Prevention and Cancer Control, Ontario Health (Cancer Care Ontario), Toronto, Ontario, Canada; Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada.
Prevention and Cancer Control, Ontario Health (Cancer Care Ontario), Toronto, Ontario, Canada; Division of Thoracic Surgery, Department of Surgery, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada.
Lung Cancer. 2021 Jun;156:31-40. doi: 10.1016/j.lungcan.2021.04.005. Epub 2021 Apr 20.
Randomized controlled trials have shown that screening with computed tomography reduces lung cancer mortality but is most effective when applied to high-risk individuals. Accurate lung cancer risk prediction models effectively select individuals for screening. Few pilots or programs have implemented risk models for enrolling individuals for screening in real-world, population-based settings. This report describes implementation of the PLCOm2012 risk prediction model in the Ontario Health (Cancer Care Ontario) lung cancer screening Pilot.
In the Pilot's Health Technology Assessment, 576 categorical age/pack-years/quit-years scenarios were evaluated using MISCAN microsimulation modeling and cost-effectiveness analyses. A preferred model was selected which provided the most life-years gained per cost. The PLCOm2012 was compared to the preferred MISCAN scenario at a threshold that yielded the same number eligible (risk ≥2.0 %/6-years).
The PLCOm2012 had significantly higher sensitivity and predictive value (68.1 % vs 59.6 %, p < 0.0001; 4.90 % vs 4.29 %, p = 0.044), and an Expert Panel selected it for use in the Pilot. The Pilot cancer detection rate was significantly higher than in the NLST (p = 0.009) or NELSON (p = 0.003) and there was a significant shift to early stage compared to historical Ontario Cancer Registry statistics (p < 0.0001). Pre- and post-Pilot evaluations found that conducting quality risk assessments were not excessively time consuming or difficult, and participants' satisfaction was high.
The PLCOm2012 was efficiently implemented in the Pilot in a real-world setting and is being used to transition into a provincial program. Compared to categorical age/pack-years/quit-years criteria, risk assessment using the PLCOm2012 can lead to effective and efficient screening.
随机对照试验表明,计算机断层扫描筛查可降低肺癌死亡率,但在应用于高危人群时效果最佳。准确的肺癌风险预测模型可以有效地选择进行筛查的个体。在真实世界的基于人群的环境中,很少有试点或计划实施风险模型来招募个体进行筛查。本报告描述了在安大略省健康(安大略省癌症护理)肺癌筛查试点中实施 PLCOm2012 风险预测模型的情况。
在试点的卫生技术评估中,使用 MISCAN 微观模拟建模和成本效益分析评估了 576 个分类年龄/包年/戒烟年情景。选择了一个首选模型,该模型每成本获得的预期寿命最长。将 PLCOm2012 与首选的 MISCAN 方案进行比较,阈值设定为产生相同数量合格者(风险≥2.0%/6 年)。
PLCOm2012 的敏感性和预测值显著更高(68.1%比 59.6%,p<0.0001;4.90%比 4.29%,p=0.044),专家组选择其用于试点。试点的癌症检出率显著高于 NLST(p=0.009)或 NELSON(p=0.003),与安大略省癌症登记处历史统计数据相比,早期阶段的比例显著增加(p<0.0001)。试点前后的评估发现,进行质量风险评估并不需要过多的时间或困难,参与者的满意度很高。
PLCOm2012 在真实环境中高效地在试点中实施,并正在过渡到省级项目。与分类年龄/包年/戒烟年标准相比,使用 PLCOm2012 进行风险评估可以实现有效的筛查。