INRODUCTION TO TREEAGE PRO

Transcription

1 INRODUCTION TO TREEAGE PRO Asrul Akmal Shafie BPharm, Pg Dip Health Econs, PhD Associate Professor & Program Chairman Universiti Sains Malaysia Board Member HTAsiaLink Adjunct Associate Professor Monash University Outline Objective To illustrates the basic tools needed for using TreeAge Pro software. To guide through the process of building a decision tree, saving and printing the tree. To perform basic foldback and sensitivity analyses. 2 1

2 Research Problem: Who should be screened for HIV? HIV screening is a specific example of a typical decision analysis application: screening for asymptomatic disease We will follow a paper by Sanders from 2005 examining this issue Assumptions: HIV infection is often asymptomatic There is benefit (anti retroviral treatment) when the disease is found early treated, which prolongs their life expectancy. For HIV positive individuals who are not screened, treatment will be delayed and the survival advantage is less than those who receive early treatment. There is harm to labeling someone as having the disease who doesn t (very rare) Sanders GD, et al. Cost-effectiveness of screening for HIV in the era of highly active retroviral therapy. N Engl J Med. 352:570-85, Screening for HIV: Step 1 Frame the problem There are many perspectives we could take Patient perspective (benefit to individual patients) Society perspective (benefit from early detection and interference with epidemic) Perspective implies differences in structure of problem and the values for the outcomes So, for this problem: Point of view: patient Outcome measure: life expectancy 4 2

3 Screening for HIV: Step 2 Structure the problem Test + (Treat) Life Expectancy, HIV +, with prophylaxis Screen HIV- Life Expectancy, HIV - Unnecessary Rx Population with specific characteristics (prevalence of HIV) No Screen Test - (No Rx) HIV- Life Expectancy, HIV +, Late Treatment Life Expectancy, HIV - No Rx Life Expectancy, HIV +, LateRx HIV- Life Expectancy, HIV - No Rx 5 Screening for HIV: Step 3 Estimating probabilities Test + (Treat) Life Expectancy, HIV +, with prophylaxis Screen HIV- Life Expectancy, HIV - Unnecessary Rx Population with specific characteristics (prevalence of HIV) No Screen p = prevalence of HIV phiv- = 1- p Test - (No Rx) HIV- HIV- Life Expectancy, HIV +, Late Treatment Life Expectancy, HIV - No Rx Life Expectancy, HIV +, LateRx Life Expectancy, HIV - No Rx 6 3

4 Screening for HIV: Step 3 Estimating probabilities The probability of a positive test is not obvious Depends upon sensitivity and specificity of the test Depends upon the prevalence of disease Information from the literature doesn t always come in the format needed for the problem Sensitivity/specificity available, predictive value needed Life expectancy available, probability of death/unit time needed 7 Relationship Btw Prev Incidence Sens Spec prevalence = probability of disease in the entire population at any point in time (i.e. 2% the Malaysia population has diabetes mellitus) incidence = probability that a patient without disease develops the disease during an interval (the incidence of diabetes mellitus is 0.2% per year, referring only to new cases) sensitivity = probability of a positive test among patients with disease specificity = probability of a negative test among patients without disease 4

5 Step 3: structure defines probability and outcome needs The natural structure of the tree may have to be modified for your particular problem Structuring the tree this way is clinically logical, but requires probabilities that are not immediately available Test - (No Rx)pHIV + T - pneg ppos = probability of positive test phiv + T + = probability of HIV given test positive phiv - T + = probability of no HIV given test positive phiv + T - = probability of HIV given test negative phiv - T - = probability of no HIV given test negative Life Expectancy, HIV +, with prophylaxis Life Expectancy, HIV - Unnecessary Rx Life Expectancy, HIV +, Late Treatment Life Expectancy, HIV - No Rx 9 Step 3: structure defines probability and outcome needs One could rearrange the tree is it made more sense: Structuring the tree this way is not clinically logical, but all of the required probabilities are entered as they are found in the literature PREV Test + (Treat) phiv + T + ppos HIVpHIV - T + HIVpHIV - T - HIV- 1-PREV Test + SENS Test - 1-SENS Test + 1-SPEC Test - SPEC Life Expectancy, HIV +, with prophylaxis Life Expectancy, HIV - Unnecessary Rx Life Expectancy, HIV +, Late Treatment Life Expectancy, HIV - No Rx 10 5

