Cancer Mortality & Incidence Rates: (Country LVL)

Investigating Cancer Trends over time

By Data Exercises [source]

About this dataset

This dataset is a comprehensive collection of data from county-level cancer mortality and incidence rates in the United States between 2000-2014. This data provides an unprecedented level of detail into cancer cases, deaths, and trends at a local level. The included columns include County, FIPS, age-adjusted death rate, average death rate per year, recent trend (2) in death rates, recent 5-year trend (2) in death rates and average annual count for each county. This dataset can be used to provide deep insight into the patterns and effects of cancer on communities as well as help inform policy decisions related to mitigating risk factors or increasing preventive measures such as screenings. With this comprehensive set of records from across the United States over 15 years, you will be able to make informed decisions regarding individual patient care or policy development within your own community!

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How to use the dataset

This dataset provides comprehensive US county-level cancer mortality and incidence rates from 2000 to 2014. It includes the mortality and incidence rate for each county, as well as whether the county met the objective of 45.5 deaths per 100,000 people. It also provides information on recent trends in death rates and average annual counts of cases over the five year period studied.

This dataset can be extremely useful to researchers looking to study trends in cancer death rates across counties. By using this data, researchers will be able to gain valuable insight into how different counties are performing in terms of providing treatment and prevention services for cancer patients and whether preventative measures and healthcare access are having an effect on reducing cancer mortality rates over time. This data can also be used to inform policy makers about counties needing more target prevention efforts or additional resources for providing better healthcare access within at risk communities.

When using this dataset, it is important to pay close attention to any qualitative columns such as “Recent Trend” or “Recent 5-Year Trend (2)” that may provide insights into long term changes that may not be readily apparent when using quantitative variables such as age-adjusted death rate or average deaths per year over shorter periods of time like one year or five years respectively. Additionally, when studying differences between different counties it is important to take note of any standard FIPS code differences that may indicate that data was collected by a different source with a difference methodology than what was used in other areas studied

Research Ideas

• Using this dataset, we can identify patterns in cancer mortality and incidence rates that are statistically significant to create treatment regimens or preventive measures specifically targeting those areas.
• This data can be useful for policymakers to target areas with elevated cancer mortality and incidence rates so they can allocate financial resources to these areas more efficiently.
• This dataset can be used to investigate which factors (such as pollution levels, access to medical care, genetic make up) may have an influence on the cancer mortality and incidence rates in different US counties

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: death .csv | Column name | Description | |:-------------------------------------------|:-------------------------------------------------------------------...

Project Title: Cancer Data Analysis for Improved Healthcare

Description:

Our Cancer Data Analysis project is a comprehensive effort aimed at harnessing the power of data to advance our understanding of cancer, improve patient care, and contribute to ongoing research in oncology. This project brings together a multidisciplinary team of researchers, data scientists, and healthcare professionals committed to making a positive impact on the fight against cancer.

Project Objectives:

Data Collection: We have compiled a diverse and extensive dataset containing information on cancer incidence, patient demographics, treatment outcomes, genomic profiles, and more. This dataset represents a valuable resource for researchers and healthcare providers.

Insights and Trends: Through advanced data analysis techniques, we aim to uncover meaningful insights into cancer trends, including the prevalence of different cancer types, regional variations, and changes over time. These insights can inform healthcare policies and resource allocation.

Treatment Optimization: By analyzing treatment outcomes and patient responses to various therapies, we aim to identify patterns that can help tailor cancer treatment plans to individual patient needs, ultimately improving survival rates and quality of life.

Epidemiological Insights: We analyze epidemiological data to track the spread of cancer

Impact:

The Cancer Data Analysis project aspires to make a significant impact on cancer research, clinical practice, and public health initiatives. By providing valuable data and insights, we hope to contribute to:

Early cancer detection and diagnosis Improved treatment protocols Enhanced patient care and support Informed healthcare policy decisions Accelerated research breakthroughs

Collaboration:

We welcome collaboration with fellow researchers, healthcare professionals, and organizations committed to the fight against cancer. Together, we can leverage data-driven approaches to drive positive change in the field of oncology.

