Getting Started

Introduction

Welcome to the CALYPSO study feasibility application. For this introduction, it is assumed that the application, database and OHDSI WebAPI have already been installed. If not, please contact your administrator and refer to the [Setup Guide] (Setup Guide) for installation instructions.

What is CALYPSO?

CALYPSO (Criteria Assessment Logic for Your Population Study in Observational data) is a browser-based application that utilizes real world data (RWD) to simulate the availability of eligible patients for a study. The tool allows users to define the index rule (primary condition under study) and inclusion rules (inclusion/exclusion criteria) and run feasibility simulations against the RWD (health insurance claims and electronic medical records). The tool allows users to visualize which inclusion/exclusion criteria have the largest impact on the availability of patients within the RWD. The index population are those patients as defined by the index rule and the matching population are those patients that meet all of the inclusion rules or those patients that you would expect to be eligible to enroll into the trial under evaluation. Using this tool can help to identify inclusion/exclusion criteria that could be limiting to study feasiblity. The tool can be used to run multiple scenarios against any study criteria to help expedite decision making.

Browser Requirements

Due to some of the advanced features for visualizations, the application requires either Google Chrome or Internet Explorer 10+.

Using the Application

To launch CALYPSO, navigate to the URL where the CALYPSO site was installed (ex: http://yourdomain.com/CALYPSO). From this URL, you are presented with the list of existing feasibility studies and a button to 'Create New Study'. For this short overview, we will create a simple study and view the simulation results.

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Figure 1: CALYPSO Home Page

Create a New Study

To begin, click the New Study button on the home page. This will present a blank study form (Figure 2) allowing you to specify information such as title and description. The title and description are very important because they will be presented on the study list. For this example, we will create a study for "A study to understand the population of adult patients with Type 2 Diabetes Mellitus (T2DM) receiving Metformin treatments and have not had an amputation."

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Figure 2: New Study

## Index Rule The first tab is the Index Rule tab (Figure 3), which is where you define the index population that you want to study. Think of the index population as the primary indication under study (example T2DM). From the index population, you will apply additional inclusion rules (inclusion/exclusion criteria) that patients must meet in order to be eligible for the study. For this example, we are going to select people with an exposure era to Oral Antidiabetic Agents. The OHDSI application HERMES can be used to locate concepts of interests, and create Concept Sets, but this topic is beyond the scope of this introduction, but it is a key application that is used to identify any condition or drug that is used in CALYPSO.

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Figure 3: CALYPSO Index Rule Tab

Inclusion Rule Tab

The second tab is the Inclusion Rule tab (Figure 4). This is where you specify additional inclusion rules (inclusion/exclusion) for study eligibility. This section is similar to the Inclusion/Exclusion (I/E) section of a clinical trial Protocol. However, CALYPSO only considers the rules as inclusion rules, but exclusion rules can be defined as inclusion rules that specify '0 occurrences of a specified criteria'. In our example, we define inclusion rules that consist of drug exposures and condition diagnoses, that both require (at least 1 occurrence) and exclude (at most 0 occurrences). There are 4 in all, each one representing the IE rules defined in the study using Person, Drug Exposure, Procedure and Condition Criteria.

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Figure 4: CALYPSO Inclusion Rule Tab

Concept Sets Tab

The third tab (Figure ) holds all the concept set definitions that will be referenced in this study. A Concept Set is a way of selecting concepts from the OMOP Vocabulary where you start with an ancestor concept ID, and select descendants or mapped concepts to be included, or excluded, from the concept set expression. An expression which selects concepts of Depressive Disorder without Bipolar would be defined as selecting all descendant concepts of 'Depressive Disorder' while excluding concepts descended from Bipolar Disorder. For this example, we will define concept sets for amputations, Metformin treatments, T1 and T2 diabetes.

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Figure : Concept Sets Tab

Results

Once a study is generated against a target CDM, the results can be viewed in the Results tab. The results show how each inclusion rule impacted the inclusion of the index population into the matching population.