6 Step 3 Estimating Probabilities There are many mechanisms for converting probabilities into the appropriate format Bayes Theorem (relates sensitivity/specificity and prevalence 11 Screening for HIV: Step 3 Estimating probabilities Assume that the following represent the probabilities in this problem SENSITIVITY of HIV test SPECIFICITY of HIV test PREVALENCE OF HIV

7 Screening for HIV: Step 3 Estimating probabilities Population with specific characteristics (prevalence of HIV) Screen No Screen You will need to use Bayes Theorem to convert these probabilities Test + (Treat) phiv + T + ppos HIVpHIV - T + pneg Test - (No Rx) phiv + T - HIVpHIV - T - phiv + HIVpHIV - Life Expectancy, HIV +, with prophylaxis Life Expectancy, HIV - Unnecessary Rx Life Expectancy, HIV +, Late Treatment Life Expectancy, HIV - No Rx Life Expectancy, HIV +, LateRx Life Expectancy, HIV - No Rx 13 Setting probabilities Using Bayes theorem, can develop formula for the probabilities in the naturally drawn tree: For a positive test, predictive value positive: phiv = Prev*Sens/(Prev*Sens+(l-Prev)*(1-Spec)) For a negative test, predictive value negative: phiv = Prev*(1-Sens)/(Prev*(1-Sens)+(1-Prev)*Spec) The probability of a positive test: Prev*Sens+(1-Prev)*(1-Spec) 14 7

8 Screening For HIV: Step 4 Estimating outcomes There are four outcomes that have to be estimated Life expectancy without HIV Life expectancy without HIV but with unnecessary Rx Life Expectancy with HIV without Rx (later treatment) Life Expectancy with HIV with early Rx 15 Screening For HIV: Step 4 Estimating outcomes The article uses a Markov Process as the mechanism for determining life expectancy HIV + phiv + T + Life Expectancy, HIV +, with prophylaxis AIDS DEAD HIVpHIV - T + Life Expectancy, HIV - Unnecessary Rx For the purpose of this course, we have simplified the problem: initially, we will assume that the life expectancies for the different outcomes are given 16 8

9 Screening for HIV: Probabilities and Structure The Sanders paper is more complicated, basing transitions on CD4 counts and viral load LE CD4 = x & Viral load = y Test - (No Rx) phiv + T - pneg Test + (Treat) phiv + T + ppos HIVpHIV - T + HIVpHIV - T - In this model, you need to know the probability of changes in CD4 and viral load with antiretroviral Rx Also need to know survival by CD4 count and viral load We won t be doing this 17 Screening For HIV: Step 4 Estimating outcomes We will provide values assuming the average age of the screened population is 43 (as in the article) Values: Life expectancy without HIV 36.6 years Life expectancy without HIV but with unnecessary Rx 36.4 years Life expectancy with HIV and early Rx years Life expectancy with HIV and delayed Rx years

10 Screening For HIV: Step 5 Analyzing the tree ( = 0.999* *36.4) Population with specific characteristics (prevalence of HIV) Screen No Screen Test + (Treat) HIV Test - (No Rx) HIV LERx = 25.5 yrs LEtox = 36.4 yrs LELateRx = 23.5 yrs LE= 36.6 yrs LELateRx = 23.5 yrs HIV LE= 36.6 yrs 19 The tree in TreeAge 20 10

