The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by year, state and metropolitan areas (MSA), age group, race, ethnicity, sex, childhood cancer classifications and cancer site. Report case counts, deaths, crude and age-adjusted incidence and death rates, and 95% confidence intervals for rates. The USCS data are the official federal statistics on cancer incidence from registries having high-quality data and cancer mortality statistics for 50 states and the District of Columbia. USCS are produced by the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), in collaboration with the North American Association of Central Cancer Registries (NAACCR). Mortality data are provided by the Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), National Vital Statistics System (NVSS).

County Cancer Death Rates

County-level cancer death rates with related variables

By Noah Rippner [source]

About this dataset

This dataset provides comprehensive information on county-level cancer death and incidence rates, as well as various related variables. It includes data on age-adjusted death rates, average deaths per year, recent trends in cancer death rates, recent 5-year trends in death rates, and average annual counts of cancer deaths or incidence. The dataset also includes the federal information processing standards (FIPS) codes for each county.

Additionally, the dataset indicates whether each county met the objective of a targeted death rate of 45.5. The recent trend in cancer deaths or incidence is also captured for analysis purposes.

The purpose of the death.csv file within this dataset is to offer detailed information specifically concerning county-level cancer death rates and related variables. On the other hand, the incd.csv file contains data on county-level cancer incidence rates and additional relevant variables.

To provide more context and understanding about the included data points, there is a separate file named cancer_data_notes.csv. This file serves to provide informative notes and explanations regarding the various aspects of the cancer data used in this dataset.

Please note that this particular description provides an overview for a linear regression walkthrough using this dataset based on Python programming language. It highlights how to source and import the data properly before moving into data preparation steps such as exploratory analysis. The walkthrough further covers model selection and important model diagnostics measures.

It's essential to bear in mind that this example serves as an initial attempt at creating a multivariate Ordinary Least Squares regression model using these datasets from various sources like cancer.gov along with US Census American Community Survey data. This baseline model allows easy comparisons with future iterations intended for improvements or refinements.

Important columns found within this extensively documented Kaggle dataset include County names along with their corresponding FIPS codes—a standardized coding system by Federal Information Processing Standards (FIPS). Moreover,Met Objective of 45.5? (1) column denotes whether a specific county achieved the targeted objective of a death rate of 45.5 or not.

Overall, this dataset aims to offer valuable insights into county-level cancer death and incidence rates across various regions, providing policymakers, researchers, and healthcare professionals with essential information for analysis and decision-making purposes

How to use the dataset

• Familiarize Yourself with the Columns:

  • County: The name of the county.
  • FIPS: The Federal Information Processing Standards code for the county.
  • Met Objective of 45.5? (1): Indicates whether the county met the objective of a death rate of 45.5 (Boolean).
  • Age-Adjusted Death Rate: The age-adjusted death rate for cancer in the county.
  • Average Deaths per Year: The average number of deaths per year due to cancer in the county.
  • Recent Trend (2): The recent trend in cancer death rates/incidence in the county.
  • Recent 5-Year Trend (2) in Death Rates: The recent 5-year trend in cancer death rates/incidence in the county.
  • Average Annual Count: The average annual count of cancer deaths/incidence in the county.

• Determine Counties Meeting Objective: Use this dataset to identify counties that have met or not met an objective death rate threshold of 45.5%. Look for entries where Met Objective of 45.5? (1) is marked as True or False.

• Analyze Age-Adjusted Death Rates: Study and compare age-adjusted death rates across different counties using Age-Adjusted Death Rate values provided as floats.

• Explore Average Deaths per Year: Examine and compare average annual counts and trends regarding deaths caused by cancer, using Average Deaths per Year as a reference point.

• Investigate Recent Trends: Assess recent trends related to cancer deaths or incidence by analyzing data under columns such as Recent Trend, Recent Trend (2), and Recent 5-Year Trend (2) in Death Rates. These columns provide information on how cancer death rates/incidence have changed over time.

• Compare Counties: Utilize this dataset to compare counties based on their cancer death rates and related variables. Identify counties with lower or higher average annual counts, age-adjusted death rates, or recent trends to analyze and understand the factors contributing ...

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.

Cancer Mortality & Incidence Rates: (Country LVL)

Investigating Cancer Trends over time

By Data Exercises [source]

About this dataset

This dataset is a comprehensive collection of data from county-level cancer mortality and incidence rates in the United States between 2000-2014. This data provides an unprecedented level of detail into cancer cases, deaths, and trends at a local level. The included columns include County, FIPS, age-adjusted death rate, average death rate per year, recent trend (2) in death rates, recent 5-year trend (2) in death rates and average annual count for each county. This dataset can be used to provide deep insight into the patterns and effects of cancer on communities as well as help inform policy decisions related to mitigating risk factors or increasing preventive measures such as screenings. With this comprehensive set of records from across the United States over 15 years, you will be able to make informed decisions regarding individual patient care or policy development within your own community!

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How to use the dataset

This dataset provides comprehensive US county-level cancer mortality and incidence rates from 2000 to 2014. It includes the mortality and incidence rate for each county, as well as whether the county met the objective of 45.5 deaths per 100,000 people. It also provides information on recent trends in death rates and average annual counts of cases over the five year period studied.