Join us in our mission to combat cancer through data-driven insights and innovative solutions. Together, we can make a difference in the lives of cancer patients and their families.

SEER Limited-Use cancer incidence data with associated population data. Geographic areas available are county and SEER registry. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute collects and distributes high quality, comprehensive cancer data from a number of population-based cancer registries. Data include patient demographics, primary tumor site, morphology, stage at diagnosis, first course of treatment, and follow-up for vital status. The SEER Program is the only comprehensive source of population-based information in the United States that includes stage of cancer at the time of diagnosis and survival rates within each stage.

ABSTRACT Breast cancer is the neoplasia with the highest incidence in the population worldwide, and lymphedema is one of the most frequent complications in the treatment. Body mass index increase is one of the risk factors for lymphedema after breast cancer treatment. The objective of this study was to verify the incidence of lymphedema in mastectomized women with overweight and obesity. The risk of lymphedema in women with overweight and obesity was four times greater (Odds Ratio, OR = 3.887). The higher the body mass index, the higher was the probability of lymphedema, with increase in the relative risk of 40% for obesity II.

Several new systemic treatments for primary metastatic prostate cancer patients (mPCa) were introduced in the last decade for both hormone-sensitive (mHSPC) and castration-resistant prostate cancer (mCRPC). However, little is known about the introduction of these treatments in clinical practice. In this national cohort study, we described users and non-users of systemic treatment beyond androgen deprivation therapy (ADT). We also explored whether there was a shift in treatment patterns after the introduction of Docetaxel for mHSPC patients. All patients registered in the Cancer Registry of Norway with mPCa diagnosed in 2010-18 were included. Data on systemic therapy (Docetaxel, Abiraterone, Enzalutamide, Cabazitaxel, and Radium-223) were provided from the Norwegian Prescription Database, the Norwegian Patient Registry, and the Norwegian Control and Payment of Health Reimbursement Database. Descriptive results about patient and disease characteristics were presented using frequencies and proportions, means and standard deviations, or medians and interquartile ranges. Of the 2770 patients included in this study, 48% received systemic treatment beyond ADT. The proportion of patients receiving systemic treatment increased during the study period. Systemic treatment users were younger, in better general condition, and had more aggressive tumors than non-users. A treatment shift was observed after 2015, with 48% of patients receiving systemic treatment (mainly Docetaxel) in the mHSPC phase compared to 4% of those diagnosed 2010-14. No significant treatment differences were observed across health regions. An increasing proportion of patients received systemic treatment during the period 2010–18. However, less than 50% of patients in our study received systemic treatment. In accordance with updated guidelines, Docetaxel was introduced after 2015 with an increasing proportion of patients receiving systemic treatment as mHSPC. Further studies should address the disease course and treatment given to patients who do not receive systemic treatment.

The aim of the National Prostate Cancer Audit (NPCA) is to evaluate the patterns of care and outcomes for patients with prostate cancer in England and Wales, and to support services to improve the quality of care. National guidelines underpin the management of patients with prostate cancer and the NPCA evaluates current patterns of care against these standards including guidance and quality standards from the National Institute for Health and Care Excellence (NICE). The information presented here reports on prostate cancer services in England and Wales, showing variation across providers. For the first time since the NPCA Annual Report 2020, we report results from all six of our performance indicators for both England and Wales, using the most recently available data to the audit. Four performance indicators: • proportion of men with low-risk localised cancer undergoing radical prostate cancer treatment • proportion of men with high-risk/locally advanced disease undergoing radical prostate cancer treatment • proportion of patients experiencing at least one genitourinary (GU) complication requiring a procedural/surgical intervention within 2 years of radical prostatectomy • proportion of patients receiving a procedure of the large bowel and a diagnosis indicating radiation toxicity up to 2 years following radical prostate radiotherapy (RT) require risk stratification using the Gleason score, which is not currently available in the Rapid Cancer Registration Dataset (RCRD) used by the NPCA for recent Annual Reports (2021 and 2022). Therefore, to include these, we have used the National Cancer Registration Dataset (NCRD) in England. The most recently available data to the audit from the NCRD in England is between 1st April 2020 and 31st March 2021. In Wales, the data we receive includes the Gleason score, and the most recently available data to the audit covers patients newly diagnosed with prostate cancer between 1st April 2021 and 31st March 2022. Previous analysis has shown that RCRD underestimated the proportion of men diagnosed with metastatic disease when compared to the NCRD, therefore we have used the NCRD in England to report this indicator. This means we report on different time frames for England and Wales. The proportion of patients who had an emergency readmission within 90 days of radical prostate cancer surgery however can be accurately calculated using the RCRD. Therefore, to compare rates between England and Wales, we selected the same timeframe for this indicator. To report on the impact of and recovery from Covid-19 for prostate cancer services, we use the most recently available data in England from the RCRD between 1st January 2022 and 31st January 2023, and in Wales between 1st April 2021 and 31st March 2022. Individual provider results and reports are available enabling regional and national comparisons to support local QI.

