This publication reports on newly diagnosed cancers registered in England in addition to cancer deaths registered in England during 2020. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document.

Background

Sarcomas are uncommon cancers that can affect any part of the body. There are many different types of sarcoma and subtypes can be grouped into soft tissue or bone sarcomas. About 15 people are diagnosed every day in the UK. 3 in every 200 people with cancer in the UK have sarcoma.

A highly granular dataset with a confirmed sarcoma event including hospital presentation, serial physiology, demography, treatment prescribed and administered, prescribed and administered drugs. The infographic includes data from 27/12/2004 to 31/12/2021 but data is available from the past 10 years+.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

EHR. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & an expanded 250 ITU bed capacity during COVID. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All hospitalised patients from 2004 onwards, curated to focus on Sarcoma. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to acute care process (timings, staff grades, specialty review, wards and triage). Along with presenting complaints, outpatients admissions, microbiology results, referrals, procedures, therapies, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations and others), and all blood results (urea, albumin, platelets, white blood cells and others). Includes all prescribed & administered treatments and all outcomes. Linked images are also available (radiographs, CT scans, MRI).

Available supplementary data: Matched controls; ambulance, OMOP data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

BackgroundCancer Waiting Time targets have been integrated into successive cancer strategies as indicators of cancer care quality in England. These targets are reported in national statistics for all cancers combined, but there is mixed evidence of their benefits and it is unclear if meeting Cancer Waiting Time targets, as currently defined and published, is associated with improved survival for individual patients, and thus if survival is a good metric for judging the utility of the targets.Methods and findingsWe used individually-linked data from the National Cancer Waiting Times Monitoring Dataset (CWT), the cancer registry and other routinely collected datasets. The study population consisted of all adult patients diagnosed in England (2009–2013) with colorectal (164,890), lung (171,208) or ovarian (24,545) cancer, of whom 82%, 76%, and 77%, respectively, had a CWT matching record.The main outcome was one-year net survival for all matched patients by target attainment (‘met/not met’). The time to each type of treatment for the 31-day and 62-day targets was estimated using multivariable analyses, adjusting for age, sex, tumour stage and deprivation.The two-week wait (TWW) from GP referral to specialist consultation and 31-day target from decision to treat to start of treatment were met for more than 95% of patients, but the 62-day target from GP referral to start of treatment was missed more often. There was little evidence of an association between meeting the TWW target and one-year net survival, but for the 31-day and 62-day targets, survival was worse for those for whom the targets were met (e.g. colorectal cancer: survival 89.1% (95%CI 88.9–89.4) for patients with 31-day target met, 96.9% (95%CI 96.1–91.7) for patients for whom it was not met). Time-to-treatment analyses showed that treatments recorded as palliative were given earlier in time, than treatments with potentially curative intent.There are possible limitations in the accuracy of the categorisation of treatment variables which do not allow for fully distinguishing, for example, between curative and palliative intent; and it is difficult in these data to assess the appropriateness of treatment by stage. These limitations in the nature of the data do not affect the survival estimates found, but do mean that it is not possible to separate those patients for whom the times between referral, decision to treat and start of treatment could actually have an impact on the clinical outcomes. This means that the use of these survival measures to evaluate the targets would be misleading.ConclusionsBased on these individually-linked data, and for the cancers we looked at, we did not find that Cancer Waiting Time targets being met translates into improved one-year survival. Patients may benefit psychologically from limited waits which encourage timely treatment, but one-year survival is not a useful measure for evaluating Trust performance with regards to Cancer Waiting Time targets, which are not currently stratified by stage or treatment type. As such, the current composition of the data means target compliance needs further evaluation before being used for the assessment of clinical outcomes.

Age-standardised proportion of adults (16+) who met the recommended guidelines of consuming five or more portions of fruit and vegetables a day by gender.

To help reduce the risk of deaths from chronic diseases such as heart disease, stroke, and cancer. The Five-a-day programme was introduced to increase fruit and vegetable consumption within the general population. Its central message is that people should eat at least five portions of fruit and vegetables a day; that a variety of fruit and vegetables should be consumed and that fresh, frozen, canned and dried fruit, vegetables and pulses all count in making up these portions. The programme includes educational initiatives to increase awareness of the Five-a-day message and the benefits of fruit and vegetable consumption, along with more direct schemes to increase access to fruit and vegetables, such as the school fruit scheme and community initiatives. Monitoring of fruit and vegetable consumption is key to evaluating the success of the policy, both at the level of individual schemes and at a more general level.

