Ignite Creation Date:
2024-05-06 @ 6:05 PM
Last Modification Date:
2024-10-26 @ 2:41 PM
Study NCT ID:
NCT05537558
Status:
UNKNOWN
Last Update Posted:
2022-09-13
First Post:
2022-08-30
Brief Title:
Precision Medicine for the Prediction of Treatment PROMPT Response PROMPT
Sponsor:
University Hospital Muenster
Organization:
University Hospital Muenster
Study Overview
Official Title:
Toward PrecisiOn Medicine for the Prediction of Treatment Response in Major Depressive Disorder Through Stratification of Combined Clinical And-omics Signatures PROMPT
Status:
UNKNOWN
Status Verified Date:
2022-09
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
PROMPT
Brief Summary:
Major depressive disorder MDD is the most common psychiatric disease worldwide with a huge socio-economic impact Pharmacotherapy represents the first-line treatment choice however only about one third of patients respond to the first trial and about 30 are classified as treatment-resistant depression TRD TRD is associated with specific clinical features and geneticgene expression signatures To date single sets of markers have shown limited power in response prediction The aim of this project is the development of a precision medicine algorithm that would help early detection of non-responder patients who might be more prone to later develop TRD
In this phase of the project a naturalistic cohort of 300 MDD patients will be recruited The data collected will be used to assess in real-world conditions the capability of an innovative algorithm integrating clinical omics and gender data of other 300 patients con MDD to predict the treatment outcomes This project represents a proof-of-concept study The obtained results will provide information about the feasibility and usefulness of the proposed approach with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians enabling a better prevention and management of MDD resistance
In this phase of the project a naturalistic cohort of 300 MDD patients will be recruited The data collected will be used to assess in real-world conditions the capability of an innovative algorithm integrating clinical omics and gender data of other 300 patients con MDD to predict the treatment outcomes This project represents a proof-of-concept study The obtained results will provide information about the feasibility and usefulness of the proposed approach with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians enabling a better prevention and management of MDD resistance
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None