Ignite Creation Date:
2024-10-26 @ 3:37 PM
Last Modification Date:
2024-10-26 @ 3:37 PM
Study NCT ID:
NCT06550739
Status:
COMPLETED
Last Update Posted:
None
First Post:
2024-08-07
Brief Title:
Comprehensive Prognostic Model The Study Introduces a Novel Prognostic Model That Incorporates a Wide Range of Clinical and Laboratory Variables Providing a More Holistic Approach to Predicting Overall Survival in HCC Patients
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Development and Validation of a New Prognostic System for Patients With Hepatocellular Carcinoma A Cohort Study in China
Status:
COMPLETED
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Background Hepatocellular carcinoma HCC is a significant health problem in China with high incidence and mortality rates This study aimed to identify the prognostic factors of elderly HCC patients in southwest China and construct a new prognostic model for predicting overall survival OS
Methods This retrospective cohort study collected clinical data from 958 patients with liver cancer on January 1 2019 and December 12 2020 The Cox regression model was used to test the significance of all available variables as prognostic factors of OS Independent prognostic factors were identified based on multivariable analysis to model nomograms The concordance index C-index the area under the receiver operating characteristic AUC the Time-dependent C-index the Time-dependent AUC the calibration curve and decision curve analysis DCA were measured to assess the model performance of the nomogram
Conclusions The comprehensive risk prediction model for OS in HCC patients developed through this retrospective cohort study offers a promising avenue for improving clinical outcomes and patient care
Methods This retrospective cohort study collected clinical data from 958 patients with liver cancer on January 1 2019 and December 12 2020 The Cox regression model was used to test the significance of all available variables as prognostic factors of OS Independent prognostic factors were identified based on multivariable analysis to model nomograms The concordance index C-index the area under the receiver operating characteristic AUC the Time-dependent C-index the Time-dependent AUC the calibration curve and decision curve analysis DCA were measured to assess the model performance of the nomogram
Conclusions The comprehensive risk prediction model for OS in HCC patients developed through this retrospective cohort study offers a promising avenue for improving clinical outcomes and patient care
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None