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

Morris, Melvin L.; Woods, Laura; Rachet, Bernard

doi:10.18632/oncotarget.10255

Cited by 14 publications

(20 citation statements)

References 39 publications

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“… 78 , 79 These studies assessed the following cancers: female breast, 8 , 9 , 13 , 17 , 18 , 26 , 29 , 30 , 32 , 36 , 44 , 49 , 53 , 59 - 61 , 65 , 67 , 77 male breast, 58 cervix, 24 , 50 ovary, 23 , 42 , 45 endometrium, 33 prostate, 7 , 34 , 43 , 64 penis, 47 colorectum, 12 , 15 , 22 , 28 , 40 , 48 , 55 , 57 , 66 , 73 lung, 10 , 11 , 16 , 20 , 25 , 41 , 56 head and neck, 31 ...…”

Section: Resultsmentioning

confidence: 99%

“…Sixteen studies examined the underlying causes of educational and socio-economic inequalities in breast cancer survival: 8 from Europe, 9 , 13 , 18 , 30 , 32 , 36 , 44 , 49 5 from the US, 59 - 61 , 65 , 67 2 from New Zealand 76 , 77 and 1 from Australia. 74 Studies from Switzerland, Italy, Ireland, New Zealand and Australia applying the difference method reported consistent findings that stage at diagnosis, other tumor characteristics, method of detection or presentation (symptomatic, screening, incidental, unknown), and receiving suboptimal treatment and sector of care (private or public) only partly explained the observed socio-economic inequalities in breast cancer survival.…”

Section: Resultsmentioning

confidence: 99%

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Factors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review

2021

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Background: There is strong and well-documented evidence that socio-economic inequality in cancer survival exists within and between countries, but the underlying causes of these differences are not well understood. Methods: We systematically searched the Ovid Medline, EMBASE, and CINAHL databases up to 31 May 2020. Observational studies exploring pathways by which socio-economic position (SEP) might causally influence cancer survival were included. Results: We found 74 eligible articles published between 2005 and 2020. Cancer stage, other tumor characteristics, health-related lifestyle behaviors, co-morbidities and treatment were reported as key contributing factors, although the potential mediating effect of these factors varied across cancer sites. For common cancers such as breast and prostate cancer, stage of disease was generally cited as the primary explanatory factor, while co-morbid conditions and treatment were also reported to contribute to lower survival for more disadvantaged cases. In contrast, for colorectal cancer, most studies found that stage did not explain the observed differences in survival by SEP. For lung cancer, inequalities in survival appear to be partly explained by receipt of treatment and co-morbidities. Conclusions: Most studies compared regression models with and without adjusting for potential mediators; this method has several limitations in the presence of multiple mediators that could result in biased estimates of mediating effects and invalid conclusions. It is therefore essential that future studies apply modern methods of causal mediation analysis to accurately estimate the contribution of potential explanatory factors for these inequalities, which may translate into effective interventions to improve survival for disadvantaged cancer patients.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Factors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review

2021

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“…We have previously shown that differences in survival by deprivation are evident among both women whose cancer was screen-detected and those not screen-detected [ 36 ] and that these differences are not entirely explained by adjustment for stage of disease and treatment received [ 39 ]. In those analyses we made corrections for potential biases due to lead time [ 40 ] and over-diagnosis.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2017

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BackgroundIn 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.MethodsIndividually-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.ResultsThe 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.ConclusionsOur 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-017-3129-4) contains supplementary material, which is available to authorized users.

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“…In the United Kingdom there have been national policies aimed at reducing inequalities ( Department of Health, 2000 ; Department of Health, 2011 ), but any changes have been minor ( Rachet et al , 2009 ; Rachet et al , 2010 ). Part of the observed differences in survival between socio-economic groups can be explained by stage at diagnosis ( Rutherford et al , 2013 ; Morris et al , 2016 ).…”

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confidence: 99%

Estimating the impact of a cancer diagnosis on life expectancy by socio-economic group for a range of cancer types in England

et al. 2017

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Background:Differences in cancer survival exist across socio-economic groups for many cancer types. Standard metrics fail to show the overall impact for patients and the population.Methods:The available data consist of a population of ∼2.5 million patients and include all patients recorded as being diagnosed with melanoma, prostate, bladder, breast, colon, rectum, lung, ovarian and stomach cancers in England between 1998 and 2013. We estimated the average loss in expectation of life per patient in years and the proportion of life lost for a range of cancer types, separately by deprivation group. In addition, estimates for the total number of years lost due to each cancer were also obtained.Results:Lung and stomach cancers result in the highest overall loss for males and females in all deprivation groups in terms of both absolute life years lost and loss as a proportion of expected life remaining. Female lung cancer patients in the least- and most-deprived group lose 14.4 and 13.8 years on average, respectively, that is translated as 86.1% and 87.3% of their average expected life years remaining. Melanoma, prostate and breast cancers have the lowest overall loss. On the basis of the number of patients diagnosed in 2013, lung cancer results in the most life years lost in total followed by breast cancer. Melanoma and bladder cancer account for the lowest total life years lost.Conclusions:There are wide differences in the impact of cancer on life expectancy across deprivation groups, and for most cancers the most affluent lose less years.

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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

Cited by 14 publications

References 39 publications

Factors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review

Factors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review

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

Estimating the impact of a cancer diagnosis on life expectancy by socio-economic group for a range of cancer types in England

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