Cancer was responsible for around *** deaths per 100,000 population in the United States in 2023. The death rate for cancer has steadily decreased since the 1990’s, but cancer still remains the second leading cause of death in the United States. The deadliest type of cancer for both men and women is cancer of the lung and bronchus which will account for an estimated ****** deaths among men alone in 2025. Probability of surviving Survival rates for cancer vary significantly depending on the type of cancer. The cancers with the highest rates of survival include cancers of the thyroid, prostate, and testis, with five-year survival rates as high as ** percent for thyroid cancer. The cancers with the lowest five-year survival rates include cancers of the pancreas, liver, and esophagus. Risk factors It is difficult to determine why one person develops cancer while another does not, but certain risk factors have been shown to increase a person’s chance of developing cancer. For example, cigarette smoking has been proven to increase the risk of developing various cancers. In fact, around ** percent of cancers of the lung, bronchus and trachea among adults aged 30 years and older can be attributed to cigarette smoking. Other modifiable risk factors for cancer include being obese, drinking alcohol, and sun exposure.

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 ...

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).

Decrease the cancer death rate from 185.7 per 100,000 in 2013 to 180.3 per 100,000 by 2019.

The rate of breast cancer deaths in the U.S. has dramatically declined since 1950. As of 2022, the death rate from breast cancer had dropped from 31.9 to 18.7 per 100,000 population. Cancer is a serious public health issue in the United States. As of 2021, cancer is the second leading cause of death among women. Breast cancer incidence Breast cancer symptoms include lumps or thickening of the breast tissue and may include changes to the skin. Breast cancer is driven by many factors, but age is a known risk factor. Among all age groups, the highest number of invasive breast cancer cases were among those aged 60 to 69. The incidence rate of new breast cancer cases is higher in some ethnicities than others. White, non-Hispanic women had the highest incidence rate of breast cancer, followed by non-Hispanic Black women. Breast cancer treatment Breast cancer treatments usually involve several methods, including surgery, chemotherapy and biological therapy. Types of cancer diagnosed at earlier stages often require fewer treatments. A majority of the early stage breast cancer cases in the U.S. receive breast conserving surgery and radiation therapy.

In 2022, there were over 9.7 million cancer deaths worldwide. It is projected that the number of deaths due to cancer worldwide will increase to almost 18.5 million by 2050. The most prevalent type of cancer in 2022 was breast cancer with around 48 prevalent cases per 100,000 population. However, lung cancer is by far the deadliest type of cancer.

Lung Cancer Lung cancer is a malignant lung tumor characterized by uncontrolled cell growth in tissues of the lung. In 2022, around 1.82 million cancer deaths, or 19 percent of all cancer deaths worldwide were attributed to lung cancer. Long-term smoking is known to be a major cause of lung cancer. People who never quit smoking are 24 percent more likely to die before age 65 than people who never smoked in their lives.

Treatment In 2023, it was estimated that there were around 4,492 cancer immunotherapy products in R&D phases, as well as another 3,622 other cancer products in the R&D product pipeline. In the same year, it was projected that there were 965 active drugs for breast cancer, as well as 925 active drugs for non-small cell lung cancer.

The rate of breast cancer deaths in the U.S. has dramatically declined since 1950. As of 2023, the death rate from breast cancer was **** per 100,000 population. However, cancer is a serious public health issue in the United States and is the second leading cause of death among women. Breast cancer incidence Breast cancer symptoms include lumps or thickening of the breast tissue and may include changes to the skin. Breast cancer is driven by many factors, but age is a known risk factor. Among all age groups, the highest number of invasive breast cancer cases were among those aged 60 to 69. The incidence rate of new breast cancer cases is higher in some ethnicities than others. White, non-Hispanic women have the highest incidence rate of breast cancer, followed by non-Hispanic Black women. Breast cancer treatment Breast cancer treatments usually involve several methods, including surgery, chemotherapy and biological therapy. Types of cancer diagnosed at earlier stages often require fewer treatments. A majority of early stage breast cancer cases in the U.S. receive breast conserving surgery and radiation therapy.

Source: https://ourworldindata.org/cancer

The dataset titled "Cancer Types Causing Death," sourced from Our World in Data, provides a comprehensive overview of global cancer mortality trends. According to the dataset, lung cancer leads as the most fatal cancer worldwide, with approximately 1.8 million deaths in 2022, accounting for 18.7% of all cancer-related fatalities . Following lung cancer, colorectal cancer ranks second, causing about 900,000 deaths (9.3%), while liver cancer and breast cancer account for 760,000 (7.8%) and 670,000 (6.9%) deaths, respectively. Stomach cancer also remains a significant cause of death, with 660,000 fatalities (6.8%) .

