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Oral Mucositis
Author Bios
Introduction
Etiology of Oral Mucositis
Prevalence
Diagnosis
Treatment
Biological Mechanisms of Mucositis
Assessment Scale
Clinical Trial Design
Population Selection and Randomization
Data Collection and Assessment Measures
Quality Control Techniques
Currently selected section: Anaysis and Presentation
Conclusion


Chapter 17: Oral Mucositis: Clinical Trial Design for Mucositis: Quality Control Techniques
        

There are several comprehensive books on statistical analysis of clinical trials which cover specific methods of analysis and how to interpret and present the data. Our purpose here is to briefly cover challenging aspects of analysis, interpretation, and presentation that are specific to a study evaluating musocitis-related pain.

The main questions surrounding data analysis are determining who should be analyzed and how to evaluate the data. Missing data and/or poor quality data can cause participants to be withdrawn from analysis. Withdrawal policies should be clearly stated in a protocol before enrolling participants. Withdrawing participants can complicate data analyses. If the loss is related to the intervention, a bias can be introduced. For instance, in this study, if patients on the placebo are generally doing worse than the study drug, they may skip diary entries, thereby causing a bias.

Patient cooperation can make or break a study, especially one involving pain. In this study, the endpoints surround the patient's daily self-assessment of pain. If a few entries are missing, it is possible to estimate the data if there is an observed rate of change seen in the days prior to and/or after the missing dates. If an observed rate of change is not seen, then the scores prior to the missing data should be used. However, this can skew the data and should be avoided if possible. For instance, if the patient was in severe pain with a WHO pain ladder of 3 for 5 days, skipped 5 days of entries and started again with no pain, filling in the missing 5 days would be difficult. The pain was severe without a rate of change and then a sudden drop was noted. In this scenario, the missing data can only be filled with the last entry of severe pain, regardless of whether pain had decreased during those days.

Presenting the data can be challenging. As with any study, over-analyzing the data should be avoided. Whether or not the study revealed positive results, the data should be presented in a straightforward manner. The goal in presentation is to state what resulted, even if the treatment--in this case the mouth rinse--did not make a significant difference. Leave the potential sources of error and questions for future studies in the discussion section.

 

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