TABLE OF CONTENTS

Example 1 - ALLHAT .............................................................................................................................. 2

Challenges ........................................................................................................................................ 2

Applying Feasibility Checklist ............................................................................................................ 3

Feasibility questionnaire ................................................................................................................... 4

Parameters Input for ALLHAT Protocol .............................................................................................. 5

ALLHAT Results ................................................................................................................................. 7

Part 1: Antihypertensive component ............................................................................................. 7

Part 2: Cholesterol lowering component ....................................................................................... 9

FIGURES

Figure 1-1. EVPI results for ALLHAT - Antihypertensive component .......................................................... 7

Figure 1-2. EVSI results for ALLHAT - Antihypertensive component .......................................................... 8

Figure 1-3. EVPI results for ALLHAT - Cholesterol lowering component .................................................... 9

Figure 1-4. EVSI results for ALLHAT - Cholesterol lowering component .................................................. 10

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OTHER EXAMPLES FOR VICTOR PLATFORM

In addition to the SHEP trial, we also use the VICTOR platform for another three trials:

(1) ALLHAT – Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (2) ACCORD – Action to Control Cardiovascular Risk in Diabetes Trial (3) AIMHIGH – Atherothrombosis Intervention in Metabolic Syndrome with low HDL/High Triglyceride

and Impact on Global Health Outcomes

For each trial, we first use feasibility checklist and questionnaire to determine whether the VICTOR platform can be used to estimate the expected value of perfect information (EVPI) and the expected value of sample information (EVSI). If so, we will list the parameters input and results, and also describe challenges and potential solutions to obtain these parameters.

Example 1 - ALLHAT

Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) is a randomized trial for high-risk hypertensive patients. The trial included two components – antihypertensive component and cholesterol lowering component. The antihypertensive part compared chlorthalidone treatment with another three alternative treatments (amlodipine, lisinopril, and doxazosin). The primary endpoint was combination of fatal coronary heart disease (CHD) and non-fatal myocardial infarction (MI). The second cholesterol lowering component compared pravastatin with usual care, and its primary endpoint was all-cause mortality. In this example, we will use VICTOR platform to calculate value of information for each component separately.

Challenges

So far, the options of primary endpoint at VICTOR platform did not include the combination of fatal CHD and non-fatal MI. After consulting with clinicians, we substituted fatal CHD with fatal MI since fatal MI is a large subset and most of fatal CHD. Thus, instead of using the annual rate of fatal CHD, we needed the annual rate of fatal MI and non-fatal MI for the antihypertensive part. However, only overall 6-year CHD rate were reported in the ALLHAT protocol. In order to use VICTOR platform, we first calculated annual rate of CHD and then derived the annual rate of fatal and non-fatal MI based on the MI percentage of the primary outcomes. According to the published ALLHAT results, fatal MI was about 35 % of primary outcomes.1 Therefore, we multiplied annual CHD rate by 35% to obtain the annual rate of fatal MI for intervention and control group separately.

Similarly, for the cholesterol lowering component, we needed to specify cardiovascular disease (CVD) mortality rather than using all-cause mortality because non-CVD mortality had already accounted for in the model. To calculate CVD mortality, we multiplied annual all-cause mortality by the percentage of CVD death among all-cause death which were reported in the publication.

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Applying Feasibility Checklist

FEASIBILITY FACTOR FEASIBILITY QUESTION EXAMPLE - ALLHAT

Part 1: Antihypertensive Part 2: cholesterol lowering

STUDY POPULATION: Is the condition of interest for your study population listed?

Patients with hypertension

STUDY TYPE: Is your proposed study design listed?

Chlorthalidone vs Amlodipine, lisinopril, doxazosin

cholesterol lowering vs usual care

ENDPOINTS: Is your proposed primary study endpoint listed?

fatal CHD & non-fatal MI all-cause mortality

INTERVENTION EFFECTS:

Can the effect of the intervention in your proposal be expressed using one of the options listed?

6-year CHD rate were reported for both groups

6-year mortality rate were reported for both groups

BACKGROUND CLINICAL DATA FOR CONTROL GROUP, BY ENDPOINT

Do you have listed data on the control group for the primary endpoint?

• Consult with clinicians • Most fatal CHD are fatal MI • 65% non-fatal MI - from

literature • Calculate rate for fatal and

non-fatal MI separately

• Get % of CVD death - from literature

• Calculate CVD mortality rate o 0.48 (300/631) for control

group o 0.47 (295/631) for

treatment group

BACKGROUND CLINICAL DATA ON INTERVENTION EFFECTS, BY ENDPOINT

Do you have listed data on selected intervention effects?

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Feasibility questionnaire Part 1: Antihypertensive

Part 2: Cholesterol Lowering

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Parameters Input for ALLHAT Protocol

• Note that we chose MI as primary endpoint for the first part (antihypertensive component) and chose all-cause mortality as primary endpoint for the second part (cholesterol lowering component). Then we needed clinical parameters input of fatal and non-fatal MI in the first part, and annual rate of CVD death in the second part.

Study Parameters

• Target population o Mean Age : 67 o Female(%) : 45 o MI history composition (%) : 50

• Study design features

o Number of comparators (Fixed at 2) o Expression of intervention effects : Absolute

level o Primary endpoint :

§ Part 1 à MI (fatal & non-fatal MI) § Part 2 à Total mortality

o Treatment effectiveness duration : 6

• Other model input o Target population size : 100,000 o Discount rate(%) : 3 o Horizon duration (years) : 20

• EVSI parameters

o Total length of proposed study : 8 o Sample size for each arm : 1,000-10,000 o Number of sample size to be evaluated : 10

• Advanced VOI parameters

o Decision-making criterion : 95% CI o Current use rate of treatment : Decision-

making criterion

Illustration for Part 1 Antihypertensive

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Part 1: Antihypertensive Part 2: Cholesterol lowering

Clinical Parameters (Mean ±SE)

• Intervention group o annual rate (%) for non-fatal MI :

0.62 ± 0.11 o annual rate (%) for fatal MI :

0.33 ± 0.11 • Control group

o annual rate (%) for non-fatal MI : 0.74 ± 0.09

o annual rate (%) for fatal MI : 0.4 ± 0.09

Clinical Parameters (Mean ±SE)

• Intervention group o annual rate (%) for CVD death :

0.915 ± 0.139 • Control group

o annual rate (%) for CVD death : 1.042 ± 0.147

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ALLHAT Results Part 1: Antihypertensive component Figure 1-1. EVPI results for ALLHAT - Antihypertensive component

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Figure 1-2. EVSI results for ALLHAT - Antihypertensive component

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Part 2: Cholesterol lowering component Figure 1-3. EVPI results for ALLHAT - Cholesterol lowering component

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Figure 1-4. EVSI results for ALLHAT - Cholesterol lowering component

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Reference 1. The, Allhat Officers, Coordinators for the, Allhat Collaborative Research Group. Major Outcomes

in High-Risk Hypertensive Patients Randomized to Angiotensin-Converting Enzyme Inhibitor or Calcium Channel Blocker vs DiureticThe Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). JAMA. 2002;288(23):2981-2997.