Individual and contextual deprivation: Association with cancer outcomes and implications for cancer policy

在英国，与生活在收入较低地区的人相比，居住在收入较低地区的人在被诊断为癌症后的寿命较短。癌症存活率的不平等至少有一部分是由于癌症护理的不平等，即使考虑到患者和肿瘤的不同因素，如诊断时的阶段。在全民保健系统的背景下，基于区域的贫困水平导致较差的个人健康结果的具体机制尚未得到很好的理解。这些分析将第一次能够检查单个患者的社会经济地位如何与英格兰较差的癌症存活率相关，并将展示这些关联可能如何被患者居住的小区域的剥夺程度所改变。我们的目标是对单个患者的剥夺与癌症存活率之间的关联进行深入研究，特别是考虑到这种关联如何受到他们的社会经济背景的影响，自确诊以来是否随着时间的推移而变化，以及是否随着日历时间的变化而变化。我们将重点关注剥夺的三个指标：收入、教育和职业。我们将首先通过这些指标来检验个体剥夺和区域剥夺之间的相关性，然后描述个体剥夺与生存之间的关联。第三，我们将评估个人剥夺与患者生存之间的联系是否被区域剥夺所改变；即，不同地区的同等剥夺的个人根据所在地区的社会经济背景，是过得更好，还是过得更差。最后，我们将获得患者、护理人员和医疗保健专业人员对这些数据的见解，并将这些数据传达给癌症政策制定者。我们将使用英国国家统计局纵向研究的数据，其中包含自1971年以来每次全国人口普查中1%的英格兰人的个人剥夺信息。国家统计局-LS与癌症登记处的数据相关联，因此可以检查队列成员中所有浸润性癌症诊断的信息。这些数据将进一步与下超输出区(LSOA，平均人口1,500)定义的多重剥夺指数(IMD)联系起来，以获得基于区域的剥夺措施。我们将拟合超额死亡率风险(EMH)的回归模型，以检验癌症存活率如何随个体剥夺状态的变化而变化。EMH代表了在癌症患者中观察到的死亡风险，并考虑了每个患者的预期死亡率。我们将使用国家统计局-LS死亡率和人口数据，构建按个人剥夺分层的生命表，以尽可能准确地计算这一背景死亡率。我们将通过使用相互作用术语来评估这些联系是否根据生态剥夺的程度而被修改。我们将使用灵活的函数检验个体剥夺和有效医疗卫生之间的时间依赖关系，并将通过共享的随机效应(定义在LSOA水平)来解释来自同一小区域的观察结果之间的相关性。结果将使我们能够确定癌症患者个人和区域剥夺之间的对应程度；评估个人剥夺(收入、教育或职业)如何与癌症特定死亡率相关；以及量化这些关联是否以及如何根据区域剥夺进行修改，以及自诊断以来这些关联如何变化。在项目的最后阶段，我们将征求患者、护理人员和医疗保健专业人员对我们调查结果的见解。然后将在半天的研讨会上直接与政策制定者分享这些信息，以便未来旨在减少社会经济不平等的政策更有针对性。

In the UK, people who reside within more income-deprived areas live a shorter period of time after a diagnosis of cancer compared to people living in less income-deprived areas. At least part of these inequalities in cancer survival are due to inequalities in cancer care, even considering differential patient and tumour factors such as stage at diagnosis. The specific mechanisms by which area-based deprivation levels lead to poorer individual health outcomes within the context of a universal healthcare system, free at the point of use, are not well understood. These analyses will enable, for the first time, the examination of how an individual patient's socio-economic status is associated with poorer cancer survival in England, and will demonstrate how these associations might be modified by the level of deprivation in the small area within which the patient resides.Our aim is to perform an in-depth study of the association between the individual patient's deprivation and cancer survival, considering in particular how this is influenced by their socio-economic context, whether it varies over time since diagnosis and whether it has changed over calendar time. We will focus on three indicators of deprivation: income, education and occupation. We will first examine the correlation between individual and area deprivation, by each of these indicators, and then secondly describe the association between individual deprivation and survival. Third, we will assess whether the association between individual deprivation and patients' survival is modified by area deprivation; that is, whether equally deprived individuals in different areas fare better, or worse, according to the socio-economic context of the area within which they live. Finally we will gain the insights of patients, carers, and healthcare professionals on these data, and communicate these to cancer policy makers.We will use data from the ONS Longitudinal Study, which contains individual deprivation information on 1% of individuals in England present at each national census since 1971. The ONS-LS is linked to Cancer Registry data so that information on all diagnoses of invasive cancer amongst cohort members can be examined. These data will be further linked to the Indices of Multiple Deprivation (IMD) defined at the Lower Super Output Area (LSOA, mean population 1,500) to obtain area-based measures of deprivation. We will fit regression models for the excess mortality hazard (EMH) in order to examine how cancer survival varies with individual deprivation status. The EMH represents the mortality hazard that is observed among cancer patients, taking into account each patient's expected mortality. We will construct life tables stratified by individual deprivation, using the ONS-LS mortality and population data, in order to account as accurately as possible for this background mortality. We will assess whether these associations are modified according to the ecological level of deprivation through the use of interaction terms. We will examine time-dependent associations between individual deprivation and the EMH using flexible functions, and will account for the correlation between observations coming from the same small area through a shared random-effect (defined at LSOA level).The results will allow us to determine the degree of correspondence between individual and area deprivation for cancer patients; to assess how individual deprivation (income, education or occupation) is associated with cancer-specific mortality; and to quantify if and how these associations are modified according to area deprivation, as well as how these associations vary by the time since diagnosis. During the final phases of the project we will seek the insights of patients, carers and healthcare professionals upon our findings. These will then be directly shared with policy makers in a half-day workshop, so that future policies aimed at reducing socio-economic inequalities are more targeted.