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.

项目概要/摘要 该提案将为减少美国甲状腺癌的过度诊断提供证据。 过度诊断是指识别出一种疾病，如果没有被发现，就不太可能引起 患者一生中出现症状或死亡会产生严重后果，例如 过度治疗会带来相关的副作用和并发症、患者焦虑以及医疗费用增加。 尽管自 20 世纪 80 年代末以来，甲状腺癌的诊断增加了三倍，但死亡率仍然很高 稳定的小型乳头状甲状腺癌很少致命，但几乎是全部病例增加的原因。 然而，认为所有小型甲状腺癌都被过度诊断是不安全的。 甲状腺癌具有侵袭性，迫切需要有效的治疗方法。 了解导致甲状腺癌过度诊断的关键因素，以便有针对性的解决方案 开发和实施以减少过度诊断。我们建议创新地使用系统工程。 和模拟建模来解决这一知识差距并提供对自然的细致入微的理解 我们将使用我们的模型来确定减少甲状腺肿瘤的转诊和使用的效果。 影像学对过度诊断的影响；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益处的下游影响也是如此。 随着时间的推移，我们的目标是创建和验证超声波的差异化使用和提高的精度。 量化甲状腺癌过度诊断的模拟模型我们将让利益相关者参与各个阶段。 开发，从模型概念到验证，以获得临床指导并为我们的模型输入提供信息， 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 多学科团队非常有资格完成这三项具体工作。 目标：(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)； 确定使患者接触的医疗保健利用模式（例如，提供者接触和转诊决定） (3) 吸引关键利益相关者 在整个项目期间确保模型具有表面有效性，并且输出可以 适用于对民众和政策制定者都很重要的问题。 美国国家癌症研究所的使命是帮助人们活得更长久、更健康，这是这一创新的成果。 模型将有助于为临床实践指南和转诊实践建议提供信息，以改善 医疗保健的质量，同时减少不适当的检测，以尽量减少过度诊断和 过度治疗。