Ignite Creation Date:
2025-12-24 @ 4:46 PM
Ignite Modification Date:
2025-12-30 @ 1:13 AM
Study NCT ID:
NCT06043050
Status:
COMPLETED
Last Update Posted:
2025-09-09
First Post:
2023-08-17
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
PRedicting OutcomeS in Preterm nEonates With thromboCyTopenia
Sponsor:
Leiden University Medical Center
Organization:
Study Overview
Official Title:
Sequential Predictions Under Repeated Interventions: Estimating the Risk of Major Bleeding or Death With and Without Prophylactic Platelet Transfusion in Thrombocytopenic Neonates.
Status:
COMPLETED
Status Verified Date:
2024-08
Last Known Status:
None
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:
PROSPECT
Brief Summary:
Preterm neonates often receive platelet transfusions when their platelet count is low to prevent bleeding. However, it is currently unclear which infants benefit from such transfusions. A recent randomized controlled trial (PlaNeT-2/MATISSE trial) showed that the higher platelet count threshold for transfusion was associated with a higher risk of major bleeding or death. Current transfusion protocols are based only on platelet count thresholds. However, neonates with similar platelet counts may have different bleeding risks due to varying clinical conditions. There is an important unmet medical need to identify which neonates with low platelet counts (i.e., severe thrombocytopenia) will benefit from a transfusion. Ideally, clinicians would be able to repeatedly predict a neonate's risk of major bleeding or death with and without giving a platelet transfusion, taking into account the neonate's clinical condition at that particular time. Obtaining personalized risk estimates under specific treatment strategies, with updated predictions at each new treatment decision moment, is called 'sequential prediction under interventions'. The investigators set up an international multicenter observational cohort study to develop a model to predict major bleeding or death with and without platelet transfusion at any time point during the first week after the onset of severe thrombocytopenia. This model is designed to support platelet transfusion decisions in the NICU and may help clinicians balance the benefits and harms of platelet transfusion based on updated characteristics of the neonate at the time of prediction.
Detailed Description:
Main objective: To develop a sequential interventional prediction model to support transfusion decisions by predicting the risk of major bleeding or death with and without giving a platelet transfusion to neonates with severe thrombocytopenia (i.e., platelet count below 50x10\^9/L), conditional on their characteristics present at the moment of prediction.
Study design: Multicenter international observational cohort study.
Study population: Neonates with a gestational age below 34 weeks and at least one platelet count below 50x10\^9/L, admitted to a neonatal intensive care unit (NICU) between January 1st 2017 and January 1st 2022.
Main study endpoint: Major bleeding or mortality during NICU admission
Assessments: Only routine care data will be collected. This includes platelet counts and transfusions, cranial (head) ultrasounds and other information on bleeding, and multiple clinical variables.
Statistical analyses: Development of a sequential prediction model under interventions using the cloning-censoring-weighting approach with inverse probability weighting. Validation of the model in a separate cohort of preterm neonates with severe thrombocytopenia.
Study design: Multicenter international observational cohort study.
Study population: Neonates with a gestational age below 34 weeks and at least one platelet count below 50x10\^9/L, admitted to a neonatal intensive care unit (NICU) between January 1st 2017 and January 1st 2022.
Main study endpoint: Major bleeding or mortality during NICU admission
Assessments: Only routine care data will be collected. This includes platelet counts and transfusions, cranial (head) ultrasounds and other information on bleeding, and multiple clinical variables.
Statistical analyses: Development of a sequential prediction model under interventions using the cloning-censoring-weighting approach with inverse probability weighting. Validation of the model in a separate cohort of preterm neonates with severe thrombocytopenia.
Study Oversight
Has Oversight DMC:
False
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?:
False
Is an FDA AA801 Violation?: