Inequalities In Breast Cancer Survival Research Articles

Epidemiology trends and progress in breast cancer survival: earlier diagnosis, new therapeutics.

In this review we will critically appraise the latest evidence on breast cancer (BC) survival trends and discuss how these may reflect breakthroughs in early diagnosis and treatment approaches. We will address the wide global inequalities in BC survival and review the ongoing initiatives aimed at improving cancer control worldwide. BC outcomes have improved in high-income countries during the last decades, following the implementation of strategies for early detection and optimal multimodality treatment. Novel therapeutics, such as anti-HER2 targeted treatments, have also contributed to the progress in BC survival. However, BC mortality is still high in low-income countries, due to the lack of optimal healthcare infrastructures. In the context of marked inequities in BC management across world regions, international collaborations such as the Global Breast Cancer Initiative and the Global Initiative for Cancer Registry Development work to foster capacity-building in developing countries, tackle the burden of BC and deliver the Sustainable Development Goals by 2030. Collection of robust, high-quality data from population-based cancer registries is crucial to drive and refine public health interventions. Population-based data are also the litmus paper to evaluate the real-world impact of clinical advances and monitor progress.

The contribution of prognostic factors to socio-demographic inequalities in breast cancer survival in Victoria, Australia.

Breast cancer survival in Australia varies according to socio-economic status (SES) and between rural and urban places of residence. Part of this disparity may be due to differences in prognostic factors at the time of diagnosis. Women with invasive breast cancer diagnosed from 2008 until 2012 (n = 14,165) were identified from the Victorian Cancer Registry and followed up for 5 years, with death from breast cancer or other causes recorded. A prognostic score, based on stage at diagnosis, cancer grade, whether the cancer was detected via screening, reported comorbidities and age at diagnosis, was constructed for use in a mediation analysis. Five-year breast cancer mortality for women with breast cancer who were in the lowest quintile of SES (10.3%) was almost double that of those in the highest quintile (5.7%). There was a small survival advantage (1.7% on average, within each socio-economic quintile) of living in inner-regional areas compared with major cities. About half of the socio-economic disparity was mediated by prognostic factors, particularly stage at diagnosis and the presence of comorbidities. The inner-regional survival advantage was not due to differences in prognostic factors. Part of the socio-economic disparity in breast cancer survival could be addressed by earlier detection in, and improved general health for, more disadvantaged women. Further research is required to identify additional causes of socio-economic disparities as well as the observed inner-regional survival advantage.

Socioeconomic inequalities in breast cancer survival in Reunion Island: The contribution of stage at diagnosis as a mediator

IntroductionAlthough breast cancer survival has improved in France, it appears that women living in deprived areas are more likely to die from breast cancer. However, no study has yet examined socioeconomic inequalities in breast cancer survival in La Réunion. Our objective was to examine whether socioeconomic inequalities in breast cancer survival exist in Reunion Island and whether stage at diagnosis could partly explain these differences. MethodsA population-based cohort study of all women on Reunion Island with primary breast cancer diagnosed between 2008 and 2016 was conducted. Each woman was assigned a deprivation index based on her area of residence at diagnosis. Net survival by deprivation group and stage at diagnosis was estimated by the non parametric Pohar Perme method. The role of stage (indirect effect) was assessed using a mediation analysis extended to the relative survival framework. ResultsAt five years, net survival was significantly lower in women living in the most deprived areas than in women living in the least deprived areas (81 % (95 % CI 77–86) and 91 % (95 % CI 89–94), respectively, p < 0.0001), and mediation analysis showed that the contribution of stage at diagnosis to these survival differences was 43 %. DiscussionOur result shows that although measures to promote earlier diagnosis are important, they would only reduce socioeconomic inequalities in breast cancer survival by 43 %. To further investigate these inequalities, future research should explore the role of unmeasured mediators, such as comorbidities and treatment received, as well as the impact of specific interventions that might address the differences in mediator distribution.

Are socio-economic inequalities in breast cancer survival explained by peri-diagnostic factors?

BackgroundPatients living in more deprived localities have lower cancer survival in England, but the role of individual health status at diagnosis and the utilisation of primary health care in explaining these differentials has not been widely considered. We set out to evaluate whether pre-existing individual health status at diagnosis and primary care consultation history (peri-diagnostic factors) could explain socio-economic differentials in survival amongst women diagnosed with breast cancer.MethodsWe conducted a retrospective cohort study of women aged 15–99 years diagnosed in England using linked routine data. Ecologically-derived measures of income deprivation were combined with individually-linked data from the English National Cancer Registry, Clinical Practice Research Datalink (CPRD) and Hospital Episodes Statistics (HES) databases. Smoking status, alcohol consumption, BMI, comorbidity, and consultation histories were derived for all patients. Time to breast surgery was derived for women diagnosed after 2005. We estimated net survival and modelled the excess hazard ratio of breast cancer death using flexible parametric models. We accounted for missing data using multiple imputation.ResultsNet survival was lower amongst more deprived women, with a single unit increase in deprivation quintile inferring a 4.4% (95% CI 1.4–8.8) increase in excess mortality. Peri-diagnostic co-variables varied by deprivation but did not explain the differentials in multivariable analyses.ConclusionsThese data show that socio-economic inequalities in survival cannot be explained by consultation history or by pre-existing individual health status, as measured in primary care. Differentials in the effectiveness of treatment, beyond those measuring the inclusion of breast surgery and the timing of surgery, should be considered as part of the wider effort to reduce inequalities in premature mortality.

Absence of socioeconomic inequalities in access to good-quality breast cancer treatment within a population-wide screening programme in Turin (Italy).

Several studies suggest that population-based breast cancer screening programmes might help reduce social inequalities in breast cancer survival both by increasing early diagnosis and by improving access to effective treatments. To start disentangling the two effects, we evaluated social inequalities in quality of treatment of screen-detected breast cancer in the city of Turin (Italy). Combining data from the Audit System on Quality of Breast Cancer Treatment and the Turin Longitudinal Study, we analysed 2700 cases in the screening target age class 50-69 diagnosed in the period 1995-2008. We selected 10 indicators of the pathway of care, relative to timeliness and appropriateness of diagnosis and treatment, and three indicators of socioeconomic position: education, occupational status and housing characteristics. For each indicator of care, relative risks of failure were estimated by robust Poisson regression models, controlling for calendar period of diagnosis, size of tumour and activity volume of the surgery units. The principal predictor of failure of the good care indicators was the calendar period of diagnosis, with a general improvement with time in the quality of diagnosis and treatment, followed by size of the tumour and volume of activity. Socioeconomic indicators show only a marginal independent effect on timeliness indicators. The observed associations of quality indicators with socioeconomic characteristics are lower than expected, suggesting a possible role of the screening programme in reducing disparities in the access to good-quality treatments thanks to its capability to enter screen-detected women into a protected pathway of care.

How much do tumor stage and treatment explain socioeconomic inequalities in breast cancer survival? Applying causal mediation analysis to population-based data.

Substantial socioeconomic inequalities in breast cancer survival persist in England, possibly due to more advanced cancer at diagnosis and differential access to treatment. We aim to disentangle the contributions of differential stage at diagnosis and differential treatment to the socioeconomic inequalities in cancer survival. Information on 36,793 women diagnosed with breast cancer during 2000–2007 was routinely collected by an English population-based cancer registry. Deprivation was determined for each patient according to her area of residence at the time of diagnosis. A parametric implementation of the mediation formula using Monte Carlo simulation was used to estimate the proportion of the effect of deprivation on survival mediated by stage and by treatment. One-third (35 % [23–48 %]) of the higher mortality experienced by most deprived patients at 6 months after diagnosis, and one tenth (14 % [−3 to 31 %]) at 5 years, was mediated by adverse stage distribution. We initially found no evidence of mediation via differential surgical treatment. However, sensitivity analyses testing some of our study limitations showed in particular that up to thirty per cent of the higher mortality in most deprived patients could be mediated by differential surgical treatment. This study illustrates the importance of using causal inference methods with routine medical data and the need for testing key assumptions through sensitivity analyses. Our results suggest that, although effort for earlier diagnosis is important, this would reduce the cancer survival inequalities only by a third. Because of data limitations, role of differential surgical treatment may have been under-estimated.Electronic supplementary materialThe online version of this article (doi:10.1007/s10654-016-0155-5) contains supplementary material, which is available to authorized users.

