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Measurements in Clinical Trials

Site: EUPATI Open Classroom
Course: Interpretation and Dissemination of Results
Book: Measurements in Clinical Trials
Printed by: Guest user
Date: Friday, 26 April 2024, 9:07 PM

Table of contents

1. Introduction

(This section is organised in the form of a book, please follow the blue arrows to navigate through the book or by following the navigation panel on the right side of the page.)


When clinical trials are conducted, medical details of participants (but not their identities) are collected for the purpose of statistical analyses in a computer database together with the results of any measurements made*. Statistical analyses are then conducted to formally assess the outcomes of the trial. These analyses cover three areas of interest:

* In cases of emergency it must be possible to identify a participant (even after the completion of the trial).

1.1. Demographic and Baseline Information – Who Took Part In The Trial?

The effects of a medicine may differ considerably between different groups of people. It is therefore important to know details of the trial participants such as:
  • Age.
  • Sex.
  • Ethnic origin.
  • Severity of their illness.
In general, the closer the match between a trial group and a population of interest, the more relevant the findings will be.

1.2. Efficacy – How Well Did The Trial Medicine Work?

Efficacy is often the main objective of the trial and is usually the aspect of highest interest. This part of the analysis is based on pre-defined ‘endpoints. These are specific measurements related to the illness in question that have been specified in advance in the protocol (the document which describes in detail how the trial is going to be performed).

Endpoints in general can be categorised as:
  • ‘Hard’ endpoints – those that take the form of numerical facts with intrinsic clinical importance. For example, how long the participant survived or what proportion of participants recovered from an infection.

  • ‘Soft’ endpoints – those which are potentially influenced by the measurement process or with questionable reproducibility. For example, a quality-of-life questionnaire or the description of the participant’s mood at a given moment. In order to be analysed statistically, soft endpoints have to be converted into a numerical format. This process can be controversial as it is subjective and potentially open to inconsistencies.

  • ‘Surrogate’ endpoints – those that are not in themselves part of the patient’s experience of the illness, but may be closely related to it. For example, the results of laboratory tests. 
Often, choosing which endpoints to use depends heavily on the nature of the illness being studied. Cancer offers obvious hard endpoints in the form of survival, whereas evaluation of depression. Other illnesses, such as diabetes, are associated with well-established surrogate endpoints such as blood sugar levels.

1.3. Safety – What Possible Side Effects Did The Medicine Have?

Participants in a clinical trial are asked to report to the investigator (or trial staff) if anything undesired has happened. The ‘adverse event’ information collected in this way is analysed to give an insight into possible side effects of the medicine, i.e. a possible causal relationship between the trial medication and the observed adverse event. Particular attention is paid to ‘serious’ adverse events – those which are life-threatening or associated with death, hospitalisation or birth abnormalities.