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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.
The rate of liver cancer diagnoses in the United States increases with age. As of 2021, those aged 75 to 79 years had the highest rates of liver cancer. Risk factors for liver cancer include smoking, drinking alcohol, being overweight or obese, and having diabetes. Who is most likely to get liver cancer? Liver cancer in the United States is much more common among men than women. In 2021, there were 12.3 new liver cancer diagnoses among men per 100,000 population, compared to just five new diagnoses per 100,000 women. Concerning race and ethnicity, non-Hispanic American Indians and Alaska Natives and Hispanic have the highest rates of new liver cancer diagnoses. The five-year survival rate for liver cancer in the United States is around 22 percent, however, this rate is much higher among non-Hispanic Asian and Pacific Islanders than other races and ethnicities. Non-Hispanic Asian and Pacific Islanders have a 33 percent chance of surviving the next five years after a liver cancer diagnosis. Deaths from liver cancer In 2020, there were an estimated 20,262 deaths in the United States due to liver cancer. However, the death rate for liver cancer has decreased over the past few years. In the period 1999 to 2020, the death rate for liver cancer reached a high of five deaths per 100,000 population in 2015 but dropped to 4.6 deaths per 100,000 population by 2020. It is estimated that in 2024, there will be over 19,000 liver and intrahepatic bile duct cancer deaths among men in the United States and 10,700 such deaths among women.
Population based cancer incidence rates were abstracted from National Cancer Institute, State Cancer Profiles for all available counties in the United States for which data were available. This is a national county-level database of cancer data that are collected by state public health surveillance systems. All-site cancer is defined as any type of cancer that is captured in the state registry data, though non-melanoma skin cancer is not included. All-site age-adjusted cancer incidence rates were abstracted separately for males and females. County-level annual age-adjusted all-site cancer incidence rates for years 2006–2010 were available for 2687 of 3142 (85.5%) counties in the U.S. Counties for which there are fewer than 16 reported cases in a specific area-sex-race category are suppressed to ensure confidentiality and stability of rate estimates; this accounted for 14 counties in our study. Two states, Kansas and Virginia, do not provide data because of state legislation and regulations which prohibit the release of county level data to outside entities. Data from Michigan does not include cases diagnosed in other states because data exchange agreements prohibit the release of data to third parties. Finally, state data is not available for three states, Minnesota, Ohio, and Washington. The age-adjusted average annual incidence rate for all counties was 453.7 per 100,000 persons. We selected 2006–2010 as it is subsequent in time to the EQI exposure data which was constructed to represent the years 2000–2005. We also gathered data for the three leading causes of cancer for males (lung, prostate, and colorectal) and females (lung, breast, and colorectal). The EQI was used as an exposure metric as an indicator of cumulative environmental exposures at the county-level representing the period 2000 to 2005. A complete description of the datasets used in the EQI are provided in Lobdell et al. and methods used for index construction are described by Messer et al. The EQI was developed for the period 2000– 2005 because it was the time period for which the most recent data were available when index construction was initiated. The EQI includes variables representing each of the environmental domains. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jagai, J., L. Messer, K. Rappazzo , C. Gray, S. Grabich , and D. Lobdell. County-level environmental quality and associations with cancer incidence#. Cancer. John Wiley & Sons Incorporated, New York, NY, USA, 123(15): 2901-2908, (2017).
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Summary statistics of average lung cancer incidence rates and average daily smokers in percentage in 8 U.S. geographic regions, 1999–2012.
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The dataset contains 2 .csv files This file contains various demographic and health-related data for different regions. Here's a brief description of each column:
avganncount: Average number of cancer cases diagnosed annually.
avgdeathsperyear: Average number of deaths due to cancer per year.
target_deathrate: Target death rate due to cancer.
incidencerate: Incidence rate of cancer.
medincome: Median income in the region.
popest2015: Estimated population in 2015.
povertypercent: Percentage of population below the poverty line.
studypercap: Per capita number of cancer-related clinical trials conducted.
binnedinc: Binned median income.
medianage: Median age in the region.
pctprivatecoveragealone: Percentage of population covered by private health insurance alone.
pctempprivcoverage: Percentage of population covered by employee-provided private health insurance.
pctpubliccoverage: Percentage of population covered by public health insurance.
pctpubliccoveragealone: Percentage of population covered by public health insurance only.
pctwhite: Percentage of White population.
pctblack: Percentage of Black population.
pctasian: Percentage of Asian population.
pctotherrace: Percentage of population belonging to other races.
pctmarriedhouseholds: Percentage of married households. birthrate: Birth rate in the region.