11 Screening For HIV: Step 6 Test Assumptions One could imagine a large number of variables that one could change Accuracy of the test Life expectancy treated/not treated Likelihood of false positive and unnecessary treatment Prevalence of disease Sensitivity analysis can assist in understanding the parameters that drive the decision 21 Screening For HIV: Step 6 Test Assumptions Useful to decide a priori what direction some sensitivity analyses should go: What should happen to the relative value of the SCREENING choice if: Prevalence of disease increases? Accuracy of the test improves? There is no value to early treatment? There is less penalty to treating unnecessarily? 22 11

12 Screening For HIV: Step 6 Test Assumptions The sensitivity analysis below indicates changes in the optimal strategy with changes in early treatment life expectancy Expected Value HIV Screen No Screen Life Expectancy Treated Applied Modeling-ISPOR European Meeting 23 Screening For HIV: Step 7 Interpret the results The answer that a decision analysis provides is straightforward: Given the structure of the problem and values of the inputs and probability estimates provided, Strategy X is superior to strategy Y This may be relatively uninteresting if the result is unstable over assumptions Interpretation also involves understanding the interaction between the model components 24 12

13 PRACTICAL Figure 1. The Decision Tree HIV Screening Problem HIV Screen No Screen Positive Test ppos Negative Test # HIV Infected phiv Not Infected # HIV Infected phiv Not Infected # HIV Infected phiv Not Infected # LERx LETox LELateRx LE LELateRx LE 25 General Notes : TreeAge Pro Decision Tree Will look similar to those drawn by hand. Consist of a series of branches with nodes on the right. Each branch will be assigned a descriptive name. Names for branches are generally not restricted

14 General Notes : TreeAge Pro Decision Tree Limitation Variable names cannot have blank spaces (use the underscore character to simulate a space) Can only contain alphabetic characters, numerals, and the underscore character. Cannot begin with a numeral Cannot be more than 16 characters long NB: TreeAge Pro variable names are case sensitive, thus Prev and prev (for example) will be seen by TreeAge Pro as different variables. When naming variables, it s important to be consistent with upper and lower case. 27 General Notes : In TreeAge Pro, all tasks can be done by using pull down menus. For the more common tasks, you can click on the short cut buttons located on the Tool Bar below the menu options

15 Node Types The name of a node is the name of the branch leading to (i.e., to the left of) that node. For example, the first node provided by TreeAge Pro is a decision node. The node types that will be covered in this tutorial are: Decision: represents choices available to the decision maker (blue square) Chance: represents alternative chance events (green circle) Terminal: represents outcomes of interest (red triangle) 29 Building a Decision Tree Once you have entered the program, a branch with a decision node (blue square) is shown in the upper left comer of the screen. Above the branch is a text insertion box. Identify the tree by typing HIV Screening Problem in the text insertion box. Click the mouse anywhere off the branch and the branch name will be incorporated into the tree. Always refer to the figure during the tree building process

16 Adding Branches First, select the decision node by clicking the node. The node will turn solid blue to indicate that it has been selected. Pull down the OPTIONS menu, and select ADD BRANCHES. With this action you added two Above the branch is a text insertion box. Branches with chance nodes (green circles), which is the default for added branches. 31 Labeling Branches The decision involves whether to screen a population for HIV or not. Using the mouse, click on the top branch (a text insertion box will appear and the node will turn solid green). To label the branch, type HIV Screen. Now click the second branch and type No Screen

17 Another Way to Add Branches Instead of using the pull down menu, You can double click on the node where you want branches added. This will generate two branches. If you need a third branch, then double click again. First select the HIV Screen chance node (solid green), then double click the node. Type Positive Test to label the top branch and Negative Test to label the bottom branch. 33 Inserting Chance Node Probabilities To insert the probability of a positive test, select Positive Test and then press the Tab key (a text box should appear below the branch). Enter a variable named ppos. Set ppos equal to a function of the prevalence of HIV and the sensitivity and specificity of the screening test. Type ppos and then click the mouse in open space. Since TreeAge Pro does not recognize ppos as a defined variable, a PROPERTIES: NEW VARIABLE dialog box will pop up. You will assign properties later, so just click OK in the dialog box (you will do this for all new variables in this tutorial)

