由于时间间隔的降低而引起的结直肠癌筛查有效性的推断
Bias due to coarsening of time intervals in the inference for the effectiveness of colorectal cancer screening
影响因子:5.90000
分区:医学2区 Top / 公共卫生1区
发表日期:2024 Jun 12
作者:
Bikram Karmakar, Ann G Zauber, Anne I Hahn, Yan Kwan Lau, Chyke A Doubeni, Marshall M Joffe
摘要
由于进行大型临床试验所需的实际局限性和时间，观察性研究经常用于估计不同结直肠癌（CRC）筛查方法的比较有效性。但是，时变的混杂因素，例如在上次筛选中的息肉检测可能会偏向统计结果。最近，鉴于它们能够说明这种时间变化的混杂因素的能力，已使用广义方法或G方法分析CRC筛选的观察性研究。当治疗和结局以连续的规模评估时，需要离散化或将连续功能转换为离散对应物的过程。本文评估了时间变化的混杂和离散化之间的相互作用，这可以诱导评估筛查有效性时诱导偏见。我们研究了在评估典型筛选频率不同的不同CRC筛选方法的效果方面的偏见。首先，使用理论，我们建立了偏见的方向。然后，我们使用假设设置的模拟来研究不同水平的离散水平，筛查频率和研究期间的偏差。我们开发了一种方法来评估由于模拟情况下的粗糙而可能导致的偏见。该提出的方法可以通过确定在平衡计算成本平衡计算成本的同时将数据降低以最大程度地减少偏见的间隔长度的选择来为未来的筛查有效性（尤其是对于CRC）提供信息。
Abstract
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.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.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.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.