This report presents one-year and five-year age-standardised net survival estimates (see Background Note 1) for the 28 Cancer Networks of England, for patients who were diagnosed with a cancer of the oesophagus, stomach, colon, lung, breast (women) or cervix during 1997–2010 and followed up to 31 December 2011. One-year survival estimates are reported for patients diagnosed in 1997, 2002, 2006 and 2010, and five-year survival estimates for those diagnosed in 1997, 2002 and 2006.
The range in one-year survival between the Cancer Networks with the highest and lowest survival in 2010 was widest for women diagnosed with stomach cancer, at 23.6%, and narrowest for women diagnosed with breast cancer, at 3.4%. For five-year survival the range between the Cancer Networks in 2006 was widest for women diagnosed with stomach cancer, at 11.8%, and narrowest for women diagnosed with lung cancer, at 5.2%.
These estimates should not be used to rank Cancer Networks by their survival, because a change of just 1 or 2 % may radically alter the ranking of a given network.
One-year and five-year age-standardised net survival estimates for each of the six cancers are presented in tables and charts in the associated data section of this publication. These tables and charts show net survival estimates by Cancer Network, sex and calendar period. Maps (Figures 2–7) show the most recent survival estimates by Cancer Network and sex for patients diagnosed in 2010 (one-year survival) and 2006 (five-year survival). A summary map (Figure 8) shows the location of the Cancer Networks in England.
Further information about cancer survival estimates published by the Office for National Statistics (ONS) can be found in the Cancer Survival Quality and Methodology Information paper. Quality and Methodology Information papers are overview notes which pull together key qualitative information on the various dimensions of the quality of statistics as well as providing a summary of the methods used to compile the output. Information about key users of these statistics is also provided.
The Scottish Cancer Registry produces statistics on cancer in Scotland.
Statistics on cancer in Wales are produced by the Welsh Cancer Intelligence and Surveillance Unit.
The Northern Ireland Cancer Registry produces statistics on cancer in Northern Ireland.
In line with recent changes to the NHS, the functions, accountability and form of Cancer Networks are likely to change over the coming 12 months. ONS plan to review the format and content of the Cancer Survival by Cancer Network in England publication in line with these changes before the next annual update.
Key users of cancer survival estimates include the Department of Health, academics and researchers, cancer charities, cancer registries, other government organisations, researchers within ONS, the media, and the general public. The Department of Health uses cancer survival figures to brief parliamentary ministers, and as part of the evidence base to inform cancer policy and programmes, for example in drives to improve survival rates. Cancer survival estimates will also be used to measure progress against NHS Outcomes Framework indicators.
Academics and researchers use the figures to inform their own research. Similarly cancer registries and other government organisations use the figures to carry out individual and collaborative projects to apply subject knowledge to practice. Charities use the data so they can provide reliable and accessible information about cancer to a wide range of groups, including patients and health professionals via health awareness campaigns and cancer information leaflets/web pages. Researchers within ONS use the data to support further research and to publish alongside other National Statistics.
In ‘Improving Outcomes: A Strategy for Cancer’ (January 2011), the Department of Health stated that although improvements have been made in the quality of cancer services in England, a significant gap remains in survival compared with the European average. Survival estimates for cervical, colorectal and breast cancer are some of the lowest among Member States of the Organisation for Economic Co-operation and Development (OECD). The strategy document sets out how the Department of Health aims to improve outcomes for all cancer patients and improve cancer survival, with the aim of saving an additional 5,000 lives every year by 2014/15.
Outcomes strategies set out how the NHS, public health and social care services will contribute to the ambitions for progress agreed with the Secretary of State in each of the high-level outcomes frameworks. The indicators set for the NHS Outcomes Framework 2013 to 2014 – focus on measuring health outcomes include one- and five-year cancer survival indicators for all cancers combined, and for colorectal, breast and lung cancers combined.
Akaike H (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-23.
Ashley J (1990). The International Classification of Diseases: the structure and content of the Tenth Revision. Health Trends, 22, 135-7.
