This statistic shows the number of registrations of newly diagnosed cases of colon cancer in England in 2022, by age group and gender. The group most affected by colon cancer was men aged 75 to 79 years, with *** thousand cases registered. It should, of course, be noted that the number of people in England in each age group varies and is therefore not necessarily a reflection of susceptibility to colon cancer.

This publication reports on newly diagnosed cancers registered in England during 2022. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document. Cancer registration estimates are provided for: • Incidence of cancer using groupings that incorporate both the location and type of cancer by combinations of gender, age, deprivation, and stage at diagnosis (where appropriate) for England, former Government office regions, Cancer alliances and Integrated care boards • Incidence and mortality (using ICD-10 3-digit codes) by gender and age group for England, former Government office regions, Cancer alliances and Integrated care boards This publication will report on 2022 cancer registrations only, trends will not be reported as the required re-stated populations for 2012 to 2020 are not expected to be published by the Office of National Statistics (ONS) until Winter 2024.

BackgroundColorectal cancer incidence in the UK and other high-income countries has been increasing rapidly among young adults. This is the first analysis of colorectal cancer incidence trends by sub-site and socioeconomic deprivation in young adults in a European country.MethodsWe examined age-specific national trends in colorectal cancer incidence among all adults (20–99 years) diagnosed during 1971–2014, using Joinpoint regression to analyse data from the population-based cancer registry for England. We fitted a generalised linear model to the incidence rates, with a maximum of two knots. We present the annual percentage change in incidence rates in up to three successive calendar periods, by sex, age, deprivation and anatomical sub-site.ResultsAnnual incidence rates among the youngest adults (20–39 years) fell slightly between 1971 and the early 1990s, but increased rapidly from then onwards. Incidence Rates (IR) among adults 20–29 years rose from 0.8 per 100,000 in 1993 to 2.8 per 100,000 in 2014, an average annual increase of 8%. An annual increase of 8.1% was observed for adults aged 30–39 years during 2005–2014. Among the two youngest age groups (20–39 years), the average annual increase for the right colon was 5.2% between 1991 and 2010, rising to 19.4% per year between 2010 (IR = 1.2) and 2014 (IR = 2.5). The large increase in incidence rates for cancers of the right colon since 2010 were more marked among the most affluent young adults. Smaller but substantial increases were observed for cancers of the left colon and rectum. Incidence rates in those aged 50 years and older remained stable or decreased over the same periods.ConclusionsDespite the overall stabilising trend of colorectal cancer incidence in England, incidence rates have increased rapidly among young adults (aged 20–39 years). Changes in the prevalence of obesity and other risk factors may have affected the young population but more research is needed on the cause of the observed birth cohort effect. Extension of mass screening may not be justifiable due to the low number of newly diagnosed cases but clinicians should be alert to this trend.

This statistic shows the amount of registrations of newly diagnosed cases of small intestine cancer in England in 2022, by age group and gender. With a total of *** cases in 2022, the age group most affected by small intestine cancer was men aged between 75 and 79 years. It should, of course, be noted that the number of people in England in each age group varies and is therefore not necessarily a reflection of susceptibility to this cancer.

In 2022, 55.8 males and 44.3 females per 100,000 population in England were registered as newly diagnosed with colon cancer. The rate of both females and males registered as newly diagnosed with colon cancer considerably decreased from the previous year. This statistic shows the rate of newly diagnosed cases of colon cancer per 100,000 population in England from 1995 to 2022, by gender.

This publication reports on newly diagnosed cancers registered in England during 2021. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document. Cancer registrations (incidence) are provided by: Diagnosis (ICD-10 3-digit codes) by gender, age group, geographic region, deprivation and stage at diagnosis for selected cancer sites Diagnosis (ICD-10 4-digit code) by gender and age group

The proportion of eligible men and women aged 60 to 74 invited for screening who had an adequate faecal occult blood test (FOBt) screening result in the previous 30 months.

