Hemmati Mehdi, Ishizawa Sayaka, Meza Rafael, Ostrin Edwin, Hanash Samir M, Antonoff Mara, Schaefer Andrew J, Tammemägi Martin C, Toumazis Iakovos
Division of Cancer Prevention and Population Sciences, Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
School of Industrial and Systems Engineering, The University of Oklahoma, Norman, OK, USA.
EClinicalMedicine. 2024 Jul 28;74:102743. doi: 10.1016/j.eclinm.2024.102743. eCollection 2024 Aug.
Lung cancer screening recommendations employ annual frequency for eligible individuals, despite evidence that it may not be universally optimal. The impact of imposing a structure on the screening frequency remains unknown. The ENGAGE framework, a validated framework that offers fully dynamic, analytically optimal, personalised lung cancer screening recommendations, could be used to assess the impact of screening structure on the effectiveness and efficiency of lung cancer screening.
In this comparative microsimulation study, we benchmarked alternative clinically relevant structured lung cancer screening programmes employing a fixed (annual or biennial) or adaptive (start with annual/biennial screening and then switch to biennial/annual at ages 60- or 65-years) screening frequency, against the ENGAGE framework. Individuals were eligible for screening according to the 2021 US Preventive Services Task Force recommendation on lung cancer screening. We assessed programmes' efficiency based on the number of screenings per death avoided (LDCT/DA) and the number of screenings per ever-screened individual (LDCT/ESI), and programmes' effectiveness using quality-adjusted life years (QALY) gained from screening, lung cancer-specific mortality reduction (MR), and number of screen-detected lung cancer cases. We used validated natural history, smoking history generator, and risk prediction models to inform our analysis. Sensitivity analysis of key inputs was conducted.
ENGAGE was the best performing strategy. Among the structured policies, adaptive biennial-to-annual at age 65 was the best strategy requiring 24% less LDCT/DA and 60% less LDCT/ESI compared to TF2021, but yielded 105 more deaths per 100,000 screen-eligible individuals (10.2% vs. 11.8% MR for TF2021, p = 0.28). Fixed annual screening was the most effective strategy but the least efficient and was ranked as the fifth best strategy. All strategies yielded similar QALYs gained. Adherence levels did not affect the rankings.
Adaptive lung cancer screening strategies that start with biennial and switch to annual screening at a prespecified age perform well and warrant further consideration, especially in settings with limited availability of CT scanners and radiologists.
National Cancer Institute.
肺癌筛查建议对符合条件的个体采用年度筛查频率,尽管有证据表明这可能并非普遍最优。对筛查频率施加一种结构的影响尚不清楚。ENGAGE框架是一个经过验证的框架,可提供完全动态、分析上最优的个性化肺癌筛查建议,可用于评估筛查结构对肺癌筛查有效性和效率的影响。
在这项比较微观模拟研究中,我们将采用固定(年度或两年一次)或适应性(开始时每年/两年一次筛查,然后在60岁或65岁时改为两年一次/每年一次)筛查频率的替代临床相关结构化肺癌筛查方案与ENGAGE框架进行了基准对比。根据2021年美国预防服务工作组关于肺癌筛查的建议,个体有资格进行筛查。我们根据避免每例死亡的筛查次数(LDCT/DA)和每名接受过筛查个体的筛查次数(LDCT/ESI)评估方案的效率,并使用从筛查中获得的质量调整生命年(QALY)、肺癌特异性死亡率降低(MR)以及筛查发现的肺癌病例数评估方案的有效性。我们使用经过验证的自然病史、吸烟史生成器和风险预测模型为分析提供信息。对关键输入进行了敏感性分析。
ENGAGE是表现最佳的策略。在结构化政策中,65岁时从两年一次改为每年一次的适应性策略是最佳策略,与TF2021相比,所需的LDCT/DA减少24%,LDCT/ESI减少60%,但每10万名符合筛查条件的个体中多产生105例死亡(TF2021的MR为11.8%,该策略为10.2%,p = 0.28)。固定年度筛查是最有效的策略,但效率最低,被列为第五好的策略。所有策略获得的QALY相似。依从水平不影响排名。
开始时每两年进行一次,在预定年龄改为每年一次的适应性肺癌筛查策略表现良好,值得进一步考虑,尤其是在CT扫描仪和放射科医生可用性有限的情况下。
美国国立癌症研究所。