University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, P.O. Box 30 001, FA40, 9700, RB, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, Groningen, Department of Radiology, PO Box 30.001, EB44, 9700, RB, Groningen, the Netherlands.
University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, P.O. Box 30 001, FA40, 9700, RB, Groningen, the Netherlands.
Breast. 2023 Oct;71:74-81. doi: 10.1016/j.breast.2023.07.012. Epub 2023 Jul 27.
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.
对导管原位癌(DCIS)的自然史进行假设是准确建模和估计过度诊断的必要条件。为了提高目前对过度诊断(0-91%)的估计,本综述的目的是确定并分析女性 DCIS 自然史建模研究中所做的假设。
对截至 2023 年 2 月 6 日在 PubMed、Embase 和 Web of Science 上发表的英文全文文章进行了系统综述。两名评审员独立进行了合格性和所有评估。进行了风险偏倚和质量评估。通过共识解决了差异。读者一致性用 Cohen 的 kappa 进行量化。使用三种表格对研究特征、模型评估和肿瘤进展进行了数据提取。
区分出 30 种模型。关于 DCIS 自然史的最重要的假设是加入 20-100%的非进展性 DCIS、将 DCIS 分为三个等级,其中高级别 DCIS 更有可能进展为浸润性乳腺癌(IBC),以及 1-4%的可能性发生消退,取决于年龄和等级。其他被确定为 DCIS 进展为 IBC 的风险因素是年龄较小、出生队列、肿瘤较大和个体风险。
为了准确地对 DCIS 的自然史进行建模,需要考虑的方面包括 DCIS 分级、非进展性 DCIS(9-80%)、从 DCIS 到无癌症(低于 10%)的消退以及使用经过充分验证的进展概率风险因素(年龄)。对研究 DCIS 时需要考虑的关键因素有更深入的了解,可以提高对过度诊断的估计,并优化筛查。