The England average, at the 95% confidence level (LCL = lower confidence interval; UCL = upper confidence interval).

Related to: https://indicators.ic.nhs.uk/webview/

Abstract copyright UK Data Service and data collection copyright owner.The National Cancer Patient Experience Surveys (NCPES) began in 2010, after the 2007 'Cancer Reform Strategy' set out a commitment to establish a new survey programme. The NCPES is intended to be a vehicle enabling and supporting quality improvement in the NHS and has been used by national bodies, NHS Hospitals, specialist cancer teams, and national and condition specific charities to improve services for patients. It is designed to monitor national progress on cancer care and to help gather vital information on the Transforming Inpatient Care Programme, the National Cancer Survivorship Initiative and the National Cancer Equality Initiative. An Advisory Group was set up for the NCPES with the National Cancer Director, professionals, voluntary sector representatives, academics and patient survey experts. The Group agreed on the following guiding principles and objectives:a standard national survey tool was to be usedsurveys would be conducted at Trust level and identify cancer groupsthe survey would cover all cancers and include the whole care pathwaythe survey should use the word 'cancer' unlike the 2000 and 2004 surveysthe survey focus would be on patients (rather than carers)the data would be used for benchmarking performance across Trusts and by cancer groups where numbers allowthe data would be used to inform national and local policythe data would be made publicly available whilst observing patient data protection requirements and maintaining confidentiality.The survey is intended to be a vehicle enabling and supporting quality improvement in the NHS and has been used by national bodies, NHS Hospitals, specialist cancer teams, and national and condition-specific charities to improve services for patients. The NCPES has been replicated in Wales (see SN 7510), Northern Ireland, the Isle of Man, parts of Australia, and the Middle East. Further information can be found on the NHS England Cancer Patient Experience Survey webpage.2010-2014 data unavailable:The 2010-2014 NCPES End User Licence data were temporarily withdrawn at the depositor's request in October 2015; only the 2015 survey (SN 8163) is currently available. In addition, there is no Special Licence version of the 2010-2014 data; 2015 is the first year in the series for which both versions are held. The purposes of the National Cancer Patient Experience Survey, 2017: Special Licence Access are: to secure continuous improvement by building on the results of previous surveys, enabling local providers and Cancer Alliances to assess their performance improvement with other providers; to enable commissioners to assess local improvements in cancer patient experience; to provide NHS England and NHS Improvement with an up to date overview of cancer patient experience across England; to provide NHS England and NHS Improvement with data on each participating trust and the areas on which quality improvement needs to be focused; to enable patients to make informed choices about where to go for cancer treatment via publishing the provider level analysis on publicly available websites.The data is based on the experience of an initial sample of 118,052 cancer patients, reduced to 110,449 through checking and deceased status measures, and in total 69,072 responded, either by post or online, phone or through the survey providers translation service. The response rate was 63% overall, in line with the levels attained in previous years. The NCPES is intended to be a vehicle enabling and supporting quality improvement in the NHS and has been used by national bodies, NHS Hospitals, specialist cancer teams, and national and condition-specific charities to improve services for patients.This study is subject to restrictive Special Licence Access conditions because it contains detailed data on the treatment and experiences of cancer patients. A less detailed version of the data, held under SN 8573, is available under standard End User Licence access conditions; it contains no geographic information and less detailed demographic information. Users are advised to check SN 8573 first to see whether it is sufficient for their research requirements before considering making a Special Licence Access application for this study. Main Topics:The data cover different stages of the patients' 'cancer journey', from diagnosis to outpatient treatment: initial GP visits before diagnosis (how many appointments, time period)diagnostic tests (understanding of these)how patients were told about the cancer diagnosis (understanding, sensitivity, written information)decisions on treatment (understanding, side effects explained, involvement in decision making, written information)whether patients were given a named key worker (Cancer Nurse Specialist provision and experience of them)support measures patients were informed about (information on support groups, financial help, free prescriptions)hospital doctors (understanding, confidence and trust in them, knowledge of patient case)ward nurses (understanding, confidence, availability)overall hospital care and treatment (information provision, privacy, knowledge of case, pain control, dignity and respect)information provided before going home (written information and understanding, information on care at home and health or social services provision)day patient experience (radiotherapy, chemotherapy, side effects, pain control, emotional support, appointment delay, time with doctor, doctor notes and case understanding)wider care experience (hospital and community staff working together, information transfer)demographic datainformation provided by the participating Trusts such as date of discharge, diagnosis etc.Standard Measures: Positive scoring methodology was used to create individual question scores. The National Report used analysis of IMD deciles based on patients' postcodes provided as part of the dataset by individual NHS Trusts. Standard statistical tests were used to establish statistical significance and a description of these is included in the National Report. The survey asked all cancer patients about their experiences of the NHS cancer pathway; from diagnosis through to treatment through to aftercare, as well as some questions about protected characteristics.