18 Another Way to Insert Chance Node Probabilities A probability must be assigned to each branch that is off a chance node. Instead of using the Tab key, Click directly below the Negative Test branch. A text box should appear below the branch. For the Negative Test branch, type # and then click the mouse in open space. The use of "#" as a probability has special meaning in TreeAge Pro and other decision analysis software. It is equal to one minus the sum of the other probabilities off the same chance node (in this case, 1 ppos). 35 Another Way to Insert Chance Node Probabilities Select the Positive Test node Double click to add two branches. Type HIV Infected to label the top branch and Not Infected to label the bottom branch. Click below the HIV Infected branch and type phiv as the probability name. Click the mouse in open space and then define phiv as a variable (just click OK in the dialog box). Click below the Not Infected branch and type # as the probability and then click the mouse in open space

19 Saving the Tree Now you will save what you have created so far in a file on whatever media (Desktop, USB drive) is most convenient for you. Pull down the FILE menu and select SAVE. Change the Save in: option to the location you wish to save it to. Name the file hiv and then click SAVE (the file will have a tre extension). You should save your tree often (FILE SAVE, or Ctrl S). 37 Changing Node Types The two branches off Positive Test should be terminal nodes (red triangles). To change the top branch, select the HIV Infected node Pull down the OPTIONS menu and select CHANGE NODE TYPE. You will be shown a menu of node types; select TERMINAL and then click OK. You will then be prompted for a payoff value

20 Payoff Values In TreeAge Pro, payoffs represent the value of the outcome of the decision analysis. In this example, you are interested in life expectancy. Although TreeAge Pro allows you to enter up to 9 different payoffs, you will now use only Payoff 1. Instead of assigning a value, you will assign a variable so that you can do sensitivity analysis on it later. The payoff variable names are shown in Figure For the HIV Infected node, type LERx in the text box for Payoff 1 (to represent the life expectancy of HIV positive individuals who screened positive and were subsequently treated) then click OK. Define LERx as a variable by clicking OK in the Properties: New Variable box

21 Another Way to Change Node Types To change the node type of Not Infected, First select the Not Infected node. Instead of using the pull down menu as you did before, click the button on the Tool Bar with the node shapes. Select TERMINAL from the menu of node types and then click OK. Type LETox in the text box for Payoff 1 (to represent the life expectancy of uninfected individuals who have a false positive test and thus are inappropriately treated) and then click OK. Create LETox as a variable by clicking OK in the Properties box. 41 Copying and Pasting Subtrees Because the 2 branches off Positive Test are the same as the 2 branches off Negative Test and No Screen, you can copy and paste the branches (i.e., the subtree). Select the Positive Test chance node. Pull down the OPTIONS menu and select SELECT SUBTREE. The nodes of the subtree will become solid colors. Pull down the EDIT menu and select COPY SUBTREE. To select the two chance nodes of the Negative Test and No Screen branches simultaneously, first click the Negative Test node, then click the No Screen node while holding down the Shift key (both chance nodes should be solid green). Pull down the EDIT menu and select PASTE SUBTREE. The subtree should be pasted at the two selected locations

22 Changing Payoff Names When you copied and pasted the subtree, you also copied the payoff names. You need to change these names to the ones shown in the figure. Select the HIV Infected nodes off both the Negative Test and No Screen branches by using the Shift key to select the second node. Pull down the VALUES menu and select CHANGE ACTIVE PAYOFF (1). Replace the payoff with LELateRx, then click OK. Click OK again to define LELateRx as a variable. Select the Not Infected nodes off both the Negative Test and No Screen branches by using the Shift key to select the second node. Pull down the VALUES menu and select CHANGE ACTIVE PAYOFF (1). Replace the payoff with LE, then click OK. Click OK again, defining LE as a variable. 43 Aligning Nodes Sometimes it is easier to look at a decision tree when certain nodes are aligned. One way to do this is to select No Screen, pull down the DISPLAY menu and select SKIP GENERATION. Now your tree should look like the one in the figure. Save the tree

