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

In England and Wales there are substantial socio-economic differentials in breast cancer survival, with survival being relatively high among more affluent women [ 1, 2]. There is increasingly strong evidence that these are due in part to later stage of disease at presentation [ 3, 4] and differences in timeliness of diagnosis [ 5, 6]. Other potential drivers of late stage at diagnosis include health system delays in primary and secondary care (practitioner delays) [ 7, 8] and differences in patients’ underlying characteristics [ 9– 11] and lifestyle choices [ 12– 16].

Past research has focused on the appraisal by patients of the seriousness of their symptoms [ 10], and the possible sources of delay after presentation using patient experience surveys and audit data [ 17– 20]. However, to date there has been little reporting of the connection between these patterns and the survival of the same women.

Our aim was to investigate the potential of pre-diagnostic factors for explaining deprivation differences in survival using the factors shown in the conceptual framework in Fig.  1. This shows the potential links between deprivation and the outcome of breast cancer survival, and patients’ biological, lifestyle, and health seeking characteristics. The primary outcomes examined were: the rate of primary care consultation; the time from last breast-related GP consultation to diagnosis, and from diagnosis to first surgery; and net survival. We first describe deprivation-specific variations in women’s baseline characteristics, pre-diagnostic primary care consultations patterns, symptom presentation, and time intervals from symptom report to diagnosis. We then examine how net survival varies with deprivation and with each of these covariates. To do so, we used individually-linked data from primary care, the screening service and the cancer registry.

Our data suggest that although more deprived women display lifestyle factors associated with poorer outcomes, their consultation frequency for both breast and non-breast symptoms, their comorbidities and the type of breast cancer symptoms they present with are similar. This interpretation is supported by the lack of difference in consultation patterns by extent of disease, BMI, smoking or alcohol consumption status coupled with the persistence of deprivation differences in survival within the sub-groups of these co-variables. We found some evidence of extended times to surgical treatment among most deprived women who were not screen-detected but who presented with symptoms in primary care. This potentially suggests that treatment delay may play a role, either due to a greater proportion of deprived women receiving neo-adjuvant treatment, or due to differences in the way more deprived patients interact with the healthcare system. Further investigation of the interrelationships between these variables within a larger and more detailed dataset is warranted.

These data were from a centre of excellence in breast cancer registration, and although small numbers limited our ability to perform multivariable analyses, our sample was representative, in terms of survival and most other characteristics, of the cohort from which they were drawn. The sample was somewhat less deprived than the cohort of women from which they came which is likely to be due to the profiles of the GP practices that contributed to the CPRD dataset within the West Midlands. In most cases there was less than 10% missing data in the analysis. The data available included women diagnosed some time ago, however, despite the changes in the healthcare system in the years since these data were collected, this study highlights some important areas that are less likely to have changed greatly. Despite a persistent deprivation gap in survival, we have found no difference in rate of consultation between the more and less deprived. In addition, changes in the system have resulted in almost unchanged high proportions of diagnoses after emergency admission for certain cancers (such as colon and lung).

Women who were not screen-detected and who presented with symptoms in primary care are those for whom policies encouraging early diagnosis are likely to be most effective. However, time from last breast-related consultation to diagnosis in this group was not significantly related to any of the variables investigated. This may suggest that patient delay prior to diagnosis is not such an important driver of survival differences within this cohort as might be assumed. On the other hand, time from last consultation to surgery in this group was longer among more deprived women, overweight or obese women, those who had a comorbidity, and those who were older. This potentially suggests that symptomatically-detected women are being referred and diagnosed just as quickly, regardless of their socio-demographic characteristics, but that differences in time to surgical treatment emerge after diagnosis. Such differences might be in part due to greater complexity in preparing more comorbid women, or women with more advanced stage of disease, for surgery, or due to differences in the way more deprived women navigate the healthcare system. In order to be able to draw firm conclusions about this, we would need specific information on treatments received including the rationale behind decisions made, in particular in relation to timing, adjuvant therapies administered, patient input into these decisions, and patient adherence. Reliable recurrence information for each woman over a medium to long period of follow-up would also be required.

There are some well-established relationships between deprivation and smoking, BMI, alcohol consumption, screening and stage at diagnosis [ 12– 16, 34– 36] but few have been investigated using the primary care data to date. BMI was associated in this sample with both deprivation and time to surgery, and may therefore explain some of the relationship between deprivation and survival. Conversely, the presence of comorbidities, while closely associated with survival and time to surgery, was not significantly related to deprivation. This contrasts with previous work where comorbidity was more frequent among the more deprived [ 37, 38]. However, in our data very few women had more than one comorbidity, probably because we included only women aged 50–70 (those eligible for breast screening). These women are generally healthier than the older women with breast cancer.

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.

This preliminary exploration of a linked sub-sample of these same data has highlighted both similarities and differences in the characteristics of women by deprivation status. It has shown a reassuring lack of difference in the impact of deprivation on consultation patterns, and a lack of association between lifestyle factors associated with deprivation and survival. On the other hand, our data point to some potential differences in time to surgical treatment that should be explored further. Our analysis demonstrates the feasibility of using primary care data to add to our understanding of what underlies survival differences. Larger samples linked to richer data on treatment decisions and pathways are required to elucidate these patterns further.