Optimization of Treatment of Papillary Thyroid Cancer: A Risk-tailored Approach

描述(由申请人提供)：在完成内分泌外科奖学金后，应聘者加入了马萨诸塞州综合医院的外科肿瘤科工作人员，并于2010年被哈佛医学院聘用。自2010年以来，她获得了公共卫生硕士学位，通过癌症结果研究培训奖学金项目与她的导师建立了富有成效的关系，并被提升为助理教授。这一职业发展奖的动机是甲状腺癌对公共健康的重要性，这种癌症影响着超过50万美国人，而且发病率和流行率都在增加。乳头状甲状腺癌(PTC)的发病率和社会成本均较高。虽然PTC的发病率增长速度比其他任何癌症都快，但大多数新诊断的患者都是低风险人群中有小肿瘤的患者，特定疾病的死亡率仍然很低，而且没有变化。鉴于疾病的死亡率相对较低，在这一人群中，以存活率为主要终点的临床试验的持续时间和成本令人望而却步。因此，大多数临床实践仅基于共识。这位候选人试图通过构建一个全面的计算机模型来模拟美国人口中的个人，以解决这些知识差距。具体来说，候选人建议：1)制定决策-- 这些研究包括：1)利用分析模型模拟未治疗和已治疗患者的乳头状甲状腺癌的自然病史；2)进行研究，利用原始患者数据为当前缺乏数据的关键模型参数提供信息，以制定PTC复发的预测算法；以及3)评估和比较标准和替代管理策略对结果的影响，包括对健康和经济结果的风险分层治疗和监测。中心假设是，将改进的风险分层与量身定制的治疗和监测方法相结合，将优化护理质量和资源利用，同时将PTC患者的过度诊断和过度治疗降至最低。K07旨在通过在决策分析、调查科学和生物统计学以及有效和富有成效的指导关系方面的高级培训来培养独立性。该应用程序以多学科的方式利用了一组不同的经验丰富的导师的优势。这些目的将使我们了解我们目前治疗PTC患者的临床实践的健康和经济后果。最终，我们将确定可能从更积极的诊断和手术方法中受益的个人，并减少因复发疾病和无效的医疗和手术干预而导致的发病率。凭借在K07颁奖期间获得的技能和基础知识，候选人将准备提交一份竞争性的R01申请。

DESCRIPTION (provided by applicant): Following completion of endocrine surgery fellowship, the candidate joined the surgical oncology staff at the Massachusetts General Hospital and was appointed at Harvard Medical School in 2010. Since 2010, she achieved a Master of Public Health degree, established productive relationships with her mentors through the Program in Cancer Outcomes Research Training fellowship, and was promoted to Assistant Professor. This Career Development Award is motivated by the public health importance of thyroid cancer, which affects over 1/2 million Americans and is increasing in incidence and prevalence. Substantial morbidity and societal cost are attributable to papillary thyroid carcinoma (PTC). While the incidence of PTC is increasing faster than any other cancer, the majority of new diagnoses is patients with small tumors in a low-risk population, and disease-specific mortality remains low and unchanged. Given the relatively low disease- specific mortality, the length and cost of clinical trials with survival as the primary endpoint in this population are prohibitive. Te majority of clinical practices are, therefore, based on consensus alone. The candidate seeks to address these knowledge gaps by constructing a comprehensive computer model to simulate individuals in the U.S. population. Specifically, the candidate proposes to: 1) develop a decision- analytic model to simulate the natural history of papillary thyroid cancer in both untreated and treated patients; 2) conduct studies to inform key model parameters where data are currently lacking using primary patient data to develop a prediction algorithm for recurrence of PTC integrating knowledge of BRAF mutational status as well as patient-reported HRQoL data; and 3) evaluate and compare effects of standard versus alternate management strategies on outcomes, including risk-stratified approaches to treatment and surveillance on health and economic outcomes. The central hypothesis is that integrating improved risk-stratification and a tailored approach to treatment and surveillance will optimize quality of care and resource utilization while minimizing over-diagnosis and over-treatment for patients with PTC. This K07 is designed to foster independence through advanced training in decision analysis, survey science, and biostatistics as well as effective and productive mentoring relationships. The application draws upon strengths of a diverse group of experienced mentors in a multidisciplinary fashion. The aims will inform our understanding of the health and economic consequences of our current `clinical practices in the treatment of patients with PTC. Ultimately, we will identify individuals likely to benefit from more aggressive diagnostic and surgical approaches and reduce morbidity both from recurrent disease and ineffective medical and surgical interventions. With the skills and groundwork obtained during the K07 award period, the candidate will be prepared to submit a competitive R01 application.