23 Assigning a Value to a Probability You need to enter values for each of the probability and payoff variables. Since the phiv variable will not always have the same value, you will define this variable at different points in the tree. For example, the phiv to the right of Positive Test represents the positive predictive value of the test (the probability that a person is HIV infected given a positive screening test). If you define phiv at Positive Test, then it will only apply to the subtree rooted at (to the right of) Positive Test. 45 Use of Formulas For persons who have a positive test, phiv equals (based on Bayes' Theorem): Prev*Sens/(Prev*Sens+(l Prev)*(1 Spec)) "Prev" represents the prevalence of HIV, "Sens" represent the sensitivity of the test, "Spec" represents the specificity of the test. To incorporate this equation into the tree, First select the Positive Test node. Pull down the VALUES menu, select VARIABLES AND TABLES, and then select phiv from the list of variables

24 Use of Formulas There are two ways that a variable can be defined: (1) at the selected node(s), or (2) as a default for the whole tree. If the variable is defined at the selected node, then the definition (or value) is only assigned in the subtree rooted at (and to the right of) the current node. If the variable is defined for the whole tree, then the definition (or value) is assigned at all locations that the variable exists. Click the DEFINE VARIABLE button and then select AT SELECTED NODE(S). Type Prev*Sens/(Prev*Sens+(1 Prev)*(1 Spec)) in the text box and then click OK. Define the variables Prev, Sens, and Spec. 47 Use of Formulas For persons who have a negative test, phiv equals the following (based on Bayes' Theorem): Prev*(1 Sens)/(Prev*(1 Sens)+(1 Prev)*Spec) To incorporate this equation in the tree, First select the Negative Test node. There is another way to assign a probability variable instead of using the pull down menus: click the V= button on the Tool Bar. Select phiv, then click the DEFINE VARIABLE button and then select AT SELECTED NODE(S). Type Prev*(1 Sens)/(Prev*(1 Sens)+(1 Prev)*Spec) in the text box and then click OK

25 Use of Formulas For persons who are not tested, phiv is equal to prevalence. Select the No Screen node, Click the V= button on the Tool Bar. Select phiv, then click the DEFINE VARIABLE button Select AT SELECTED NODE(S). Type Prev in the text box and then click OK. 49 Use of Formulas The only probability variable left to assign is ppos, also a function of Prev, Sens, and Spec. To assign the formula to this variable, First select the HIV Screen node, Click the V= button on the Tool Bar. Select ppos, then click the DEFINE VARIABLE button Sselect AT SELECTED NODE(S). Type Prev*Sens+(1 Prev)*(1 Spec) in the text box and then click OK

26 Use of Formulas At this point, we ll check the tree to make sure the variables were defined at the correct nodes in the tree. A nice feature allows you to see variable definitions displayed on the tree. To do this, pull down the EDIT menu, select PREFERENCES, then VARIABLES/MARKOV INFO, and then click SHOW DEFINITIONS and EXPAND NODE TO FIT VARIABLES. Your tree should now look like Fig 2: 51 Use of Formulas Figure 2. Tree with definitions of phiv and ppos HIV Screening Problem HIV Infected Positive Test phiv LERx phiv=prev*sens/(prev*sens+(1-prev)*(1-spec)) Not Infected HIV Screen ppos LETox # HIV Infected Negative Test phiv LELateRx phiv=prev*(1-sens)/(prev*(1-sens)+(1-prev)*spec) Not Infected LE # # HIV Infected No Screen phiv LELateRx Not Infected LE # ppos=prev*sens+(1-prev)*(1-spec) phiv=prev 52 26

