A novel ecological methodology for constructing ethnic-majority life tables in the absence of individual ethnicity information

Bidirectional association between allergic rhinitis and attention-deficit/hyperactivity disorder: A systematic review and meta-analysis

BACKGROUND

This meta-epidemiological study seeks to further investigate the reciprocal relationship between allergic rhinitis (AR) and attention-deficit/hyperactivity disorder (ADHD).

METHODS

A comprehensive search of the databases was conducted up to March 3, 2024. We performed a synthesis and meta-analysis of odds ratios and their corresponding 95 % confidence intervals using Stata 14.0. Funnel plot analysis and Egger's regression test were utilized to assess potential publication bias.

RESULTS

Eighteen articles involving 4,289,444 participants were included. AR patients had an increased risk of developing ADHD (OR: 1.83; 95 % CI: 1.37-2.43), while ADHD patients were also more likely to have AR (OR: 1.38; 95 % CI: 1.11-1.72). Subgroup analysis indicated a predisposition of AR patients to autism spectrum disorder (OR: 1.34; 95 % CI: 0.86-1.0) and a higher risk of ADHD in cohort studies (OR: 1.90; 95 % CI: 1.26-2.88). Female AR patients were more likely to develop ADHD than males (OR: 1.86; 95 % CI: 1.43-2.43), and children aged ≤8 years with AR were at greater risk for ADHD compared to older children (OR: 1.75; 95 % CI: 1.14-2.69).

CONCLUSIONS

This meta-analysis confirms a bidirectional association between AR and ADHD, indicating that they are mutually independent risk factors.

The fraction of life years lost after diagnosis (FLYLAD): a person-centred measure of cancer burden

BACKGROUND

Cancer control initiatives are informed by quantifying the capacity to reduce cancer burden through effective interventions. Burden measures using health administrative data are a sustainable way to support monitoring and evaluating of outcomes among patients and populations. The Fraction of Life Years Lost After Diagnosis (FLYLAD) is one such burden measure. We use data on Aboriginal and non-Aboriginal South Australians from 1990 to 2010 to show how FLYLAD quantifies disparities in cancer burden: between populations; between sub-population cohorts where stage at diagnosis is available; and when follow-up is constrained to 24-months after diagnosis.

METHOD

FLYLADcancer is the fraction of years of life expectancy lost due to cancer (YLLcancer) to life expectancy years at risk at time of cancer diagnosis (LYAR) for each person. The Global Burden of Disease standard life table provides referent life expectancies. FLYLADcancer was estimated for the population of cancer cases diagnosed in South Australia from 1990 to 2010. Cancer stage at diagnosis was also available for cancers diagnosed in Aboriginal people and a cohort of non-Aboriginal people matched by sex, year of birth, primary cancer site and year of diagnosis.

RESULTS

Cancers diagnoses (N = 144,891) included 777 among Aboriginal people. Cancer burden described by FLYLADcancer was higher among Aboriginal than non-Aboriginal (0.55, 95% CIs 0.52-0.59 versus 0.39, 95% CIs 0.39-0.40). Diagnoses at younger ages among Aboriginal people, 7 year higher LYAR (31.0, 95% CIs 30.0-32.0 versus 24.1, 95% CIs 24.1-24.2) and higher premature cancer mortality (YLLcancer = 16.3, 95% CIs 15.1-17.5 versus YLLcancer = 8.2, 95% CIs 8.2-8.3) influenced this. Disparities in cancer burden between the matched Aboriginal and non-Aboriginal cohorts manifested 24-months after diagnosis with FLYLADcancer 0.44, 95% CIs 0.40-0.47 and 0.28, 95% CIs 0.25-0.31 respectively.

CONCLUSION

FLYLAD described disproportionately higher cancer burden among Aboriginal people in comparisons involving: all people diagnosed with cancer; the matched cohorts; and, within groups diagnosed with same staged disease. The extent of disparities were evident 24-months after diagnosis. This is evidence of Aboriginal peoples' substantial capacity to benefit from cancer control initiatives, particularly those leading to earlier detection and treatment of cancers. FLYLAD's use of readily available, person-level administrative records can help evaluate health care initiatives addressing this need.

