Carter Jamie L, Coletti Russell J, Harris Russell P
Department of Medicine, University of California, San Francisco, San Francisco, CA 94110, USA.
Division of General Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
BMJ. 2015 Jan 7;350:g7773. doi: 10.1136/bmj.g7773.
To determine the optimal method for quantifying and monitoring overdiagnosis in cancer screening over time.
Systematic review of primary research studies of any design that quantified overdiagnosis from screening for nine types of cancer. We used explicit criteria to critically appraise individual studies and assess strength of the body of evidence for each study design (double blinded review), and assessed the potential for each study design to accurately quantify and monitor overdiagnosis over time.
PubMed and Embase up to 28 February 2014; hand searching of systematic reviews.
English language studies of any design that quantified overdiagnosis for any of nine common cancers (prostate, breast, lung, colorectal, melanoma, bladder, renal, thyroid, and uterine); excluded case series, case reports, and reviews that only reported results of other studies.
52 studies met the inclusion criteria. We grouped studies into four methodological categories: (1) follow-up of a well designed randomized controlled trial (n=3), which has low risk of bias but may not be generalizable and is not suitable for monitoring; (2) pathological or imaging studies (n=8), drawing conclusions about overdiagnosis by examining biological characteristics of cancers, a simple design limited by the uncertain assumption that the measured characteristics are highly correlated with disease progression; (3) modeling studies (n=21), which can be done in a shorter time frame but require complex mathematical equations simulating the natural course of screen detected cancer, the fundamental unknown question; and (4) ecological and cohort studies (n=20), which are suitable for monitoring over time but are limited by a lack of agreed standards, by variable data quality, by inadequate follow-up time, and by the potential for population level confounders. Some ecological and cohort studies, however, have addressed these potential weaknesses in reasonable ways.
Well conducted ecological and cohort studies in multiple settings are the most appropriate approach for quantifying and monitoring overdiagnosis in cancer screening programs. To support this work, we need internationally agreed standards for ecological and cohort studies and a multinational team of unbiased researchers to perform ongoing analysis.
确定随时间推移对癌症筛查中的过度诊断进行量化和监测的最佳方法。
对任何设计的原发性研究进行系统评价,这些研究对九种癌症筛查中的过度诊断进行了量化。我们使用明确的标准对各个研究进行严格评估,并评估每种研究设计的证据强度(双盲评审),并评估每种研究设计随时间准确量化和监测过度诊断的潜力。
截至2014年2月28日的PubMed和Embase;对系统评价进行手工检索。
对九种常见癌症(前列腺癌、乳腺癌、肺癌、结直肠癌、黑色素瘤、膀胱癌、肾癌、甲状腺癌和子宫癌)中的任何一种进行过度诊断量化的任何设计的英文研究;排除仅报告其他研究结果的病例系列、病例报告和综述。
52项研究符合纳入标准。我们将研究分为四个方法学类别:(1)精心设计的随机对照试验的随访(n = 3),其偏倚风险低,但可能不具有普遍性且不适合监测;(2)病理学或影像学研究(n = 8),通过检查癌症的生物学特征得出关于过度诊断的结论,这是一种简单的设计,受测量特征与疾病进展高度相关这一不确定假设的限制;(3)建模研究(n = 21),可以在较短时间内完成,但需要复杂的数学方程来模拟筛查发现的癌症的自然病程,这是一个基本的未知问题;(4)生态学和队列研究(n = 20),适合随时间进行监测,但受缺乏商定标准、数据质量可变、随访时间不足以及人群水平混杂因素的可能性的限制。然而,一些生态学和队列研究已经以合理的方式解决了这些潜在的弱点。
在多种环境中进行的精心设计的生态学和队列研究是量化和监测癌症筛查项目中过度诊断的最合适方法。为支持这项工作,我们需要国际商定的生态学和队列研究标准以及一个由无偏见研究人员组成的跨国团队进行持续分析。