This file contains demographic information about different regions, including details about household size and geographical location. Here's a description of each column:
statefips: The FIPS code representing the state.
countyfips: The FIPS code representing the county or census area within the state.
avghouseholdsize: The average household size in the region.
geography: The geographical location, typically represented as the county or census area name followed by the state name.
Each row in the file represents a specific region, providing details about household size and geographical location. This information can be used for various demographic analyses and studies.
This is a linked dataset between drinking water data and cancer data. Drinking Water Data: County-level concentrations of arsenic from CWSs between 2000 and 2010 were collected from the Center for Disease Control and Prevention’s (CDC) National Environmental Public Health Tracking Network (NEPHTN) (Centers for Disease Control and Prevention, 2018a). Annual mean drinking water arsenic concentrations from 2000 to 2010 were available for a total of 87,662 samples from 75,453 CWS from 26 states, representing 1,425 counties. For samples identified as non-detects, the most frequently reported values were 0.5 ppb and 1 ppb, with a range of 0 ppb to 10 ppb. For non-detect samples reported as zero, the value was substituted with a constant of 0.25 ppb (Almberg et al., 2017; Bulka et al., 2016). Of the samples that were reported as non-detects, 10.87% were reported as zeros. Cancer Data: County-level cancer counts and incidence rates for bladder, colorectal, and kidney cancers were acquired from the National Cancer Institute (NCI) and CDC’s State Cancer Profiles for 2011 through 2015 for adults (age ≥ 50) to match the counties with exposure data (National Cancer Institute and Centers for Disease Control and Prevention, 2018a). We utilized the time period 2011-2015 to provide a lag following the exposure period of 2000-2010. The State Cancer Profiles provide age-adjusted county-level cancer incidence, prevalence, mortality rates and average annual counts for 20 different types of cancers and select demographics (National Cancer Institute and Centers for Disease Control and Prevention, 2018b). Counties where there were less than 16 reported cases in a specific county, sex, and/or race category were suppressed to ensure confidentiality and stability of rate estimates (National Cancer Institute and Centers for Disease Control and Prevention, 2018a). This dataset is associated with the following publication: Krajewski, A., M. Jimenez, K. Rappazzo, D. Lobdell, and J. Jagai. Aggregated Cumulative County Arsenic in Drinking Water and Associations with Bladder, Colorectal, and Kidney Cancers, Accounting for Population Served. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 31(6): 979-989, (2021).
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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.
Between 2017 and 2021, adults aged 80 to 84 years had the highest incidence of alcohol-associated cancer in the United States, with a rate of around 572 per 100,000 people. This graph shows the rate of alcohol-related cancers per 100,000 people from 2017 to 2021 in the United States, by age.
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US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 11.800 NA in 2016. This records an increase from the previous number of 11.600 NA for 2015. US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 11.800 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 14.600 NA in 2000 and a record low of 11.600 NA in 2015. US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
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BackgroundCervical cancer incidence and mortality rates in the United States have substantially declined over recent decades, primarily driven by reductions in squamous cell carcinoma cases. However, the trend in recent years remains unclear. This study aimed to explore the trends in cervical cancer incidence and mortality, stratified by demographic and tumor characteristics from 1975 to 2018.MethodsThe age-adjusted incidence, incidence-based mortality, and relative survival of cervical cancer were calculated using the Surveillance, Epidemiology, and End Results (SEER)-9 database. Trend analyses with annual percent change (APC) and average annual percent change (AAPC) calculations were performed using Joinpoint Regression Software (Version 4.9.1.0, National Cancer Institute).ResultsDuring 1975–2018, 49,658 cervical cancer cases were diagnosed, with 17,099 recorded deaths occurring between 1995 and 2018. Squamous cell carcinoma was the most common histological type, with 34,169 cases and 11,859 deaths. Over the study period, the cervical cancer incidence rate decreased by an average of 1.9% (95% CI: −2.3% to −1.6%) per year, with the APCs decreased in recent years (−0.5% [95% CI: −1.1 to 0.1%] in 2006–2018). Squamous cell carcinoma incidence trends closely paralleled overall cervical cancer patterns, but the incidence of squamous cell carcinoma in the distant stage increased significantly (1.1% [95% CI: 0.4 to 1.8%] in 1990–2018). From 1995 to 2018, the overall cervical cancer mortality rate decreased by 1.0% (95% CI: −1.2% to −0.8%) per year. But for distant-stage squamous cell carcinoma, the mortality rate increased by 1.2% (95% CI: 0.3 to 2.1%) per year.ConclusionFor cervical cancer cases diagnosed in the United States from 1975 to 2018, the overall incidence and mortality rates decreased significantly. However, there was an increase in the incidence and mortality of advanced-stage squamous cell carcinoma. These epidemiological patterns offer critical insights for refining cervical cancer screening protocols and developing targeted interventions for advanced-stage cases.
