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Clinical Trials

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...

Clinical Trials: Overview

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...

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When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...

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Updated: Jul 5, 2026

Quantitative Autonomic Testing

Quantitative Autonomic Testing

Published on: July 19, 2011

Validation testing in thorough QT/QTc clinical trials.

Yi Tsong¹, Jinglin Zhong, Wen Jen Chen

¹Office of Biostatistics/Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland 20993, USA. yi.tsong@cder.hhs.gov

Journal of Biopharmaceutical Statistics

|May 13, 2008

Summary

This study compares two methods for validating clinical trials using positive controls. Both intersection-union and global average tests can validate QT/QTc intervals, with combined approaches potentially improving efficiency.

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Last Updated: Jul 5, 2026

Quantitative Autonomic Testing

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Published on: July 19, 2011

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

Area of Science:

Pharmacology
Clinical Trials
Biostatistics

Background:

ICH E14 guidelines recommend positive controls for validating QT/QTc interval clinical trials.
Validation is typically achieved when a positive control alters the mean QT/QTc interval by approximately 5 ms.
Existing methods include the intersection-union test and global average test approaches.

Purpose of the Study:

To further discuss the differences and relationships between the intersection-union and global average test hypotheses.
To compare the efficiencies of these two validation approaches.
To determine optimal strategies for assessing clinical trial validation using positive controls.

Main Methods:

Comparative analysis of statistical hypotheses for intersection-union and global average tests.
Evaluation of Type I error rates and statistical power for each approach.
Assessment of validation efficiency using simulated or real-world clinical trial data.

Main Results:

Both intersection-union and global average tests can achieve validation if null hypotheses are rejected without inflating family-wise Type I error rates.
The study elaborates on the statistical nuances and relationships between the two hypothesis testing frameworks.
Differences in efficiency between the two approaches are discussed in detail.

Conclusions:

Validation of QT/QTc interval trials is achievable through either the intersection-union or global average test approach.
Employing both validation assessment approaches may enhance the overall efficiency and reliability of the validation process.
Further research into combined approaches could refine clinical trial validation strategies.