27 Assigning Variables Globally Click the V= button on the Tool Bar. First select LE from the variable list, then select the following variables while holding down the Ctrl key: LELateRx, LERx, LETox, Prev, Sens, and Spec. By holding down the Ctrl key, variables can be selected simultaneously. Click DEFINE VARIABLE button and then select DEFAULT FOR TREE. You will be prompted to enter a value for each of the variables. 53 Assigning Variables Globally Enter the following values when prompted and then click OK. When you have finished entering the values, save the tree. You are now ready for analysis. Variable Value Spec Sens Prev 0.01 LETox 36.4 LERx 25.5 LELateRx 23.5 LE

28 Evaluating the Tree The default is to present expected values in dollar units with no significant decimal places. To change this, pull down the EDIT menu and select NUMERIC FORMATTING. Change DECIMAL PLACES to 4, SHOW NUMBERS to Exactly and UNITS to None, then click OK. To evaluate the tree, select the root node (i.e., the decision node). Pull down the ANALYSIS menu and select ROLL BACK. Another way to perform a rollback analysis is to click the beach ball button on the Tool Bar. The averaged out and folded back values are shown at each node. The expected values of HIV Screen and No Screen are and years, respectively. Click the beach ball button to return to the tree. 55 Sensitivity Analysis To perform a 1 way sensitivity analysis on Prev (prevalence), select the decision node. Pull down the ANALYSIS menu, select SENSITIVITY ANALYSIS, and then select ONE WAY. In the Sensitivity Analysis dialog box, select Prev under Variable and enter 0 as the Low value, 0.01 as the High value, and 5 as the Number of Intervals, then click OK. The result is a graph with Prev on the x axis and Expected Value on the y axis. To the right of the graph, TreeAge Pro provides a threshold value of for the 2 strategies (the point at which both expected values are equal). The threshold is not exactly

29 Sensitivity Analysis In order to view this value with greater precision, click on the X axis, then pull down the Edit menu and select Numeric Formatting. Change the number of Decimal places to 6 and then click OK. Notice that the threshold is , meaning that No Screen is more effective than Screen if prevalence is less than 1 per 1,000, Making a Text Report TreeAge Pro will provide a text report of the points on the graph. To get a text report window, click the ACTIONS button then TEXT REPORT. The first column provides various values for Prev based on the low and high values that you entered before in the Sensitivity Analysis dialog box, and the number of intervals. The second and third columns provide the expected values for the HIV Screen and No Screen strategies, respectively, for each of the prevalence values. You have the option, after clicking EXPORT, to save a text file, export directly to Excel, or write the text report to the clipboard. If you write to the clipboard, then you can immediately paste the output into programs such as Excel or Word. To exit the Text Report, click OK

30 Closing a Graph To close the graph and return to the tree, pull down the FILE menu, and select CLOSE. TreeAge Pro will prompt you to save the file; click NO. 59 Printing the Tree To get a preview of the printed tree, pull down the FILE menu and select PRINT PREVIEW. You can reposition the tree on the page by moving the red triangle in the upper left comer; you can resize the tree by moving the black triangle in the lower right. You can switch between landscape and portrait mode by clicking SETUP, or you can add a header or footer by clicking Headers. If you want to print the tree, click PRINT followed by OK

31 PART 1: Cost effectiveness analysis In this exercise, you will turn your decision tree into a costeffectiveness model. Before you can perform a cost effectiveness analysis, you must change the analysis method. Pull down the EDIT menu and choose PREFERENCES. Under CALCULATION METHOD select COST EFFECTIVENESS, changing COST to Payoff 2 and EFFECTIVENESS TO Payoff 1. Click OK You ll now add a second payoff expression for cost. 61 PART 1: Cost effectiveness analysis Click on the first terminal node, pull down the VALUES menu, select CHANGE PAYOFF, and type CostTest+Costlnf in the text box for the Cost payoff (the second field), then click OK. Make sure you don t type over the effectiveness value you entered previously. Define CostTest and Costlnf as variables. CostTest and Costlnf represent the cost of testing and the cost of HIV infection, respectively. Now go to each of the remaining terminal nodes and enter CostTest+Costlnf for the Cost payoff (you can do this using Copy and Paste)

