Social inequalities widen after a breast cancer
Authors:
José Luis Sandoval
,Gwenn Menvielle
Date of publication: 14 January 2025
Last update: 14 January 2025
1. Social determinants of health and health inequalities
The study of disease causes has intrigued generations of researchers, driven by the potential to discover new treatments or simply out of curiosity. Progress in understanding the biological mechanisms of various diseases has shaped different eras in public health, each closely linked to breakthroughs in understanding disease etiology and pathophysiology.
In recent years, socioeconomic factors have been recognized as major determinants of health, leading to a renewed focus on the upstream factors - the so-called “causes of causes” - contributing to health inequalities. As a result, accurately measuring and analyzing these inequalities is essential for identifying their underlying causes and developing effective strategies to address them.
Large population-based studies have revealed that health inequalities are widespread and not just statistical anomalies (Marmot et al. 1978; Marmot et al. 1991). These studies also showed that health inequalities do not only affect the socially worst-off people but cross the whole population along a so-called social gradient in health. The importance of health inequalities has gained increasing recognition, prompting the UK government to commission the "Fair Society, Healthy Lives" report, commonly referred to as the Marmot Review (Marmot 2013; Marmot et al. 2008). This landmark report identified the most effective evidence-based policies to reduce health inequalities.
Lastly, the WHO has underscored the importance of addressing the social determinants of health in order to achieve a "health for all" policy, producing several reports that highlight health equity gaps and propose potential solutions (Health and Organization 2008; Marmot et al. 2012).
2. Inequalities in the breast cancer care continuum
The cancer care continuum is a framework that outlines six critical stages in cancer care: prevention, early detection, diagnosis, treatment, survivorship, and end-of-life care. Each stage influences patient outcomes, from reducing cancer risk through preventive measures and early detection to managing treatment, survivorship, and end-of-life care. Patients may transition between these stages, with some stages potentially overlapping. Understanding this continuum is crucial for enhancing patient outcomes, coordinating care, and ensuring effective resource allocation (IOM 2013). Socioeconomic inequalities across these stages can result in unequal cancer outcomes, including differences in incidence, survival, and quality of life (QoL).
Cancer incidence is shaped by both unavoidable factors, like aging and genetic mutations, and modifiable behaviors, such as smoking and alcohol consumption. Exposure to harmful substances, including tobacco, alcohol, obesity, occupational hazards, environmental pollution and oncogenic viruses, tends to be higher in lower socioeconomic groups, increasing their cancer risk (Bloomfield et al. 2006; Bosdriesz et al. 2015; Devaux and Sassi 2013; Huisman, Kunst, and Mackenbach 2005; Menvielle et al. 2010; Moayyedi et al. 2002; Shi et al. 2014; Singh, Siahpush, and Kogan 2010; Stuver, Boschi-Pinto, and Trichopoulos 1997; Hajat, Hsia, and O'Neill 2015). Socioeconomic inequalities have also been reported in adherence to preventive measures, such as smoking cessation and HPV vaccination (Kurani et al. 2022; Slattelid Schreiber et al. 2015; Sandoval et al. 2018). These inequalities in exposure and prevention contribute to differences in cancer incidence among socioeconomic groups.
For breast cancer in particular, modifiable risk factors such as sedentarism, obesity, and alcohol consumption have been shown to be socially patterned (Sandoval et al. 2019; Sfm et al. 2020) and could potentially contribute to a higher incidence of breast cancer in patients with lower socioeconomic status (SES).
In addition, mammographic screening is associated with a substantial increase in diagnosed breast cancer cases (Bleyer and Welch 2012). Multiple population-based studies have characterized the inequality gap in breast cancer screening, with a higher probability of screening uptake by women with higher SES, influencing the inequality trends of breast cancer incidence, which is reported to be more frequently diagnosed in women with a higher SES (Damiani et al. 2015; Duport and Ancelle-Park 2006; Missinne and Bracke 2015; Zackrisson et al. 2004).
Extensive research has highlighted significant socioeconomic inequalities in cancer survival and mortality outcomes, with individuals from lower socioeconomic backgrounds consistently facing poorer results (Lundqvist et al. 2016; Kogevinas and Porta 1997). This issue was first thoroughly reviewed by the International Agency for Research on Cancer (IARC), which emphasized the pronounced differences in survival and mortality across various cancers and populations (Kogevinas and Porta 1997). Later research by Coleman and colleagues further solidified the understanding that SES is a crucial prognostic factor in adult cancers(Woods, Rachet, and Coleman 2006). Those with lower SES generally have worse survival rates and higher mortality compared to their wealthier counterparts.
