Ignite Creation Date:
2024-07-17 @ 11:37 AM
Last Modification Date:
2024-10-26 @ 3:33 PM
Study NCT ID:
NCT06483919
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-07-03
First Post:
2024-06-26
Brief Title:
The Predictive Value of Proteome Profiling for Brain Metastasis in Limited-Stage Small-Cell Lung Cancer
Sponsor:
Jinming Yu
Organization:
Shandong Cancer Hospital and Institute
Study Overview
Official Title:
The Predictive Value of Proteome Profiling for Brain Metastasis in Limited-Stage Small-Cell Lung Cancer
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-06
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:
None
Brief Summary:
This study aims to evaluate the predictive value of proteome profiling for brain metastasis in limited-stage small-cell lung cancer
Detailed Description:
Small-cell lung cancer SCLC constitutes approximately 15 of all lung cancer cases and is characterized by a highly aggressive disease course and poor prognosis The brain is the most common metastatic site of SCLC and it is also an important cause of high mortality More than 20 of SCLC patients have developed brain metastasis BM at the first diagnosis Prophylactic cranial irradiation PCI as an essential part of the treatment of limited-stage small-cell lung cancer LS-SCLC inevitably leads to neurotoxicity Therefore there is an urgent need for a convenient and effective prediction model to realize the early prediction of SCLC brain metastasis Patients at high risk of brain metastases were treated with individualized PCI
In the current study the investigators have analyzed the proteome profiling using Data-independent Acquisition mass spectrometry DIA-MS method in formalin-fixed paraffin-embedded FFPE tissues from patients with limited-stage small-cell lung cancer The prognostic biomarkers were developed based on machine learning in the non-PCI group Patients in the non-PCI group were classified into modeling cohort and external validation cohort Furthermore the prognostic value of the candidate biomarkers be evaluated in a prospective cohort Based on the brain metastasis model patients were divided into high- and low-risk groups The benefit value of PCI was analyzed in high-risk and low-risk groups
In the current study the investigators have analyzed the proteome profiling using Data-independent Acquisition mass spectrometry DIA-MS method in formalin-fixed paraffin-embedded FFPE tissues from patients with limited-stage small-cell lung cancer The prognostic biomarkers were developed based on machine learning in the non-PCI group Patients in the non-PCI group were classified into modeling cohort and external validation cohort Furthermore the prognostic value of the candidate biomarkers be evaluated in a prospective cohort Based on the brain metastasis model patients were divided into high- and low-risk groups The benefit value of PCI was analyzed in high-risk and low-risk groups
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