Estimating and Mitigating Thyroid Cancer Overdiagnosis: A Mathematical Modeling Approach

项目摘要/摘要 这项建议将产生证据，以减少美国对甲状腺癌的过度诊断。 过度诊断是对一种疾病的识别，如果没有检测到它，就不太可能导致这种疾病 病人一生中的症状或死亡。过度诊断会产生重大后果，例如 过度治疗伴随着相关的副作用和并发症、患者焦虑和医疗成本增加。 尽管自20世纪80年代末以来，甲状腺癌的确诊病例增加了三倍，但死亡率仍然很高。 稳定。很少致命性的小乳头状甲状腺癌几乎是全部增长的原因。 在发病率上。然而，假设所有的小甲状腺癌都被过度诊断是不安全的；一些小的甲状腺癌 甲状腺癌可能是侵袭性的，确实需要治疗。迫切需要有效的方法来 了解导致甲状腺癌过度诊断的关键因素，以便有针对性地解决问题 开发和实施以减少过度诊断。我们建议创新运用系统工程。 和模拟建模，以解决这一知识鸿沟，并提供对自然 甲状腺肿瘤病史。我们将使用我们的模型来确定减少转诊和使用甲状腺的效果 影像对过度诊断的影响；改变活检大小阈值对过度诊断的影响； 减少过度诊断对治疗的危害和好处的下游影响。这种方法还 说明了随着时间的推移，超声波的不同使用和提高的精确度。我们的目标是创建和验证 一个量化甲状腺癌过度诊断的模拟模型。我们将在所有阶段都与利益相关者接触 开发，从模型构思到验证，以获得临床指导并为我们的模型输入提供信息， 成果和传播战略。我们的研究团队由一名工业系统工程师组成， 癌症建模方面的专业知识，以及甲状腺癌、癌症流行病学、卫生服务方面的专家 研究和交流。多学科团队非常有资格完成三个具体的 目的：(1)开发并验证一个模拟模型，以量化美国甲状腺癌的过度诊断；(2) 确定医疗保健利用模式(例如，提供者会面和转诊决定)，使患者面临 增加甲状腺成像、活检和对甲状腺癌的过度诊断；(3)吸引关键利益相关者参与 在项目的整个持续时间内，确保模型具有表面有效性，并确保输出可以 适用于对临床医生和决策者都很重要的问题。拟议的研究与 国家癌症研究所的使命是帮助人们活得更长、更健康。这一创新的结果 模型将有助于告知临床实践指南和转诊实践建议，以改进 医疗保健质量，同时减少不适当的检查，以最大限度地减少过度诊断和 过度治疗。

Project Summary/Abstract This proposal will generate evidence to reduce the overdiagnosis of thyroid cancer in the United States. Overdiagnosis is the identification of a disease that, had it not been detected, would be unlikely to cause symptoms or death during a patient’s lifetime. Overdiagnosis has significant consequences, such as overtreatment with associated side effects and complications, patient anxiety, and increased healthcare costs. Despite a three-fold increase in thyroid cancer diagnoses since the late 1980s, the mortality rate remains stable. Small papillary thyroid cancers, which are rarely lethal, are responsible for virtually the entire increase in incidence. However, it is not safe to assume that all small thyroid cancers are overdiagnosed; some small thyroid cancers can be aggressive and do need treatment. Effective methods are urgently needed to understand the key factors contributing to thyroid cancer overdiagnosis, so that directed solutions can be developed and implemented to reduce overdiagnosis. We propose the innovative use of systems engineering and simulation modeling to address this knowledge gap and provide a nuanced understanding of the natural history of thyroid tumors. We will use our model to identify the effect of reducing referrals for and use of thyroid imaging on overdiagnosis; the effect of changing the size threshold for biopsy on overdiagnosis; and the downstream impact of reducing overdiagnosis on harms and benefits of treatment. This approach also accounts for differential use and improved precision of ultrasound over time. Our goal is to create and validate a simulation model that quantifies overdiagnosis in thyroid cancer. We will engage stakeholders at all stages of development, from model conception to validation, to elicit clinical guidance and inform our model inputs, outcomes, and dissemination strategies. Our research team comprises an industrial-systems engineer with expertise in cancer modeling, as well as experts in thyroid cancer, cancer epidemiology, health services research, and communication. The multidisciplinary team is highly qualified to complete the three specific aims: (1) Develop and validate a simulation model to quantify overdiagnosis of thyroid cancer in the US; (2) Identify healthcare utilization patterns (e.g., provider encounters and referral decisions) that expose patients to increased thyroid imaging, biopsies, and the overdiagnosis of thyroid cancer; (3) Engage key stakeholders throughout the duration of the project to ensure that the model has face validity, and that the output can be applied to questions important to both clinicians and policy makers. The proposed research aligns with the National Cancer Institute’s mission to help people live longer and healthier lives. Results from this innovative model will help to inform clinical practice guidelines and referral practice recommendations to improve the quality of health care, while reducing inappropriate testing, to minimize overdiagnosis and overtreatment.