RationaleBowel cancer screening supports early detection of cancer and polyps which are not cancers but may develop into cancers over time. About one in 20 people in the UK will develop bowel cancer during their lifetime. This indicator provides an opportunity to incentivise screening promotion and other local initiatives to increase coverage of bowel cancer screening. Improvements in coverage would mean more bowel cancers are detected at earlier, more treatable stages, and more polyps are detected and removed, reducing the risk of bowel cancer developing.

Definition of numeratorAdequately screened (numerator) is the number of eligible men and women who have had an adequate gFOBT screening result recorded in the past 30 months.

Definition of denominatorEligible population (denominator) is the number of men and women aged 60 to 74 years resident in the area (determined by postcode of residence) who are eligible for bowel cancer screening at a given point in time, excluding those whose recall has been ceased for clinical reasons (e.g. no functioning colon) or if they opt out of the programme.

CaveatsData for ICBs are estimated from local authority data. In most cases ICBs are coterminous with local authorities, so the ICB figures are precise. In cases where local authorities cross ICB boundaries, the local authority data are proportionally split between ICBs, based on population located in each ICB.The affected ICBs are:Bath and North East Somerset, Swindon and Wiltshire;Bedfordshire, Luton and Milton Keynes;Buckinghamshire, Oxfordshire and Berkshire West;Cambridgeshire and Peterborough;Frimley;Hampshire and Isle of Wight;Hertfordshire and West Essex;Humber and North Yorkshire;Lancashire and South Cumbria;Norfolk and Waveney;North East and North Cumbria;Suffolk and North East Essex;Surrey Heartlands;Sussex;West Yorkshire.Please be aware that the April 2019 to March 2020, April 2020 to March 2021 and April 2021 to March 2022 data covers the time period affected by the COVID19 pandemic and therefore data for this period should be interpreted with caution.This indicator gives screening coverage by local authority of residence. This is not the same as the indicator based on population registered with primary care organisations which include patients wherever they live. This is likely to result in different England totals depending on selected (registered or resident) population footprint.The indicator excludes women outside the target age range for the screening programme who may self-refer for screening.The data for bowel screening indicators has been refreshed for all years, back to the 2013 to 2014 financial year. This is due to a methodology change, to ensure the data periods run up to the end of March in the given financial year.

In 2022, 4.1 males and 2.9 females per 100,000 population in England were registered as newly diagnosed with cancer of the small intestine. The rate of registrations of newly diagnosed cases of small intestine cancer had a certain increase for the male population. This statistic shows the rate of newly diagnosed cases of small intestine cancer per 100,000 population in England from 1995 to 2022, by gender.

One-year and five-year net survival for adults (15-99) in England diagnosed with one of 29 common cancers, by age and sex.

This release summarises the diagnoses in 2019 registered by NDRS covering all registerable neoplasms (all cancers, all in situ tumours, some benign tumours and all tumours that have uncertain or unknown behaviours)

Source of original data: ONS [1].

National Cancer Registration And Analysis Service (NCRAS). (2020). Cancer Registration: Epidemiology of Colorectal Cancer (2000 - 2017). Public Health England. https://doi.org/10.25503/wd5j-e989.

• PSEUDO_TUMOURID (Project specific Pseudonymised Tumour ID)

• AGE_GROUP (age at diagnosis aggregated as <40, then in 5 year age bands to 90+)

• SEX (coded as 1=Male, 2=Female)

• DIAGNOSISYEAR (year of diagnosis)

• SITE_GROUP (ICD10 C18.0-C18.4 “proximal colon”, ICD10 C18.5-C18.7 “distal colon”, ICD10 C19-C20 “rectum”, ICD10 C18.8 and C18.9 “overlapping/ unspecified neoplasms of the colon”)

• STAGE_BEST_GROUP2012 (coded as 1, 2, 3, 4, 'U/UK' = U, 0, 6, ? and blanks. Tumours diagnosed pre 2012 classified "NA" i.e. Not Applicable due to poor completion of stage before 2012.