Legacy unique identifier: P01733

Appetite is frequently affected in cancer patients, leading to anorexia and consequently insufficient food intake. In this study, we report on hypothalamic gene expression profile of a cancer cachectic mouse model with increased food intake. In this model, mice bearing C26 colon adenocarcinoma have an increased food intake subsequently to the loss of body weight. We hypothesize that in this model, appetite regulating systems in the hypothalamus, which apparently fail in anorexia, are still able to adapt adequately to changes in energy balance. Therefore studying the changes that occur on appetite regulators in the hypothalamus might reveal targets for treatment of cancer-induced eating disorders. By applying transcriptomics, many appetite regulating systems in the hypothalamus could be taken into account, providing an overview of changes that occur in the hypothalamus during tumour growth. We show that hypothalamic expression of orexigenic neuropeptides NPY and AgRP was higher, whereas expression of anorexigenic genes CCK and POMC were lower in TB compared to controls. In addition, serotonin and dopamine signalling pathways were found to be significantly altered in TB mice. Serotonin levels in brain showed to be lower in TB mice compared to control mice, while dopamine levels did not change. Moreover, serotonin levels inversely correlated with food intake. Transcriptomic analysis of the hypothalamus of cachectic TB mice with an increased food intake showed changes in NPY, AgRP and serotonin signalling. Serotonin levels in the brain showed to correlate with changes in food intake. Targeting these systems seems a promising strategy to avoid the development of cancer-induced eating disorders. C26-colon adenocarcinoma cells were subcutaneously inoculated in CDF1 mice. After 20 days, hypothalami were dissected and subjected to gene expression profiling. The total dataset consists of 2 parts; dataset 1, a pilot stuy in which mice were injected with increasing number of tumour cells and pooled samples were arrayed; and dataset 2, the main study in which mice were injected with 1 million tumour cells and samples were individually arrayed.

