tools/ssm].Healthy People 2020 Objectives [www.healthypeople.gov]provided by the Centers for Disease Control and Prevention [www.cdc.gov]. Michigan Data do not include cases diagnosed in other states for those states in which the data exchange agreement specifically prohibits the release of data to third parties.Trend Data not available for Nevada.Data Source Field Key:(1) Source: CDC's National Program of Cancer Registries Cancer Surveillance System (NPCR-CSS) November 2018 data submission and SEER November 2018 submission as published in United States Cancer Statistics nccd.cdc.gov/uscs Source: State Cancer Registry and the CDC's National Program of Cancer Registries Cancer Surveillance System (NPCR-CSS) November 2018 data submission. State rates include rates from metropolitan areas funded by SEER [seer.cancer.gov/registries].(6) Source: State Cancer Registry and the CDC's National Program of Cancer Registries Cancer Surveillance System (NPCR-CSS) November 2018 data submission.(7) Source: SEER November 2018 submission.8 Source: Incidence data provided by the SEER Program. [seer.cancer.gov] AAPCs are calculated by the Joinpoint Regression Program [surveillance.cancer.gov/joinpoint] and are based on APCs. Data are age-adjusted to the 2000 US standard population www.seer.cancer.gov/stdpopulations/single_age.html. 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 1969-2017 US Population Data [seer.cancer.gov/popdata] File is used with SEER November 2018 data. Please note that the data comes from different sources. Due to different years [statecancerprofiles.cancer.gov/historicaltrend/differences.html] of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. [seer.cancer.gov/seerstat] Please refer to the source for each graph for additional information. Some data are not available [http://statecancerprofiles.cancer.gov/datanotavailable.html] for combinations of geography, cancer site, age, and race/ethnicity.

Search
Clear search
Close search
Google apps
Main menu