## Welcome to CompARE!

This tutorial introduces you to CompARE, a web-tool for designing trials with composite endpoints.

### What is a Composite Endpoint?

There are some diseases for which more than one clinical outcome is important and where all outcomes are expected to be affected by the treatment. When a single outcome is not sufficient to capture the treatment benefits, the use of more than one primary variable may become necessary^{1}.

Instead of using each as a separate primary endpoint (creating multiplicity) or selecting just one to be the primary endpoint, it may be appropriate to combine those clinical outcomes into a single variable^{2}.

The so-called `Composite Endpoint`

(or composite outcome) consists of two or more component outcomes. Patients who have experienced any one of the events specified by the components are considered to have experienced the composite outcome.

### Benefits and Risks

Composite endpoints are frequently chosen as primary endpoint in many health areas and specially in cardiovascular and oncology trials. There are three key advantages for using a composite. First, they avoid the need of multiplicity adjustment. Second, a composite endpoint contains more information on the course of the disease than a single endpoint providing a better explanation about the differences between treatment groups. Third, the increment of the number of observed events is expected to increase the power.

The main drawback of using a composite endpoint is its interpretation since its components rarely have comparable clinical importance and similar treatment effects. The addition of components that are not relevant enough could compromise the interpretation of results and reduce power. Hence, the choice of the particular components for the composite has a great importance in the design phase.

## Why use CompARE?

CompARE is intended to provide guidance on how to deal with composite endpoints in the planning and statistical analysis of clinical trials. CompARE helps researchers to study:

- Sample size calculation in trials with Composite Time to Event Endpoints.
- Effect size calculation for Time to Event Endpoints.
- Endpoint selection.

## What do we need to use CompARE?

### Structure of CompARE

CompARE is composed of three main parts:

- Input panel
- Menu bar
- Output panel

The user is prompted for the anticipation of different parameter values summarized in the following section.

### Input Panel

For each `Composite Component`

, you need:

- To specify if it corresponds to a terminating endpoint.
- To provide the probability of observing the event in the control group.
- To provide the effect measure, Hazard Ratio (HR) you expect.
- To specify if the risk over time is Constant, Increasing or Decreasing.

Additionally, regarding to the `Association`

between components you need to provide: - The `Correlation`

between the `Composite Components`

. - The measure of corelation: Spearman or Tau - The copula used to derive the joint distribution.

For calculating the sample size, you need to provide:

- The significance level \(\alpha\).
- The desired power \(1 - \beta\)
- The formula for estimating the sample size: Shoendfeld or Freedman

Finally, you need to provide the study times:

- The time of folow-up
- The Recruitment time (not yet implemented)

## What does CompARE do?

### Key messages and short report

In the first tab, CompARE shows a key messages about the trial design as well as a short report according to the parameters anticipated in the Input Panel.

### Sample Size

When designing a study, investigators need to determine how many subjects should be included. By enrolling too few subjects, a study may not have enough statistical power to detect a treatment difference. Including too many patients can be unnecessarily costly or time-consuming.

To size a trial with a time-to-event endpoint, one needs to specify the event rates and the effect sizes of the composite components along with the correlation between them. In practice, the marginal parameters of the components can be obtained from previous studies or pilot trials, however, the correlation is often not previously reported and thus usually unknown.

By means of CompARE, the user can calculate the required total sample size for:

- Each single component
- For the composite endpoint based on two metodologies:
- Naive (averaging HRs)
- ARE

- Using the maximum \(HR^*(t)\)
- Using the average \(HR^*(t)\)
- Using the minimum \(HR^*(t)\)

Learn more in:

Sample size calculation for Composite Binary Endpoints using CompARE.

### Effect Size

Before a study is conducted, investigators need to know if the hazard Ratio can be considered constant over time or not.

By means of CompARE, you can draw the shape of \(HR^*(t)\) along time based on the imput parameters.

Learn more in:

Effect size calculation for Composite Binary Endpoints using CompARE.

### Endpoint Selection

CompARE can help you to make a more informed decision on the `Primary Endpoint`

you should use in your study.

Considering the `Endpoint 1`

as the indispensable endpoint you must use in your trial to test the treatment efficacy, CompARE will help you to choose between a `Endpoint 1`

and the `Composite Endpoint`

as the primary endpoint for the trial.

Learn more in:

Endpoint Selection in trials involving Composite Binary Endpoints using CompARE.

## Dictionary

`Primary Endpoint`

: The primary endpoint of a clinical trial is the endpoint for which subjects are randomized and for which the trial is powered.`Composite Endpoint`

: combination of more than one outcome (or endpoint) into a unique response.`Endpoint 1`

and`Endpoint 2`

: Composite components.`Effect size`

: The effect size is the quantified difference between two groups.`Sample size`

: The sample size is a term used in clinical trials for defining the number of subjects included in the trial.