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.

How much of socioeconomic differences in survival in patients with breast cancer can be explained by differences in stage of diagnosis and treatment? Application of causal mediation analysis to routine data

BackgroundSubstantial socioeconomic inequalities in breast cancer survival exist in England. Late presentation at more advanced stages and differential access to treatment are two main factors that might contribute to the survival differences. We aimed to adapt methods from the causal inference setting to examine what proportions of the differences in survival can be explained by these factors. MethodsInformation for 36 793 women diagnosed with breast cancer between 2000 and 2007 was gathered by the population-based Northern and Yorkshire Cancer Registry. Vital status was ascertained until the end of 2007, at which point 29 009 women were still alive. Information on surgical treatment was retrieved from the Hospital Episode Statistics (HES) dataset. Hierarchical matching was done using a unique identification number, date of birth, postcode, and sex. The OPCS-4 (Office of Population Censuses and Surveys Classification of Interventions and Procedures) codes from HES within 1 month before and 6 months after cancer diagnosis were dichotomised into major versus minor or no procedures using recommendations from a clinical reference group. Deprivation category, based on the indices of multiple deprivation (income domain), was allocated to each patient according to their area of residence at the time of diagnosis. G-computation procedures were used to estimate the proportion of the effect of deprivation on treatment mediated by stage, survival mediated by stage, and survival mediated by treatment. Single stochastic imputation was incorporated in the g-computation procedures to handle missing stage (8%). FindingsNet survival differed between the most affluent and the most deprived patients by 3·6% at 1 year (97·2% vs 93·6%) and 10·0% at 5 years (85·9% vs 75·9%) after diagnosis. Adverse stage distribution was associated with more deprived patients (localised stage 43% [2622 of 6045] in most affluent, 38% [2861 of 7489] in most deprived; distant metastasis 4% [224 of 6045] in most affluent, 6% [484 of 7489] in most deprived; p<0·0001). The more advanced the stage at diagnosis, the less likely the patient received major surgical treatment (p<0·0001). The most deprived patients were 9% (95% CI 1–18) more likely to receive major surgery than the most affluent patients. However, if most deprived patients had the stage distribution of the most affluent, they would be 8% (95% CI 5–13) more likely to receive such treatment. This effect was not noted for the other deprivation categories. The most deprived patients were almost three times more likely to die within 6 months after diagnosis than the most affluent patients (odds ratio 2·77, 95% CI 2·17–3·53); a third of this was mediated by adverse stage distribution (proportion mediated 0·35, 95% CI 0·23–0·48) whereas none was mediated through differential surgical treatment (p>0·5). InterpretationPreliminary results elucidate how much effect different contributory factors have on the differential short-term cancer survival between deprivation groups in patients with breast cancer. Efforts to advance diagnoses are important, but would reduce the socioeconomic inequalities in cancer survival by only a third. These results are based on population-based data—ie, they include virtually all patients diagnosed with a breast cancer in Yorkshire and the northeast of England, including those who were diagnosed with advanced stage and those who did not receive optimum treatment. Our study is nevertheless observational. We used a causal approach in which age, year of diagnosis, and regions of England were adjusted. We did not have reliable information on comorbidity, another potential mediator on the causal pathway. Quantifying the proportions of the deprivation gap mediated via comorbidity, stage, and treatment separately informs us about the parts they played and, ultimately, what could be done to most effectively reduce the deprivation gap in cancer survival. FundingNone.

