Lung cancer is the deadliest cancer worldwide, accounting for 1.82 million deaths in 2022. The second most deadly form of cancer is colorectum cancer, followed by liver cancer. However, lung cancer is only the sixth leading cause of death worldwide, with heart disease and stroke accounting for the highest share of deaths. Male vs. female cases Given that lung cancer causes the highest number of cancer deaths worldwide, it may be unsurprising to learn that lung cancer is the most common form of new cancer cases among males. However, among females, breast cancer is by far the most common form of new cancer cases. In fact, breast cancer is the most prevalent cancer worldwide, followed by prostate cancer. Prostate cancer is a very close second to lung cancer among the cancers with the highest rates of new cases among men. Male vs. female deaths Lung cancer is by far the deadliest form of cancer among males but is the second deadliest form of cancer among females. Breast cancer, the most prevalent form of cancer among females worldwide, is also the deadliest form of cancer among females. Although prostate cancer is the second most prevalent cancer among men, it is the fifth deadliest cancer. Lung, liver, stomach, colorectum, and oesophagus cancers all have higher deaths rates among males.

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.

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

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.

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.

Introduction

Cancer Statistics: Cancer continues to be a major global health challenge, with significant increases in both incidence and mortality. In 2022, there were an estimated 20 million new cancer cases and 9.7 million cancer-related deaths worldwide. The most common cancers included lung, breast, colorectal, prostate, and stomach cancers. The global cancer burden is projected to rise substantially, with estimates suggesting 35.3 million new cases and 18.5 million cancer-related deaths by 2050.

This increase is attributed to factors such as population growth, aging, and exposure to risk factors like tobacco use, obesity, and environmental pollutants. The economic impact of cancer is also profound, with direct medical costs in the United States alone reaching nearly $209 billion in 2020.

These statistics underscore the urgent need for enhanced prevention, early detection, and treatment strategies to address the growing cancer burden globally. The information is presented from a market researcher's point of view, incorporating the latest data and trends.

In 2023, it was estimated that there would be **** deaths per 100,000 population due to kidney cancer in Canada. Cancer is one of the leading causes of premature death in Canada. This statistic shows the estimated age-standardized mortality rates for cancer in Canada by cancer type, as of 2023.

Age-standardised rate of mortality from oral cancer (ICD-10 codes C00-C14) in persons of all ages and sexes per 100,000 population.RationaleOver the last decade in the UK (between 2003-2005 and 2012-2014), oral cancer mortality rates have increased by 20% for males and 19% for females1Five year survival rates are 56%. Most oral cancers are triggered by tobacco and alcohol, which together account for 75% of cases2. Cigarette smoking is associated with an increased risk of the more common forms of oral cancer. The risk among cigarette smokers is estimated to be 10 times that for non-smokers. More intense use of tobacco increases the risk, while ceasing to smoke for 10 years or more reduces it to almost the same as that of non-smokers3. Oral cancer mortality rates can be used in conjunction with registration data to inform service planning as well as comparing survival rates across areas of England to assess the impact of public health prevention policies such as smoking cessation.References:(1) Cancer Research Campaign. Cancer Statistics: Oral – UK. London: CRC, 2000.(2) Blot WJ, McLaughlin JK, Winn DM et al. Smoking and drinking in relation to oral and pharyngeal cancer. Cancer Res 1988; 48: 3282-7. (3) La Vecchia C, Tavani A, Franceschi S et al. Epidemiology and prevention of oral cancer. Oral Oncology 1997; 33: 302-12.Definition of numeratorAll cancer mortality for lip, oral cavity and pharynx (ICD-10 C00-C14) in the respective calendar years aggregated into quinary age bands (0-4, 5-9,…, 85-89, 90+). This does not include secondary cancers or recurrences. Data are reported according to the calendar year in which the cancer was diagnosed.Counts of deaths for years up to and including 2019 have been adjusted where needed to take account of the MUSE ICD-10 coding change introduced in 2020. Detailed guidance on the MUSE implementation is available at: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/articles/causeofdeathcodinginmortalitystatisticssoftwarechanges/january2020Counts of deaths for years up to and including 2013 have been double adjusted by applying comparability ratios from both the IRIS coding change and the MUSE coding change where needed to take account of both the MUSE ICD-10 coding change and the IRIS ICD-10 coding change introduced in 2014. The detailed guidance on the IRIS implementation is available at: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/impactoftheimplementationofirissoftwareforicd10causeofdeathcodingonmortalitystatisticsenglandandwales/2014-08-08Counts of deaths for years up to and including 2010 have been triple adjusted by applying comparability ratios from the 2011 coding change, the IRIS coding change and the MUSE coding change where needed to take account of the MUSE ICD-10 coding change, the IRIS ICD-10 coding change and the ICD-10 coding change introduced in 2011. The detailed guidance on the 2011 implementation is available at https://webarchive.nationalarchives.gov.uk/ukgwa/20160108084125/http://www.ons.gov.uk/ons/guide-method/classifications/international-standard-classifications/icd-10-for-mortality/comparability-ratios/index.htmlDefinition of denominatorPopulation-years (aggregated populations for the three years) for people of all ages, aggregated into quinary age bands (0-4, 5-9, …, 85-89, 90+)