The causes of these inequalities are complex and varied. Vagero and Persson (Vagero and Persson 1987) identified several key factors contributing to these differences:
Early Detection: People with higher SES are more likely to benefit from early cancer detection due to better access to screening and diagnostic services. Early detection often leads to more favorable treatment outcomes and improved survival rates.
Treatment Quality: There is evidence that treatment quality varies, with those of higher SES receiving more timely and effective cancer care. This inequality in treatment directly affects prognosis, as individuals from lower socioeconomic backgrounds often experience delays in treatment or receive less effective care.
Host Factors: Differences in overall health, nutrition, and comorbidities affect a person’s susceptibility to cancer and their response to treatment. Individuals from lower socioeconomic backgrounds may have additional health challenges or limited access to supportive care, negatively impacting their cancer outcomes.
Tumor Biology: Variations in the biological characteristics of tumors are also observed, with certain types of tumors being more or less common depending on SES. These differences can affect the cancer’s aggressiveness and the success of treatment, further contributing to survival inequalities.
In summary, the reasons for socioeconomic inequalities in cancer survival and mortality can be categorized into three main areas: patient-related, disease-related, and healthcare-related factors. Patient-related factors include differences in health behaviors and comorbidities. Disease-related factors involve variations in tumor biology and the nature of the cancer itself. Healthcare-related factors pertain to inequalities in access to early detection and quality, timeliness, and access to healthcare services.
a. Patient characteristics
Cancer mortality outcomes are shaped not only by the disease itself but also by various patient-related factors, including comorbidities, unhealthy behaviors, nutrition, and social support. Comorbidities can reduce the likelihood of receiving effective treatment, while behaviors such as smoking and alcohol use - more common in lower socioeconomic groups—can further exacerbate mortality rates. Proper nutrition is vital for cancer patients to endure treatment, but obesity, which is more prevalent in lower socioeconomic groups, has been shown to impact survival negatively (Demark-Wahnefried et al. 2012). Social support, including factors like marital status and the strength of social networks, also plays a significant role in cancer survival, and these aspects are typically more advantageous for those with higher SES (Ell et al. 1992; Pinquart and Duberstein 2010). These factors contribute to the overall socioeconomic inequalities in cancer outcomes.
b. Disease severity
The stage at which cancer is diagnosed is a key factor in determining survival outcomes (McPhail et al. 2015; Sant et al. 2003), guiding treatment choices to maximize cure rates or improve QoL. Socioeconomic inequalities in the stage at diagnosis contribute significantly to inequalities in cancer survival and mortality, with lower SES often associated with later-stage diagnoses (Clegg et al. 2009; Lantz et al. 2006; Schwartz et al. 2003; Wells and Horm 1992). However, research has shown that the stage at diagnosis alone does not fully explain these inequalities, particularly when area-level deprivation indicators are considered (Kaffashian et al. 2003).
Additional factors beyond the stage at diagnosis, such as environmental context and access to healthcare resources, may also play a role. The concept of "stage migration" (Feinstein, Sosin, and Wells 1985) – where the use of better diagnostic technology by those with higher SES could artificially improve survival statistics - has been considered, but studies have generally ruled it out as a main driver of these inequalities (Thomson et al. 2001; Wrigley et al. 2003).
Moreover, there is evidence that the biological characteristics of cancers, such as tumor grade and subtype, may differ by SES. For example, lower SES has been linked to higher tumor grades in ovarian cancer (Peterson et al. 2014) and a higher prevalence of aggressive breast cancer subtypes, like triple-negative breast cancer, particularly among certain racial and ethnic groups (Aoki et al. 2021; Bauer et al. 2007; Parise and Caggiano 2017). However, the relationship between SES and breast cancer tumor grade remains unclear (Adams, White, and Forman 2004).
c. Health care
The design of the healthcare system and the organization of cancer care networks can influence how SES affects access to specialized care. For instance, despite France’s reputation for having a healthcare system that provides free universal coverage and achieves excellent outcomes, studies have identified SES-related inequalities in access to highly specialized centers (Blais et al. 2006; Gentil et al. 2012). In the United States, individuals who are uninsured or covered by Medicaid (a program primarily supporting those with lower incomes) are less likely to receive care at high-volume hospitals (Nabi et al. 2021).