The dataset highlights that lung cancer's prevalence is closely linked to tobacco use, particularly in regions like Asia. In contrast, breast cancer predominantly affects women, while colorectal cancer impacts both genders equally. Notably, the dataset indicates a decline in age-standardized death rates for certain cancers, such as stomach cancer, due to improved hygiene, sanitation, and antibiotic treatments targeting Helicobacter pylori infections . Our World in Data

Additionally, the dataset underscores the global disparity in cancer mortality, with approximately 70% of cancer deaths occurring in low- and middle-income countries . This disparity is attributed to factors like limited access to early detection, treatment, and preventive measures. The dataset serves as a valuable resource for understanding the global burden of cancer and the need for targeted public health interventions. World Health Organization

Content

In this dataset you'll find the deaths from cancer at hospitals in the respective 50 states in America.

Acknowledgements

This dataset comes from https://data.world/dartmouthatlas/cancer-patients-death.

BackgroundThe role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates.Patients and MethodsThe Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk.ResultsThe observed and predicted RR of breast cancer death were 0.72 (0.56–0.94) and 0.98 (0.77–1.24) in the HIP trial, and 0.79 (0.78–1.01) and 0.90 (0.80–1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62–0.87), while the predicted RR was 0.89 (0.75–1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70–0.97) if extra cancers were excluded.ConclusionsIn breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.

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.

Legacy unique identifier: P00508

Legacy unique identifier: P00624

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: NHS Health and Social Care Information Centre (NHS-HSCIC) (Dataset unique identifier P00399). This data is updated annually.

The number of deaths caused by cancer among men in Sweden was higher than the number of cancer deaths among women in all years during the period from 2009 to 2023. For both men and women, the number of cancer deaths were generally decreasing over the period. In 2023, the death rate from cancer was around *** deaths per hundred thousand inhabitants among men and around *** among women.

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

Legacy unique identifier: P00628

BackgroundThe success of the “war on cancer” initiated in 1971 continues to be debated, with trends in cancer mortality variably presented as evidence of progress or failure. We examined temporal trends in death rates from all-cancer and the 19 most common cancers in the United States from 1970–2006.Methodology/Principal FindingsWe analyzed trends in age-standardized death rates (per 100,000) for all cancers combined, the four most common cancers, and 15 other sites from 1970–2006 in the United States using joinpoint regression model. The age-standardized death rate for all-cancers combined in men increased from 249.3 in 1970 to 279.8 in 1990, and then decreased to 221.1 in 2006, yielding a net decline of 21% and 11% from the 1990 and 1970 rates, respectively. Similarly, the all-cancer death rate in women increased from 163.0 in 1970 to 175.3 in 1991 and then decreased to 153.7 in 2006, a net decline of 12% and 6% from the 1991 and 1970 rates, respectively. These decreases since 1990/91 translate to preventing of 561,400 cancer deaths in men and 205,700 deaths in women. The decrease in death rates from all-cancers involved all ages and racial/ethnic groups. Death rates decreased for 15 of the 19 cancer sites, including the four major cancers, with lung, colorectum and prostate cancers in men and breast and colorectum cancers in women.Conclusions/SignificanceProgress in reducing cancer death rates is evident whether measured against baseline rates in 1970 or in 1990. The downturn in cancer death rates since 1990 result mostly from reductions in tobacco use, increased screening allowing early detection of several cancers, and modest to large improvements in treatment for specific cancers. Continued and increased investment in cancer prevention and control, access to high quality health care, and research could accelerate this progress.

Mortality from lung cancer (ICD-10 C33-C34 equivalent to ICD-9 162). To reduce deaths from lung cancer. Legacy unique identifier: P00508

Two datasets that explore causes of death due to cancer in South Africa, drawing on data from the Revised Burden of Disease estimates for the Comparative Risk Factor Assessment for South Africa, 2000.

The number and percentage of deaths due to cancer by cause are ranked for persons, males and females in the tables below.

Lung cancer is the leading cause of cancer in SA accounting for 17% of all cancer deaths. This is followed by oesophagus Ca which accounts for 13%, cervix cancer accounting for 8%, breast cancer accounting for 8% and liver cancer which accounts for 6% of all cancers. Many more males suffer from lung and oesophagus cancer than females.