PurposeThis study reviewed palliative radiation therapy (RT) practices and outcomes and compared the percentage of remaining life spent receiving RT (PRLSRT) in patients treated for osseous metastases.MethodsA retrospective analysis was conducted using the National Cancer Database (2010–2016) to evaluate metastatic patients who received palliative bone RT. Common palliative RT schemes were analyzed to determine treatment patterns and outcomes. Palliative outcomes, including median PRLSRT, RT completion, and mortality rates, were calculated. Binary logistic regression was performed to identify factors affecting RT completion, and a scoring system was developed to identify patients at risk for poor palliative outcomes.ResultsA total of 50,929 patients were included, with the majority diagnosed with NSCLC (45.2%), breast cancer (15.1%), or prostate cancer (10.8%). The median overall survival after palliative RT was 5.74 months. Patients receiving lower doses per fraction (2.5 Gy/Fx) tended to be younger, healthier, and yet experienced worse palliative outcomes. Binary logistic regression identified age, race, income quartile, and Gy/Fx as significant factors affecting RT completion. Median PRLSRTs were as follows: 14.95% for GI NOS, 9.89% for upper GI, 9.46% for NSCLC, 8.67% for skin, 7.06% for SCLC, 6.10% for lower GI, 5.59% for GYN, 5.44% for GU, 5.35% for HNC, 2.05% for endocrine, 2.03% for prostate cancer, and 1.82% for breast cancer. Patients receiving 2.5 and 3 Gy/Fx were less likely to complete RT compared to those receiving 4 Gy/Fx (OR, 1.429 and 3.780, respectively; p < 0.001). Age, comorbidities, primary tumor, target location, and metastatic burden were associated with PRLSRT ≥ 25%.ConclusionDose regimens and patient selection influence palliative bone RT outcomes. Both factors should be carefully considered to minimize the burden of care and maximize treatment benefits.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of cancer (in persons of all ages). Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.ANALYSIS METHODOLOGYThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to cancer (in persons of all ages).This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.The percentage of each MSOA’s population (all ages) with cancer was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of registered patients that have that illness The estimated percentage of each MSOA’s population with cancer was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with cancer, within the relevant age range.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have cancerB) the NUMBER of people within that MSOA who are estimated to have cancerAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA that are estimated to have cancer, compared to other MSOAs. In other words, those are areas where it’s estimated a large number of people suffer from cancer, and where those people make up a large percentage of the population, indicating there is a real issue with cancer within the population and the investment of resources to address that issue could have the greatest benefits.LIMITATIONS1. GP data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children (see the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset), we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of populations that are registered with each GP practice or who live within each MSOA. Populations might be concentrated in certain areas of a GP practice’s catchment area or MSOA and relatively sparse in other areas. Therefore, the dataset should be used to identify general areas where there are high levels of cancer, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of cancer.TO BE VIEWED IN COMBINATION WITH:This dataset should be viewed alongside the following datasets, which highlight areas of missing data and potential outliers in the data:Health and wellbeing statistics (GP-level, England): Missing data and potential outliersLevels of obesity, inactivity and associated illnesses (England): Missing dataDOWNLOADING THIS DATATo access this data on your desktop GIS, download the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset.DATA SOURCESThis dataset was produced using:Quality and Outcomes Framework data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.GP Catchment Outlines. Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Data was cleaned by Ribble Rivers Trust before use.MSOA boundaries: © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021.Population data: Mid-2019 (June 30) Population Estimates for Middle Layer Super Output Areas in England and Wales. © Office for National Statistics licensed under the Open Government Licence v3.0. © Crown Copyright 2020.COPYRIGHT NOTICEThe reproduction of this data must be accompanied by the following statement:© Ribble Rivers Trust 2021. Analysis carried out using data that is: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital; © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021. © Crown Copyright 2020.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