In 2021, Utah had the highest rate of skin cancer, with an estimated 46 people out of 100,000 diagnosed with melanoma or another non-epithelial skin cancer. This statistic shows the incidence rate of skin cancer in the U.S. in 2021, by state, per 100,000 population.
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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.
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United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 14.600 % in 2016. This records an increase from the previous number of 14.300 % for 2015. United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 14.600 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 18.000 % in 2000 and a record low of 14.300 % in 2015. United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;
From 2018 to 2022, around 34 percent of prostate cancer deaths in the United States were among men aged 75 to 84 years. During that period, the median age of death for prostate cancer was 79 years. This statistic shows the distribution of prostate cancer deaths in the United States between 2018 and 2022, by age.
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Background. Age-adjusted US total pediatric cancer incidence rates (TPCIR) rose 49% 1975-2015 for unknown reasons. Prenatal cannabis exposure has been linked with several pediatric cancers which together comprise the majority of pediatric cancer types. We investigated whether cannabis use was related spatiotemporally and causally to TPCIR.
Methods. State-based age-adjusted TPCIR data was taken from the CDC Surveillance, Epidemiology and End Results cancer database 2003-2017. Drug exposure was taken from the nationally-representative National Survey of Drug Use and Health, response rate 74.1%. Drugs included were: tobacco, alcohol, cannabis, opioid analgesics and cocaine. This was supplemented by cannabinoid concentration data from the Drug Enforcement Agency and ethnicity and median household income data from US Census.
Results. TPCIR rose while all drug use nationally fell, except for cannabis which rose. TPCIR in the highest cannabis use quintile was greater than in the lowest (β-estimate=1.31 (95%C.I. 0.82, 1.80), P=1.80x10-7) and the time:highest two quintiles interaction was significant (β-estimate=0.1395 (0.82, 1.80), P=1.00x10-14). In robust inverse probability weighted additive regression models cannabis was independently associated with TPCIR (β-estimate=9.55 (3.95, 15.15), P=0.0016). In interactive geospatiotemporal models including all drug, ethnic and income variables cannabis use was independently significant (β-estimate=45.67 (18.77, 72.56), P=0.0009). In geospatial models temporally lagged to 1,2,4 and 6 years interactive terms including cannabis were significant. Cannabis interactive terms at one and two degrees of spatial lagging were significant (from β-estimate=3954.04 (1565.01, 6343.09), P=0.0012). The interaction between the cannabinoids THC and cannabigerol was significant at zero, 2 and 6 years lag (from β-estimate=46.22 (30.06, 62.38), P=2.10x10-8). Cannabis legalization was associated with higher TPCIR (β-estimate=1.51 (0.68, 2.35), P=0.0004) and cannabis-liberal regimes were associated with higher time:TPCIR interaction (β-estimate=1.87x10-4, (2.9x10-5, 2.45x10-4), P=0.0208). 33/56 minimum e-Values were >5 and 6 were infinite.
Conclusion. Data confirm a close relationship across space and lagged time between cannabis and TPCIR which was robust to adjustment, supported by inverse probability weighting procedures and accompanied by high e-Values making confounding unlikely and establishing the causal relationship. Cannabis-liberal jurisdictions were associated with higher rates of TPCIR and a faster rate of TPCIR increase. Data inform the broader general consideration of cannabinoid-induced genotoxicity.
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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.