This dataset can be extremely useful to researchers looking to study trends in cancer death rates across counties. By using this data, researchers will be able to gain valuable insight into how different counties are performing in terms of providing treatment and prevention services for cancer patients and whether preventative measures and healthcare access are having an effect on reducing cancer mortality rates over time. This data can also be used to inform policy makers about counties needing more target prevention efforts or additional resources for providing better healthcare access within at risk communities.

When using this dataset, it is important to pay close attention to any qualitative columns such as “Recent Trend” or “Recent 5-Year Trend (2)” that may provide insights into long term changes that may not be readily apparent when using quantitative variables such as age-adjusted death rate or average deaths per year over shorter periods of time like one year or five years respectively. Additionally, when studying differences between different counties it is important to take note of any standard FIPS code differences that may indicate that data was collected by a different source with a difference methodology than what was used in other areas studied

Research Ideas

• Using this dataset, we can identify patterns in cancer mortality and incidence rates that are statistically significant to create treatment regimens or preventive measures specifically targeting those areas.
• This data can be useful for policymakers to target areas with elevated cancer mortality and incidence rates so they can allocate financial resources to these areas more efficiently.
• This dataset can be used to investigate which factors (such as pollution levels, access to medical care, genetic make up) may have an influence on the cancer mortality and incidence rates in different US counties

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: death .csv | Column name | Description | |:-------------------------------------------|:-------------------------------------------------------------------...

Analysis of ‘🎗️ Cancer Rates by U.S. State’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/cancer-rates-by-u-s-statee on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

In the following maps, the U.S. states are divided into groups based on the rates at which people developed or died from cancer in 2013, the most recent year for which incidence data are available.

The rates are the numbers out of 100,000 people who developed or died from cancer each year.

Incidence Rates by State
The number of people who get cancer is called cancer incidence. In the United States, the rate of getting cancer varies from state to state.

• *Rates are per 100,000 and are age-adjusted to the 2000 U.S. standard population.

• ‡Rates are not shown if the state did not meet USCS publication criteria or if the state did not submit data to CDC.

• †Source: U.S. Cancer Statistics Working Group. United States Cancer Statistics: 1999–2013 Incidence and Mortality Web-based Report. Atlanta (GA): Department of Health and Human Services, Centers for Disease Control and Prevention, and National Cancer Institute; 2016. Available at: http://www.cdc.gov/uscs.

Death Rates by State
Rates of dying from cancer also vary from state to state.

• *Rates are per 100,000 and are age-adjusted to the 2000 U.S. standard population.

• †Source: U.S. Cancer Statistics Working Group. United States Cancer Statistics: 1999–2013 Incidence and Mortality Web-based Report. Atlanta (GA): Department of Health and Human Services, Centers for Disease Control and Prevention, and National Cancer Institute; 2016. Available at: http://www.cdc.gov/uscs.

Source: https://www.cdc.gov/cancer/dcpc/data/state.htm

This dataset was created by Adam Helsinger and contains around 100 samples along with Range, Rate, technical information and other features such as: - Range - Rate - and more.

How to use this dataset

• Analyze Range in relation to Rate
• Study the influence of Range on Rate
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Adam Helsinger

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

📄 Dataset Description: This dataset contains global cancer patient data reported from 2015 to 2024, designed to simulate the key factors influencing cancer diagnosis, treatment, and survival. It includes a variety of features that are commonly studied in the medical field, such as age, gender, cancer type, environmental factors, and lifestyle behaviors. The dataset is perfect for:

Exploratory Data Analysis (EDA)

Multiple Linear Regression and other modeling tasks

Feature Selection and Correlation Analysis

Predictive Modeling for cancer severity, treatment cost, and survival prediction

Data Visualization and creating insightful graphs

Key Features: Age: Patient's age (20-90 years)

Gender: Male, Female, or Other

Country/Region: Country or region of the patient

Cancer Type: Various types of cancer (e.g., Breast, Lung, Colon)

Cancer Stage: Stage 0 to Stage IV

Risk Factors: Includes genetic risk, air pollution, alcohol use, smoking, obesity, etc.

Treatment Cost: Estimated cost of cancer treatment (in USD)

Survival Years: Years survived since diagnosis

Severity Score: A composite score representing cancer severity

This dataset provides a broad view of global cancer trends, making it an ideal resource for those learning data science, machine learning, and statistical analysis in healthcare.

Annual percent change and average annual percent change in age-standardized cancer incidence rates since 1984 to the most recent diagnosis year. The table includes a selection of commonly diagnosed invasive cancers, as well as in situ bladder cancer. Cases are 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) from 1992 to the most recent data year and on the International Classification of Diseases, ninth revision (ICD-9) from 1984 to 1991.

Annual percent change and average annual percent change in age-standardized cancer mortality rates since 1984 to the most recent data year. The table includes a selection of commonly diagnosed invasive cancers and causes of death are defined based on the World Health Organization International Classification of Diseases, ninth revision (ICD-9) from 1984 to 1999 and on its tenth revision (ICD-10) from 2000 to the most recent year.

