Alberta Research Centre for Health Evidence, University of Alberta, 11405 87 Avenue NW, Edmonton, Alberta, T6G 1C9, Canada.
Department of Medicine, University of Alberta, Edmonton, Canada.
Syst Rev. 2024 Mar 16;13(1):88. doi: 10.1186/s13643-024-02506-3.
Lung cancer is the leading cause of cancer deaths in Canada, and because early cancers are often asymptomatic screening aims to prevent mortality by detecting cancer earlier when treatment is more likely to be curative. These reviews will inform updated recommendations by the Canadian Task Force on Preventive Health Care on screening for lung cancer.
We will update the review on the benefits and harms of screening with CT conducted for the task force in 2015 and perform de novo reviews on the comparative effects between (i) trial-based selection criteria and use of risk prediction models and (ii) trial-based nodule classification and different nodule classification systems and on patients' values and preferences. We will search Medline, Embase, and Cochrane Central (for questions on benefits and harms from 2015; comparative effects from 2012) and Medline, Scopus, and EconLit (for values and preferences from 2012) via peer-reviewed search strategies, clinical trial registries, and the reference lists of included studies and reviews. Two reviewers will screen all citations (including those in the previous review) and base inclusion decisions on consensus or arbitration by another reviewer. For benefits (i.e., all-cause and cancer-specific mortality and health-related quality of life) and harms (i.e., overdiagnosis, false positives, incidental findings, psychosocial harms from screening, and major complications and mortality from invasive procedures as a result of screening), we will include studies of adults in whom lung cancer is not suspected. We will include randomized controlled trials comparing CT screening with no screening or alternative screening modalities (e.g., chest radiography) or strategies (e.g., CT using different screening intervals, classification systems, and/or patient selection via risk models or biomarkers); non-randomized studies, including modeling studies, will be included for the comparative effects between trial-based and other selection criteria or nodule classification methods. For harms (except overdiagnosis) we will also include non-randomized and uncontrolled studies. For values and preferences, the study design may be any quantitative design that either directly or indirectly measures outcome preferences on outcomes pertaining to lung cancer screening. We will only include studies conducted in Very High Human Development Countries and having full texts in English or French. Data will be extracted by one reviewer with verification by another, with the exception of result data on mortality and cancer incidence (for calculating overdiagnosis) where duplicate extraction will occur. If two or more studies report on the same comparison and it is deemed suitable, we will pool continuous data using a mean difference or standardized mean difference, as applicable, and binary data using relative risks and a DerSimonian and Laird model unless events are rare (< 1%) where we will pool odds ratios using Peto's method or (if zero events) the reciprocal of the opposite treatment arm size correction. For pooling proportions, we will apply suitable transformation (logit or arcsine) depending on the proportions of events. If meta-analysis is not undertaken we will synthesize the data descriptively, considering clinical and methodological differences. For each outcome, two reviewers will independently assess within- and across-study risk of bias and rate the certainty of the evidence using GRADE (Grading of Recommendations Assessment, Development, and Evaluation), and reach consensus.
Since 2015, additional trials and longer follow-ups or additional data (e.g., harms, specific patient populations) from previously published trials have been published that will improve our understanding of the benefits and harms of screening. The systematic review of values and preferences will allow fulsome insights that will inform the balance of benefits and harms.
PROSPERO CRD42022378858.
肺癌是加拿大癌症死亡的主要原因,由于早期癌症通常没有症状,因此筛查旨在通过更早地发现癌症来预防死亡,此时治疗更有可能治愈。这些综述将为加拿大预防保健工作组更新有关肺癌筛查的建议提供信息。
我们将更新 2015 年为工作组进行的 CT 筛查的收益和危害综述,并对以下方面的比较效果进行新的综述:(i)试验基础选择标准和使用风险预测模型与(ii)试验基础结节分类和不同的结节分类系统,以及患者的价值观和偏好。我们将通过同行评审的搜索策略、临床试验登记处以及纳入研究和综述的参考文献列表,在 Medline、Embase 和 Cochrane Central(用于 2015 年的收益和危害问题;2012 年的比较效果)以及 Medline、Scopus 和 EconLit(用于 2012 年的价值观和偏好)上搜索。两名审查员将筛选所有引用(包括之前综述中的引用),并根据共识或另一名审查员的仲裁做出纳入决定。对于收益(即全因和癌症特异性死亡率以及健康相关生活质量)和危害(即过度诊断、假阳性、偶然发现、筛查的心理社会危害以及由于筛查而导致的侵袭性程序的主要并发症和死亡率),我们将包括肺癌可疑的成年人的研究。我们将包括比较 CT 筛查与无筛查或替代筛查方式(例如胸部 X 射线)或策略(例如使用不同筛查间隔、分类系统和/或通过风险模型或生物标志物进行患者选择的 CT)的随机对照试验;将包括非随机研究,包括建模研究,用于比较基于试验和其他选择标准或结节分类方法。对于危害(除过度诊断外),我们还将包括非随机和非对照研究。对于价值观和偏好,研究设计可以是直接或间接测量与肺癌筛查相关的结果偏好的任何定量设计。我们仅将在非常高人类发展国家进行的、具有英语或法语全文的研究纳入。由一名审查员提取数据,另一名审查员进行验证,死亡率和癌症发病率的结果数据除外(用于计算过度诊断),在这些情况下将进行重复提取。如果两项或多项研究报告了相同的比较,如果认为合适,我们将使用平均值差异或标准化平均值差异(如适用)汇总连续数据,并使用相对风险和 DerSimonian 和 Laird 模型汇总二项数据,除非事件很少(<1%),在这种情况下,我们将使用 Peto 方法或(如果没有事件)相反治疗臂大小校正的倒数来汇总比值比。对于汇总比例,我们将根据事件的比例应用适当的转换(对数或反正弦)。如果不进行荟萃分析,我们将根据临床和方法学差异进行描述性综合数据。对于每个结局,两名审查员将独立评估研究内和研究间的偏倚风险,并使用 GRADE(推荐评估、制定与评价)对证据的确定性进行评级,并达成共识。
自 2015 年以来,已经发表了更多的试验和更长的随访时间或之前发表试验的额外数据(例如危害、特定患者群体),这将提高我们对筛查收益和危害的理解。价值观和偏好的系统综述将提供充分的见解,为收益和危害的平衡提供信息。
PROSPERO CRD42022378858。