Burden of allergic disease among ethnic minority groups in high-income countries

The COVID‐19 pandemic raised acute awareness regarding inequities and inequalities and poor clinical outcomes amongst ethnic minority groups. Studies carried out in North America, the UK and Australia have shown a relatively high burden of asthma and allergies amongst ethnic minority groups. The precise reasons underpinning the high disease burden are not well understood, but it is likely that this involves complex gene–environment interaction, behavioural and cultural elements. Poor clinical outcomes have been related to multiple factors including access to health care, engagement with healthcare professionals and concordance with advice which are affected by deprivation, literacy, cultural norms and health beliefs. It is unclear at present if allergic conditions are intrinsically more severe amongst patients from ethnic minority groups. Most evidence shaping our understanding of disease pathogenesis and clinical management is biased towards data generated from white population resident in high‐income countries. In conjunction with standards of care, it is prudent that a multi‐pronged approach towards provision of composite, culturally tailored, supportive interventions targeting demographic variables at the individual level is needed, but this requires further research and validation. In this narrative review, we provide an overview of epidemiology, sensitization patterns, poor clinical outcomes and possible factors underpinning these observations and highlight priority areas for research.

The changing health needs of the UK population

The demographics of the UK population are changing and so is the need for health care. In this Health Policy, we explore the current health of the population, the changing health needs, and future threats to health. Relative to other high-income countries, the UK is lagging on many health outcomes, such as life expectancy and infant mortality, and there is a growing burden of mental illness. Successes exist, such as the striking improvements in oral health, but inequalities in health persist as well. The growth of the ageing population relative to the working-age population, the rise of multimorbidity, and persistent health inequalities, particularly for preventable illness, are all issues that the National Health Service (NHS) will face in the years to come. Meeting the challenges of the future will require an increased focus on health promotion and disease prevention, involving a more concerted effort to understand and tackle the multiple social, environmental, and economic factors that lie at the heart of health inequalities. The immediate priority of the NHS will be to mitigate the wider and long-term health consequences of the COVID-19 pandemic, but it must also strengthen its resilience to reduce the impact of other threats to health, such as the UK leaving the EU, climate change, and antimicrobial resistance.

Life Expectancy of the Ethnically Mixed: Register-Based Evidence from Native Finns

As the ethnic composition around the world is becoming more diverse, the need to produce vital statistics for ethnically mixed populations is continuously increasing. Our aim is to provide the first life expectancy estimates for individuals with uniform Finnish, uniform Swedish, and mixed Finnish-Swedish backgrounds, based on individuals in the native population of Finland who can be linked to both their parents. Life expectancy at birth in the period 2005–2015 was calculated from population and mortality numbers at the one-year level based on each person’s sex, year of birth, and the unique ethnolinguistic affiliation of the index person and each parent. Swedish-registered individuals with Swedish-registered parents had the longest life expectancy at birth, or 85.68 years (95% CI: 85.60–85.77) for females and 81.36 for males (95% CI: 81.30–81.42), as compared to 84.76 years (95% CI: 84.72–84.79) and 78.89 years (95% CI: 78.86–78.92) for Finnish-registered females and males with Finnish-registered parents. Persons with mixed backgrounds were found in between those with uniform Finnish and uniform Swedish backgrounds. An individual’s own ethnolinguistic affiliation is nevertheless more important for longevity than parental affiliation. Similar register-based analyses for other countries with mixed populations would be useful.

Correcting inaccurate background mortality in excess hazard models through breakpoints

BACKGROUND

Methods for estimating relative survival are widely used in population-based cancer survival studies. These methods are based on splitting the observed (the overall) mortality into excess mortality (due to cancer) and background mortality (due to other causes, as expected in the general population). The latter is derived from life tables usually stratified by age, sex, and calendar year but not by other covariates (such as the deprivation level or the socioeconomic status) which may lack though they would influence background mortality. The absence of these covariates leads to inaccurate background mortality, thus to biases in estimating the excess mortality. These biases may be avoided by adjusting the background mortality for these covariates whenever available.

METHODS

In this work, we propose a regression model of excess mortality that corrects for potentially inaccurate background mortality by introducing age-dependent multiplicative parameters through breakpoints, which gives some flexibility. The performance of this model was first assessed with a single and two breakpoints in an intensive simulation study, then the method was applied to French population-based data on colorectal cancer.

RESULTS

The proposed model proved to be interesting in the simulations and the applications to real data; it limited the bias in parameter estimates of the excess mortality in several scenarios and improved the results and the generalizability of Touraine's proportional hazards model.