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

The graph illustrates the number of deaths from cancer in the United States over the period from 1999 to 2022. The x-axis represents the years, labeled with two-digit abbreviations from '99 to '22, while the y-axis displays the annual number of cancer-related deaths. Throughout this 24-year span, the number of deaths ranges from a minimum of 549,829 in 1999 to a maximum of 608,366 in 2022. The data shows a gradual increase in annual deaths over the years. Notably, the number surpassed 550,000 in 2000 with 553,080 deaths, reached 574,738 in 2010, and exceeded 600,000 in 2020 with 602,347 deaths. The figures continued to rise, culminating in the highest recorded number of 608,366 deaths in 2022.

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.

ABSTRACT OBJECTIVE To analyze inequalities in incidence, mortality, and estimated survival for neoplasms in men according to social vulnerability. METHODS Analysis of cases and deaths of all neoplasms and the five most common in men aged 30 years or older in the city of Campinas (SP), between 2010 and 2014, using data from the Population-Based Cancer Registry (RCBP) and the Mortality Information System (SIM). The areas of residence were grouped into five social vulnerability strata (SVS) using São Paulo Social Vulnerability Index. For each SVS, age-standardized incidence and mortality rates were calculated. A five-year survival proxy was calculated by complementing the ratio of the mortality rate to the incidence rate. Inequalities between strata were measured by the ratios between rates, the relative inequality index (RII) and the angular inequality index (AII). RESULTS RII revealed that the incidence of all neoplasms (0.66, 95%CI 0.62–0.69) and colorectal and lung cancers were lower among the most socially vulnerable, who presented a higher incidence of stomach and oral cavity cancer. Mortality rates for stomach, oral cavity, prostate and all types of cancer were higher in the most vulnerable segments, with no differences in mortality for colorectal and lung cancer. Survival was lower in the most social vulnerable stratum for all types of cancer studied. AII showed excess cases in the least vulnerable and deaths in the most vulnerable. Social inequalities were different depending on the tumor location and the indicator analyzed. CONCLUSION There is a trend of reversal of inequalities between incidence-mortality and incidence-survival, and the most social vulnerable segment presents lower survival rates for the types of cancer, pointing to the existence of inequality in access to early diagnosis and effective and timely treatment.

In 2018, Croatia reported **** cancer deaths from colorectal cancer per 100,000 population, the highest mortality rate of colorectal cancer in Europe. In the same year, Croatia reported also to have the highest mortality rate of breast cancer (females only) with **** deaths per 100,000 population, while Estonia reported to have the highest mortality rate of prostate cancer with **** deaths per 100,000 population. This statistic shows the mortality rates of selected types of cancers in European countries in 2018.

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.