Does breast cancer screening level health inequalities out? A population-based study in an Italian region

Although population-based screening has the potential to reduce inequalities in breast cancer survival, evidence on this topic is controversial. The objective of this study was to evaluate whether the full implementation of a mammography screening programme in Emilia-Romagna in Italy had an impact on variations in breast cancer survival by educational level. A cohort study was performed, including all women <70 years and residing in Emilia-Romagna who had infiltrating breast cancer registered in 1997-2000 (transitional screening period) or 2001-03 (consolidation screening period). Cancer cases were retrieved from the regional Breast Cancer Registry and followed up for 5 years. Educational level was determined from census data and allocated to cancer cases by individual record linkage. Age at diagnosis was classified into two groups (30-49, 50-69: screening target population). A total of 9639 cases were analyzed. In the 1997-2000 period, low-educated women had significantly lower survival compared with high-educated women, both in the younger and in the older age-groups. After the full implementation of the screening programme, these differences decreased in both age-groups, until disappearing completely among women in the age-group invited to screening. Our findings suggest that a fee-free population-based organized mammography screening programme with active invitation of the whole target population could be effective in reducing differences in survival in the population targeted by the screening.

How much of the deprivation gap in cancer survival can be explained by variation in stage at diagnosis: An example from breast cancer in the East of England

Socioeconomic differences in cancer patient survival exist in many countries and across cancer sites. In our article, we estimated the number of deaths in women with breast cancer that could be avoided within 5 years from diagnosis if it were possible to eliminate socioeconomic differences in stage at diagnosis. We analysed data on East of England women with breast cancer (2006-2010). We estimated survival for different stage-age-deprivation strata using both the observed and a hypothetical stage distribution (assuming all women acquired the stage distribution of the most affluent women). Data were analysed on 20,738 women with complete stage information (92%). Affluent women were less likely to be diagnosed in advanced stage. Relative survival decreased with increasing level of deprivation. Eliminating differences in stage at diagnosis could be expected to nearly eliminate differences in relative survival for women in deprivation groups 3 and 4, but would only approximately halve the difference in relative survival for women in the most deprived group (5). This means, for a typical cohort of women diagnosed in a calendar year with breast cancer, eliminating deprivation differences in stage at diagnosis would prevent ∼40 deaths in the East of England from occurring within 5 years from diagnosis. Using appropriate weighting we estimated the respective number of avoidable deaths for the whole of England to be ∼450. The findings suggest that policies aimed at reducing inequalities in stage at diagnosis between women with breast cancer are important to reduce inequalities in breast cancer survival.

Survival from breast cancer in relation to access to tertiary healthcare, body mass index, tumor characteristics and treatment: a Hellenic Cooperative Oncology Group (HeCOG) study

Apart from tumour, treatment and patient characteristics at diagnosis, access to healthcare delivery may as well play a significant role in breast cancer prognosis. This study aimed to assess the additional impact exerted on survival by travel burden-a surrogate indicator of limited access to healthcare- expressed as geographical distance and/or time needed to reach the tertiary healthcare center from the patient's residence. Between 1997 and 2005, 2,789 women participated in therapeutic clinical trials conducted by the Hellenic Cooperative Oncology Group. The effect of geographical distance and travel time between patient's residence and treating hospital on survival was estimated using Cox proportional hazards regression adjusting for age, menopausal status, tumour size/grade, positive nodes (number), hormonal receptor status, HER2 overexpression, surgery type/treatment protocol as well as for body mass index>30 kg/m2. More aggressive tumour features, older treatment protocols and modifiable patient characteristics, such as obesity (HR: 1.27) adversely impacted on breast cancer survival. In addition, less studied indicators of access to healthcare, such as geographic distance>350 km and travel time>4 h were independently and significantly associated with worse outcomes (HR=1.43 and 1.34 respectively). In conclusion, to address inequalities in breast cancer survival, improvements in access to healthcare services related to increased travel burden especially for patients of lower socioeconomic status should be considered, more than ever at times of financial crisis and independently of already known modifiable patient characteristics.

