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

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

About this dataset

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

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

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

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

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

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

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

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

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

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

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

How to use this dataset

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

Acknowledgements

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

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

The number of new cases, age-standardized rates and average age at diagnosis of cancers diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Cancer incidence rates are age-standardized using the direct method and the final 2011 Canadian postcensal population structure. Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

Users can access data about cancer incidence and mortality for all the countries of the world as of 2008. Background GloboCan is a project of the International Agency for Research on Cancer and the World Health Organization (WHO). GloboCan presents estimates of the burden of cancer in 184 countries or territories around the world. User functionality GloboCan provides access to the most recent estimates (from 2008) of the incidence and mortality of 27 major cancers. Users can create fact sheets or do online analysis to create tables, graphs, maps, and predictions. Users c an choose to create tables by population or by cancer type. Covariates for analysis include age group, sex, and continent. Users are able to choose between mortality and incidence statistics. Users can choose to create age specific cancer curves, bar charts, maps, and pie charts. The prediction option allows the user to estimate the future burden of a selected cancer in selected population for a selected year. Data Notes Data sources and methods are clearly outlined on the “Data Sources and Methods” section of the website. Users are able to download their online analysis in PDF or html format. GloboCan uses the definitions outlined in the United Nations, World Population Prospects, 2008 revision (except Cyprus located in Southern Europe and Taiwan is located in Eastern Asia).

The PRAIM study (PRospective multicenter observational study of an integrated AI system with live Monitoring) assessed the impact of an AI-based decision support software on breast cancer screening outcomes. This Dryad data package contains the anonymized data from 461 818 screening cases across 12 screening sites in Germany. Variables include screening outcomes like cancer detection, use of AI software, radiologist assessments, cancer characteristics, and further metadata. The data can be used to reproduce the analyses on performance of AI-supported breast cancer screening versus standard of care published in Nature Medicine: Nationwide real-world implementation of AI for cancer detection in population-based mammography screening., , , # Nationwide real-world implementation of AI for cancer detection in population-based mammography screening (PRAIM) – Dataset

The PRAIM study (PRospective multicenter observational study of an integrated Artificial Intelligence system with live Monitoring) was a study conducted within the German breast cancer screening program from July 2021 to February 2023 to assess the impact of an AI-based decision support software. This dataset contains the data from PRAIM.

Context

The PRAIM study has been published in Nature Medicine. Please refer to the article Nationwide real-world implementation of AI for cancer detection in population-based mammography screening for further information on study design, results, and discussion of impact. The study has been previously registered in the German Clinical Trials Register and the study protocol can be found on the [website of the Univ...

Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').

Lung Cancer Diagnostic Tests Market Outlook

The lung cancer diagnostic tests market size was valued at USD 2.5 billion in 2023 and is projected to reach USD 6.1 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 10.5% during the forecast period. This substantial growth can be attributed to the rising prevalence of lung cancer globally, advancements in diagnostic technologies, and increasing awareness regarding early detection and treatment of lung cancer. The growing aging population and the high incidence of smoking, which is a leading cause of lung cancer, further propel the demand for diagnostic tests.

The increasing prevalence of lung cancer is one of the primary drivers of market growth. Lung cancer remains the leading cause of cancer-related deaths worldwide, necessitating the development of more accurate and early diagnostic methods. With advancements in medical technology, such as molecular diagnostics and non-invasive imaging techniques, the accuracy and efficiency of lung cancer diagnosis have significantly improved. These innovations not only enhance the detection rate but also facilitate personalized treatment plans, thereby improving patient outcomes.

Furthermore, government initiatives and funding for cancer research play a crucial role in market expansion. Many countries are investing heavily in cancer research, leading to the development of new diagnostic tools and techniques. For instance, organizations such as the National Cancer Institute (NCI) in the United States provide substantial grants for lung cancer research, fostering innovations in diagnostics. In addition, public awareness campaigns and screening programs conducted by healthcare organizations and governments encourage early diagnosis, which is vital for successful treatment and survival rates.

The integration of artificial intelligence (AI) and machine learning in diagnostic tools is another significant factor contributing to market growth. AI algorithms can analyze medical images with high precision, aiding radiologists in identifying lung cancer at earlier stages. Moreover, AI-driven software can evaluate large datasets from genetic and molecular tests, providing insights into the most effective treatment options based on individual patient profiles. This technological advancement not only enhances the accuracy of diagnostics but also reduces the time required for analysis, thereby increasing the efficiency of healthcare services.