A significant, and perhaps the most apparent, healthcare-related factor is the inequality in treatment received based on SES. These inequalities have been observed across different stages of the care continuum, even in high-income countries or with universal healthcare coverage.
For patients with non-metastatic breast cancer, breast-conserving surgery followed by radiotherapy has been shown to offer similar survival outcomes to mastectomy with less associated morbidity. Consequently, it has become a standard treatment for early breast cancer. However, inequalities in the likelihood of receiving breast-conserving surgery have been documented in various countries(Baade et al. 2016; Bouchardy, Verkooijen, and Fioretta 2006; Lautner et al. 2015). In resource-poor countries, these inequalities might be attributed to a lack of radiotherapy facilities (Vanderpuye et al. 2017), but this is not the case in resource-rich countries like the United States and those in Europe.
Since survival outcomes are similar between mastectomy and breast-conserving surgery, these inequalities are not expected to affect patient survival rates directly. However, inequalities in receiving radiotherapy after breast-conserving surgery have been identified even in resource-rich countries, with clear implications for patient survival outcomes (Eaker et al. 2009; Nayyar et al. 2019).
3. Inequalities in Breast Cancer Survivorship
a. Available evidence
As mentioned earlier, advances in cancer diagnosis and treatment have led to higher survival rates, resulting in an increasing number of cancer survivors (Brenner 2002). Consequently, survivorship has become a more critical phase of the cancer care continuum.
For employed working-age individuals, returning to work after breast cancer treatment can be delayed due to a reduced QoL (Dumas et al. 2020). Research indicates that lower education and income levels are associated with a delayed return to work following breast cancer treatment (Fantoni et al. 2010; van Muijen et al. 2013). Additionally, women with low SES are more likely to experience a decrease in household income after a cancer diagnosis (Alleaume et al. 2019). These inequalities may be due to differences in job types between socioeconomic groups and a higher burden of symptoms that hinders the ability to resume pre-diagnosis workload and productivity.
These findings emphasize that the roots of inequalities in QoL and other health outcomes extend beyond the healthcare sector and have significant implications. While survival outcomes often receive more attention, a comprehensive understanding of the burden of disease requires considering both its length and associated QoL.
In economic terms, the impact of inequalities on healthcare costs has been recognized. A study estimated that health inequalities in the European Union account for 9.4% of GDP, about 15% of social security benefits, and 20% of total healthcare costs (Mackenbach, Meerding, and Kunst 2011). A significant portion of these costs may be linked to the economic consequences of QoL in cancer survivors.
However, research on inequalities in the QoL of cancer survivors is limited. Inequalities have been observed mainly in cross-sectional studies that evaluated the QoL of patients with a breast cancer at various stages of survivorship and different disease stages (both advanced and early breast cancer) (Ahn et al. 2007; Alonso-Molero et al. 2020; Graells-Sans et al. 2018; Han et al. 2021; Levinsen et al. 2023).
For instance, Graells-Sans et al. explored how social and economic factors affect the QoL in breast cancer survivors (Graells-Sans et al. 2018). Conducted on 2,235 women treated between 2003 and 2013 in Barcelona (Spain), this study highlighted significant inequalities in QoL based on social class and social network support. Women with lower SES and those socially isolated reported poorer QoL outcomes across various functional scales, including physical, emotional, and social well-being.
Alonso-Molero et al. investigated the long-term QoL of breast cancer survivors, focusing on the influence of sociodemographic factors such as educational level (Alonso-Molero et al. 2020). Conducted on 1,078 women treated for breast cancer in Spain, the study used two standardized and validated questionnaires, the SF-12 and FACT/NCCN Breast Symptom Index (FBSI), to assess QoL. Women with higher education levels reported significantly better QoL scores across all measures. The differences in QoL scores between women with university degrees and those without schooling were substantial, highlighting the impact of education on long-term well-being.
Ahn et al. analyzed the determinants of the QoL of disease-free breast cancer survivors (Ahn et al. 2007). Conducted on 1,933 disease-free survivors who had been diagnosed with stages 0 to III breast cancer, the study employed several standardized QoL instruments and also analyzed the educational level of patients. In multivariate analysis, lower educational level was significantly associated with lower QoL in breast cancer survivors. However, these studies did not involve repeated measurements hampering the study of possible changes in these inequalities over time after breast cancer diagnosis, or had incomplete data on factors such as menopausal status and cancer treatment.