Mortality from lung cancer, 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 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. Lung cancer accounts for 7% of all deaths among men and in England every year and 4% of deaths among women every year. This amounts to 24% of all cancer deaths among men in England and 18% of all cancer deaths among women in England1. 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 2008/09-2010/111. This indicator has been produced in order to quantify inequalities in lung cancer mortality by deprivation. This indicator has been discontinued and so there will be no further updates. Legacy unique identifier: P01406

In 2010, cancer deaths accounted for more than 15% of all deaths worldwide, and this fraction is estimated to rise in the coming years. Increased cancer mortality has been observed in immigrant populations, but a comprehensive analysis by country of birth has not been conducted. We followed all individuals living in Sweden between 1961 and 2009 (7,109,327 men and 6,958,714 women), and calculated crude cancer mortality rates and age-standardized rates (ASRs) using the world population for standardization. We observed a downward trend in all-site ASRs over the past two decades in men regardless of country of birth but no such trend was found in women. All-site cancer mortality increased with decreasing levels of education regardless of sex and country of birth (p for trend <0.001). We also compared cancer mortality rates among foreign-born (13.9%) and Sweden-born (86.1%) individuals and determined the effect of education level and sex estimated by mortality rate ratios (MRRs) using multivariable Poisson regression. All-site cancer mortality was slightly higher among foreign-born than Sweden-born men (MRR = 1.05, 95% confidence interval 1.04–1.07), but similar mortality risks was found among foreign-born and Sweden-born women. Men born in Angola, Laos, and Cambodia had the highest cancer mortality risk. Women born in all countries except Iceland, Denmark, and Mexico had a similar or smaller risk than women born in Sweden. Cancer-specific mortality analysis showed an increased risk for cervical and lung cancer in both sexes but a decreased risk for colon, breast, and prostate cancer mortality among foreign-born compared with Sweden-born individuals. Further studies are required to fully understand the causes of the observed inequalities in mortality across levels of education and countries of birth.

BackgroundThe 5-year survival rate of cancer patients is the most commonly used statistic to reflect improvements in the war against cancer. This idea, however, was refuted based on an analysis showing that changes in 5-year survival over time bear no relationship with changes in cancer mortality.MethodsHere we show that progress in the fight against cancer can be evaluated by analyzing the association between 5-year survival rates and mortality rates normalized by the incidence (mortality over incidence, MOI). Changes in mortality rates are caused by improved clinical management as well as changing incidence rates, and since the latter can mask the effects of the former, it can also mask the correlation between survival and mortality rates. However, MOI is a more robust quantity and reflects improvements in cancer outcomes by overcoming the masking effect of changing incidence rates. Using population-based statistics for the US and the European Nordic countries, we determined the association of changes in 5-year survival rates and MOI.ResultsWe observed a strong correlation between changes in 5-year survival rates of cancer patients and changes in the MOI for all the countries tested. This finding demonstrates that there is no reason to assume that the improvements in 5-year survival rates are artificial. We obtained consistent results when examining the subset of cancer types whose incidence did not increase, suggesting that over-diagnosis does not obscure the results.ConclusionsWe have demonstrated, via the negative correlation between changes in 5-year survival rates and changes in MOI, that increases in 5-year survival rates reflect real improvements over time made in the clinical management of cancer. Furthermore, we found that increases in 5-year survival rates are not predominantly artificial byproducts of lead-time bias, as implied in the literature. The survival measure alone can therefore be used for a rough approximation of the amount of progress in the clinical management of cancer, but should ideally be used with other measures.

Cervical cancer (CC) is a public health problem with a high disease burden and mortality in developing countries. In Brazil, areas with low human development index have the highest incidence rates of Brazil and upward temporal trend for this disease. The Northeast region has the second highest incidence of cervical cancer (20.47 new cases / 100,000 women). In this region, the mortality rates are similar to rates in countries that do not have a health system with a universal access screening program, as in Brazil. Thus, this study aimed to analyze the effects of age, period and birth cohorts on mortality from cervical cancer in the Northeast region of Brazil. Estimable functions predicted the effects of age, period and birth cohort. The average mortality rate was 10.35 deaths per 100,000 women during the period analyzed (1980–2014). The highest mortality rate per 100,000 women was observed in Maranhão (24.39 deaths), and the lowest mortality rate was observed in Bahia (11.24 deaths). According to the period effects, only the state of Rio Grande do Norte showed a reduction in mortality risk in the five years of the 2000s. There was a reduction in mortality risk for birth cohorts of women after the 1950s, except in Maranhão State, which showed an increasing trend in mortality risk for younger generations. We found that the high rates of cervical cancer mortality in the states of northeastern Brazil remain constant over time. Even after an increase in access to health services in the 2000s, associated with increased access to the cancer care network, which includes early detection (Pap Test), cervical cancer treatment and palliative care. However, it is important to note that the decreased risk of death and the mortality rates from CC among women born after the 1960s may be correlated with increased screening coverage, as well as increased access to health services for cancer treatment observed in younger women.