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ObjectiveUsing the latest cohort study of prostate cancer patients, explore the epidemiological trend and prognostic factors, and develop a new nomogram to predict the specific survival rate of prostate cancer patients.MethodsPatients with prostate cancer diagnosed from January 1, 1975 to December 31, 2019 in the Surveillance, Epidemiology, and End Results Program (SEER) database were extracted by SEER stat software for epidemiological trend analysis. General clinical information and follow-up data were also collected from 105 135 patients with pathologically diagnosed prostate cancer from January 1, 2010 to December 1, 2019. The factors affecting patient-specific survival were analyzed by Cox regression, and the factors with the greatest influence on specific survival were selected by stepwise regression method, and nomogram was constructed. The model was evaluated by calibration plots, ROC curves, Decision Curve Analysis and C-index.ResultsThere was no significant change in the age-adjusted incidence of prostate cancer from 1975 to 2019, with an average annual percentage change (AAPC) of 0.45 (95% CI:-0.87~1.80). Among the tumor grade, the most significant increase in the incidence of G2 prostate cancer was observed, with an AAPC of 2.99 (95% CI:1.47~4.54); the most significant decrease in the incidence of G4 prostate cancer was observed, with an AAPC of -10.39 (95% CI:-13.86~-6.77). Among the different tumor stages, the most significant reduction in the incidence of localized prostate cancer was observed with an AAPC of -1.83 (95% CI:-2.76~-0.90). Among different races, the incidence of prostate cancer was significantly reduced in American Indian or Alaska Native and Asian or Pacific Islander, with an AAPC of -3.40 (95% CI:-3.97~-2.82) and -2.74 (95% CI:-4.14~-1.32), respectively. Among the different age groups, the incidence rate was significantly increased in 15-54 and 55-64 age groups with AAPC of 4.03 (95% CI:2.73~5.34) and 2.50 (95% CI:0.96~4.05), respectively, and significantly decreased in ≥85 age group with AAPC of -2.50 (95% CI:-3.43~-1.57). In addition, age, tumor stage, race, PSA and gleason score were found to be independent risk factors affecting prostate cancer patient-specific survival. Age, tumor stage, PSA and gleason score were most strongly associated with prostate cancer patient-specific survival by stepwise regression screening, and nomogram prediction model was constructed using these factors. The Concordance indexes are 0.845 (95% CI:0.818~0.872) and 0.835 (95% CI:0.798~0.872) for the training and validation sets, respectively, and the area under the ROC curves (AUC) at 3, 6, and 9 years was 0.7 or more for both the training and validation set samples. The calibration plots indicated a good agreement between the predicted and actual values of the model.ConclusionsAlthough there was no significant change in the overall incidence of prostate cancer in this study, significant changes occurred in the incidence of prostate cancer with different characteristics. In addition, the nomogram prediction model of prostate cancer-specific survival rate constructed based on four factors has a high reference value, which helps physicians to correctly assess the patient-specific survival rate and provides a reference basis for patient diagnosis and prognosis evaluation.
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Note: For carbon tetrachloride, we applied the average DALYs for different types of cancers of 8.5 years, since available information does not provide DALY per case estimate for this type of cancer.Disability adjusted life years (DALY) per cancer case corresponding to the cancer type for the 10 air toxics with the highest national average cancer risks.
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In the United States, around 9,729 new testicular cancer cases are estimated to be diagnosed in 2025, as per the American Cancer Society. Further, nearly 600 deaths are projected to occur in the country in 2025 due to testicular cancer. The average age of testicular cancer diagnosis is reported to be about 33 years.
The North America cancer therapy market size was USD XX Billion in 2022 and is likely to reach USD XX Billion by 2031, expanding at a CAGR of 8.1% during 2023–2031.The growth of market is attributed due to increasing prevalence of cancer, investments on R&D, and rising government initiatives for cancer awareness.
The demand for personalized medicines and increasing number of cancer cases is expected to ascend the demand for advanced cancer therapies for the effective treatment of the sufferers.
Targeted therapy segment is expected to witness rapid growth in the field of cancer research, and researchers are primarily focused on studying various new targets with increasing favorable government support on product approvals and research initiatives regarding target therapy against cancer, is anticipated to surge during the forecast period.
According to the research report of Canadian Cancer Society (CCS) 2020 it is expected to showcase, 225,790 new cancer cases and 83,000 deaths to strike in Canada during forecast period. In an average approximately, 600 Canadian people are diagnosed with cancer on daily basis.
With the COVID-19 outbreak and China being the global manufacturing hub, and the largest raw material supplier globally, the overall market shattered owing to the corona virus affecting the growth market. Temporarily shutting down of factories, disruption in supply chain, and downfall of the economy has affected the industries in various countries.
Increasing number of cancer cases and research activities is expected to drive the market during forecast period.
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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.