The EGFR Mutation Test is a pivotal advancement in the realm of lung cancer diagnostics, offering a more personalized approach to treatment. This test specifically identifies mutations in the Epidermal Growth Factor Receptor (EGFR) gene, which are often present in non-small cell lung cancer (NSCLC) patients. By detecting these mutations, healthcare providers can tailor therapies that target the specific genetic alterations, thereby improving treatment efficacy and patient outcomes. The growing adoption of EGFR Mutation Tests underscores the shift towards precision medicine, where treatments are increasingly customized based on individual genetic profiles. This approach not only enhances the effectiveness of therapies but also minimizes adverse effects, as treatments are more accurately aligned with the patient's unique genetic makeup.

Regionally, North America holds the largest share of the lung cancer diagnostic tests market, followed by Europe and Asia Pacific. The dominance of North America can be attributed to the presence of advanced healthcare infrastructure, high healthcare expenditure, and a robust research landscape. The Asia Pacific region, however, is expected to witness the highest growth rate during the forecast period, driven by increasing healthcare investments, growing awareness about lung cancer, and rising incidences of the disease in countries like China and India. The growing middle-class population and improving healthcare access in these countries further support market growth.

Test Type Analysis

The lung cancer diagnostic tests market is segmented by test type into imaging tests, sputum cytology, tissue biopsy, molecular tests, and others. Imaging tests are one of the most commonly used diagnostic methods for lung cancer detection. Techniques such as X-rays, CT scans, and PET scans provide detailed visuals of the lungs, helping in identifying abnormal growths or tumors. The non-invasive nature of these tests and their ability to provide quick results make them a preferred choice among healthcare

Snapshot img

Cancer Registry Software Market Size 2025-2029

The cancer registry software market size is forecast to increase by USD 121.9 million, at a CAGR of 14% between 2024 and 2029.

The market is witnessing significant growth, driven by the increasing prevalence of cancer cases and the rising demand for accurate and comprehensive data for clinical research in oncology. The growing number of cancer diagnoses worldwide necessitates advanced solutions for managing and analyzing patient data, fueling market expansion. Furthermore, the importance of data privacy and security in the healthcare sector poses a challenge for market participants. Ensuring the confidentiality and protection of sensitive patient information is crucial to maintain trust and regulatory compliance.
Companies in this market must navigate these challenges while continuing to innovate and deliver solutions that address the evolving needs of healthcare providers and researchers. By focusing on data security and privacy, as well as integrating advanced analytics capabilities, market participants can capitalize on the opportunities presented by the growing demand for cancer registry software.

What will be the Size of the Cancer Registry Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by advancements in technology and the increasing demand for efficient and accurate cancer data management. Cloud computing plays a significant role in the market's dynamics, enabling remote access to data and reducing the need for on-premise infrastructure. Technical support, audit trails, and cancer surveillance are integral components of these solutions, ensuring data security and regulatory compliance. Data warehousing and business intelligence capabilities enable data cleansing, data validation, and data analysis, leading to improved data quality and clinical insights. User experience and customizable reports cater to diverse user needs, while machine learning and artificial intelligence facilitate predictive modeling and statistical analysis.

Healthcare regulations mandate stringent data governance and access control, making data security a top priority. Case management and healthcare IT integration streamline workflows and facilitate data exchange between various stakeholders. Database management and reporting features provide real-time data visualization and decision support, enhancing operational efficiency. Data migration and software updates ensure seamless integration with existing systems, while data validation and data entry tools maintain data accuracy. Tumor registry solutions enable comprehensive cancer surveillance and population health management, contributing to public health initiatives. The market's continuous dynamism reflects the ongoing integration of various technologies and the evolving needs of healthcare providers and regulatory bodies.

How is this Cancer Registry Software Industry segmented?

The cancer registry software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Government and third party
  Pharma biotech and medical device companies
  Hospitals and medical practice
  Private payers
  Research institutes


Type

  Stand-alone software
  Integrated software


Deployment

  On-premises
  Cloud-based


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    Spain
    UK


  APAC

    China
    Japan


  Rest of World (ROW)

By End-user Insights

The government and third party segment is estimated to witness significant growth during the forecast period.

