Suppr超能文献

在结直肠癌筛查有效性推断中因时间间隔粗化导致的偏差。

Bias due to coarsening of time intervals in the inference for the effectiveness of colorectal cancer screening.

作者信息

Karmakar Bikram, Zauber Ann G, Hahn Anne I, Lau Yan Kwan, Doubeni Chyke A, Joffe Marshall M

机构信息

Department of Statistics, College of Liberal Arts and Sciences, University of Florida, Gainesville, FL, USA.

Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

出版信息

Int J Epidemiol. 2024 Jun 12;53(4). doi: 10.1093/ije/dyae096.

Abstract

BACKGROUND

Observational studies are frequently used to estimate the comparative effectiveness of different colorectal cancer (CRC) screening methods due to the practical limitations and time needed to conduct large clinical trials. However, time-varying confounders, e.g. polyp detection in the last screening, can bias statistical results. Recently, generalized methods, or G-methods, have been used for the analysis of observational studies of CRC screening, given their ability to account for such time-varying confounders. Discretization, or the process of converting continuous functions into discrete counterparts, is required for G-methods when the treatment and outcomes are assessed at a continuous scale.

DEVELOPMENT

This paper evaluates the interplay between time-varying confounding and discretization, which can induce bias in assessing screening effectiveness. We investigate this bias in evaluating the effect of different CRC screening methods that differ from each other in typical screening frequency.

APPLICATION

First, using theory, we establish the direction of the bias. Then, we use simulations of hypothetical settings to study the bias magnitude for varying levels of discretization, frequency of screening and length of the study period. We develop a method to assess possible bias due to coarsening in simulated situations.

CONCLUSIONS

The proposed method can inform future studies of screening effectiveness, especially for CRC, by determining the choice of interval lengths where data are discretized to minimize bias due to coarsening while balancing computational costs.

摘要

背景

由于开展大型临床试验存在实际限制和所需时间,观察性研究经常被用于估计不同结直肠癌(CRC)筛查方法的比较效果。然而,随时间变化的混杂因素,例如上次筛查中息肉的检测情况,可能会使统计结果产生偏差。近来,广义方法(G-方法)已被用于结直肠癌筛查观察性研究的分析,因为其有能力考虑此类随时间变化的混杂因素。当治疗和结局以连续尺度评估时,G-方法需要进行离散化,即将连续函数转换为离散对应物的过程。

进展

本文评估了随时间变化的混杂因素与离散化之间的相互作用,这可能会在评估筛查效果时导致偏差。我们在评估典型筛查频率不同的各种结直肠癌筛查方法的效果时,研究了这种偏差。

应用

首先,通过理论我们确定了偏差的方向。然后,我们使用假设情境的模拟来研究不同离散化水平、筛查频率和研究周期长度下的偏差幅度。我们开发了一种方法来评估模拟情境中由于数据粗化可能产生的偏差。

结论

所提出的方法可以通过确定数据离散化时的区间长度选择,在平衡计算成本的同时将因粗化导致的偏差降至最低,从而为未来关于筛查效果的研究提供参考,尤其是针对结直肠癌的研究。

相似文献

3
Measures implemented in the school setting to contain the COVID-19 pandemic.学校为控制 COVID-19 疫情而采取的措施。
Cochrane Database Syst Rev. 2022 Jan 17;1(1):CD015029. doi: 10.1002/14651858.CD015029.
5
Selenium for preventing cancer.硒预防癌症。
Cochrane Database Syst Rev. 2018 Jan 29;1(1):CD005195. doi: 10.1002/14651858.CD005195.pub4.

本文引用的文献

1
Cancer statistics, 2022.癌症统计数据,2022 年。
CA Cancer J Clin. 2022 Jan;72(1):7-33. doi: 10.3322/caac.21708. Epub 2022 Jan 12.
6
10
Strategies for Colorectal Cancer Screening.结直肠癌筛查策略。
Gastroenterology. 2020 Jan;158(2):418-432. doi: 10.1053/j.gastro.2019.06.043. Epub 2019 Aug 5.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验