To circumvent these limitations, Sandoval et al. assessed QoL at diagnosis and one and two years post-diagnosis, using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) (Sandoval et al. 2024). The authors draw on data from 5,915 women participating in the French CANTO cohort. This cohort includes women with early breast cancer and with a longitudinal follow-up of QoL, a detailed socioeconomic characterization as well as complete data on breast cancer disease characteristics and treatment.
The study's findings reveal significant socioeconomic inequalities in QoL at diagnosis. Women from lower SES groups, as defined by financial difficulties, income levels, and educational attainment, reported notably poorer QoL than their higher SES counterparts. These inequalities did not remain static; they significantly widened over the first two years following diagnosis. This suggests that women with lower SES are more likely to experience a more significant decline in QoL as they navigate through treatment and the initial recovery period.
Whatever the SES indicator considered, women from lower SES groups at diagnosis exhibited the most pronounced decreases in QoL over time. The study highlighted a stark difference in QoL between those low and high SES, underscoring the profound impact that SES can have on a breast cancer survivor's QoL. These SES factors influenced the overall QoL and specific symptoms and side effects that patients experienced during and after their treatment.
Importantly, these inequalities were significant despite taking into account important variables such as stage at diagnosis in the statistical modelling, suggesting that the differences in QoL were not merely the consequence of women with lower SES having a more severe disease requiring more intensive treatment with a higher impact on QoL.
The researchers further stratified the results by menopausal status and type of systemic treatment, including chemotherapy and endocrine therapy. Across all subgroups, lower SES consistently corresponded with worse QoL outcomes. This trend persisted even among participants in clinical trials, who might be expected to receive more consistent, equitable and intensive care. Despite such access to specialized care, the persistence of these inequalities suggests that they are deeply entrenched and not easily mitigated by healthcare interventions alone.
The study emphasizes that the observed inequalities are not simply initial discrepancies but are dynamic, growing more pronounced over time. This finding points to the necessity of long-term interventions that address these inequalities in order to prevent the widening QoL gap among breast cancer survivors. The results underscore the importance of incorporating socioeconomic factors into cancer care strategies. Addressing these inequalities is essential not only for improving the long-term QoL of breast cancer survivors but also for ensuring that all patients, regardless of their socioeconomic background, have the opportunity to recover and thrive after their treatment.
b. Explaining the inequalities in survivorship and their widening over time after diagnosis
As with breast cancer incidence and survival outcomes, patient QoL during survivorship is influenced by several factors related to patient characteristics before the diagnosis (e.g., the existence of comorbidities), the disease characteristics (e.g., stage at diagnosis and the need for more QoL impacting treatments), and factors related to the resources that could help patients better cope with the treatments and their burden on QoL (e.g., social networks, work stability, access to psychological support activities that may mitigate the side effects of treatment).
Due to the complex interplay between these factors, how they concur, resulting in the observed inequalities in QoL and their widening after a breast cancer diagnosis, has not been formally elucidated or demonstrated. Nevertheless, some plausible options can be identified and could be the object of future research projects.
As previously mentioned, a higher stage at diagnosis has been described in women with lower SES (Clegg et al. 2009; Lantz et al. 2006; Schwartz et al. 2003; Wells and Horm 1992). A higher stage is associated with a treatment associated with higher morbidity, such as the use of chemotherapy or lymph node dissection (Loibl et al. 2023). Furthermore, patients with comorbidities may have an increased symptom burden related to the side effects of treatment (Arneja and Brooks 2021; Fu et al. 2015). In addition, unhealthy behavior, such as tobacco and alcohol consumption or sedentarism, may be associated with decreased QoL (Buffart et al. 2017; Chen et al. 2023; Nolazco et al. 2023; Price et al. 2023). Of note, comorbidities and unhealthy behaviors are socially patterned (Fowler et al. 2020; Pampel, Krueger, and Denney 2010).
Factors affecting which treatments are provided to women with early breast cancer can also impact their QoL (Ferreira et al. 2019). The last decades have seen a push towards a better tailoring of treatments in order to avoid overtreating patients (Angarita et al. 2022; Sacchini and Norton 2022; Trapani et al. 2022). The better selection of patients is sometimes contingent on the availability of expensive technology, such as expensive genomic testing (Piccart et al. 2021). In countries without universal healthcare or that rely on considerable out-of-pocket payments, the affordability of these tests may preclude patients with lower SES from benefiting from de-escalated treatments.