Spatial inequalities in colorectal and breast cancer survival: Premature deaths and associated factors

This study examines the influence of cancer stage, distance to treatment facilities and area disadvantage on breast and colorectal cancer spatial survival inequalities. We also estimate the number of premature deaths after adjusting for cancer stage to quantify the impact of spatial survival inequalities. Population-based descriptive study of residents aged <90 years in Queensland, Australia diagnosed with primary invasive breast (25,202 females) or colorectal (14,690 males, 11,700 females) cancers during 1996–2007. Bayesian hierarchical models explored relative survival inequalities across 478 regions. Cancer stage and disadvantage explained the spatial inequalities in breast cancer survival, however spatial inequalities in colorectal cancer survival persisted after adjustment. Of the 6,019 colorectal cancer deaths within 5 years of diagnosis, 470 (8%) were associated with spatial inequalities in non-diagnostic factors, i.e. factors beyond cancer stage at diagnosis. For breast cancers, of 2,412 deaths, 170 (7%) were related to spatial inequalities in non-diagnostic factors. Quantifying premature deaths can increase incentive for action to reduce these spatial inequalities.

Does an organised screening programme reduce the inequalities in breast cancer survival?

The aim of the present study was to examine whether the implementation of an organised mammographic screening programme in Florence has been successful in reducing socioeconomic inequalities in breast cancer survival. All invasive breast cancer cases diagnosed in women resident in the city of Florence in a prescreening period and in the first 10 years of the screening programme were selected. Their socioeconomic status (SES) was determined by using the national census 2001 data. All breast cancers were followed up to 10 years after the diagnosis. In the prescreening period, the survival of deprived women was 12 percentage points lower than the reference class, both in the younger age class (<50 years old) and in the age class target of the screening programme (50-69 years old). This difference progressively decreases until disappearing completely during the first 10 years of the screening programme for the age class invited to screening, whereas it remains stable in the younger age class. Participation in breast cancer screening and diagnostic accuracy were similar by SES. The organised breast cancer screening implemented in the Florentine area achieved the goal of reducing inequalities in breast cancer survival.

Socio-economic inequalities in survival from screen-detected breast cancer in South West England: population-based cohort study

Socio-economic inequalities in breast cancer survival have been reported worldwide, but whether these exist in screen detected as well as symptomatic women has not been established. Making this distinction will allow inferences about the relative contributions of pre- and post-diagnostic delay to these inequalities. Screening-eligible women diagnosed with breast cancer in South West England (2002-06) were followed-up to 2007. Five-year relative survival ratios (RSRs) were calculated for each deprivation quintile, using deprivation-specific life-tables and a period approach. The 'deprivation gap' in survival was calculated as the slope index of inequality between least and most deprived women. The study included 11 018 women, of whom 1176 died during follow-up. Screening status of 54% of women was missing. A clear gradient in survival across deprivation groups ranged from 83.6% [95% confidence interval (CI) 80.0, 86.6] in the most deprived to 90.8% (95% CI 89.0, 92.3) in the least deprived group. Comparing the most deprived to least deprived women, the estimated deprivation gap was -9.42% (95% CI -12.80, -6.04, P = 0.003). Among screen-detected women, inequalities were attenuated, but persisted, ranging from 95.6% (95% CI 90.6, 98.0) in the most deprived to 98.2% (95% CI 95.9, 99.2) in least deprived; the estimated deprivation gap was -3.03% (95% CI -5.75, -0.85, P = 0.023). The deprivation gap in survival does not appear as marked with screen-detected breast cancer as the other groups, though still apparent. Efforts to eliminate inequalities should consider both increasing breast screening participation and ensuring equal access through secondary care systems for women of lower socio-economic position.

Changes over time in socioeconomic inequalities in breast and rectal cancer survival in England and Wales during a 32-year period (1973–2004): the potential role of health care

BackgroundSocioeconomic inequalities in cancer survival are well documented but they vary for different cancers and over time. Reasons for these differences are poorly understood. Patients and methodsFor England and Wales, we examined trends in socioeconomic survival inequalities for breast cancer in women and rectal cancer in men during the 32-year period 1973–2004. We used a theoretical framework based on Victora's ‘inverse equity’ law, under which survival inequalities could change with the advent of successive new treatments, of varying effectiveness, which are disseminated with different speed among patients of different socioeconomic groups. We estimated 5-year relative survival for patients of different deprivation quintiles and examined trends in survival inequalities in light of major treatment innovations. ResultsInequalities in breast cancer survival (921,611 cases) narrowed steadily during the study (from -10% to -6%). In contrast, inequalities in rectal cancer survival (187,104 cases) widened overall (form -5% to -11%) with fluctuating periods of narrowing inequality. ConclusionsTrends in socioeconomic differences in tumour or patient factors are unlikely explanations of observed changes over time in survival inequalities. The sequential introduction into clinical practice of new treatments of progressively smaller incremental benefit may partly explain the reduction in inequality in breast cancer survival.