CONCLUSION

Finally, the proposed model is a good approach to correct reliably inaccurate background mortality by introducing multiplicative parameters that depend on age and on an additional variable through breakpoints.

Life Expectancy of White and Non-White Elite Heavyweight Boxers

BACKGROUND

In post-industrial countries, ethnic minorities suffer poorer health and premature deaths. The present study examined ethnic differences in life expectancy and related features among elite heavyweight boxers.

METHODS

Dates of birth and death, anthropometry, and championship years were gathered from media archives for champions and challengers (never been a champion) between years 1889 and 2019. Cox regression adjusted for age at contest, nationality, BMI, champion/challenger status, and number of contests was used to assess survival.

RESULTS

All 237 boxers, 83 champions (37.3% whites) and 154 challengers (61.0% whites), who contested for heavyweight championships were identified. By 2019, 110 (75 whites, 34 non-whites) were known to have died. Non-white boxers died at an earlier age than whites boxers (mean ± SD = 59.8 ± 14.2 years versus 67.3 ± 16.4 years, p = 0.018) and had shorter survival: HR = 2.13 (95% CI = 1.4-3.3). Among non-white boxers, deaths were higher from neurological disorders: OR = 8.2 (95% CI = 1.3-13.5) and accidents: OR = 15.1 (95% CI = 2.3-98.2), while death from natural causes was lower: OR = 0.2 (95% CI = 0.03-0.8). After boxing careers, fewer non-white boxers had non-manual jobs (34.4% versus 71.8%) than manual (34.4% versus 19.7%) or were unemployed (28.1% versus 2.8%). Reported substance abuse was similar across ethnicity (8.0% versus 8.8%) but conviction rates were higher among non-white boxers (17.6%) than white (1.3%).

CONCLUSIONS

Compared with white boxers, non-white boxers tend to die younger with excess neurological and accidental deaths, and they have lower social positions in later life. Sporting authorities should reappraise the wisdom of permitting head injuries in sport and monitor and support the health and wellbeing of sports men and women after retirement.

Ethnic density and other neighbourhood associations for mortality in severe mental illness: a retrospective cohort study with multi-level analysis from an urbanised and ethnically diverse location in the UK

BACKGROUND

Neighbourhood social context might play a role in modifying mortality outcomes in severe mental illness, but has received little attention to date. Therefore, we aimed to assess in an ethnically diverse and urban location the association of neighbourhood-level characteristics and individual-level factors for all-cause, natural-cause, and unnatural-cause mortality in those with severe mental illness.

METHODS

We did a retrospective cohort study using a case-registry from a large secondary mental health-care Trust in an ethnically diverse and urban location in south London, UK. Linked data for deaths and areas of residence were identified from the case-registry. We included all individuals aged 15 years or more at the time of diagnosis for a severe mental illness from Jan 1, 2007, to Dec 31, 2014. We used individual-level information in our analyses, such as gender, marital status, and the presence of current or previous substance use disorders. We assessed neighbourhood or area-level indicators at the Lower Super Output Area level. Association of neighbourhood-level characteristics, which included the interaction between ethnicity and own ethnic density, deprivation, urbanicity, and social fragmentation, alongside individual-level factors for all-cause, natural-cause, and unnatural-cause mortality in those with severe mental illness was assessed.

FINDINGS

A total of 18 201 individuals were included in this cohort for analyses, with a median follow-up of 6·36 years. There were 1767 (9·7%) deaths from all causes, 1417 (7·8%) from natural causes, and 192 (1·1%) from unnatural causes. In the least ethnically dense areas, the adjusted rate ratio (aRR) for all-cause mortality in ethnic minority groups with severe mental illness compared with white British people with severe mental illness were similar (aRR 0·96, 95% CI 0·71-1·29); however in the highest ethnic density areas, ethnic minority groups with severe mental illness had a lower risk of death (aRR 0·52, 95% CI 0·38-0·71; p<0·0001), with similar trends for natural-cause mortality (p=0·071 for statistical interaction). In the cohort with severe mental illness, residency in deprived, urban, and socially fragmented neighbourhoods was not associated with higher mortality rates. Compared with the general population, age-standardised and gender-standardised mortality ratios were elevated in the cohort with severe mental illness across all neighbourhood-level characteristics assessed.

