Creating Results Metadata for Kaplan-Meier Analysis in Clinical Trials
Clinical trials play a critical role in the development and testing of new treatments for a variety of medical conditions. As part of the clinical trial reporting process, results metadata are created to support the analysis of the data. In this article, we will focus on the creation of results metadata for a Kaplan-Meier analysis in a clinical trial.
To start, let’s take a look at the results metadata table. From the table, we can see that there are two main sections. The first section shows basic frequencies of the number of subjects in the population, the number who were censored, and the number who were not censored. The second section performs the Kaplan-Meier analysis.
In order to create the results metadata, we need to fill in several key fields. These include the display identifier, the result identifier, the parameter code (PARAMCD), the analysis variable, the selection criteria, documentation, and programming statements. Let’s take a closer look at each of these fields.
The display identifier is a unique identifier used to distinguish the table from other tables in the report. This identifier is used to reference the table in other sections of the report, such as the clinical study report (CSR).
The result identifier is another unique identifier used to distinguish the table from other tables in the report. This identifier is typically used to reference the table in statistical analysis reports and other documents.
The parameter code (PARAMCD) is a code that identifies the variable being analyzed in the Kaplan-Meier analysis. For example, in our example analysis, the parameter code might be “time to first diastolic blood pressure ≤ 90 mmHg.”
The analysis variable is the variable being analyzed in the Kaplan-Meier analysis. This variable is typically a time-to-event variable, such as time to disease progression or time to death.
The selection criteria describe the criteria used to select subjects for the analysis. For example, in our example analysis, the selection criteria might include subjects who achieved a diastolic blood pressure ≤ 90 mmHg within a certain timeframe.
Documentation provides a brief description of the table and the analysis being performed. This may include information about the study population, the treatment groups, and the statistical methods being used.
Programming statements provide details on the programming logic used to create the table. This includes information on how the data was processed, how missing data was handled, and how statistical methods were applied.
Once the results metadata table has been completed, we can move on to the Kaplan-Meier analysis. This involves applying appropriate statistical methods, such as the Kaplan-Meier estimator, to estimate the probability of survival or time until the event occurs for each treatment group. The resulting table will include key variables such as the number of subjects at risk, the number of events, and the probability of survival or time until the event occurs for each treatment group.
In conclusion, creating results metadata for Kaplan-Meier analysis tables is an important part of clinical trial reporting. By using a structured approach to capturing the necessary data and variables, we can create tables that provide critical information on the probability of survival or time until a specific event occurs. It is important to carefully consider the selection criteria, documentation, and programming statements to ensure that the analysis is conducted accurately and transparently.