Investigating reasons for ethnic inequalities in breast cancer survival in New Zealand

Objective. This study investigated the role that demographic and tumour factors play in explaining ethnic inequalities in breast cancer survival. Design. Breast cancer cases notified to the New Zealand Cancer Registry (NZCR) from April 2005 to April 2007 were followed up to April 2009. Māori, Pacific and non-Māori/non-Pacific women were categorised according to ethnicity on the NZCR. Deprivation was analysed as quintiles of the New Zealand area-based index of socio-economic position. Relative survival rates were estimated using ethnic-specific life tables. Missing values were imputed and excess mortality modelling was used to estimate the contribution of demographic and tumour factors to ethnic inequalities in survival. Results. There were 2968 breast cancer cases (76.5% non-Māori/non-Pacific, 17% Māori, and 6.5% Pacific) included and 433 recorded deaths. Relative survival rates at 4 years were 91.5% (95% confidence interval (CI) 89.7 to 92.9) for non-Māori/non-Pacific, 86.2% (CI 80.3 to 90.4) for Māori, and 79.6% (CI 68.2 to 87.2) for Pacific women. Using non-Māori/non-Pacific as the reference group, the age-adjusted hazard ratio (HR) dropped for Māori from 1.76 (CI 1.22 to 2.48) to 1.43 (CI 0.97 to 2.10) when further adjusted by deprivation. For Pacific the HR dropped from 2.49 (CI 1.57 to 3.94) to 1.94 (CI 1.20 to 3.13). Inequalities persisted after adjustment for subtype variables (ER/PR/HER2), but adjusting for access to care variables (extent/size) eliminated the ethnic inequalities in excess mortality. Conclusion. Ethnic disparities in breast cancer survival in New Zealand can be attributed to deprivation and differential access to health care rather than differences in breast cancer subtypes.

Investigating reasons for socioeconomic inequalities in breast cancer survival in New Zealand

Background: This study investigated the role that demographic and tumour factors play in explaining socioeconomic inequalities in breast cancer survival. Methods: Breast cancer cases notified to the New Zealand Cancer Registry (NZCR) from April 2005 to April 2007 were followed up to April 2009. The New Zealand area-based deprivation index (NZDep) was used as a measure of socioeconomic position. Relative survival rates were estimated using sex-, deprivation- and ethnic-specific life tables. Multiple imputation was used to impute missing data. Excess mortality modelling was used to estimate the contribution of demographic and tumour factors to inequalities in survival. Results: There were 2968 breast cancer cases included and 433 recorded deaths. Relative survival rates at 4 years varied across deprivation groups. Using NZDep deciles 1–4 (least deprived) as the reference group, the age- and ethnicity-adjusted hazard ratio (HR) for NZDep deciles 7–8 was 2.03 (CI 1.36–3.04) and for NZDep deciles 9–10 was 1.93 (CI 1.28–2.92). In the fully adjusted model there remained 50% excess mortality for the two most deprived groups compared to the most affluent. Variables which measured timely access to care (extent/size) accounted for more of the survival disparity than breast cancer subtype variables (ER/PR/HER2). Conclusion: Women from deprived areas in New Zealand who are diagnosed with breast cancer are less likely to survive as long as those from affluent areas. A substantial proportion of these socioeconomic disparities can be attributed to differential access to health care although other factors, currently unknown, are also likely to play an important role.

Do Lifestyle or Social Factors Explain Ethnic/Racial Inequalities in Breast Cancer Survival?

