Efficacy of three or more treatments on the change in a biomarker between two time points
In the context of randomized clinical trials, health care professionals are often asked to compare a new therapeutic approach, both with the already existing one, and with a placebo in terms of their effectiveness in improving the levels of a biomarker between two points in time (e.g. study start – after 12 months of treatment).
Examples: A research group wishes to develop a new treatment for patients with type II diabetes that will help reduce glycated hemoglobin levels after 12 months of administration and in order to support its necessity and utility in the treatment of patients, he should compare it with the usual therapeutic practice as well as with a placebo, so as to prove its necessity and superiority.
The problem
In the context of randomized clinical trials, healthcare professionals are often asked to compare a new therapeutic approach, both with the already existing one, and with a placebo in terms of their effectiveness in improving the levels of a biomarker between two points in time (e.g. study start – after 12 months of treatment). For example, a research group wishes to develop a new treatment for patients with type II diabetes that will help reduce glycated hemoglobin levels after 12 months of administration and in order to support its necessity and utility in the treatment of patients, he should compare it with the usual therapeutic practice as well as with a placebo, so as to prove its necessity and superiority.
The purpose
Indication of the most effective treatment for improving the levels of a biomarker between two time points in subjects participating in a clinical trial.
The solution
By using the appropriate statistical methodology (One-way ANOVA, Kruskal-Wallis test) and after the test of the assumptions, the three or more therapeutic approaches that the user will enter into the application will be compared in terms of improving a biomarker between two time points of individuals, and the most effective treatment will be identified.
The benefit
Healthcare professionals will be able to easily, quickly and without prior statistical knowledge, compare three or more therapeutic approaches with regard to the improvement of a biomarker between two time points of the subjects participating in their study, and thus arrive at the conclusion about which treatment is most effective.
Indicative presentation of the data needed
- The first column of the data file must contain the patient code (e.g. Unique Patient Code). In case there is no patient code in the user's data file, then in the first column he should add a serial number.
- The second column should contain the information about the treatment to which each person has been subjected (e.g. 0: Placebo, 1: Standard treatment, 2: New suggested treatment).
- The following two columns of the file should contain the values of the biomarker of interest to the user, such as: Glycosylated hemoglobin (HbA1c), both at the start of the study and after some time of treatment administration (e.g. after 12 months of administration).
Table 1. Indicative table of input data from the application user
|
Patient Code |
Treatment |
Glycosylated hemoglobin |
Glycosylated hemoglobin |
|
1 |
Placebo |
7.0 |
7.0 |
|
2 |
Placebo |
8.5 |
8.2 |
|
3 |
Placebo |
12.0 |
12.5 |
|
4 |
Standard treatment |
7.2 |
7.0 |
|
5 |
Standard treatment |
9.0 |
8.5 |
|
6 |
Standard treatment |
11.5 |
10.0 |
|
7 |
Recommended treatment |
6.5 |
5.7 |
|
8 |
Recommended treatment |
8.7 |
7.0 |
|
9 |
Recommended treatment |
12.5 |
9.0 |
System Prerequisites:
- Toolbox accepts xlsx or csv files.
- The variable denoting the treatment must not contain missing data.
- The two variables denoting the biomarker levels must not have missing data. If at least one of the two time fields has missing data, then that subject is removed from the analysis.
Output:
After the data has been entered by the user and after a short period for the automated analysis to be completed, a report of the results and the statistical methods used is extracted from the system.
Note: For any clarification you need regarding the content of the use case or any information related to the collection or validity of your data please contact us.