Cancer registry software plays a vital role in assisting government and third-party agencies in managing and analyzing data related to cancer cases. These solutions enable the collection, storage, and processing of patient data, clinical information, and statistical analysis. The integration of business intelligence and data warehousing facilitates data mining, trend analysis, and pattern recognition, which is essential for public health planning and resource allocation. Machine learning and artificial intelligence technologies enhance the capabilities of cancer registry software by automating data entry, improving data accuracy, and enabling predictive modeling. User-friendly interfaces, customizable reports, and decision support systems cater to the needs of healthcare IT professionals, medical informatics specialists, and other stakeholders.

Database management, workflow management, and access control ensure data security and privacy, while data governance and da

BackgroundNASH-associated liver cancer (NALC) is a significant contributor to global cancer mortality, closely linked to the increasing prevalence of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). This study comprehensively examines the global burden of NALC from 1990 to 2021.MethodsThis study used data from the Global Burden of Disease (GBD) 2021 database to analyze NALC death and age-standardized death rates (ASDR) globally and regionally from 1990 to 2021. We applied Joinpoint regression analysis to assess temporal trends, calculating the annual percent change (APC) and average annual percent change (AAPC). Decomposition analysis was performed to break down mortality changes into contributions from population aging, growth, and epidemiological changes. A frontier analysis was used to evaluate the relationship between NALC burden and sociodemographic development using the Socio-Demographic Index (SDI). Prediction analysis of NALC deaths and ASDR from 2021 to 2045 were estimated using the Nordpred model.ResultsFrom 1990 to 2021, the global burden of NALC deaths increased significantly, with the ASDR rising from 0.38 per 100,000 in 1990 to 0.48 per 100,000 in 2021. Age-specific data in 2021 revealed that NALC deaths peaked in the 65–69 age group for men and 70–74 age group for women. Decomposition analysis indicated that population growth was the most significant contributor to the global NALC death toll, followed by population aging and epidemiological changes. Frontier analysis showed that countries like Mongolia and Gambia were farthest from the disease burden frontier, while Morocco and Ukraine were closest. Prediction analysis suggest a significant increase in NALC deaths by 2045 compared to 2021, with a larger rise in deaths among women.ConclusionThrough this study, a data-driven approach is provided to reduce the global disease burden of NALC. Essential data support for public health prevention strategies is offered, helping guide the development of targeted government interventions. Trends across global regions, countries, age groups, and genders have been analyzed, providing valuable insights for the formulation of evidence-based policies aimed at mitigating the impact of NALC worldwide.

Cancer is a global health problem and one of the leading causes of human death. According to the data released by the International Agency for Research on Cancer (IARC) in 2022, there were 19.3 million new cancer cases and nearly 10 million cancer deaths worldwide in 2020. At the same time, with rising morbidity and mortality, cancer has become the leading cause of death and a major public health problem for the Chinese population. China ranked first in the world in the number of new cancer cases and deaths in 2020. Camptothecin (CPT) , which has extensive antitumor activity, is a natural pentacyclic monoterpene alkaloid isolated from Camptotheca acuminata by Wall and Wani in 1966. In the 1970s, CPT was clinically approved to treat stomach cancer, bladder cancer, and certain types of leukemia. Camptothecin, as a natural drug candidate parent nucleus, has developed so far, and a large number of derivatives have been derived. The CDAD database integrates the latest laboratory data on the inhibition of cancer cells by camptothecin derivatives, as well as the anti-cancer data of camptothecin derivatives in the previously published literature. Each entry contains detailed information about the camptothecin derivatives, such as SMILE, molecular weight, IUPAC designation, median inhibition concentration (IC50), duration of action, target and related literature and patents, etc. This data will contribute to the further development of camptothecin derivatives and promote the anticancer research of camptothecin derivatives.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: per 100,000 Population data was reported at 13.800 Ratio in 2016. United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: per 100,000 Population data is updated yearly, averaging 13.800 Ratio from Dec 2016 (Median) to 2016, with 1 observations. United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Health Statistics. Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Abstract

