流行病临床决策分析

1、2022/8/241临床决策分析Clinical Decision Analysis中南大学公共卫生学院流行病教研室22022/8/24What is a decision?Choicegamble32022/8/24WHAT IS DECISION ANALYSISDecision analysis is a systematic approach to decision making under uncertainty.it is taught and practiced today in diverse fields, such as oil and gas exploration, b

2、usiness, healthcare, law, and engineering.42022/8/24Decision analysisAn explicit, quantitative and systematic approach to decision making under uncertainty. Handdix et al., Prevention Effectiveness Oxford University Press 199652022/8/24The process of decisionThe process of complex decisions involve

3、many elements:the range of possible consequences of actions (or inaction)preferences among different sets of consequencesthe impact of complex, unpredictable systems and processes (e.g., markets, geological structure, health)the actions of others (e.g., consumers, competitors, regulators, patients)6

4、2022/8/24Clinical decision makingMany clinical decisions involve uncertainty and risk. Medical therapies and some diagnostic technologies (biopsies and angiography, for example) sometimes lead side effects（risk）undesirable complications or serious secondary infectionssmall but measurable hazard. In

5、many clinical situations, therefore, we want to Balance the overall expected benefit and the overall expected risk. 72022/8/24Clinical decisionUncertainty: 机会事件发生的概率；决策结果的不确定82022/8/24Objectiveto be able to do your own decision analysis of a clinical problem?read relative literatures with understand

6、ing 92022/8/24决策树 Decision tree决策树分析法是临床决策分析中最常见的方法，它模拟临床医生在诊疗过程中的分析过程，采用分层的方法，用概率表示各种诊疗过程中的决策和其相应的结局，犹如一棵不断分支的树，因而称为决策树。102022/8/24决策树的结构 Tree structure112022/8/24Tree structure基本的树形结构决策结：decision node-square机会结: chance node-circle决策枝：one decision branch denote one choice or strategy机会枝：one chance

7、branch denote one uncertainty e122022/8/24Types of NodesThree kinds of basic node types:Choice, or Decision NodeChance NodeTerminal NodeChoice or Decision Chance Terminal132022/8/24Tree structure各种随机事件的发生概率（probability）RCT trailmeta-analysisSystematic reviewCase-based data 142022/8/24Tree structure每

8、一个结局的效用值（Utility）。可以反映决策目标的量化的指标，不同的结局效应值不同 。效应值是指研究者和病人对该结局的一个偏好评价。 152022/8/24决策树的绘制和分析 基本步骤明确决策问题，确定备选方案 列出所有可能的结局 明确各种结局出现的概率 确定各种结局的效应值 计算备选方案的期望值 敏感性试验或灵敏度分析 162022/8/24Tool for decision analysis Download a trial copy from: Limited in sizeWorks for 21 days from first time it is opened 172022/8

9、/24What Can TreeAge do?Decision AnalysisCost-Effectiveness AnalysisBaseline and Sensitivity AnalysesMarkov ModelsMonte Carlo SimulationInfluence Diagrams182022/8/24决策树的绘制和分析 明确决策问题，确定备选方案 决策问题：就是指通过决策树分析需要解决的问题：病人是否患有某种疾病？某种疾病的病人应该选择哪一种治疗方案？192022/8/24决策树的绘制和分析 明确决策问题，确定备选方案决策目标：主要是最大限度的延长期望寿命或减少死亡或

10、致病水平。备选方案：所有的临床治疗方案，有多少备选方案，就决定了决策树第一层有多少分支，即从第一个决策结可以引出多少分支。 202022/8/24决策树的绘制和分析 列出所有可能的结局直接结局 immediate e ：每一个机会结点上可能发生的事件，每一个机会结可以引出两个和两个以上的结局，这些结局是互相排斥的，他们发生的概率之和应该是1。最终结局 final e：一系列机会事件的最终结果212022/8/24决策树的绘制和分析确定备选方案和各种结局后，我们可以绘制决策树的基本结构。决策树至左向右，最初等决策结在最左边，中间是一系列的机会结和相应得结局(或机会事件)，最右边是最终结局，用结局

11、结表示。222022/8/24决策树的绘制和分析 明确各结局发生的概率Probability 概率RCT trailmeta-analysisSystematic reviewCase-based data 232022/8/24决策树的绘制和分析 明确各结局的效用值utility：反映决策目标：延长病人的生命期望寿命提高病人生命质量质量调整的期望寿命减少费用医疗费用242022/8/24决策树的绘制和分析 计算备选方案的期望效用值从最终结局（树尖）开始向最初决策（树根）的方向，采用概率相乘的办法，计算备选方案的expected utility value回乘法 averaging and f

