Trends and Disparities in Bladder Cancer Treatment

项目摘要/摘要：膀胱癌是男性的第四大常见癌症。 在美国女性中最常见的癌症排名第12位。它也是最昂贵的癌症 以病人为单位进行治疗。膀胱癌复发、进展和生存率的差异一直是 按患者性别、种族/民族和年龄报告。质量差距和待遇不平等可能会导致 结果不一致。与遗传或解剖特征等不可改变的因素相比，治疗 不平等代表了一个可修改的因素。因此，我们的研究将确定膀胱癌护理和 阐明治疗差异，以便为未来的质量改进干预措施提供信息。 膀胱癌的有效治疗方法已经存在，但可能在诊断的所有阶段都未得到充分利用。治疗 包括在初次经尿道膀胱电切术后24小时内使用膀胱内化疗 肿瘤和新辅助化疗联合根治性膀胱切除术的应用。未能使用膀胱内注射 已经估计了肿瘤切除后立即化疗(从而防止肿瘤复发)。 每年给美国造成约2000万美元的损失。因此，增加对指南一致性护理的使用 有可能改善患者的结果，减少差异，同时还降低医疗成本。 已经观察到不同患者组之间的治疗差异，尽管结果并不一致。 大多数研究没有全面评估膀胱癌的治疗，而是集中在少数几个方面 治疗实践，现有的研究也可能没有反映当代的治疗模式。 我们建议综合评估膀胱癌的治疗，并按患者性别、种族/民族、 年龄(目标1)和日历时间(目标2)，以确定质量差距和待遇不平等。我们的研究 该团队包括一名流行病学家、卫生经济学家、两名泌尿科医生和一名生物统计学家/分析师。我们会 建立2001年间所有21岁或以上被诊断为膀胱癌的患者的回顾队列- 2013年，在南加州凯撒永久会所庞大、多样化、以社区为基础的会员中 (KPSC)。我们将使用我们的高质量癌症登记和丰富的电子健康记录来评估 超过9000名膀胱癌患者。治疗实践将被编码为是/否，以表明遵守 完善的治疗建议。多变量Logistic回归模型将用于 评估不同患者组之间治疗依从性的差异。泊松回归或自回归 综合移动平均(ARIMA)模型将被用来评估一段时间内的治疗实践。 这些目标的完成将提供推荐治疗和实际治疗的详细比较 按患者性别、种族/民族、年龄和日历时间进行的广泛的膀胱癌治疗实践 建议。未来的质量改进工作可能会以结果为基础，针对治疗差距 最有潜力缩小差距，改善护理提供和患者结果。

Project Summary / Abstract: Bladder cancer is the fourth most common cancer among males and the twelfth most common cancer among females in the United States. It is also the most expensive cancer to treat on a per patient basis. Disparities in bladder cancer recurrence, progression and survival have been reported by patient sex, race/ethnicity, and age. Quality gaps and treatment inequity may contribute to outcomes disparities. In contrast to immutable factors such as genetic or anatomic characteristics, treatment inequity represents a modifiable factor. Thus, our study will identify quality gaps in bladder cancer care and elucidate treatment disparities in order to inform future quality improvement interventions. Effective treatments for bladder cancer exist but may be underutilized at all stages of diagnosis. Treatments include the use of intravesical chemotherapy within 24 hours of the initial transurethral resection of bladder tumor and use of neoadjuvant chemotherapy with radical cystectomy. Failure to use intravesical chemotherapy immediately post-tumor resection (and thus to prevent tumor recurrences) has been estimated to cost the United States around $20 million annually. Increasing the use of guideline-consistent care thus has the potential to improve patient outcomes and reduce disparities while also decreasing healthcare costs. Treatment disparities across patients group have been observed, although findings have not been consistent. Most studies have not comprehensively evaluated bladder cancer care but instead have focused on a few treatment practices, and existing research also may not reflect contemporary treatment patterns. We propose to comprehensively evaluate bladder cancer treatment overall and by patient sex, race/ethnicity, age (Aim 1) and calendar time (Aim 2) in order to identify quality gaps and treatment inequities. Our research team includes an epidemiologist, health economist, two urologists, and a biostatistician/analyst. We will create a retrospective cohort of all patients age 21 years or older diagnosed with bladder cancer during 2001- 2013 within the large, diverse, community-based membership of Kaiser Permanente Southern California (KPSC). We will use our high-quality cancer registry and rich electronic health record to evaluate care among over 9,000 bladder cancer patients. Treatment practices will be coded as yes/no to indicate adherence to well-established treatment recommendations. Multivariable logistic regression models will be used to evaluate differences in treatment adherence across patients groups. Poisson regression or Auto-Regressive Integrated Moving Average (ARIMA) models will be employed to evaluate treatment practices over time. The completion of these aims will provide a detailed comparison of recommended and actual treatment practices by patient sex, race/ethnicity, age, and calendar time for a wide range of bladder cancer treatment recommendations. Future quality improvement efforts may build upon the results to target the treatment gaps with the greatest potential to reduce disparities and improve care delivery and patient outcomes.