Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands (BJHvK, BSF, AH, SS, MGMH)
Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (BJHvK, BSF, SS, MGMH)
Med Decis Making. 2012 May-Jun;32(3):507-16. doi: 10.1177/0272989X12439754. Epub 2012 Apr 3.
Modeling studies that evaluate statin treatment for the prevention of cardiovascular disease (CVD) use different methods to model the effect of statins. The aim of this study was to evaluate the impact of using different modeling methods on the optimal decision found in such studies.
We used a previously developed and validated Monte Carlo-Markov model based on the Rotterdam study (RISC model). The RISC model simulates coronary heart disease (CHD), stroke, cardiovascular death, and death due to other causes. Transition probabilities were based on 5-year risks predicted by Cox regression equations, including (among others) total and high-density lipoprotein (HDL) cholesterol as covariates. In a cost-effectiveness analysis of implementing the ATP-III guidelines, we evaluated the impact of using 3 different modeling methods of statin effectiveness: 1) through lipid level modification: statins lower total cholesterol and increase HDL cholesterol, which through the covariates in the Cox regression equations leads to a lower incidence of CHD and stroke events; 2) fixed risk reduction of CVD events: statins decrease the odds of CHD and stroke with an associated odds ratio that is assumed to be the same for each individual; 3) risk reduction of CVD events proportional to individual change in low-density lipoprotein (LDL) cholesterol: the relative risk reduction with statin therapy on the incidence of CHD and stroke was assumed to be proportional to the absolute reduction in LDL cholesterol levels for each individual. The probability that the ATP-III strategy was cost-effective, compared to usual care as observed in the Rotterdam study, was calculated for each of the 3 modeling methods for varying willingness-to-pay thresholds.
Incremental cost-effectiveness ratios for the ATP-III strategy compared with the reference strategy were €56,642/quality-adjusted life year (QALY), €21,369/QALY, and €22,131/QALY for modeling methods 1, 2, and 3, respectively. At a willingness-to-pay threshold of €50,000/QALY, the probability that the ATP-III strategy was cost-effective was about 40% for modeling method 1 and more than 90% for both methods 2 and 3. Differences in results between the modeling methods were sensitive to both the time horizon modeled and age distribution of the target
Modeling the effect of statins on CVD through the modification of lipid levels produced different results and associated uncertainty than modeling it directly through a risk reduction of events. This was partly attributable to the modeled effect of cholesterol on the incidence of stroke.
评估他汀类药物治疗预防心血管疾病（CVD）的作用的建模研究使用不同的方法来模拟他汀类药物的作用。本研究的目的是评估在这些研究中使用不同建模方法对最佳决策的影响。
我们使用了先前开发并基于鹿特丹研究验证的蒙特卡罗-马尔可夫模型（RISC 模型）。RISC 模型模拟冠心病（CHD）、中风、心血管死亡和其他原因导致的死亡。转移概率基于 Cox 回归方程预测的 5 年风险，包括（除其他外）总胆固醇和高密度脂蛋白（HDL）胆固醇作为协变量。在对实施 ATP-III 指南的成本效益分析中，我们评估了使用 3 种不同他汀类药物效果建模方法的影响：1）通过脂质水平改变：他汀类药物降低总胆固醇并增加 HDL 胆固醇，这通过 Cox 回归方程中的协变量导致 CHD 和中风事件的发生率降低；2）CVD 事件风险固定降低：他汀类药物降低 CHD 和中风的几率，假定每个个体的关联比值相同；3）与个体 LDL 胆固醇变化成比例的 CVD 事件风险降低：他汀类药物治疗对 CHD 和中风发生率的相对风险降低与个体 LDL 胆固醇水平的绝对降低成比例。对于每个建模方法，我们计算了与观察到的鹿特丹研究中的常规治疗相比，ATP-III 策略的成本效益概率，对于不同的意愿支付阈值。
与参考策略相比，ATP-III 策略的增量成本效益比分别为 56642 欧元/质量调整生命年（QALY）、21369 欧元/QALY 和 22131 欧元/QALY，用于建模方法 1、2 和 3。在意愿支付阈值为 50000 欧元/QALY 时，ATP-III 策略具有成本效益的概率对于建模方法 1 约为 40%，对于方法 2 和 3 则超过 90%。建模方法之间的结果差异对所建模的时间范围和目标人群的年龄分布均敏感。
通过脂质水平的改变来模拟他汀类药物对 CVD 的作用产生的结果及其相关不确定性与通过事件风险降低直接模拟他汀类药物作用不同。这部分归因于胆固醇对中风发生率的建模影响。