Prospective Payment System (PPS)-Exempt Cancer Hospital Quality Reporting (PCHQR) Complications and Unplanned Hospital Visits. This dataset evaluates the percentage of patients who are receiving PCH-based outpatient chemotherapy treatment for all cancer types except leukemia who were admitted to the hospital or visited the emergency department for one of 10 conditions within 30 days after treatment.

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

Clinical and sociodemographic characteristics of the patient sample.

The National Prostate Cancer Audit (NPCA) evaluates patterns of care and outcomes and reports on diagnosis, treatment and outcomes for men diagnosed with prostate cancer in England and Wales. This second publication of the NPCA State of the Nation report in 2025 reflects the move to the National Cancer Audit Collaborating Centre (NATCAN) reporting cycle. The NPCA derives its indicators using information that is routinely collected by the NHS as part of the care and support given to men diagnosed with prostate cancer, rather than data collected specifically for the Audit. For men diagnosed or treated in England, the data are collated, maintained and quality assured by NHS England’s National Disease Registration Service (NDRS). For men diagnosed or treated in Wales, data are provided by Wales Cancer Network (WCN) using the Cancer Network Information System Cymru (CaNISC) or Cancer Dataset Form (CDF). We use the National Cancer Registration Dataset (NCRD) for England, which is considered the ‘gold standard’ because it draws data from various sources. It also benefits from enhanced data processing by cancer registration officers and follow-up from NHS hospital trusts. NCRD data is currently available for patients diagnosed up to December 2022. The Rapid Cancer Registration Dataset (RCRD) includes proxy tumour registrations, providing more up-to-date data but with less accuracy than the NCRD. The RCRD is used in the NPCA Data Dashboard, updated quarterly, and in section 4 of this report. Data were impacted by the COVID-19 pandemic and so will be atypical to some degree during 2020-21. We present results from eight key performance indicators (PIs) in the management of prostate cancer, as well as the variation in performance among providers in England and Wales. For the first time, we report the proportion of men with metastatic disease who receive systemic treatment intensification (PI4a and PI4b) and report the proportion of genitourinary complications occurring after radiotherapy to the prostate, with or without pelvic lymph nodal radiation (PI8). Please refer to the NPCA methodology supplement for comprehensive details regarding this report’s data sources and methodology. Additional supplementary materials, including a glossary of technical terms, an appendix, an action plan template, a patient and public-friendly summary, details of our outlier process and each NHS provider’s results for data completeness and performance indicators, are available on the NPCA State of the Nation report 2025 webpage.

Number and percentage of patients who agreed with their radiation oncologists about the aim of current cancer treatment (n = 138).

Background This study sought to describe the pattern of complementary/alternative medicine (CAM) use among a group of patients with advanced breast cancer, to examine the main reasons for their CAM use, to identify patient's information sources and their communication pattern with their physicians. Methods Face-to-face structured interviews of patients with advanced-stage breast cancer at a comprehensive oncology center. Results Seventy three percent of patients used CAM; relaxation/meditative techniques and herbal medicine were the most common. The most commonly cited primary reason for CAM use was to boost the immune system, the second, to treat cancer; however these reasons varied depending on specific CAM therapy. Friends or family members and mass media were common primary information source's about CAM. Conclusions A high proportion of advanced-stage breast cancer patients used CAM. Discussion with doctors was high for ingested products. Mass media was a prominent source of patient information. Credible sources of CAM information for patients and physicians are needed.

