为准确地对原位导管癌（DCIS）的自然历史进行建模和估计过度诊断率，有必要进行假设。为改进当前对过度诊断率（0-91%）的估计，本综述的目的是确定和分析在女性DCIS自然历史建模研究中所做的假设。对英文全文文章进行了系统审查，使用PubMed、Embase和Web of Science数据库，截止到2023年2月6日。两名评估员独立地进行了资格和所有评估。进行了偏倚风险和质量评估，通过共识解决了差异。使用Cohen's kappa量化了读者一致性。使用三种表格进行了数据提取，包括研究特征、模型评估和肿瘤进展。共区分了30个模型。关于DCIS的自然历史最重要的假设是新增非进展性DCIS（20-100%），将DCIS分类为三个等级，其中高等级DCIS有较高的进展为浸润性乳腺癌（IBC）的机会，以及根据年龄和等级可能出现1-4%的倒退情况。DCIS向IBC进展的其他已确认危险因素包括年龄较小、出生时期、较大的肿瘤大小和个体风险。为了准确地对DCIS的自然历史进行建模，需要考虑的因素包括DCIS等级、非进展性DCIS（9-80%）、从DCIS到无癌症的倒退率（低于10%）以及使用已确立的进展概率的风险因素（年龄）。了解研究DCIS时需要考虑的关键因素可以改善过度诊断的估计和筛查优化。版权所有 © 2023 The Authors. 由Elsevier Ltd.发表。保留所有权利。

Assumptions on the natural history of ductal carcinoma in situ (DCIS) are necessary to accurately model it and estimate overdiagnosis. To improve current estimates of overdiagnosis (0-91%), the purpose of this review was to identify and analyse assumptions made in modelling studies on the natural history of DCIS in women.A systematic review of English full-text articles using PubMed, Embase, and Web of Science was conducted up to February 6, 2023. Eligibility and all assessments were done independently by two reviewers. Risk of bias and quality assessments were performed. Discrepancies were resolved by consensus. Reader agreement was quantified with Cohen's kappa. Data extraction was performed with three forms on study characteristics, model assessment, and tumour progression.Thirty models were distinguished. The most important assumptions regarding the natural history of DCIS were addition of non-progressive DCIS of 20-100%, classification of DCIS into three grades, where high grade DCIS had an increased chance of progression to invasive breast cancer (IBC), and regression possibilities of 1-4%, depending on age and grade. Other identified risk factors of progression of DCIS to IBC were younger age, birth cohort, larger tumour size, and individual risk.To accurately model the natural history of DCIS, aspects to consider are DCIS grades, non-progressive DCIS (9-80%), regression from DCIS to no cancer (below 10%), and use of well-established risk factors for progression probabilities (age). Improved knowledge on key factors to consider when studying DCIS can improve estimates of overdiagnosis and optimization of screening.Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.