INTERPRETATION

For ethnic minority groups with severe mental illness, residency in areas of higher own-group ethnic density is associated with lower mortality compared to white British groups with severe mental illness.

FUNDING

Health Foundation, National Institute for Health Research, EU Seventh Framework, and National Institute of Mental Health.

Deprivation-specific life tables using multivariable flexible modelling - trends from 2000-2002 to 2010-2012, Portugal

BACKGROUND

Completing mortality data by information on possible socioeconomic inequalities in mortality is crucial for policy planning. The aim of this study was to build deprivation-specific life tables using the Portuguese version of the European Deprivation Index (EDI) as a measure of area-level socioeconomic deprivation, and to evaluate mortality trends between the periods 2000-2002 and 2010-2012.

METHODS

Statistics Portugal provided the counts of deaths and population by sex, age group, calendar year and area of residence (parish). A socioeconomic deprivation level was assigned to each parish according to the quintile of their national EDI distribution. Death counts were modelled within the generalised linear model framework as a function of age, deprivation level and calendar period. Mortality Rate Ratios (MRR) were estimated to evaluate variations in mortality between deprivation groups and periods.

RESULTS

Life expectancy at birth increased from 74.0 and 80.9 years in 2000-2002, for men and women, respectively, and to 77.6 and 83.8 years in 2010-2012. Yet, life expectancy at birth differed by deprivation, with, compared to least deprived population, a deficit of about 2 (men) and 1 (women) years among most deprived in the whole study period. The higher mortality experienced by most deprived groups at birth (in 2010-2012, mortality rate ratios of 1.74 and 1.29 in men and women, respectively) progressively disappeared with increasing age.

CONCLUSIONS

Persistent differences in mortality and life expectancy were observed according to ecological socioeconomic deprivation. These differences were larger among men and mostly marked at birth for both sexes.

Adjusting Expected Mortality Rates Using Information From a Control Population: An Example Using Socioeconomic Status

Expected or reference mortality rates are commonly used in the calculation of measures such as relative survival in population-based cancer survival studies and standardized mortality ratios. These expected rates are usually presented according to age, sex, and calendar year. In certain situations, stratification of expected rates by other factors is required to avoid potential bias if interest lies in quantifying measures according to such factors as, for example, socioeconomic status. If data are not available on a population level, information from a control population could be used to adjust expected rates. We have presented two approaches for adjusting expected mortality rates using information from a control population: a Poisson generalized linear model and a flexible parametric survival model. We used a control group from BCBaSe-a register-based, matched breast cancer cohort in Sweden with diagnoses between 1992 and 2012-to illustrate the two methods using socioeconomic status as a risk factor of interest. Results showed that Poisson and flexible parametric survival approaches estimate similar adjusted mortality rates according to socioeconomic status. Additional uncertainty involved in the methods to estimate stratified, expected mortality rates described in this study can be accounted for using a parametric bootstrap, but this might make little difference if using a large control population.

Life tables for global surveillance of cancer survival (the CONCORD programme): data sources and methods

BACKGROUND

We set out to estimate net survival trends for 10 common cancers in 279 cancer registry populations in 67 countries around the world, as part of the CONCORD-2 study. Net survival can be interpreted as the proportion of cancer patients who survive up to a given time, after eliminating the impact of mortality from other causes (background mortality). Background mortality varies widely between populations and over time. It was therefore necessary to construct robust life tables that accurately reflected the background mortality in each of the registry populations.

METHODS

Life tables of all-cause mortality rates by single year of age and sex were constructed by calendar year for each population and, when possible, by racial or ethnic sub-groups. We used three different approaches, based on the type of mortality data available from each registry. With death and population counts, we adopted a flexible multivariable modelling approach. With unsmoothed mortality rates, we used the Ewbank relational method. Where no data were available from the registry or a national statistical office, we used the abridged UN Population Division life tables and interpolated these using the Elandt-Johnson method. We also investigated the impact of using state- and race-specific life tables versus national race-specific life tables on estimates of net survival from four adult cancers in the United States (US).

RESULTS

We constructed 6,514 life tables covering 327 populations. Wide variations in life expectancy at birth and mortality by age were observed, even within countries. During 1995-99, life expectancy was lowest in Nigeria and highest in Japan, ranging from 47 to 84 years among females and 46 to 78 years among males. During 2005-09, life expectancy was lowest in Lesotho and again highest in Japan, ranging from 45 to 86 years among females and 45 to 80 years among males. For the US, estimates of net survival differed by up to 4% if background mortality was fully controlled with state- and race-specific life tables, rather than with national race-specific life tables.

