Understanding Clinical Laboratory Data in Pharmaceutical Trials: Categories, Challenges, and Presentation Methods
Introduction:
Clinical trials are an essential part of the drug development process, and the safety and efficacy of a new pharmaceutical agent are evaluated through a variety of methods, including clinical laboratory data. Clinical laboratory data is a crucial component of the safety profile for any drug under study. It helps to evaluate the safety and efficacy of the drug and provides vital information on the pharmacokinetics, pharmacodynamics, and toxicology of the drug.
In this article, we will explore the categories and types of laboratory parameters commonly collected in clinical trials. We will also discuss the differences between local and central laboratories in handling and analyzing the data. Additionally, we will outline the need for unit conversion and various SAS methods used for this purpose. Finally, we will provide examples of typical summary tables and graphs used to present clinical laboratory results.
Categories and Types of Laboratory Parameters:
Clinical laboratory parameters can be broadly classified into two categories: safety and efficacy. Safety parameters are used to assess the safety of the drug under study, while efficacy parameters are used to evaluate its efficacy.
Safety parameters include measurements of vital signs, electrocardiograms, clinical chemistry, hematology, and urinalysis. Vital signs such as blood pressure, heart rate, and respiratory rate are monitored to detect any changes that may indicate adverse effects of the drug. Electrocardiograms are used to assess the effects of the drug on cardiac function, and clinical chemistry tests are used to evaluate liver and kidney function. Hematology tests are used to assess the effects of the drug on blood cells, while urinalysis is used to evaluate kidney function.
Efficacy parameters include biomarkers, which are used to measure the drug’s intended effects on the body. These can include measurements of drug concentrations in blood or urine, receptor occupancy, or changes in disease-specific biomarkers.
Local vs. Central Laboratories:
In clinical trials, laboratory data can be collected and analyzed in two ways: by a local laboratory or a central laboratory. A local laboratory is typically located at the clinical site, while a central laboratory is a specialized facility that handles laboratory analysis for multiple clinical sites.
Local laboratories offer several advantages, such as faster turnaround time for results, greater control over the handling of samples, and the ability to provide immediate feedback to the study team. However, there are also several drawbacks, including the potential for inconsistent data due to differences in equipment, reagents, and methodologies used between sites.
Central laboratories, on the other hand, offer several benefits, including standardized methodology, greater accuracy, and the ability to analyze samples from multiple sites in a single batch. However, they may be more expensive, and the turnaround time for results may be longer.
Unit Conversion and SAS® Methods:
In clinical trials, laboratory data is often collected in various units of measure, such as milligrams per deciliter or micromoles per liter. It is essential to convert the data into a common unit of measure to facilitate analysis and interpretation.
SAS® is a software suite widely used in clinical trials for data analysis and reporting. SAS® includes several built-in functions for unit conversion, including the FACTOR function, which can be used to convert data between different units of measure. Additionally, SAS® offers several procedures, such as PROC TRANSPOSE and PROC MEANS, which can be used to summarize and analyze laboratory data.
Summary Tables and Graphs:
After laboratory data is collected, analyzed, and converted into a common unit of measure, it is typically presented in summary tables and graphs. These help to convey the results of the study to stakeholders, including regulatory agencies, sponsors, and study investigators.
Descriptive statistics, such as means, medians, and standard deviations, are commonly used to summarize laboratory data. Shift tables, which compare the percentage of subjects with abnormal laboratory values at baseline and after treatment, are also commonly used CTC (Common Terminology Criteria) grading summaries are another type of summary table commonly used in clinical trials. They provide a standardized method for reporting the severity of adverse events based on a graded scale from 0 to 5. The CTC grading system is widely used in oncology trials to report adverse events related to chemotherapy or other cancer treatments.
Graphs are also commonly used to present clinical laboratory results. SAS/GRAPH® is a module within the SAS® software suite that provides a wide range of graphical tools for data visualization. Common types of graphs used in clinical trials include scatterplots, boxplots, and histograms.
Scatterplots are used to visualize the relationship between two continuous variables, such as drug concentration and time. Boxplots are used to display the distribution of a continuous variable across different treatment groups or time points. Histograms are used to visualize the distribution of a continuous variable across a single treatment group or time point.
Conclusion:
Clinical laboratory data is a critical component of the safety profile for any drug under study. It helps to evaluate the safety and efficacy of the drug and provides vital information on the pharmacokinetics, pharmacodynamics, and toxicology of the drug. The categories and types of laboratory parameters commonly collected in clinical trials include safety and efficacy parameters.
Local and central laboratories can be used to collect and analyze laboratory data, each with its own advantages and disadvantages. Unit conversion is necessary to facilitate analysis and interpretation of laboratory data, and SAS® provides several built-in functions and procedures for this purpose.
Finally, summary tables and graphs are commonly used to present clinical laboratory results. Descriptive statistics, shift tables, and CTC grading summaries are common types of summary tables, while scatterplots, boxplots, and histograms are common types of graphs. SAS/GRAPH® provides a wide range of graphical tools for data visualization in clinical trials. Overall, clinical laboratory data plays a crucial role in the drug development process, and effective analysis and presentation of this data are essential for ensuring the safety and efficacy of new pharmaceutical agents.
