Self-Selection Bias in Randomized and Observational Studies on Screening Mammography: A Quantitative Assessment.

IF 3.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Clinical Epidemiology Pub Date : 2025-05-01 eCollection Date: 2025-01-01 DOI:10.2147/CLEP.S515464
Philippe Autier
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引用次数: 0

Abstract

Background: Observational studies aimed at evaluating the effectiveness of screening mammography are prone to self-selection due to differences in personal characteristics between women attending and those not attending screening. A method based on a quantity Dr has been promoted to correct for this bias, Dr being the risk of breast cancer death in a group of women not attending screening compared to the risk of breast cancer death in a population without screening.

Objective: To estimate the amount of self-selection in observational studies aimed at evaluating screening mammography effectiveness and to estimate Dr quantities needed to correct for this bias.

Methods: A first step quantified self-selection and Dr quantities specific to Swedish randomized trials using the most recent publications. A second step estimated self-selection specific to cohort studies on screening mammography effectiveness using the relative risk of 0.54 for all-cause death from these studies and the relative risk of all-cause death of 0.98 reported in Swedish trials. Using self-selection estimated from cohort studies, the Dr quantity needed to correct observational studies on screening mammography effectiveness was estimated. In a last step, corrections for self-selection in observational studies on screening mammography were retrieved.

Results: The self-selection bias was 2.10 in Swedish trials. Self-selection in cohort studies was computed as (0.98/0.54) = 1.78. The Dr quantity required to correct results of observational studies was 1.53. In 19 case-control and cohort studies on screening mammography effectiveness, the median Dr quantity used for correction purposes was 1.16 (IQR: 1.11-1.28).

Conclusion: Compared to women attending screening, the risk of breast cancer death was approximately two times greater in women not attending screening. This increased risk was independent of screening effects. Most observational studies have overestimated the effectiveness of screening mammography because they used Dr quantities that were too small to correct for self-selection.

随机和观察性乳腺筛查研究中的自我选择偏倚:定量评估。
背景:观察性研究旨在评估筛查性乳房x光检查的有效性,由于参加筛查的妇女和未参加筛查的妇女之间的个人特征差异,这些研究倾向于自我选择。一种基于数量Dr的方法已被推广以纠正这种偏差,Dr是未参加筛查的一组妇女的乳腺癌死亡风险与未进行筛查的人群的乳腺癌死亡风险的比较。目的:估计旨在评估筛查性乳房x光检查有效性的观察性研究中自我选择的数量,并估计纠正这种偏倚所需的Dr量。方法:第一步量化自我选择和博士数量具体到瑞典随机试验使用最新的出版物。第二步,使用来自这些研究的全因死亡相对危险度为0.54,瑞典试验报告的全因死亡相对危险度为0.98,对筛查乳房x线照相术有效性队列研究的自我选择进行估计。使用从队列研究中估计的自我选择,估计纠正筛查乳房x光检查有效性的观察性研究所需的Dr量。在最后一步中,对乳房x光筛查观察性研究中自我选择的修正进行了检索。结果:瑞典试验的自我选择偏倚为2.10。队列研究的自我选择计算为(0.98/0.54)= 1.78。校正观察性研究结果所需的Dr量为1.53。在19项关于筛查乳房x线摄影有效性的病例对照和队列研究中,用于校正目的的Dr量中位数为1.16 (IQR: 1.11-1.28)。结论:与参加筛查的女性相比,未参加筛查的女性乳腺癌死亡风险约为其两倍。这种增加的风险与筛查效果无关。大多数观察性研究都高估了筛查性乳房x光检查的有效性,因为它们使用的Dr量太小,无法进行自我选择。
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来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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