Legacy unique identifier: P01735

Legacy unique identifier: P01734

Legacy unique identifier: P01744

Abstract copyright UK Data Service and data collection copyright owner. The Organisation for Economic Co-operation and Development (OECD) Health Statistics offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems. Within UKDS.Stat the data are presented in the following databases: Health status This datasets presents internationally comparable statistics on morbidity and mortality with variables such as life expectancy, causes of mortality, maternal and infant mortality, potential years of life lost, perceived health status, infant health, dental health, communicable diseases, cancer, injuries, absence from work due to illness. The annual data begins in 2000. Non-medical determinants of health This dataset examines the non-medical determinants of health by comparing food, alcohol, tobacco consumption and body weight amongst countries. The data are expressed in different measures such as calories, grammes, kilo, gender, population. The data begins in 1960. Healthcare resources This dataset includes comparative tables analyzing various health care resources such as total health and social employment, physicians by age, gender, categories, midwives, nurses, caring personnel, personal care workers, dentists, pharmacists, physiotherapists, hospital employment, graduates, remuneration of health professionals, hospitals, hospital beds, medical technology with their respective subsets. The statistics are expressed in different units of measure such as number of persons, salaried, self-employed, per population. The annual data begins in 1960. Healthcare utilisation This dataset includes statistics comparing different countries’ level of health care utilisation in terms of prevention, immunisation, screening, diagnostics exams, consultations, in-patient utilisation, average length of stay, diagnostic categories, acute care, in-patient care, discharge rates, transplants, dialyses, ICD-9-CM. The data is comparable with respect to units of measures such as days, percentages, population, number per capita, procedures, and available beds. Health Care Quality Indicators This dataset includes comparative tables analyzing various health care quality indicators such as cancer care, care for acute exacerbation of chronic conditions, care for chronic conditions and care for mental disorders. The annual data begins in 1995. Pharmaceutical market This dataset focuses on the pharmaceutical market comparing countries in terms of pharmaceutical consumption, drugs, pharmaceutical sales, pharmaceutical market, revenues, statistics. The annual data begins in 1960. Long-term care resources and utilisation This dataset provides statistics comparing long-term care resources and utilisation by country in terms of workers, beds in nursing and residential care facilities and care recipients. In this table data is expressed in different measures such as gender, age and population. The annual data begins in 1960. Health expenditure and financing This dataset compares countries in terms of their current and total expenditures on health by comparing how they allocate their budget with respect to different health care functions while looking at different financing agents and providers. The data covers the years starting from 1960 extending until 2010. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, and United States. Social protection This dataset introduces the different health care coverage systems such as the government/social health insurance and private health insurance. The statistics are expressed in percentage of the population covered or number of persons. The annual data begins in 1960. Demographic references This dataset provides statistics regarding general demographic references in terms of population, age structure, gender, but also in term of labour force. The annual data begins in 1960. Economic references This dataset presents main economic indicators such as GDP and Purchasing power parities (PPP) and compares countries in terms of those macroeconomic references as well as currency rates, average annual wages. The annual data begins in 1960. These data were first provided by the UK Data Service in November 2014.

Characteristics of the patients included in the study.

Human embryonal carcinoma (EC) cells are the stem cells of nonseminoma testicular germ cells tumors (TGCTs) and share remarkable similarities to human embryonic stem (ES) cells. In prior work we found that EC cells are hypersensitive to low nanomolar doses of 5-aza deoxycytidine (5-aza) and that this hypersensitivity partially depended on unusually high levels of the DNA methyltransferase, DNMT3B. We show here that low-dose 5-aza treatment results in DNA damage and induction of p53 in NT2/D1 cells. In addition, low-dose 5-aza results in global and gene specific promoter DNA hypomethylation. Low-dose 5-aza induces a p53 transcriptional signature distinct from that induced with cisplatin in NT2/D1 cells and also uniquely downregulates genes associated with pluripotency including NANOG, SOX2, GDF3 and Myc target genes. Changes in the p53 and pluripotency signatures with 5-aza were to a large extent dependent on high levels of DNMT3B. In contrast to the majority of p53 target genes upregulated by 5-aza that did not show DNA hypomethylation, several other genes induced with 5-aza had corresponding decreases in promoter methylation. These genes include RIN1, SOX15, GPER, and TLR4 and are novel candidate tumors suppressors in TGCTs. Our studies suggest that the hypersensitivity of NT2/D1 cells to low-dose 5-aza is multifactorial and involves the combined activation of p53 targets, repression of pluripotency genes, and activation of genes repressed by DNA methylation. Low-dose 5-aza therapy may be a general strategy to treat those tumors that are sustained by cells with embryonic stem-like properties. Total RNA obtained from NT2/D1-R1 sh control or NT2/D1-R1 sh DNMT3B knockdown cells treated with vehicle or 10 nM 5-aza deoxycytidine for 3 days. Four groups in biological triplicate for total of 12 hybridizations on Illumina HT-12v3 beadarray.

This indicator measures the percentage of admissions of people who returned to hospital as an emergency within 30 days of the last time they left hospital after a stay. Admissions for cancer and obstetrics are excluded as they may be part of the patient’s care plan.

Purpose

This indicator aims to measure the success of the NHS in helping people to recover effectively from illnesses or injuries. If a person does not recover well, it is more likely that they will require hospital treatment again within the 30 days following their previous admission. Thus, readmissions are widely used as an indicator of the success of healthcare in helping people to recover.

Current version updated: Feb-14

Next version due: To be confirmed