Purpose: The multi-country Study on Global Ageing and Adult Health (SAGE) is run by the World Health Organization's Multi-Country Studies unit in the Innovation, Information, Evidence and Research Cluster. SAGE is part of the unit's Longitudinal Study Programme which is compiling longitudinal data on the health and well-being of adult populations, and the ageing process, through primary data collection and secondary data analysis. SAGE baseline data (Wave 0, 2002/3) was collected as part of WHO's World Health Survey http://www.who.int/healthinfo/survey/en/index.html (WHS). SAGE Wave 1 (2007/10) provides a comprehensive data set on the health and well-being of adults in six low and middle-income countries: China, Ghana, India, Mexico, Russian Federation and South Africa. Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults Methods: SAGE's first full round of data collection included both follow-up and new respondents in most participating countries. The goal of the sampling design was to obtain a nationally representative cohort of persons aged 50 years and older, with a smaller cohort of persons aged 18 to 49 for comparison purposes. In the older households, all persons aged 50+ years (for example, spouses and siblings) were invited to participate. Proxy respondents were identified for respondents who were unable to respond for themselves. Standardized SAGE survey instruments were used in all countries consisting of five main parts: 1) household questionnaire; 2) individual questionnaire; 3) proxy questionnaire; 4) verbal autopsy questionnaire; and, 5) appendices including showcards. A VAQ was completed for deaths in the household over the last 24 months. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey. Content Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 8000 Impact of Caregiving 9000 Interviewer Assessment

Geographic coverage

National coverage

Analysis unit

households and individuals

Universe

The household section of the survey covered all households in all nine provinces in South Africa. Institutionalised populations are excluded. The individual section covered all persons aged 18 years and older residing within individual households. As the focus of SAGE is older adults, a much larger sample of respondents aged 50 years and older were selected with a smaller comparative sample of respondents aged 18-49 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

South Africa used a stratified multistage cluster sample design. Strata were defined by the nine provinces:(Eastern Cape, Free State, Gauteng, Kwa-Zulu Natal, Limpopo, Mpumalanga, North West, Northern Cape and Western Cape), locality (urban or rural), and predominant race group (African/Black, White, Coloured and Indian/Asian), as not all combinations of stratification variables were possible, there were 50 strata in total. The Human Science Research Council's master sample was used as the sampling frame which comprised 1000EAs. A sample of 600 EAs was selected as the primary sampling units(PSU). The number of EAs to be selected from each strata was based on proportional allocation (determined by the number of EAs in each strataspecified on the Master Sample). EAs were then selected from each strata with probability proportional to size; the measure of size being the number of individuals aged 50 years or more in the EA. In each selected EA 30 households were randomly selected from the Master Sample. A listing of the 30 selected households was conducted to classify each household into one of two mutually exclusive categories: (1) households with one or more members aged 50 years or more (defined as '50 plus households'); (2) households which did not include any members aged 50 years or more, but included residents aged 18-49 (defined as '18-49 households'). All 50 plus households were eligible for the household interview, and all 50 plus members of the household were eligible for the individual interview. Two of the remaining 18-49 households were randomly selected for the household interview. In each of these household one person aged 18-49 was eligible for the individual interview, and the individual to be included was selected using a Kish Grid.

Stages of selection Strata: Province, Predominant Race Group, Locality=50 PSU: EAs=408 surveyed SSU: Households=4020 surveyed TSU: Individual=4227 surveyed

Sampling deviation

Originally 600 EAs were drawn into the sample. However due to time and financial contraints only 396 EAs were visited.

Mode of data collection

Face-to-face [f2f] PAPI

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. A Verbal Autopsy questionnaire was administered to households that had a death in the last 24 months. An Individual questionnaire was administered to eligible respondents identified from the household roster. A Proxy questionnaire was administered to individual respondents who had cognitive limitations. The questionnaires were developed in English and were piloted as part of the SAGE pretest in 2005. All documents were translated into six of the major languages in South Africa: Afrikaans, IsiZulu, IsiXhosa, Sepedi, Setswana and Xitsonga. All SAGE generic questionnaires are available as external resources.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

Household Response rate=67% Cooperation rate=99%

Individual: Response rate=77% Cooperation rate=99%

EPIC-Oxford is the Oxford component of the European Prospective Investigation into Cancer and Nutrition (EPIC), a large multi-centre cohort study with participants enrolled from 10 European countries. The EPIC-Oxford study began in the 1990s and follows the health of 65,000 men and women living throughout the UK, many of whom are vegetarian. The main objective of EPIC Oxford is to examine how diet influences the risk of cancer, particularly for the most common types of cancer in Britain, as well as the risks of other chronic diseases.

EPIC-Europe was initiated in 1992. It involves over 500,000 people from 23 centres in 10 European countries. It is coordinated by the World Health Organization International Agency for Research on Cancer in Lyon, and supported by the European Union and national funding agencies.