12、olding back。252022/8/24决策树的绘制和分析 敏感性试验或灵敏度分析sensitive analysis目的：测试决策分析结果的真实性即当机会事件发生的概率或结局的效用值在一定的范围内波动时，决策分析的结果是否稳定或是否具有真实性。262022/8/24决策树的绘制和分析 敏感性试验或灵敏度分析产品：灵敏度分析就是改变某一参数的值，观察各个策略效用值的变化，以参数为横轴，效应值为纵轴绘制效应值随参数变化的灵敏度曲线272022/8/24决策树的绘制和分析 敏感性试验或灵敏度分析one-way sensitivity analysis：改变某个参数，观察效用值的变化 two-

13、way sensitivity analysis：同时改变两个因素所进行的灵敏度分析，表示两个参数的不同组合下，最佳方案的变化和决策。282022/8/24Abdominal Aortic Aneurysm (AAA)AAAs: 5% - 7% of people over age 60，Most commonly affect Men, Age 40-70.Usually asymptomatic, often until ruptureOptions are surgery and watchful waiting, with some decision rule as to when t

14、o operate based on the size of the AAA.Our example will be based largely on the work of Katz and Cronenwett (1994).292022/8/24Reference Case：60-year old male4 cm abdominal aortic aneurysmOtherwise, patient is in good healthSurgery vs Watchful WaitingTime horizon: 1 year302022/8/24决策问题：How to therapy

15、?决策目标：Survival312022/8/24备选方案：Watchful waitingElective surgery决策树表现为在最初等决策结上引出二条主要的决策臂，一条表示手术、一条表示等待。 322022/8/24Start with a choice node, with each possible strategy coming out of this node.332022/8/24可能的机会事件Elective surgery:Live or dieWatchful waiting:Expansion or no expansion in 1 year Expansion:

16、 rupture or notNo expansion: live342022/8/24 e measure: UtilityAlive = 1Dead = 0352022/8/24Tree structure362022/8/24Parameter Values: Probability Name ValueLowHighpDieBeforeSurgery 0.550.27 0.82pDieDuringSurgeryAfterRupture0.540.27 0.81pDieElectiveSurgery0.0460.0230.069pDieSurgeryNoRupture0.230.110.

17、34pExpansion 0.033 0.0160.049pRupture0.920.880.96372022/8/24382022/8/24Probabilities go below the branch:You can put in the actual numbers for the probabilities. We suggest you do this only when you draw the tree manually. You can use variables. (strongly mended)392022/8/24Variables Variables settin

18、g is the key step when you using TREEAGE software. use variables makes it easy to change its value, even if it appears in many places in the tree. More importantly, it allows us to do sensitivity analysis on that parameter.eg: pDieBeforeSurgery pDie_During_Surgery_After_Rupture402022/8/24Expected Va

19、lues: Roll back412022/8/24At each node there is a number in a box indicating the expected value of the e from that point forwardAt the choice node, it also indicates which strategy is optimal. The nodes in the optimal path are all highlighted.At all terminal nodes, it first shows the e score associa

20、ted with that result, and then shows the probability of the path ending in that terminal node.All of the variable names are temporarily replaced by their values.422022/8/24Sensitivity Analysis 432022/8/24442022/8/24Graph shows how the expected value changes based on the mortality rate from elective

21、surgery over the range of values specified (0.0230.069).Watchful waiting is unaffected because elective surgery isnt in its path.The point of intersection, known as the threshold value, is shown on the graph and the point and its associated mean is shown in the right margin.452022/8/24Sensitivity an

22、alysisTreeAge Pro Line GraphSensitivity Analysis on Die from E surgeryDie from E surgery Elective SurgeryWatchful Waiting0.023 0.977 0.975317320.038333333 0.961666667 0.975317320.053666667 0.946333333 0.975317320.069 0.931 0.97531732Threshold Values:Lines (Elective Surgery, Watchful Waiting) Die fro

23、m E surgery = 0.0247/EV = 0.9753The following duplicate output may offer better import into other software.Die from E surgery0.0230.0383333330.0536666670.069Elective Surgery 0.9770.9616666670.9463333330.931Watchful Waiting 0.97531732 0.975317320.97531732 0.97531732462022/8/24Two-way sensitivity analysis472022/8/24Two-way sensitivity analysisTreeAge Pro Two-Way Sensitivity AnalysisProbability of expansion 0.016000.024250.032500.040750.04900Die from E surgery0.06900 0.9310.9310.9310.9310.931 0.9880330.9818620.9756910.9695210.96