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Common methods of analyzing response data in clinical trials.

D P Harrington¹, J W Andersen

¹Division of Biostatistics and Epidemiology, Dana-Farber Cancer Institute.

Oncology (Williston Park, N.Y.)

|January 1, 1990

Summary

This study outlines key criteria for evaluating clinical trial reports, focusing on clear objectives, patient populations, and unbiased data analysis for reliable treatment effectiveness assessment. It details statistical methods for analyzing outcomes, particularly objective disease response.

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Area of Science:

Clinical trial methodology
Biostatistics
Evidence-based medicine

Background:

Evaluating published clinical trial reports is crucial for evidence-based medicine.
Ensuring the reliability of trial data requires careful attention to methodological rigor.

Purpose of the Study:

To outline essential criteria for critically appraising clinical trial publications.
To describe statistical approaches for analyzing clinical trial outcomes, including disease response.

Main Methods:

Review of best practices in clinical trial reporting and evaluation.
Explanation of statistical concepts for outcome analysis, including hypothesis testing and effect estimation.
Description of methods for analyzing data with multiple response categories.

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Main Results:

Key evaluation criteria include clear objectives, well-defined patient populations, and unbiased patient allocation.
Statistical analysis of outcomes estimates treatment effects and tests hypotheses.
Objective response of disease post-therapy is a primary measure of effectiveness.

Conclusions:

Adherence to rigorous reporting standards enhances the interpretability and validity of clinical trial findings.
Appropriate statistical methods are essential for accurately assessing therapeutic effectiveness.
Standardized definitions of endpoints ensure comparability across studies.