• MORPH_GROUP (adenocarcinomas (between '814%' and '838%'), mucinous (like '848%) and other). Coded in ICD-O-2.

• DTH_CAUSE_UNDERLYING2 ("CRC", "no CRC" in case of cause of death from colorectal cancer or from any other cause, respectively). Cause of death is based primarily on underlying cause of death and only 1a then 1b, 1c, 2 if the preceding field is null.

• VITALSTATUS (coded as A =Alive, D =Dead, X =Exit posting)

• DAYS_DX_VITALSTATUS (The number of days between diagnosis and vital status date). Provided when data quality sufficient and at least date/month of diagnosis & vital status dates known.

• GRADE (grade of tumour coded as GX = Grade of differentiation is not appropriate or cannot be assessed G1 = Well differentiated G2 = Moderately differentiated G3 = Poorly differentiated G4 = Undifferentiated / anaplastic) • SCREENDETECTED (N = No, Y = Yes, 9 = Not known). From 2006 when national screening programme started.

• BASISOFDIAGNOSIS (Non-microscopic: 0 = Death certificate 1 = Clinical: Diagnosis made before death without (2-7) 2 = Clinical investigation: Includes all diagnostic techniques without a tissue diagnosis 4 = Specific tumour markers: Includes biochemical and/or immunological markers which are site specific Microscopic: 5 = Cytology: Examination of cells whether from a primary or secondary site, including fluids aspirated using endoscopes or needles. Also including microscopic examination of peripheral blood films and trephine bone marrow aspirates 6 = Histology of a metastases: Includes autopsy specimens 7 = Histology of a primary tumour: Includes all cutting and bone marrow biopsies. Also includes autopsy specimens of a primary tumour 9 = Unknown, e.g. PAS or HISS record only)

Whenever it is possible and practicable to do so, data released by PHE will be anonymous and made available under an Open Government License. To render the data anonymous it must be stripped of direct identifiers and privacy by design methods applied in line with the rules in the ISB Anonymisation Standard for Publishing Health and Social Care Data Specification (2013).

The Cancer Awareness Measure (CAM) is a validated set of questions designed to reliably assess awareness of cancer. It was developed by Cancer Research UK, University College London, King's College London and University of Oxford in 2007-8, and is also known as the National Awareness and Early Diagnosis Initiative Cancer Awareness Measure (NAEDI-CAM). The survey includes measures of awareness of signs and symptoms of cancer, cancer risk factors, age-related risk, the bowel cancer screening programme and potential barriers to seeing the GP. Since 2008, the CAM has been used to collect data every two years from a sample representative of Great Britain (England, Scotland and Wales). As part of the wider cancer strategy, the NHS Cancer Action Team funded the Merseyside and Cheshire Cancer Network (MCCN) to survey levels of cancer awareness in the local population. The MCCN subsequently commissioned the University of Liverpool to carry out this work.

The aims of the survey were to contribute to the national picture of levels of cancer awareness and generate evidence to support MCCN strategies for identifying and addressing inequalities across the network. The survey used the nationally validated Cancer Awareness Measure (CAM) which has been developed by a Cancer Research UK team to assess awareness of cancer amongst the general population.

Respondents were identified from a random sample of 5,250 residents accessed through the edited versions on the Electoral Rolls for the MCCN region. The MCCN region includes seven Primary Care Trusts (PCTs) (Liverpool PCT, Warrington PCT, Wirral PCT, Halton and St Helens PCT, Knowsley PCT, Sefton PCT, Western Cheshire PCT).

This publication reports on newly diagnosed cancers registered in England during 2023. Information is supplied as: a summary report showing key findings; spreadsheet tables (counts and age-standardised rates); an interactive dashboard (counts, age-standardised rates, non-standardised rates and age-specific rates); and a methodology document.