EPIC-Oxford is one of two EPIC cohorts in the UK, the other is EPIC-Norfolk.

For further details on the study design, recruitment, data collection and other aspects of the EPIC-Oxford study, please visit https://www.ceu.ox.ac.uk/research/epic-oxford-1

BackgroundThe assessment of cancer survival is crucial for evaluating advancements in cancer management. As part of the nationwide HUN-CANCER EPI study, we examined the net survival of the Hungarian cancer patient population in 2011–2019.MethodsUsing extracted data from the Hungarian National Health Insurance Fund (NHIF) database, the HUN-CANCER EPI study aimed to assess net survival probabilities for various cancer types over the past decade by the Pohar Perme Estimator method, providing insights for sex and age-specific differences and enabling comparative analysis with other European countries.ResultsBetween 2011 and 2019, 526,381 newly diagnosed cancer cases were identified, with colorectal, lung, breast, prostate, and bladder cancers being the most common. Age-standardized 5-year net survival rates showed significant improvements from 2011-12 till 2017-19 periods for colorectal cancer from 55.08% to 59.78% (4.70%), lung cancer from 20.10% to 23.55% (3.45%), liver cancer from 11.21% to 16.97% (5.76%) and melanoma from 90.06% to 93.80% (3.73%), while clinically relevant, but not significant improvements for breast cancer from 85.03% to 86.84% (1.81%), prostate cancer from 88.13% to 89.76% (1.63%) and thyroid cancer from 87.23% to 92.36% (5.12%). Women generally had better survival probabilities, with notable variations across cancer types. We found no significant age-related differences in cancer survival in women, while survival improvements of colorectal cancer were more pronounced in younger cohorts among male patients. International comparisons using different mortality life tables demonstrated favorable breast and prostate cancer survival rates in Hungary compared to other Central Eastern European countries.ConclusionThe HUN-CANCER EPI study revealed positive trends in cancer survival for most cancer types between 2011 and 2019. The study highlights the continued positive trajectory of cancer survival in Hungary like to more developed European countries.

BackgroundProstate cancer in men's health has become a significant driver of global disease burden, impacting aging populations worldwide. This study assesses its prevalence from 1990 to 2021 to reveal ongoing epidemiological trends and inform effective public health strategies.MethodsProstate cancer prevalence estimates, including their 95% uncertainty intervals (UIs), were derived from the Global Burden of Disease (GBD) 2021 study. Then, temporal trends spanning the past 32 years were thoroughly analyzed using Joinpoint regression, with projections for the next 25 years made using the Bayesian Age-Period-Cohort (BAPC) model. Concurrently, disease trends were decomposed into components of population growth, aging, and epidemiological changes. Additionally, age-period-cohort (APC) models were also employed to explore the impact of age, time, and cohort effect on the relative risk of prostate cancer prevalence. And the cross-country inequalities in the prevalence of prostate cancer burden were meticulously evaluated through the Socio-Demographic Index (SDI), revealing significant disparities across socio-economic strata.ResultIn 2021, over 10 million prostate cancer cases were recorded worldwide—a 188.85% increase from 3.6 million in 1990. The age-standardized prevalence rate (ASPR) rose at an estimated annual percentage change of 0.64% (95% UI: 0.47%−0.82%); Joinpoint regression revealed a steady increase in case numbers over 32 years, while the ASPR peaked and then slightly declined. Decomposition analysis showed population growth as the main driver (65.62%), with epidemiological changes and aging accounting for 17.97 and 16.41%, respectively. APC modeling indicated the highest relative risk around age 75—nearly 10 times that of the general population (RR: 9.99; 95% CI: 9.97–10.01). Projections through 2046 forecast a continued rise in both total cases and ASPR.ConclusionsAs a major health concern among older adult men, the global prevalence of prostate cancer has risen steadily since 1990, with population growth identified as the primary driver. Moreover, SDI-related disparities across 204 countries and territories have widened over time. Finally, the APC model forecasts a continuous increase in prevalence over the next 25 years, underscoring the growing disease burden and the urgent need for more targeted and effective management strategies.