This dataset provides ZIP Code Tabulation Area–level data across the United States to support the analysis of spatial and telehealth accessibility to cancer care. The dataset includes the following key components: Broadband availability: Coverage estimates for fixed and wireless broadband, including technologies such as 5G Broadband subscription rates: Residential uptake of broadband services Travel time: Estimated drive time from population-weighted centroids to the nearest cancer care providers based on OSRM Cancer incidence: Estimated cancer case counts and rates at the ZIP Code Tabulation Area level Provider locations: Geocoded locations and specialties of cancer care physicians and facilities All variables are spatially aligned to ZIP Code Tabulation Areas and can be used for accessibility modeling and health disparity research. Please cite: Liu, L., Onega, T., Moen, E. L., Tosteson, A. N. A., Smith, R. E., Wang, Q., Cowan, L., & Wang, F. (2025). Digital divides in telehealth accessibility for cancer care in the United States. NPJ digital medicine, 8(1), 534. https://doi.org/10.1038/s41746-025-01931-5 Reference: Liu, L., Cowan, L., Wang, F., & Onega, T. (2025). A multi-constraint Monte Carlo Simulation approach to downscaling cancer data. Health & Place, 91, 103411. https://doi.org/10.1016/j.healthplace.2024.103411 Liu, L., Wang, F., & Onega, T. (2025). Cancer incidence data at the ZIP Code Tabulation Area level in the United States interpolated by Monte Carlo simulation with multiple constraints. Scientific Data, 12(1), 1-10. https://doi.org/10.1038/s41597-025-05254-8

This dataset provides insights into one-year survival rates from all cancers, serving as a key indicator of early cancer outcomes. It measures the proportion of individuals diagnosed with an invasive cancer who survive for at least one year following their diagnosis. The dataset includes all invasive tumours classified under ICD-10 codes C00 to C97, excluding non-melanoma skin cancer (C44). It supports analysis across different population groups and geographies, including ethnicity, deprivation levels, and the Birmingham and Solihull (BSol) area.

Rationale

Improving one-year survival rates is a critical goal in cancer care, as it reflects the effectiveness of early diagnosis and initial treatment. This indicator helps monitor progress in reducing early mortality from cancer and supports targeted interventions to improve outcomes.

Numerator

The numerator includes individuals who were diagnosed with a specific type of cancer and died from the same type of cancer within one year of diagnosis. Only invasive cancers are included, as defined by ICD-10 codes C00 to C97, excluding non-melanoma skin cancer (C44). Data is sourced from the National Cancer Registration and Analysis Service (NCRAS).

Denominator

The denominator comprises all individuals diagnosed with an invasive cancer (ICD-10 codes C00 to C97, excluding C44) within a five-year period. This data is also sourced from the National Cancer Registration and Analysis Service (NCRAS).

Caveats

This dataset uses a simplified methodology that differs from the national calculation of one-year cancer survival. As a result, the figures presented here may not align with nationally published statistics. However, this approach enables the provision of survival data disaggregated by ethnicity, deprivation, and local geographies such as BSol, which is not always possible with national data.

External references

For more information, visit the National Cancer Registration and Analysis Service (NCRAS).

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

1 in 17 people are born with or develop a rare disease during their lifetime. 80% of rare diseases have an identified genetic component. However, there are usually significant diagnostic delays. The 100k Genome project was established to collect clinical data, genomic sequencing and samples from people with cancer and rare diseases, to better understand disease and find novel treatments and interventions. This includes rare cardiovascular, ciliopathy, endocrine, gastroenterological, haematological, metabolic, neurological, renal, respiratory skeletal and rheumatological disorders and cancers.

