Understand Disparities in Cervical Cancer Survival

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名妇女被诊断为宫颈癌，300人死于这种疾病。最近的几项研究表明，贫穷而不是少数族裔可能是生存不佳的一个重要预测因素，特别是对于那些在早期被诊断的人。该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。德克萨斯州是一个幅员辽阔的州，种族、收入和城乡多样性很大。我们提出了一项基于人群的队列研究，研究对象是1995-2002年间德克萨斯州癌症登记处(TCR)报告的所有被诊断为宫颈癌的女性(N&GT；8800名女性)。具体目标是(1)确定少数族裔或民族(相对于白人的亚裔、西班牙裔和非裔美国人)、收入或教育程度较低的女性以及被诊断为CxCA的女性中生活在较农村地区的女性是否更有可能死亡或生存时间较短，按肿瘤分期进行分层。(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通过她们所接受的治疗、确诊时的肿瘤阶段或合并疾病来解释。我们计划使用(A)地理编码数据，以实现更精确的人口普查区域水平，以衡量社会经济状况和(B)多种来源的癌症治疗数据(德克萨斯州医疗补助、联邦医疗保险和医院出院数据与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(1)宫颈癌存活率，(2)中期结果(诊断和次优治疗的晚期)和(3)共病条件中的作用。多水平Logistic回归和COX比例风险模型分别用于估计死亡风险和生存时间。R21将提供干预前数据，以确定那些差异指标，这些指标应该成为积极的个人和医疗保健提供者层面干预的目标，以早期发现宫颈癌，并及时获得所需的有效治疗。

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.