BackgroundProstate cancer in men's health has become a significant driver of global disease burden, impacting aging populations worldwide. This study assesses its prevalence from 1990 to 2021 to reveal ongoing epidemiological trends and inform effective public health strategies.MethodsProstate cancer prevalence estimates, including their 95% uncertainty intervals (UIs), were derived from the Global Burden of Disease (GBD) 2021 study. Then, temporal trends spanning the past 32 years were thoroughly analyzed using Joinpoint regression, with projections for the next 25 years made using the Bayesian Age-Period-Cohort (BAPC) model. Concurrently, disease trends were decomposed into components of population growth, aging, and epidemiological changes. Additionally, age-period-cohort (APC) models were also employed to explore the impact of age, time, and cohort effect on the relative risk of prostate cancer prevalence. And the cross-country inequalities in the prevalence of prostate cancer burden were meticulously evaluated through the Socio-Demographic Index (SDI), revealing significant disparities across socio-economic strata.ResultIn 2021, over 10 million prostate cancer cases were recorded worldwide—a 188.85% increase from 3.6 million in 1990. The age-standardized prevalence rate (ASPR) rose at an estimated annual percentage change of 0.64% (95% UI: 0.47%−0.82%); Joinpoint regression revealed a steady increase in case numbers over 32 years, while the ASPR peaked and then slightly declined. Decomposition analysis showed population growth as the main driver (65.62%), with epidemiological changes and aging accounting for 17.97 and 16.41%, respectively. APC modeling indicated the highest relative risk around age 75—nearly 10 times that of the general population (RR: 9.99; 95% CI: 9.97–10.01). Projections through 2046 forecast a continued rise in both total cases and ASPR.ConclusionsAs a major health concern among older adult men, the global prevalence of prostate cancer has risen steadily since 1990, with population growth identified as the primary driver. Moreover, SDI-related disparities across 204 countries and territories have widened over time. Finally, the APC model forecasts a continuous increase in prevalence over the next 25 years, underscoring the growing disease burden and the urgent need for more targeted and effective management strategies.

BackgroundThe multiple imputation approach to missing data has been validated by a number of simulation studies by artificially inducing missingness on fully observed stage data under a pre-specified missing data mechanism. However, the validity of multiple imputation has not yet been assessed using real data. The objective of this study was to assess the validity of using multiple imputation for “unknown” prostate cancer stage recorded in the New South Wales Cancer Registry (NSWCR) in real-world conditions.MethodsData from the population-based cohort study NSW Prostate Cancer Care and Outcomes Study (PCOS) were linked to 2000–2002 NSWCR data. For cases with “unknown” NSWCR stage, PCOS-stage was extracted from clinical notes. Logistic regression was used to evaluate the missing at random assumption adjusted for variables from two imputation models: a basic model including NSWCR variables only and an enhanced model including the same NSWCR variables together with PCOS primary treatment. Cox regression was used to evaluate the performance of MI.ResultsOf the 1864 prostate cancer cases 32.7% were recorded as having “unknown” NSWCR stage. The missing at random assumption was satisfied when the logistic regression included the variables included in the enhanced model, but not those in the basic model only. The Cox models using data with imputed stage from either imputation model provided generally similar estimated hazard ratios but with wider confidence intervals compared with those derived from analysis of the data with PCOS-stage. However, the complete-case analysis of the data provided a considerably higher estimated hazard ratio for the low socio-economic status group and rural areas in comparison with those obtained from all other datasets.ConclusionsUsing MI to deal with “unknown” stage data recorded in a population-based cancer registry appears to provide valid estimates. We would recommend a cautious approach to the use of this method elsewhere.

