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.

项目总结/摘要 该提案将为减少美国甲状腺癌的过度诊断提供证据。 过度诊断是指对一种疾病的识别，如果它没有被发现， 在病人的一生中出现症状或死亡。过度诊断有严重的后果，例如 过度治疗与相关的副作用和并发症、患者焦虑和增加的医疗费用。 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。 稳定小乳头状甲状腺癌，这是很少致命的，是负责几乎整个增加 在发病率。然而，假设所有的小甲状腺癌都被过度诊断是不安全的;一些小的甲状腺癌被过度诊断。 甲状腺癌可能具有侵袭性，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，以便能够找到针对性的解决方案。 制定和实施，以减少过度诊断。我们建议创新地使用系统工程 和仿真建模，以解决这一知识差距，并提供一个细致入微的理解自然 甲状腺肿瘤病史我们将使用我们的模型来确定减少甲状腺的转诊和使用的影响。 影像学检查对过度诊断的影响;改变活检的尺寸阈值对过度诊断的影响;以及 减少过度诊断对治疗利弊的下游影响。这种方法还 说明了随着时间的推移超声的不同使用和改进的精度。我们的目标是创造和验证 量化甲状腺癌过度诊断的模拟模型。我们将在所有阶段与利益相关者合作， 开发，从模型概念到验证，以引出临床指导并告知我们的模型输入， 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、健康服务方面的专家 研究和沟通。该多学科小组是高素质的，以完成三个具体的 目的：（1）开发并验证模拟模型，以量化美国甲状腺癌的过度诊断;（2） 识别医疗保健利用模式（例如，提供者接触和转诊决定），使患者暴露于 甲状腺成像、活检和甲状腺癌过度诊断增加;（3）吸引关键利益相关者的参与 在整个项目期间，以确保模型具有表面有效性，并且输出可以 适用于对临床医生和政策制定者都很重要的问题。拟议的研究符合 国家癌症研究所的使命是帮助人们活得更长、更健康。这一创新成果 模型将有助于告知临床实践指南和转诊实践建议，以改善 提高医疗质量，同时减少不适当的检测，以尽量减少过度诊断， 过度治疗