Besides direct costs, indirect costs may also induce inequalities. For instance, breast conservative surgery, when indicated, is now recognized as being associated with the same survival benefit as mastectomy while having less impact on patient QoL (Hanson et al. 2022; Lautner et al. 2015). However, breast-conservative surgery is contingent on patients undergoing adjuvant radiotherapy. Even when available, patients with lower SES, less social support, and in a precarious work situation may opt for mastectomy as they cannot afford the time off from work or other familial and societal obligations or simply the traveling to treating centers (Lautner et al. 2015). Furthermore, as in other specialized surgeries, breast cancer surgery outcomes, including morbidity associated with complications or less than optimal cosmetical outcomes, are influenced by the experience and the caseload of the surgeon (de Camargo Cancela, Comber, and Sharp 2013; Sainsbury et al. 1995). It is thus also possible that women with lower SES have less access to specialized, experienced surgeons compared to those with a higher SES.
However, the inequalities in patient QoL have been described so far in high-income countries and, in the case of France, as being independent of age, patient comorbidities, stage of diagnosis, and received treatment (Sandoval et al. 2024). The genesis of the inequalities and their widening trends therefore probably lie – at least partly – outside the healthcare sector. Several interventions including physical activity, behavioral cognitive therapy or yoga and mindfulness interventions have been identified as effective in mitigating the side effects of early breast cancer treatment, particularly endocrine therapy. When available, these interventions are proposed to patients undergoing breast cancer treatment (Franzoi et al. 2021). As such, lower awareness level of the existence of these interventions by those with lower SES as well as increased barriers to their use (either financial or practical, such as availability in relative proximity to their residence) may contribute to the inequalities in QoL.
Furthermore, a considerable proportion of women with breast cancer are at childbearing age or at an age when their children have not achieved adulthood. Consequently, the existence of a good family and social network, coupled with a stable source of income, could help reduce the stress and associated loss of QoL when women are faced with challenges to continue to assume familial, social, and work responsibilities. These factors are often socially patterned and women from high SES groups benefit from a more socially and financially supportive environment.
c. Tackling the inequalities in survivorship
As we have discussed, the inequalities in breast cancer survivorship are quite probably the product of multiple concurrent factors. As a consequence and as with any complex system, mitigating these inequalities requires different levels of action, both inside and outside the healthcare system.
First, even in countries with universal healthcare system and affordable care, where access to optimal early breast cancer is – in theory – not socially patterned, inequalities in treatment may still exist (Bouchardy, Verkooijen, and Fioretta 2006). As such, independently of the health system characteristics of a particular setting, it remains important to identity and tackle the barriers that hinder equal treatment for patients in equal need, independent of their SES. This is of utmost importance in an era of increasing personalized medicine to ensure that all patients benefit from these medical advances.
Second, it is important to ensure that the probability of early detection is equal across the socioeconomic gradient. Studies have consistently described inequalities in mammographic screening that are not abrogated through the implementation of organized screening. Although some studies have already investigated possible strategies to decrease social inequalities in screening attendance (Guillaume et al. 2017), a better understanding of why women with lower SES forgo screening is still critical to devising screening strategies that remove or make barriers to screening less pronounced.
Third, supportive care with a particular focus on the breast cancer survivorship period is a relatively recent concern of health care and public health professionals and society in general. The focus on QoL is leading to the development of survivorship programs, including multilevel interventions such as stimulating physical activity and psychological support. However, this supportive care is seldom recognized as part of the early breast cancer care bundle with either low levels of reimbursement from insurance or investment from governments when compared to oncology drugs expenditure. This can lead to the access and use of supportive care for breast cancer survivors to be socially patterned. Besides the direct cost of supportive care, indirect costs may also play a role, with women with more labor-intensive and precarious jobs not being able to afford the time from work or family to participate in these activities. As such, policymakers should pay increased attention to this issue and pursue an optimized reimbursement of breast cancer survivorship supportive care. Furthermore, regularly evaluating the socioeconomic equality or inequality of access to and use of these services is crucial to prevent them from exacerbating existing inequalities.
Finally, the social context is a main determinant of overall QoL, as can be deducted by the fact that inequalities in QoL exist at diagnosis and before any breast cancer treatment. Moreover, impaired QoL can negatively impact patients' social and working lives, potentially delaying their return to work following early breast cancer treatment and, in some cases, having a negative impact on an already precarious socioeconomic situation. As such, understanding and providing the required levels of social support during breast cancer survivorship is fundamental to lessen the impact of the disease on patients' SES and QoL.
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