Cancer Research UK Cancer Survival Group (2004). Life tables for England and Wales by sex, calendar period, region and deprivation. London School of Hygiene and Tropical Medicine.
Danieli C, Remontet L, Bossard N, Roche L, Belot A (2012). Estimating net survival: the importance of allowing for informative censoring. Statistics in Medicine, 31, 775-786.
Department of Health (2000). The NHS Cancer Plan. London, Department of health.
Ellis L, Rachet B, Coleman MP (2007). Cancer survival indicators by Cancer Network: a methodolgical perspective. Health Statistics Quarterly, 36 (Winter), 36-41.
Expert Advisory Group on Cancer (1995). A policy framework for commissioning cancer services. London, Department of Health.
Lambert PC, Royston P (2009). Further development of flexible parametric models for survival analysis. Stata Journal, 9, 265-290.
Royston P, Parmar MK (2002). Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects. Statistics in Medicine, 21, 2175-2197.
StataCorp (2011). STATA statistical software, Version 12. College Station, Texas, Stata Corporation.
Ula Nura, Michel P Colemana, Sarah Whiteheadb and Bernard Racheta
This report was produced by the Cancer Research UK Cancer Survival Group at London School of Hygiene and Tropical Medicinea (LSHTM), the National Cancer Registry at the Office for National Statisticsb (ONS) and funded by the Department of Health.
The National Cancer Registry at the Office for National Statistics, the National Cancer Intelligence Network and the London School of Hygiene and Tropical Medicine wish to thank the Geographic Information Systems Team at West Midlands Cancer Intelligence Unit for providing the digital boundary data. They also acknowledge the work of the regional cancer registries in England, which provide the raw data for these analyses.
Net survival in a population of cancer patients is their survival from the cancer of interest in the absence of other causes of death. It was estimated at one and five years after diagnosis for each cancer, sex and year of diagnosis. Net survival was estimated with an excess hazard model in which the all-cause mortality is modelled as the sum of the excess (cancer-related) mortality hazard and the expected (or background) mortality. The background mortality is defined by life tables from the general population. This approach enables population-level cancer survival to be estimated in the absence of detailed data on the cause of death. To obtain an unbiased estimation of net survival, age needs to be carefully modelled to account for the informative censoring associated with age (Danieli et al., 2012).
We used flexible parametric models (Royston and Parmar, 2002) with age and year of diagnosis as main effects and an interaction between age and year of diagnosis. We also examined interactions between year and follow-up time and between age and follow-up time to deal with potential non-proportionality of the excess hazards over time since diagnosis. The Akaike Information Criterion (AIC) (Akaike, 1974) was used to select the best-fitting statistical model using the relative goodness of fit. The publicly available program, stpm2, was used to estimate net survival (Lambert and Royston, 2009). Analyses were performed in Stata 12 (Statacorp, 2011).
National cancer registration data for England were received from the National Cancer Registry at the Office for National Statistics (ONS), which collates cancer registrations submitted by regional cancer registries in England. The NHS Information Centre (NHS IC) updates these records with the registration of death or emigration. The data used in these analyses were extracted from the live database at ONS on 18 May 2012 and provided to the Cancer Research UK Cancer Survival Group at the London School of Hygiene and Tropical Medicine on 8 June 2012.
All adults (15–99 years) who were diagnosed with a first, invasive, primary, malignancy during the period 1997–2010 were eligible for inclusion in the analyses. We excluded patients who were diagnosed with a tumour that was benign (behaviour code 0), in situ (2) or of uncertain behaviour (1). Patients were excluded if their cancer was only registered from a death certificate. Patients with zero recorded survival time were included in the analyses with one day added to their survival. Table 2 shows the number of patients excluded and Table 3 shows the final number of patients in each Cancer Network who were included in the analyses.