Despite numerous studies documenting ethnic inequalities in breast cancer survival between minority and majority ethnic groups worldwide, reasons for these inequalities remain unclear. The authors performed a systematic review of published literature to identify studies that investigated the explanatory power of smoking, alcohol consumption, body mass index (BMI), and socioeconomic position (SEP) on ethnic inequalities in breast cancer survival. Sixteen studies were included in the review. From 5 studies, the authors found that differences in breast cancer survival between ethnic groups may be in part explained by BMI, but there was little evidence to implicate smoking or alcohol consumption as explanatory factors of this inequality. From 12 studies, the authors found that SEP explains part of the ethnic inequality in all-cause survival but that it was not evident for breast-cancer-specific survival. SEP explains more of the disparities among African-American versus white women in the United States compared with other ethnic comparisons. Furthermore, given social patterning of BMI and other lifestyle habits, it is possible that results for SEP and BMI are measuring the same effect. In this review, the authors make suggestions regarding the role of epidemiology in facilitating further research to better inform the development of effective policies to address ethnic differences in survival.

Long-term inequalities in breast cancer survival – a ten year follow-up study of patients managed within a National Health Care System (Sweden)

Introduction. Converging epidemiological evidence based on studies of different designs in a variety of populations and settings show that cancer survival tends to be poorer in low compared to high socioeconomic groups. In an extension of an earlier register-based study, we examined the influence of socioeconomic factors on long-term survival in women with a first diagnosis of invasive breast cancer in 1993 in Sweden, a country with a policy of providing equal access to health care to all at nominal cost within a National Health Care System. Material and methods. The study was based on data set generated by record linkages between the Swedish Cancer Register, Census databases and the Cause of Death Register. Four different categorical variables were used as indicators of socioeconomic standing. Cox proportional hazard regression models were used to estimate the effects of socioeconomic status on risk of death. Results. Of 4 645 eligible women with breast cancer, 1 016 had died from breast cancer at the end of follow-up on December 31, 2003. After adjustment for tumour size and age at diagnosis, risk of death was 19% lower among women belonging to a household of high compared to low socioeconomic status (HR high versus low 0.81; 95% CI: 0.67–0.97). Discussion. These findings indicate that social inequalities in breast cancer survival persist at least up to ten years after an initial diagnosis. While social gradients detected shortly after diagnosis may mainly reflect an influence of socioeconomic differences in overall health status and frailty, differentials persisting beyond five years rather point to a long-term influence of disparities in management of both primary tumours and recurrences. Further studies are needed to explore whether the present findings reflect amendable inequalities in access to state-of- the-art treatment. For all calendar periods, observed survival in the most privileged groups sets the goal for what is achievable for all breast cancer patients.

Social class is an important and independent prognostic factor of breast cancer mortality

Reasons of the important impact of socioeconomic status on breast cancer prognosis are far from established. This study aims to evaluate and explain the social disparities in breast cancer survival in the Swiss canton of Geneva, where healthcare costs and life expectancy are among the highest in the world. This population-based study included all 3,920 female residents of Geneva, who were diagnosed with invasive breast cancer before the age of 70 years between 1980 and 2000. Patients were divided into 4 socioeconomic groups, according to the woman's last occupation. We used Cox multivariate regression analysis to identify reasons for the socioeconomic inequalities in breast cancer survival. Compared to patients of high social class, those of low social class had an increased risk (unadjusted hazard ratio [HR] 2.4, 95% CI: 1.6-3.5) of dying as a result of breast cancer. These women were more often foreigners, less frequently had screen-detected cancer and were at more advanced stage at diagnosis. They less frequently underwent breast-conserving surgery, hormonal therapy, and chemotherapy, in particular, in case of axillary lymph node involvement. When adjusting for all these factors, patients of low social class still had a significantly increased risk of dying of breast cancer (HR 1.8, 95% CI: 1.2-2.6). Overmortality linked to low SES is only partly explained by delayed diagnosis, unfavorable tumor characteristics and suboptimal treatments. Other factors, not measured in this study, also could play a role. While waiting for the outcome of other researches, we should consider socioeconomic status as an independent prognostic factor and provide intensified support and surveillance to women of low social class.