32 PART 1: Cost effectiveness analysis CostTest and Costlnf will be set equal to 0 at the root (decision) node and then they will be "turned on" at the appropriate place downstream in the tree. Click the V= button on the Tool Bar. Simultaneously select CostTest and Costlnf. Click the DEFINE VARIABLE button and then select DEFAULT FOR TREE. When prompted for a value for each variable, enter PART 1: Cost effectiveness analysis Select the HIV Infected node off the Positive Test branch and click the V= button on the toolbar. Select CostTest, click the DEFINE VARIABLE button and then select AT SELECTED NODE(S). When prompted for a value, enter CostPos, then click OK. (Costs are higher for patients with positive tests due to confirmatory tests.) Next, select the Not Infected node off the Positive Test branch, click the V= button, select CostTest, click the DEFINE VARIABLE button then AT SELECTED NODE(S). Enter CostPos + CostFalsePos (added costs due to repeat testing and the possibility of short term therapy). At the Negative Test node define CostTest locally as CostNeg

33 PART 1: Cost effectiveness analysis Next we ll locally define CostInf. Select the HIV Infected node off of Positive Test and click the V= button. Select Costlnf, click the DEFINE VARIABLE button then AT SELECTED NODE(S). When prompted for a value, enter CostDetect. At the HIV Infected nodes off both the Negative Test and the No Screen nodes, define Costlnf locally as CostNotDetect. 65 PART 1: Cost effectiveness analysis To define the cost variables globally, select the root node and click the V= button on the Tool Bar. Simultaneously select CostDetect, CostFalsePos, CostNeg, CostNotDetect, and CostPos. Click the DEFINE VARIABLE button and then select DEFAULT FOR TREE. When prompted for each variable enter the following: CostPos = 323 CostNotDetect= CostNeg= 48 CostFalsePos= 710 CostDetect=

34 PART 1: Cost effectiveness analysis Your tree should now look like the figure 3: Cost effectiveness tree HIVScreening Problem CostDetect= CostFalsePos=710 CostInf=0 CostNeg=48 CostNotDetect= CostPos=323 CostTest=0 LE=36.6 LELateRx=23.5 LERx=25.5 LETox=36.4 Prev=0.01 Sens=0.995 Spec= HIVScreen ppos=prev*sens+(1-prev)*(1-spec) NoScreen phiv=prev PositiveTest phiv=prev*sens/(prev*sens+(1-prev)*(1-spec)) NegativeTest ppos CostTest=CostNeg phiv=prev*(1-sens)/(prev*(1-sens)+(1-prev)*spec) # HIVInfected CostInf=CostDetect CostTest=CostPos phiv Not Infected CostTest=CostPos+CostFalsePos # HIVInfected CostInf=CostNotDetect phiv Not Infected # HIVInfected CostInf=CostNotDetect phiv Not Infected # (CostTest+CostInf)/LERx (CostTest+CostInf)/LETox (CostTest+CostInf)/LELateRx (CostTest+CostInf)/LE (CostTest+CostInf)/LELateRx (CostTest+CostInf)/LE 67 PART 1: Cost effectiveness analysis To perform the analysis, select the root node, pull down the ANALYSIS menu and choose COST EFFECTIVENESS. TreeAge Pro provides two graph display options; just click OK. You will see a plot of Cost vs. Effectiveness. To get a text report, click the ACTIONS button then TEXT REPORT. You should get the expected value for both cost and effectiveness for each strategy. The last entry in the HIV Screen row gives the marginal (incremental) C/E ratio of screening vs. not screening: $20,151/additional year of life saved. To return to the tree, click OK on the text report, then FILE CLOSE the graph without saving the graph

35 PART 1: Cost effectiveness analysis The next step will be to convert this tree to a Markov model. 69 Thank You 35