|Malignancy||ICD-10 code2||Eligible for analysis||Exclusions||Patients included|
|N01||Lancashire and South Cumbria||3,063||3,234||8,015||14,438||14,883||1,259|
|N02||Greater Manchester & Cheshire||5,714||6,548||14,788||28,778||28,170||2,235|
|N03||Merseyside & Cheshire||4,146||4,620||10,742||21,948||19,898||1,574|
|N07||Humber & Yorkshire Coast||2,087||2,379||5,613||11,221||10,489||1,023|
|N21||North West London||1,833||2,042||5,810||9,933||13,320||857|
|N23||North East London||1,754||2,493||5,158||10,663||10,731||830|
|N24||South East London||1,882||2,376||5,523||11,356||12,127||904|
|N25||South West London||2,080||2,001||6,634||9,938||14,001||825|
|N28||Avon, Somerset & Wiltshire||3,415||3,151||10,335||12,872||19,763||1,522|
|N31||Central South Coast||3,383||3,327||11,048||14,264||20,704||1,212|
|N32||Surrey, West Sussex & Hampshire||1,773||1,562||5,649||7,428||11,825||566|
|N34||Kent & Medway||2,979||2,515||7,554||12,969||16,084||957|
|N36||North of England||5,286||7,907||17,391||37,386||29,211||2,442|
|Missing Cancer Network code||1||-||2||2||7||-|
Life tables were constructed for the years 1997, 2002, and 2006 using the mid-year population estimates and the mean annual number of deaths in the three years centred on those index years (Cancer Research UK Cancer Survival Group, 2004). Life tables for each year from 1997 to 2005 were created by linear interpolation. The life table for 2005 was used for 2006–10. Background mortality changes with time and varies by sex, age, socio-economic status and region, so life tables were created by single year of age, sex, region and deprivation quintile for each calendar year of death.
The age distribution of cancer patients at diagnosis changes with time and varies between Cancer Networks. Since survival also varies with age at diagnosis, robust summary comparisons of survival require control for these differences. The directly standardised overall survival figure for each cancer is a weighted average of the age-specific survival estimates, with standard weights taken from the proportionate distribution by age and sex of patients diagnosed in England and Wales during 1996–99.
Age-standardisation requires a set of survival estimates for each age group. It is not always possible to obtain an estimate for each combination of cancer, age group, sex and calendar year of diagnosis in geographic units with small populations because of the limited number of cases. In this situation, the missing estimate was replaced by the equivalent age-specific estimate for England.
A 95% confidence interval is a measure of the uncertainty around an estimate. It provides a range of values which contains the true population value with a 95% level of confidence.
Cancer Networks were formed in 2001 following the recommendations of the Calman–Hine report (Expert Advisory Group on Cancer, 1995) and the NHS Cancer Plan (Department of Health, 2000). The most recent Cancer Network boundaries were applied to the whole period 1991–2006, enabling geographic trends to be charted over time (Figure 8). Cancer Network populations range from 0.6 to 3.0 million (2002 figures), making them more suitable for detailed statistical comparison of survival than smaller health geographies such as Primary Care Trusts.
The role of Cancer Networks in the organisation of cancer services, and in improving regional equity in cancer management, makes them a meaningful unit with which to describe the geography of cancer survival in England (Ellis et al., 2007). In line with recent changes to the NHS, the functions, accountability and form of Cancer Networks are likely to change over the coming 12 months. ONS plan to review the format and content of the Cancer Survival by Cancer Network in England publication in line with these changes before the next annual update.
Cancers were defined by codes in the International Classification of Diseases, Tenth Revision (ICD-10) and International Classification of Diseases for Oncology, Second Edition (ICD-O-2) (Ashley, 1990). See Table 2.
A list of the names of those given pre-publication access to the statistics and written commentary is available in Pre-release Access List: Cancer Survival by Cancer Networks, England: Patients diagnosed 1997-2010 and followed up to 2011 (33.6 Kb Pdf) . The rules and principles which govern pre-release access are featured within the Pre-release Access to Official Statistics Order 2008.
Special extracts and tabulations of cancer data for England are available to order for a charge (subject to legal frameworks, disclosure control, resources and agreement of costs, where appropriate). Such enquiries should be made to:
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|Sarah Whitehead||+44 (0)1633 456021||Cancer Analysis Teamemail@example.com|