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

Summary-level GWAS data for 53 traits generated by Genomics plc as presented in:

Thompson D. et al. UK Biobank release and systematic evaluation of optimised polygenic risk scores for 53 diseases and quantitative traits (https://doi.org/10.1101/2022.06.16.22276246)

If you have any questions or comments regarding these files, please contact Genomics plc at research@genomicsplc.com

NOTES

These analyses were carried out using the full UK Biobank (UKB) imputation data release (v3b). After removal of exclusions and withdrawals, a subset of 337,151 UKB individuals, the White British Unrelated (WBU) subgroup, was defined as the intersection of two sample groups created by Bycroft et al 2018 (Nature 562, 203-209): the ‘White British ancestry’ group (UKB Data Field 22006) and the ‘used in genetic principal components’ group (UKB Data Field 22020), the latter being high quality samples that were filtered to avoid closely related individuals. All GWAS analyses were performed on the WBU subgroup.

Phenotypes were defined as described in Supplementary Table 1 ‘Phenotype definitions’ using a combination of Hospital Episode Statistics, Cancer Registry reports (where applicable) and self-report responses.

All analyses included Age at assessment, sex (for non-sex specific traits), genotyping chip, and 10 principal components as covariates.

GWAS summary statistics for each trait were generated by applying PLINK 2.0 to the WBU subgroup, using a logistic regression for disease traits, and a linear regression model for quantitative traits. For chromosome X variants males were treated as having 0 or 2 alternative alleles.

The results are not adjusted for genomic control.

DATA FILE CONTENT DESCRIPTION (DISEASE TRAITS)

    cpra
    Variant ID in ‘CPRA’ format. Position reflects position in b37


    chrom
    Chromosome


    pos
    Position in base pairs (b37, 1-based)


    alt
    Alternative allele (effect allele)


    beta
    Effect size (log odds ratio)


    standard_error
    Standard error of beta


    minus_log10_p
    Minus log(base 10) of P-value


    ref
    Reference allele (non-effect allele)


    ncase
    Number of cases


    ncontrol
    Number of controls

DATA FILE CONTENT DESCRIPTION (QUANTITATIVE TRAITS)

    cpra
    Variant ID in ‘CPRA’ format. Position reflects position in b37


    chrom
    Chromosome


    pos
    Position in base pairs (b37, 1-based)


    alt
    Alternative allele (effect allele)


    beta
    Effect size (log odds ratio


    standard_error
    Standard error of beta


    minus_log10_p
    Minus log(base 10) of P-value


    ref
    Reference allele (non-effect allele)


    ntotal
    Total sample size

PHENOTYPE CODES

The following is a list of traits and their phenotype codes (as used in file naming).

