Medical Decision Modeling Inc., Indianapolis, IN, USA.
BMC Med Inform Decis Mak. 2010 Apr 30;10:24. doi: 10.1186/1472-6947-10-24.
Alzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development.
A time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age > or =55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death.
The base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90).
This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.
阿尔茨海默病（AD）每年影响着越来越多的人群。新型疗法有望减缓 AD 症状的进展，并完全避免 AD 的发生。基于生物标志物筛选工具识别出无症状个体，为 AD 的潜在病理启动治疗，这将是理想的做法。早期模型为潜在结果提供了预测，并为政策制定提供了信息。
使用时间到事件（TTE）模拟方法，对筛查 55 岁及以上一般人群中无症状患者的情况进行了估计，并评估了治疗对达到 AD 诊断患者数量的影响。患者从 AD 筛查开始一直随访到全因死亡。基线的敏感性和特异性分别为 0.87 和 0.78，阳性筛查时进行治疗。治疗使疾病进展速度减慢了 50%。使用基于文献的 AD 和死亡年龄依赖性发病率安排事件。
基础病例结果表明，通过延迟发病，AD 无病年数（AD-FYs）增加，每 1000 名筛查个体中减少 20 例 AD 病例。完全避免 AD 的患者占所增加 AD-FYs 的 61%。每 1000 名筛查患者的治疗总年数为 2611 年。需要筛查的人数为 51 人，需要治疗的人数为 12 人，以避免 1 例 AD 病例。单向敏感性分析表明，筛查敏感性持续时间和重新筛查间隔是影响 AD-FYs 的最重要因素。双向敏感性分析发现，对于敏感性延长（15 年）的测试，对于敏感性和特异性更高（0.90，0.90）的测试，避免的 AD 病例数为 6000-7000 例。
本研究在 AD 筛查研究的早期阶段获得了有价值的参数范围估计。分析确定了筛查敏感性持续时间是一个关键变量，可能无法从临床试验中获得。