BackgroundThis population-based study investigated the relationship between individual and neighborhood socioeconomic status (SES) and mortality rates for major cancers in Taiwan. MethodsA population-based follow-up study was conducted with 20,488 cancer patients diagnosed in 2002. Each patient was traced to death or for 5 years. The individual income-related insurance payment amount was used as a proxy measure of individual SES for patients. Neighborhood SES was defined by income, and neighborhoods were grouped as living in advantaged or disadvantaged areas. The Cox proportional hazards model was used to compare the death-free survival rates between the different SES groups after adjusting for possible confounding and risk factors. ResultsAfter adjusting for patient characteristics (age, gender, Charlson Comorbidity Index Score, urbanization, and area of residence), tumor extent, treatment modalities (operation and adjuvant therapy), and hospital characteristics (ownership and teaching level), colorectal cancer, and head and neck cancer patients under 65 years old with low individual SES in disadvantaged neighborhoods conferred a 1.5 to 2-fold higher risk of mortality, compared with patients with high individual SES in advantaged neighborhoods. A cross-level interaction effect was found in lung cancer and breast cancer. Lung cancer and breast cancer patients less than 65 years old with low SES in advantaged neighborhoods carried the highest risk of mortality. Prostate cancer patients aged 65 and above with low SES in disadvantaged neighborhoods incurred the highest risk of mortality. There was no association between SES and mortality for cervical cancer and pancreatic cancer. ConclusionsOur findings indicate that cancer patients with low individual SES have the highest risk of mortality even under a universal health-care system. Public health strategies and welfare policies must continue to focus on this vulnerable group.

ObjectiveObesity-related health burdens have emerged as particularly intractable public health issues on a global scale. This study aims to analyze the association between body mass index (BMI) and 12 types of cancer, examine the regional, gender, and age disparities in cancer burden attributable to high BMI, and project the disease burden trends over the next decade based on available data.MethodsData for this study were sourced from the Integrative Epidemiology Unit (IEU) Open Genome-Wide Association Study (GWAS) Project and the 2021 Global Burden of Disease (GBD) database. Using Mendelian randomization (MR), we investigated the association between BMI and 12 cancer types. We also collected and analyzed epidemiological data on cancers attributable to high BMI, calculated the estimated annual percentage change (EAPC) across 21 regions, and examined disparities in mortality and disability-adjusted life years (DALYs) by age, sex, and cancer type. Finally, we used the autoregressive integrated moving average (ARIMA) model to predict trends in various cancers attributable to high BMI over the next 10 years.ResultsIn 2021, high BMI accounted for 356,738 cancer deaths worldwide and 8,894,525 DALYs, representing an increase of 160% in deaths and 151% in DALYs compared to 1990 (which recorded 137,353 deaths and 3,549,049 DALYs). Among the cancers attributable to high BMI, colon and rectal cancer accounted for the highest disease burden, while thyroid cancer accounted for the lowest proportion of disease burden. Gender-stratified analysis revealed a notably higher disease burden among women compared to men. An age-specific assessment revealed a disproportionately higher disease burden in the 50–79 age cohort. Additionally, both the age-standardized mortality rate (ASMR) and age-standardized disability rate (ASDR) showed positive correlations with the Socio-demographic Index (SDI). Finally, projections from the ARIMA model indicate that over the next decade, the ASMR for most cancers attributable to high-BMI will remain stable or increase, except for colon, rectal, and uterine cancers. The MR analysis indicated a causal relationship between BMI and 11 cancer types (colon and rectal cancer, liver cancer, gallbladder and biliary tract cancer, pancreatic cancer, breast cancer, uterine cancer, ovarian cancer, kidney cancer, lymphoma, multiple myeloma, and leukemia), while no causal association was found between BMI and thyroid cancer.ConclusionMendelian randomization analysis indicated a notable association between elevated BMI and an increased risk of 11 cancer types. Over the past three decades, the cancer burden attributable to high BMI has demonstrated a marked increasing trend, with notable variations observed across geographic regions, gender groups, and age categories regarding predominant cancer types. These findings underscore the need to develop targeted prevention strategies and health promotion interventions that are tailored to specific demographic and regional profiles.