In the period 2018 to 2022, a total of approximately *** men per 100,000 inhabitants died of cancers of all kinds in the United States, compared to an overall cancer death rate of *** per 100,000 population among women. This statistic shows cancer death rates in the U.S. for the period from 2018 to 2022, by type and gender.

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.

Breast cancer was the cancer type with the highest rate of death among females worldwide in 2022. That year, there were around 13 deaths from breast cancer among females per 100,000 population. The death rate for all cancers among females was 76.4 per 100,000 population. This statistic displays the rate of cancer deaths among females worldwide in 2022, by type of cancer.

Cancer survival statistics are typically expressed as the proportion of patients alive at some point subsequent to the diagnosis of their cancer. Statistics compare the survival of patients diagnosed with cancer with the survival of people in the general population who are the same age, race, and sex and who have not been diagnosed with cancer.

This dataset contains estimates for 29 cancer-specific age-standardized mortality rates for specific cancer types at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014 (quinquennial), as well as the changes in rates during this period.

Lung cancer was the cancer type with the highest rate of death among males worldwide in 2022. In that year there were around 25 deaths from trachea, bronchus and lung cancer among males per 100,000 population. The death rate for all cancers among males was 109 per 100,000 population. This statistic shows the rate of cancer deaths among males worldwide in 2022, by type of cancer.

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

This data provides high-level data on historical registrations (or cases) and deaths, including information about the cancer types and breakdowns by gender variables.

Mortality from all cancers, directly age-standardised rate, persons, under 75 years, 2004-08 (pooled) per 100,000 European Standard population by Local Authority by local deprivation quintile. Local deprivation quintiles are calculated by ranking small areas (Lower Level Super Output Areas (LSOAs)) within each Local Authority based on their Index of Multiple Deprivation 2007 (IMD 2007) deprivation score, and then grouping the LSOAs in each Local Authority into five groups (quintiles) with approximately equal numbers of LSOAs in each. The upper local deprivation quintile (Quintile 1) corresponds with the 20% most deprived small areas within that Local Authority. The mortality rates have been directly age-standardised using the European Standard Population in order to make allowances for differences in the age structure of populations. There are inequalities in health. For example, people living in more deprived areas tend to have shorter life expectancy, and higher prevalence and mortality rates of most cancers. Cancer accounts for nearly 30% of all deaths among men in England every year and nearly 25% of deaths among women every year1. Reducing inequalities in premature mortality from all cancers is a national priority, as set out in the Department of Health’s Vital Signs Operating Framework 2008/09-2010/112 and the PSA Delivery Agreement 183. However, existing indicators for premature cancer mortality do not take deprivation into account. This indicator has been produced in order to quantify inequalities in cancer mortality by deprivation. This indicator has been discontinued and so there will be no further updates. Legacy unique identifier: P01368

The cancer type with the highest age-standardized mortality rate in Latin America and the Caribbean in 2022 was prostate cancer with 13.9 deaths per 100,000 population. Breast cancer ranked second, with a mortality rate of 13.2 people per 100,000 population. In that year, breast cancer was the cancer type with the highest prevalence in the region.

This data package contains information on cancer its type, its occurrence by age, type and site. It also provides detailed data on adult and childhood cancer survival rates and deaths caused by breast cancer in females.

Variables included in the best fitted models for different types of cancer morbidity; main variables are denoted as age (a), year (t), gender (g), region (r), deprivation (d), with corresponding interactions shown as, e.g., a:t.

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.

AbstractIn Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009–2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies. Methods For a given locality, year, and cause of death, the SMR is the ratio between the observed number of deaths (Om) and the number of expected deaths (Em): SMR = Om/Em (1) where Om should be an available observational data and Em is estimated as the weighted sum of age-specific population size for the given locality (ni) per age-specific death rates of the reference population (MRi): Em = sum(MRi x ni) (2) MRi could be provided by a public health organization or be estimated as the ratio between the age-specific number of deaths of reference population (Mi) to the age-specific reference population size (Ni): MRi = Mi/Ni (3) Thus, the value of Em is weighted by the age distribution of deaths and population size. SMR assumes value 1 when the number of observed and expected deaths are equal. Following eqns. (1-3), the SMR was computed for single years of the period 2009-2018 and for single cause of death as defined by the International ICD-10 classification system by using the following data: age-specific number of deaths by cause of reference population (i.e., Mi) from the Italian National Institute of Statistics (ISTAT, (http://www.istat.it/en/, last access: 26/01/2022)); age-specific census data on reference population (i.e., Ni) from ISTAT; the observed number of deaths by cause (i.e., Om) from ISTAT; the age-specific census data on population (ni); the SMR was estimated at three different level of aggregation: municipal, provincial (equivalent to the European classification NUTS 3) and regional (i.e., NUTS2). The SMR was also computed for the broad category of malignant tumors (i.e. C00-C979, hereinafter cancer macro-type C), and for the broad category of malignant tumor plus non-malignant tumors (i.e. C00-C979 plus D0-D489, hereinafter cancer macro-type CD). Lower 90% and 95% confidence intervals of 10-year average values were computed according to the Byar method.

Absolute deprivation differences (ADt,r), per 100,000 people, in age-standardised fitted mortality rates in 2001 and 2016 for all regions in England and both genders; 95% credible intervals in brackets.

The German Centre for Cancer Registry Data (ZfKD) provides the topical cancer statistics for Germany. In an interactive database query you will get information on incidence and mortality rates as well as for prevalence and survival rates for different types of cancer.

Overall-temporal-changes (ACd,r, per 100,000 people) from 2001 to 2016, in age-standardised fitted mortality rates for deprivation levels 1 and 10 and all regions in England for both genders; 95% credible intervals in brackets.

Introduction

Breast Cancer Statistics: Breast cancer remains one of the most prevalent and concerning health challenges, mostly among women. It is the most common cancer diagnosed in women worldwide and the second leading cause of cancer-related deaths among women in the United States. The impact of breast cancer is significant, with millions of new cases diagnosed each year and hundreds of thousands of deaths attributed to the disease.

This article will provide critical insights into the incidence, survival rates, mortality, and disparities across different demographics, including age, race, and ethnicity. Understanding the latest statistics on breast cancer is crucial for driving progress in reducing the incidence and mortality rates, improving survival outcomes, and ultimately, finding a cure.

This report includes cancer statistics for all cancer sites combined (all-site cancer), as well as eight specific cancer types. These cancer statistics reflect mortality data for 2008-2012.

Mortality from lung cancer (ICD-10 C33-C34 equivalent to ICD-9 162). To reduce deaths from lung cancer. Legacy unique identifier: P00516