CONCLUSIONS

Background mortality varies worldwide. This emphasises the importance of using population-specific life tables for geographic and international comparisons of net survival.

Do pre-diagnosis primary care consultation patterns explain deprivation-specific differences in net survival among women with breast cancer? An examination of individually-linked data from the UK West Midlands cancer registry, national screening programme and Clinical Practice Research Datalink

BACKGROUND

In England and Wales breast cancer survival is higher among more affluent women. Our aim was to investigate the potential of pre-diagnostic factors for explaining deprivation-related differences in survival.

METHODS

Individually-linked data from women aged 50-70 in the West Midlands region of England, diagnosed with breast cancer 1989-2006 and continuously eligible for screening, was retrieved from the cancer registry, screening service and Clinical Practice Research Datalink. Follow-up was to the end of July 2012. Deprivation was measured at small area level, based on the quintiles of the income domain of the English indices of deprivation. Consultation rates per woman per week, time from last breast-related GP consultation to diagnosis, and from diagnosis to first surgery were calculated. We estimated net survival using the non-parametric Pohar-Perme estimator.

RESULTS

The rate of primary care consultations was similar during the 18 months prior to diagnosis in each deprivation group for breast and non-breast symptoms. Survival was lower for more deprived women from 4 years after diagnosis. Lower net survival was associated with more advanced extent of disease and being non-screen-detected. There was a persistent trend of lower net survival for more deprived women, irrespective of the woman's obesity, alcohol, smoking or comorbidity status. There was no significant variation in time from last breast symptom to diagnosis by deprivation. However, women in more deprived categories experienced significantly longer periods between cancer diagnosis and first surgery (mean = 21.5 vs. 28.4 days, p = 0.03). Those whose surgery occurred more than 12 weeks following their cancer diagnosis had substantially lower net survival.

CONCLUSIONS

Our data suggest that although more deprived women with breast cancer display lifestyle factors associated with poorer outcomes, their consultation frequency, comorbidities and the breast cancer symptoms they present with are similar. We found weak evidence of extended times to surgical treatment among most deprived women who were not screen-detected but who presented with symptoms in primary care, which suggests that treatment delay may play a role. Further investigation of interrelationships between these variables within a larger dataset is warranted.

No 'cure' within 12 years of diagnosis among breast cancer patients who are diagnosed via mammographic screening: women diagnosed in the West Midlands region of England 1989-2011

BACKGROUND

We have previously reported that there is little evidence of population 'cure' among two populations of women diagnosed with invasive breast cancer. 'Cure' has not yet been examined in the context of screen-detection.

PATIENTS AND METHODS

We examined cancer registry data on 19 800 women aged 50-70, diagnosed with a primary, invasive, non-metastatic breast cancer between 1 April 1989 and 31 March 2011 in the West Midlands region of England, linked to Hospital Episode Statistics (HES) and the National Breast Screening Service (NBSS). Follow-up was complete on all women up to 31 July 2012. Analyses were stratified by screening status, age, tumour stage, deprivation and ethnicity. We estimated net survival for the whole cohort and each subgroup. Population 'cure' was evaluated by fitting flexible parametric log-cumulative excess hazard regression models in which the excess hazard of breast cancer death was assumed to be equal to zero after a given follow-up time.

RESULTS

There was an overall lack of evidence for 'cure'. Across all subgroups examined, the general pattern was that of a continuous decrease in net survival over time, with no obvious asymptotic tendency within 12 years of follow-up. Model-based analyses confirmed this observation.

CONCLUSIONS

Despite dramatic improvements in survival over past decades, diagnosis with breast cancer remains associated with a small but persistent increased risk of death for all groups of women, including those whose cancer is detected asymptomatically. These findings are unlikely to be due to methodological inadequacies. Communication of these long-term consequences of breast cancer among women recently diagnosed and to those considering undergoing screening should take due consideration of these patterns.

What might explain deprivation-specific differences in the excess hazard of breast cancer death amongst screen-detected women? Analysis of patients diagnosed in the West Midlands region of England from 1989 to 2011

BACKGROUND

Breast cancer survival is higher in less deprived women, even amongst women whose tumor was screen-detected, but reasons behind this have not been comprehensively investigated.