ObjectsThe aim of this study is to explore the epidemiological characteristics of peripheral T-cell lymphoma in Beijing.Methods All data were extracted from the Beijing Cancer Registry database from January 1, 2007, to December 31, 2018. Segi’s World Standard Population was used to estimate the age-standardized rate (ASR). Changes in trends were examined using joinpoint regression analysis. The observed survival was estimated by the Kaplan–Meier method. Relative survival was calculated using Ederer II and standardized using the Brenner method and International Cancer Survival Standard (ICSS) group 1 age structure. Stratified by gender, area, and histological type, incidence, mortality, and age of onset trends were observed in Beijing.Results In Beijing, there were 801 new cases and 463 deaths of T-cell lymphoma from 2007 to 2018. Peripheral T-cell lymphoma not otherwise specified (PTCL-NOS) was the most prevalent subtype (37.45%), followed by angioimmunoblastic T-cell lymphoma (AITL; 20.35%), NK/T-cell lymphoma (NK/TCL; 17.60%), and anaplastic large cell lymphoma (ALCL; 10.24%). The crude incidence and mortality rates were 0.52 and 0.30 per 100,000 person-years, respectively, whereas the age-standardized incidence and mortality rates (ASIR and ASMR) were 0.35 and 0.18 per 100,000 person-years, respectively. Both ASIR and ASMR were more prevalent in men (0.48 and 0.24 per 100,000) and urban area (0.38 and 0.19 per 100,000) than in women (0.22 and 0.11 per 100,000) and rural area (0.30 and 0.15 per 100,000). The average annual percentage change (AAPC) of ASIR and ASMR was 5.72% (95% confidence interval (CI): 1.79%–9.81%) and 4.35% (95% CI: −0.09%–8.99%), respectively. The age-specific incidence rate increased with age and peaked at the age groups of 10–14 and 80–84. The mean and median age of onset increased between 2007 and 2018. In addition, it decreased after the age of onset was age standardization (β = −0.41, P = 0.26). The 5-year age-standardized relative survival was 39.02% for all patients, 58.14% for NK/TCL, 57.60% for ALCL, 31.38% for AITL, and 29.18% for PTCL-NOS.Conclusions T-cell lymphoma incidence was rising, but survival was dismal in Beijing, indicating the need for improved early diagnosis and standardized treatment.

BackgroundThe assessment of cancer survival is crucial for evaluating advancements in cancer management. As part of the nationwide HUN-CANCER EPI study, we examined the net survival of the Hungarian cancer patient population in 2011–2019.MethodsUsing extracted data from the Hungarian National Health Insurance Fund (NHIF) database, the HUN-CANCER EPI study aimed to assess net survival probabilities for various cancer types over the past decade by the Pohar Perme Estimator method, providing insights for sex and age-specific differences and enabling comparative analysis with other European countries.ResultsBetween 2011 and 2019, 526,381 newly diagnosed cancer cases were identified, with colorectal, lung, breast, prostate, and bladder cancers being the most common. Age-standardized 5-year net survival rates showed significant improvements from 2011-12 till 2017-19 periods for colorectal cancer from 55.08% to 59.78% (4.70%), lung cancer from 20.10% to 23.55% (3.45%), liver cancer from 11.21% to 16.97% (5.76%) and melanoma from 90.06% to 93.80% (3.73%), while clinically relevant, but not significant improvements for breast cancer from 85.03% to 86.84% (1.81%), prostate cancer from 88.13% to 89.76% (1.63%) and thyroid cancer from 87.23% to 92.36% (5.12%). Women generally had better survival probabilities, with notable variations across cancer types. We found no significant age-related differences in cancer survival in women, while survival improvements of colorectal cancer were more pronounced in younger cohorts among male patients. International comparisons using different mortality life tables demonstrated favorable breast and prostate cancer survival rates in Hungary compared to other Central Eastern European countries.ConclusionThe HUN-CANCER EPI study revealed positive trends in cancer survival for most cancer types between 2011 and 2019. The study highlights the continued positive trajectory of cancer survival in Hungary like to more developed European countries.

The global incidence of early-onset colorectal cancer (EO-CRC) is increasing. Although the mortality rate is relatively stable, some comorbidities have been associated with a higher mortality rate. This study estimated the mortality risk in patients with EO-CRC with various comorbidities using real-world data to identify the high-risk group using Cox proportional regression for overall and cancer-specific mortality. The incidence rate of EO-CRC significantly increased from 6.04 per 100,000 population in 2007 to 12.97 per 100,000 population in 2017. The five-year overall mortality rate was 101.50 per 1000 person year and the cancer-specific mortality rate was 94.12 per 1000 person year. Patients with cerebrovascular disease (CVD) had a higher mortality risk (hazard ratio (HR): 1.68; 95% confidence interval (CI): 1.25-2.28; p=0.0007). After subgroup analyses based on age, sex, clinical stage, and treatment type, patients with CVD had a higher overall mortality risk compared to non-CVD patients, except for patients undergoing surgery and chemotherapy. Patients with chronic kidney disease had a higher mortality risk in the early clinical stages (HR: 2.31; 95% CI: 1.08-4.96; p=0.0138). Patients who underwent radiotherapy had a higher overall mortality risk (HR: 1.38; 95% CI: 1.04-1.85; p=0.0285) than those without liver disease. Identifying specific comorbidity mortality risks in patients with EO-CRC allows for risk stratification when screening target groups and may lower disease mortality.