Estimating and Mitigating Thyroid Cancer Overdiagnosis: A Mathematical Modeling Approach

估计和减轻甲状腺癌过度诊断：数学建模方法

• 批准号: 10415124
• 负责人: Oguzhan Alagoz
• 金额: $ 44.8万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-14 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10415124
• 关键词: Accounting; Address; Age; Anxiety; Biological; Biopsy; Breast; Caliber; Calibration; Cancer Model; Cessation of life; Clinical; Clinical Practice Guideline; Clinical Trials; Colorectal; Communication; Conceptions; Data; Development; Diagnosis; Disease; Engineering; Ensure; Exposure to; Face; Goals; Growth; Guidelines; Health Care Costs; Health Policy; Health Services Research; Healthcare Systems; Histologic; Image; Incidence; Industrialization; Intervention; Knowledge; Lead; Lesion; Lung; Machine Learning; Malignant Neoplasms; Malignant neoplasm of thyroid; Medical Care Costs; Methods; Mission; Modeling; Morbidity - disease rate; National Cancer Institute; Natural History; Nodule; Non-Malignant; Outcome; Output; Papillary thyroid carcinoma; Patient imaging; Patients; Pattern; Persons; Policy Maker; Predisposing Factor; Procedures; Prostate; Provider; Quality of life; Quality-Adjusted Life Years; Recommendation; Research; Resources; Risk; Symptoms; System; Testing; Thyroid Gland; Time; United States; Validation; Withholding Treatment; cancer diagnosis; cancer epidemiology; cancer site; clinically relevant; dissemination strategy; follow-up; health care quality; health care service utilization; high risk; improved; innovation; mathematical model; model development; models and simulation; mortality; multidisciplinary; novel; overtreatment; patient population; patient subsets; public health relevance; sex; side effect; thyroid neoplasm; tumor growth; ultrasound; unethical; virtual; virtual laboratory

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.

项目摘要/摘要 该提案将产生证据，以减少美国甲状腺癌的过度诊断。 过度诊断是对疾病的鉴定，如果未检测到，则不太可能引起 患者一生中的症状或死亡。过度诊断有重大后果，例如 过度治疗与相关的副作用和并发症，患者动画以及医疗保健成本的增加。 尽管自1980年代后期以来甲状腺癌诊断增加了三倍，但死亡率仍然存在 稳定的。很少致命的小甲状腺甲状腺癌几乎是全部增加的 在事件中。但是，假设所有小甲状腺癌均已过度诊断，这是不安全的。一些小 甲状腺癌可能是侵略性的，并且确实需要治疗。迫切需要有效的方法 了解导致甲状腺癌过度诊断的关键因素，以便有定向溶液可以是 开发和实施以减少过度诊断。我们提出了系统工程的创新使用 和模拟建模以解决这一知识差距，并提供对自然的细微理解 甲状腺肿瘤的史。我们将使用我们的模型来确定减少甲状腺的转介和使用的效果 成像过度诊断；改变活检对过度诊断的大小阈值的影响；和 减少过度诊断对治疗危害和益处的下游影响。这种方法也是如此 随着时间的推移，超声波的差异使用和提高了精度。我们的目标是创建和验证 量化甲状腺癌过度诊断的模拟模型。我们将在各个阶段的利益相关者与 从模型概念到验证的开发，从 结果和传播策略。我们的研究团队由 癌症建模方面的专业知识以及甲状腺癌，癌症流行病学，卫生服务专家 研究和沟通。多学科团队有资格完成三个特定的特定 目的：（1）开发和验证一个模拟模型来量化美国甲状腺癌的过度诊断； （2） 确定医疗保健利用模式（例如提供者遇到和推荐决定），使患者暴露于 甲状腺癌的甲状腺成像，活检和过度诊断增加； （3）聘请主要利益相关者 在项目的整个过程中，以确保模型具有面部有效性，并且输出可以是 适用于对临床医生和政策制定者都很重要的问题。拟议的研究与 国家癌症研究所的使命是帮助人们生活更长，更健康的生活。创新的结果 模型将有助于告知临床实践指南和推荐实践建议以改进 医疗保健的质量，同时减少不适当的测试，以最大程度地诊断和 过度治疗。