Effectiveness of one treatment in terms of the change of a biomarker between two time points
In the context of prospective studies, interventional or non-interventional, health professionals are asked to evaluate the effectiveness of a therapeutic treatment in terms of the change in the values of basic biomarkers, between two points in time (e.g. the start of the study and after a certain period of treatment administration).
Examples: In the context of a non-interventional prospective study, a research group wishes to evaluate the effectiveness of statin therapy in reducing total cholesterol levels in patients with high cardiovascular risk after 6 months of treatment. For this reason, their aim is to compare the mean total cholesterol levels recorded at the start of the study, with the corresponding levels recorded after 6 months of statin treatment. The same research question is also found in interventional studies, where researchers give their patients a specific medication for a period of time, and after the end of this period they wish to know the effectiveness of this administration.
The problem
In the context of prospective studies, interventional or non-interventional, healthcare professionals are asked to evaluate the effectiveness of a therapeutic treatment in terms of the change in the values of basic biomarkers, between two points in time (e.g. the start of the study and after a certain period of treatment administration). For example, in the context of a non-interventional prospective study, a research group wishes to evaluate the effectiveness of statin therapy in reducing total cholesterol levels in patients with high cardiovascular risk after 6 months of treatment. For this reason, their aim is to compare the mean total cholesterol levels recorded at the start of the study, with the corresponding levels recorded after 6 months of statin treatment. The same research question is also found in interventional studies, where researchers give their patients a specific medication for a period of time, and after the end of this period they wish to know the effectiveness of this administration.
The purpose
Indication of the effectiveness of a specific therapeutic treatment in terms of the change in the levels of key biomarkers, after a specific period of treatment.
The solution
By using the appropriate statistical methodology (Paired samples t-test, Wilcoxon signed rank test) and after the test of the assumptions, a comparison will be made between the levels of the biomarker at the beginning of the study with the corresponding levels after a specific period of time, in order to allow the user to evaluate the effectiveness of the treatment in which he is interested.
The benefit
Healthcare professionals will be able to easily, quickly and without prior statistical knowledge, evaluate the effectiveness of a treatment they are interested in, in terms of the change in the levels of various biomarkers.
Indicative presentation of the data needed
- The first column of the data file must contain the code of the patients receiving the treatment the user is interested in (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 values of the biomarker of interest to the user at the 1st time point.
- The third column should contain the values of the biomarker of interest to the user at the 2nd time point.
Table 1. Indicative table of input data from the application user
|
Patient Code |
Total cholesterol |
Total cholesterol |
|
1 |
200 |
180 |
|
2 |
210 |
190 |
|
3 |
240 |
200 |
|
4 |
220 |
190 |
|
5 |
230 |
210 |
|
6 |
200 |
170 |
System Prerequisites:
- Toolbox accepts xlsx or csv files.
- The two variables denoting the biomarker levels must not have missing data. If at least one of the two time points has missing data, then that subject is removed from the analysis.
Output:
After the data input 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.