METHODS

The excess hazard of breast cancer death in 20,265 women diagnosed with breast cancer, followed up to 2012, was estimated for screen-detected and non-screen-detected women, comparing more deprived to less deprived women using flexible parametric models. Models were adjusted for individual and tumor factors, treatment received and comorbidity. For screen-detected women, estimates were also corrected for lead-time and overdiagnosis.

RESULTS

The excess hazard ratio (EHR) of breast cancer death in the most deprived group, adjusted only for age and year of diagnosis, was twice that of the least deprived among screen-detected women (EHR=2.12, 95%CI 1.48-2.76) and 64% higher among non-screen-detected women (EHR=1.64, 95%CI 1.41-1.87). Adjustment for stage at diagnosis lowered these estimates by 25%. Further adjustment had little extra impact. In the final models, the excess hazard for the most deprived women was 54% higher (EHR=1.54, 95%CI 1.10-1.98) among screen-detected women and 39% higher (EHR=1.39, 95%CI 1.20-1.59) among non-screen-detected women.

CONCLUSION

A persistent socio-economic gradient in breast cancer-related death exists in this cohort, even for screen-detected women. The impact of differential lifestyles, management and treatment warrant further investigation.

Life expectancy of different ethnic groups using death records linked to population census data for 4.62 million people in Scotland

Background

Few countries record the data needed to estimate life expectancy by ethnic group. Such information is helpful in assessing the extent of health inequality.

Method

Life tables were created using 3 years of deaths (May 2001–April 2004) linked to Scottish 2001 Census data for 4.62 million individuals with self-reported ethnicity. We created 8 ethnic groups based on the census definitions, each with at least 5000 individuals and 40 deaths. Life expectancy at birth was calculated using the revised Chiang method.

Results

The life expectancy of White Scottish males at birth was 74.7 years (95% CI 74.6 to 74.8), similar to Mixed Background (73.0; 70.2 to 75.8) and White Irish (75.0; 74.0 to 75.9), but shorter than Indian (80.9; 78.4 to 83.4), Pakistani (79.3; 76.9 to 81.6), Chinese (79.0; 76.5 to 81.5), Other White British (78.9; 78.6 to 79.2) and Other White (77.2; 76.4 to 78.1). The life expectancy of White Scottish females was 79.4 years (79.3 to 79.5), similar to mixed background (79.3; 76.6 to 82.0), but shorter than Pakistani (84.6; 82.0 to 87.3), Chinese (83.4; 81.1 to 85.7), Indian (83.3; 80.7 to 85.9), Other White British (82.6; 82.3 to 82.9), other White (82.0; 81.3 to 82.8) and White Irish (81; 80.2 to 81.8).

Conclusions

Males and females in most of the larger ethnic minority groups in Scotland have longer life expectancies than the majority White Scottish population.

Ethnicity, deprivation and screening: survival from breast cancer among screening-eligible women in the West Midlands diagnosed from 1989 to 2011

BACKGROUND

Social inequalities in breast cancer survival are smaller when the cancer is screen-detected. We examined survival from screen-detected and non screen-detected breast cancer by ethnicity and deprivation.

METHODS

Cancer registry data for 20 283 women aged 50-70 years, diagnosed between 1989-2011 and invited for screening, were linked with screening and ethnicity data. We examined Asian, Black and White groups, less deprived and middle/more deprived women. Net survival was estimated using ethnic- and deprivation-specific life tables. Estimates were corrected for lead-time bias and over-diagnosis.

RESULTS

Net survival varied by screening history. No significant differences in survival were found by ethnicity. Five-year net survival was 90.0% (95% CI, 89.3-90.8%) in less deprived groups and 86.7% (85.9-87.4%) among middle/more deprived women. Screening benefitted all ethnic and both deprivation groups. Whether screen-detected or not, more deprived women had significantly poorer outcomes: 5-year net survival was 78.0% (76.7-79.2%) for deprived women who were not screen-detected compared with 94.0% (93.1-95.1%) for less deprived women who were screen-detected.

CONCLUSIONS

The three ethnic groups differed little in their breast cancer survival. Although screening confers a survival benefit to all, there are still wide disparities in survival by deprivation. More needs to be done to determine what underlies these differences and tackle them.