Users can access data about cancer statistics in the United States including but not limited to searches by type of cancer and race, sex, ethnicity, age at diagnosis, and age at death. Background Surveillance Epidemiology and End Results (SEER) database’s mission is to provide information on cancer statistics to help reduce the burden of disease in the U.S. population. The SEER database is a project to the National Cancer Institute. The SEER database collects information on incidence, prevalence, and survival from specific geographic areas representing 28 percent of the United States population. User functionality Users can access a variety of reso urces. Cancer Stat Fact Sheets allow users to look at summaries of statistics by major cancer type. Cancer Statistic Reviews are available from 1975-2008 in table format. Users are also able to build their own tables and graphs using Fast Stats. The Cancer Query system provides more flexibility and a larger set of cancer statistics than F ast Stats but requires more input from the user. State Cancer Profiles include dynamic maps and graphs enabling the investigation of cancer trends at the county, state, and national levels. SEER research data files and SEER*Stat software are available to download through your Internet connection (SEER*Stat’s client-server mode) or via discs shipped directly to you. A signed data agreement form is required to access the SEER data Data Notes Data is available in different formats depending on which type of data is accessed. Some data is available in table, PDF, and html formats. Detailed information about the data is available under “Data Documentation and Variable Recodes”.

The interannual variability of SMR for a given administrative unit might be large under small populations. Indeed, being the SMR a rate standardized over the population size, the expected mortality (i.e., Em) in small populations will result low (say 10-2) and in turn, according to eq. (1), even a few deaths (say 1 or 2) in a year could yield a relatively high SMR as shown in Figure 3. For this reason, we recommend avoiding using single-year estimates and using the average SMR and/or lower 90% or 95% confidence intervals.

Cancer diagnoses and age-standardised incidence rates for all types of cancer by age and sex including breast, prostate, lung and colorectal cancer.

This data shows premature deaths (Age under 75) from all Cancers, numbers and rates by gender, as 3-year moving-averages. Cancers are a major cause of premature deaths. Inequalities exist in cancer rates between the most deprived areas and the most affluent areas. Directly Age-Standardised Rates (DASR) are shown in the data (where numbers are sufficient) so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: Office for Health Improvement and Disparities (OHID), indicator ID 40501, E05a. This data is updated annually.

Age standardized rate of cancer incidence, by selected sites of cancer and sex, three-year average, census metropolitan areas.

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.

This dataset provides a detailed and structured overview of oral cancer cases worldwide. It includes key risk factors, symptoms, cancer staging, survival rates, treatment approaches, and economic burden to facilitate research and prediction modeling. The dataset is based on real-world oral cancer statistics, aligning with global health reports and studies.

Key Highlights: Covers high-incidence regions (India, Pakistan, Sri Lanka, Taiwan) and emerging trends in Western nations. Includes tobacco, alcohol, HPV infection, betel quid use, and dietary factors as primary risk factors. Captures economic burden (treatment costs, workdays lost) to assess the financial impact of oral cancer. Provides cancer staging, survival rates, and early diagnosis indicators for better treatment predictions. This dataset is valuable for medical professionals, researchers, data scientists, and policymakers aiming to develop early detection models, assess regional disparities, and improve cancer prevention strategies.

Columns Overview ID – Unique identifier Country – Country name Age – Age of the individual Gender – Male/Female Tobacco Use – Yes/No Alcohol Consumption – Yes/No HPV Infection – Yes/No Betel Quid Use – Yes/No Chronic Sun Exposure – Yes/No Poor Oral Hygiene – Yes/No Diet (Fruits & Vegetables Intake) – Low/Moderate/High Family History of Cancer – Yes/No Compromised Immune System – Yes/No Oral Lesions – Yes/No Unexplained Bleeding – Yes/No Difficulty Swallowing – Yes/No White or Red Patches in Mouth – Yes/No Tumor Size (cm) – Numerical value Cancer Stage – 0 (No Cancer), 1, 2, 3, 4 Treatment Type – Surgery/Radiation/Chemotherapy/Targeted Therapy/No Treatment Survival Rate (5-Year, %) Cost of Treatment (USD) Economic Burden (Lost Workdays per Year) Early Diagnosis (Yes/No) Oral Cancer (Diagnosis) – Yes/No (Target Variable)

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.

One-year and five-year net survival for adults (15-99) in England diagnosed with one of 29 common cancers, by age and sex.

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

Mortality Rates for Lake County, Illinois. Explanation of field attributes: Average Age of Death – The average age at which a people in the given zip code die. Cancer Deaths – Cancer deaths refers to individuals who have died of cancer as the underlying cause. This is a rate per 100,000. Heart Disease Related Deaths – Heart Disease Related Deaths refers to individuals who have died of heart disease as the underlying cause. This is a rate per 100,000. COPD Related Deaths – COPD Related Deaths refers to individuals who have died of chronic obstructive pulmonary disease (COPD) as the underlying cause. This is a rate per 100,000.

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.