The PIONEER University Hospital Birmingham (UHB) secondary care 100k genomics dataset contains granular demographic, morbidity, treatment and outcome data, supplemented with acute care contacts with serial physiology, blood biomarker data from UHB patients recruited to this programme, to better understand the acute healthcare needs of this group of patients.

PIONEER geography: The West Midlands has a population of 5.9M and includes a diverse ethnic and socio-economic mix. There is a higher than average percentage of minority ethnic groups and a higher than average proportion of patients with rare diseases. Birmingham is home to the first Centre for Rare Diseases for adults and children, treating more than 500 rare diseases and 9000 patients per year.

Electronic Health Records: University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services and specialist care across four hospital sites, with 2.2M patient episodes per year, 2750 beds and 100 ITU beds.

Scope: All patients recruited to the 100K genome project from UHB. This includes all routinely collected health data for all these patients, but data is uniquely supplemented with all acute care contacts through UHB. The dataset includes highly granular patient demographics and co-morbidities taken from ICD-10 and SNOMED-CT codes. Serial, structured data pertaining to acute care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed and administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

Available supplementary data: Matched controls; ambulance, synthetic data. Available supplementary support: Analytics, Model build, validation and refinement; A.I.; Data partner support for ETL process, Clinical expertise, Patient and end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Treatment patterns and types of surgery performed on the study population.

This data set is for the journal article "Gaps in cancer care in a multi-ethnic population in Sarawak: A central referral-centre study. Melissa Lim Siaw Han, Voon Pei Jye, Adibah Ali, Fitri Suraya Mohamad, Jong Lin Lin, Chew Lee Ping, Mohamad Adam Bujang, Yolanda Augustin, Cheng Yuong Kang

Abstract Background: The state of Sarawak on the island of Borneo in East Malaysia, in working towards developing and strengthening cancer services through a holistic patient-centred approach, must focus on the comprehensive needs of cancer patients by taking into account the psycho-social, cultural and spiritual aspects of Sarawak’s multi-ethnic, multi-cultural population.

Methods: A 42-item survey questionnaire was developed and validated with a total of 443 patients. The perceived importance of information provided and level of patient satisfaction were assessed with a 5-point Likert scale in 10 domains (Diagnosis, Surgery, Radiotherapy, Systemic therapy, Clinical trials, Pain management, Treatment monitoring, Psychosocial support, Sexual care and fertility issues, and Financial support) . A paired sample t-test was applied to determine statistically significant differences in mean score between perceived importance and patient satisfaction.

Results: Overall, patients were more satisfied with information related to treatment, surgery and diagnosis but less satisfied with information pertaining to sexual aspects of care and family planning, psycho-social support and financial support. The majority of patients were satisfied with the level of treatment-related information received but preferred the information to be delivered in more easily comprehendible formats. Sexual aspects of care and family planning, psychosocial support and treatment monitoring post-discharge were perceived as important but seldom addressed by health care professionals due to lack of professional counselors, social workers and clinical nurse specialists. Many patients face financial toxicity following a cancer diagnosis, particularly when diagnosed with advanced cancer requiring complex multi-modality treatment.

Conclusion: Cancer patients in Sarawak have various unmet information needs. Written information and educational videos in local indigenous languages may be more suitable for Sarawak’s multi-ethnic population. Sexual aspects of care and family planning is a challenging but essential topic to discuss, in particular due to the high prevalence rates of breast and cervical cancer amongst young women in Sarawak. Financial assessment and information on support services offered by government and non-government organisations should be provided to eligible patients. A holistic needs assessment of each patient at time of diagnosis and support through their cancer journey requires a multi-disciplinary team of medical, nursing and allied health professionals including clinical nurse specialists, pharmacists, counsellors, physiotherapists, occupational therapists, speech and language therapists, dieticians and social workers.

Keywords: cancer, gaps in cancer care, information needs, multi-ethnic, indigenous, patient perceptions

Crude and adjusted models by curative treatment: Surgery only [Ref] vs. surgery with adjuvant therapy.