Get Help With Statistical Analysis of Clinical Trial Data

Statistical analysis is the collection and analysis of large data volumes to identify patterns and trends and gain meaningful insights. A clinical trial is an experiment in which a group of participants is given an intervention, and the outcome measures are taken then compared to individuals not given the treatment. Statistical analysis of clinical trial data is the transformation of raw data into actionable insights that guide patient care and medical procedures. If you are in need of statistical analysis services, then look no further because our company offers personalized clinical data analysis services including clinical trial data extraction and management, process automation, and creating easily interpretable visualizations for a comprehensive understanding of complicated clinical data.

Statistical analysis of clinical trial data is considered the standard for the evaluation of treatments, disease screening, and diagnostics procedures. Different statistical methods are applied depending on the nature of the data. This post is a comprehensive guide to the classification of clinical trials, data management and visualization of clinical data, and an example.

What is a Clinical Trial?

A clinical trial is an experiment that evaluates the effect of a new drug on human volunteers. This procedure can be used to evaluate the safety of a new drug in healthy human volunteers or to assess the treatment benefits in patients with a specific disease. Clinical trials can compare a new drug against existing ones or dummy medications.

Types of Clinical Trials

Clinical trials depend on who is conducting the trial. Device manufacturers use the trials to demonstrate the efficiency of their new device, pharmaceutical companies conduct trials to evaluate new drugs, and clinical investigators investigate the best duration of treatment for efficiency. Different types of trials are thus needed, and they can be classified according to phases, design, and number of centers.

(1). Clinical Trial Design

Classification by trial design describes how patients are randomized to treatment. The most common design is the parallel-group trial then crossover, factorial, and cluster randomized trials. Below is a detailed guide to each:

• In parallel-group trial design, the patients are randomized to a new treatment and then followed up to determine the effect of every treatment in parallel groups.
• The factorial trial design assigns patients to more than one treatment comparison group.
• Cluster randomized trials are administered when larger groups, such as patients of a specific hospital, are randomized instead of individual patients.
• Crossover trials randomize the patients to a different procedure of treatments but they all get the full treatment but in varying order.

(2). Number of Centers

Classification of clinical trials according to the number of centers is based on the number of sites involved. Trials can be categorized as single-center and multicenter. The former is conducted at a single location, while the latter is conducted at multiple areas and can be carried out at any stage of clinical development.

Hire the Best Clinical Trial Data Services

Our services have worked with multiple industries, such as biotechnology firms, pharmaceutical companies, and medical device manufacturers, among others, to discover meaningful insights for their clinical trial data. Our experts apply their knowledge and expertise to conduct rigorous clinical trial data analytics and draw useful conclusions about the safety and efficiency of new medical interventions. In this section, we discuss how you manage data in a clinical trial, methods of data analysis, and data visualization.

Clinical Trial Data Management

Clinical data management is the procedure of processing the clinical trial data. This method involves working with a range of computer applications and database systems to support collection and analysis, cleaning, and management of trial data. During the clinical trial, the researcher collects data on the patient's health for a certain period and then sends it to the trial sponsor who analyzes the data using statistical analysis software such as Python, SAS, Stata, SPSS, and R. Below are the series of steps followed in this procedure:

Step 1: Data Collection

Data collection is done using a case report form that exists in the form of a paper or an electronic version. The forms collect the data responses and then transport them to the database by the process of data entry. In the electronic forms, the researcher logs into the clinical data management system and enters the data directly into the site.

Step 2: Clinical Trial Data Extraction

The data extraction step involves acquiring relevant information from the study and assessing the quality of the available data. Information on the study design, patient characteristics, treatments, and other primary outcomes are extracted to be used for statistical analysis. Clinical trial data extraction is often performed using custom query tools and scripts.

Step 3: Data Entry

Double data entry is normally performed where the data is entered by two researchers. The second entry ensures the reliability of the data by removing transcription errors and discrepancies caused by inaccurate data. This step follows the guidelines of the data management plan.

Step 4: Data Validation

Data validation is the process of testing for the accuracy and consistency of the data set. Data validation is done using edit check programs, which are located in the database. To ensure their reliability, these programs are first tested with dummy data containing errors and discrepancies.

Step 5: Data Cleanup

Data cleanup is the process through which clinical trial data is refined to produce data free of errors. It is achieved by checking for missing data, inspecting for odd ranges, and assigning queries to the clinical staff to have the issues resolved. It is often done by experts such as professional statisticians and clinical trial managers.

Step 6: Data Analysis

The methods of data analysis used are according to the ones defined in the data management plan. The researcher can opt to use data analysis software such as R, SPSS, and SAS. Data is exported to the software then an analysis is conducted.

Step 7: Data Reporting

To interpret the findings of a clinical trial, the reader should understand the rationale for and how your findings relate to further clinical practice. Your clinical analysis report includes information on how the trial was conducted. The document consists of six key areas, which are the abstract, introduction, methods, results, discussion and conclusion. It should also include a CONSORT statement.

Clinical Trial Data Visualization Services

Clinical trial data analysis results are presented in statistical tables that allow a rapid comparison between treatment effects. The reader should be able to interpret the tables and figures easily. Our experts use a standardized row and column format and informative headings to demonstrate information concisely. Common data visualization features are such as standard and complex tables.

Example of Clinical Trial Data Analysis

A pharmaceutical company conducted a randomized controlled trial to evaluate the effectiveness and safety of two COVID-19 vaccines, Pfizer-BioNTech and Moderna mRNA. They selected a group of 120,000 adults to which they randomized two groups which were the vaccine group and the control group. They collected data through monitoring the participants' symptoms and using their health records then conducted a subgroup analysis to evaluate how the treatment affected each individual.

Summary

Statistical analysis of clinical trial data is the transformation of raw data into meaningful insights about the safety and efficacy of new medical interventions. For the analysis to be done, clinical trial data has to go through the procedure of data management to process and prepare it for data analysis. This process involves data collection, extraction, entry, validation, clean-up, analysis, and reporting. Our experts offer professional, personalized clinical trial data analysis help for your data. They apply their knowledge and expertise to conduct an analysis using advanced software such as R, Stata, and SAS and deliver accurate, meaningful insights. Discover more about our clinical trial data analysis services today on our services! Contact us today for inquiries and you will get a prompt response from our excellent customer support team.