Understand Disparities in Cervical Cancer Survival

子宫颈癌是一种完全可以预防的疾病，但在德克萨斯州，每年约有1200名妇女新确诊，300人死于这种疾病。最近的几项研究表明，贫困而非少数民族可能是生存不良的一个重要预测因素，特别是对那些在早期阶段被诊断出来的人来说。这个项目的目的是探索德克萨斯州宫颈癌在诊断、治疗和生存阶段的差异，这是一个种族、收入和城乡差异很大的大州。我们提出一项基于人群的队列研究，纳入1995-2002年期间所有被诊断为宫颈癌并向德州癌症登记处（TCR）报告的妇女（nbb8800名妇女）。具体目的是：(1)确定少数种族或族裔（亚洲人、西班牙人、相对于白人的非裔美国人）、收入或教育水平较低、生活在农村地区较多的被诊断患有CxCa的妇女是否更容易死亡或生存时间较短，并按肿瘤分期分层。(2)确定不同种族、收入或农村妇女的生存差异在多大程度上可以用她们所接受的治疗、诊断时的肿瘤分期或合并症来解释。我们计划使用(a)地理编码数据，以便对社会经济地位进行更精确的人口普查区水平测量；(b)多种来源的癌症治疗数据（德克萨斯州医疗补助、医疗保险和医院出院与TCR癌症和死亡率数据合并）。提出了一个概念模型来评估差异在以下方面的作用：(1)宫颈癌生存率，(2)中间结果（诊断晚期和次优治疗），以及(3)合并症。多水平logistic回归和Cox比例风险模型分别用于估计死亡率和生存时间的风险。该R21将提供干预前数据，以确定这些差异指标，这些指标应成为积极的个人和保健提供者一级干预的目标，以便及早发现宫颈癌，并及时为妇女提供所需的有效治疗。

Cervical cancer is an entirely preventable disease yet in Texas approximately 1200 women are newly diagnosed and 300 die with this disease per year. Several recent studies suggest that poverty not minority ethnicity may be an important predictor of poor survival particularly for those diagnosed at an early stage. The purpose of this project is to explore disparities in cervical cancer stage at diagnosis, treatment and survival in Texas, a large state with great ethnic, income, and rural / urban diversity. We propose a population-based cohort study of all women diagnosed with cervical cancer and reported to the Texas Cancer Registry (TCR) between 1995-2002 (N>8800 women). Specific Aims are (1) To determine whether women of minority race or ethnicity (Asian, Hispanic, and African-American relative to White), those with lower income or education, and those living in more rural regions among women diagnosed with CxCa are more likely to die or have shorter survival, stratified by tumor stage. (2) To determine to what extent the differences in survival experienced by women of diverse ethnicity, income, or rurality can be explained by their treatment received, tumor stage at diagnosis or comorbid conditions. We plan to use (a) geocoded data to allow a more precise census tract level measures of socio-economic status and (b) multiple sources of cancer treatment data (Texas Medicaid, Medicare, and Hospital Discharge merged with TCR cancer and mortality data). A conceptual model is proposed to assess the role of disparities in (1) cervical cancer surivival, (2) intermediate outcomes (late stage at diagnosis and suboptimal treatment), and (3) comorbid conditions. Multilevel logistic regression and Cox proportional hazards modeling are planned to estimate the risk of mortality and survival time, respectively. This R21 will provide pre-intervention data to identify those disparities indicators which should be the target of aggressive individual and health care provider level interventions to identify cervical cancer early and get women needed effective treatment in a timely manner.