DISEASE TRAITS

    Age-related macular degeneration
    AMD


    Alzheimer's disease
    AD


    Asthma
    AST


    Atrial fibrillation
    AF


    Bipolar disorder
    BD


    Bowel cancer
    CRC


    Breast cancer
    BC


    Cardiovascular disease
    CVD


    Coeliac disease
    CED


    Coronary artery disease
    CAD


    Crohn's disease
    CD


    Epithelial ovarian cancer
    EOC


    Hypertension
    HT


    Ischaemic stroke
    ISS


    Melanoma
    MEL


    Multiple sclerosis
    MS


    Osteoporosis
    OP


    Prostate cancer
    PC


    Parkinson's disease
    PD


    Primary open angle glaucoma
    POAG


    Psoriasis
    PSO


    Rheumatoid arthritis
    RA


    Schizophrenia
    SCZ


    Systemic lupus erythematosus
    SLE


    Type 1 diabetes
    T1D


    Type 2 diabetes
    T2D


    Ulcerative colitis
    UC


    Venous thromboembolic disease
    VTE

QUANTITATIVE TRAITS

    Age at menopause
    AAM


    Apolipoprotein A1
    APOEA


    Apolipoprotein B
    APOEB


    Body mass index
    BMI


    Calcium
    ACALMD


    Docosahexaenoic acid
    DOA


    Estimated bone mineral density T-score
    EBMDT


    Estimated glomerular filtration rate (creatinine based)
    EGCR


    Estimated glomerular filtration rate (cystatin based)
    EGCY


    Glycated haemoglobin
    HBA1C_DF


    High density lipoprotein cholesterol
    HDL


    Height
    HEIGHT


    Intraocular pressure
    IOP


    Low density lipoprotein cholesterol
    LDL_SF


    Omega-6 fatty acids
    OSFA


    Omega-3 fatty acids
    OTFA


    Phosphatidylcholines
    PDCL


    Phosphoglycerides
    PHG


    Polyunsaturated fatty acids
    PFA


    Resting heart rate
    RHR


    Remnant cholesterol (Non-HDL, Non-LDL cholesterol)
    RMNC


    Sphingomyelins
    SGM


    Total cholesterol
    TCH


    Total fatty acids
    TFA


    Total triglycerides
    TTG

Legacy unique identifier: P00225

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

National Cancer Registration and Analysis Service (NCRAS). (2019). Cancer Registration: Trends in incidence of common cancer in adolescents and young adults in England (1985-2016) [Data set]. Public Health England. https://doi.org/10.25503/cbbh-vg22 This data set contains patient level data for common cancers in adolescents and young adults in England between the years 1985 to 2016. Male cancers included in the dataset are: testis (C62), non-Hodgkin lymphoma (NHL) (C82-C85), rectosigmoid junction/rectal (C19/C20), and colon (C18) Female cancers include: breast (C50), cervix uteri (C53), thyroid (C73), rectosigmoid junction/rectal (C19/C20), and colon (C18) Variables included: • Pseudonymised Patient ID • Patient age (in 5- or 10-year bands) • Sex (1=M, 2=F) • Diagnosis year (in 5-year bands) • Basis of diagnosis (coded as 1, 2, 3, 4, 5, 6, 7, 9, &) • Death certificate only (DCO) (coded as Y=Yes and N=No) • 4-digit ICD10 code (for colon) • 3-digit ICD10 code (for all other sites) • Histology code/description (5-digit code) • Grade of cancer • Laterality (if relevant, coded as; 1, 2, 3, 9, &, B, L, M, R) • Pathology stage (coded as 0,1, 2, 4, 5, 6, ?, 1A, 1A1, 1A2, 1B, 1B1, 1B2, 1C, 1E, 1S, 2A, 2A1, 2B, 2C, 3A, 3B, 3C, 4A, 4B, U, X) • Stage best (coded as, 0, 1, 2, 3, 4, 5, 6, &, ?, 1A, 1A1, 1A2, 1B, 1B1, 1B2, 1C, 1E, 1S, 2A, 2A1, 2A2, 2B, 2C, 2E, 2S, 3A, 3B, 3E, 3S, 4A, 4B, 4C, 4S, U, X) • Quintile deprivation index from 2015 (for years 2012-2016) (Quintile score [1-5], describing income deprivation where 1= least deprived to 5= most deprived) Data for years 1985-1994 has been extracted from the ONS Incidence Dataset. Data for years 1995-2016 has been extracted from Cancer Registration database. Caution must be taken when using older data as it is not of as high a quality as data from more recent years. Differences in the registration process over time will explain some differences seen in the data. Additionally, improvements over time in the coding accuracy and methods used to identify cancers (e.g. biopsy, imaging) will be responsible for some of the increases in the registration of certain cancers. More information about the cancer registration process and database used can be found here: Data Resource Profile: National Cancer Registration Dataset in England (https://academic.oup.com/ije/advance-article/doi/10.1093/ije/dyz076/5476570). 'Histology coded' applies different coding systems depending on the diagnosis year of the given tumour. Tumours diagnosed from 1985-1989 are coded using MOTNAC (Manual of Tumor Nomenclature and Coding), tumours from 1990-1994 use ICD-O, and cases from 1995-2016 use ICD10. Histolology coded description and pathology stage are not available for data from 1985-1994. The variable 'Stage best' is not equivalent in the two different datasets and should not be compared.

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