Wang, Lu
(2013)
Post-transplant survival in pediatric liver transplant patients with biliary atresia: a comparison of competing risk models.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
Liver transplantation is the ultimate treatment for patients with end-stage liver diseases. Among the primary diagnosis of pediatric liver transplant candidates, biliary atresia is the most common cause of liver failure. In this study, we aimed to identify factors associated with marginal posttransplant survival among pediatric liver transplant recipients with primary diagnosis of biliary atresia. The main event of interest was time from transplant to death. Retransplantation was the competing event and alive at the study cutoff was indepenent censoring. We analyzed data using five different competing risks regression models and compared the results. These models include Cox proportional hazards (PH) model treating competing events as censoring, Cox PH model treating competing events as the main event, Fine and Gray proportional subdistribution hazards model, random signs censoring regression model, and the joint model of time to the main event and time to the competing event. The assumptions of each method are described in this thesis. Joint model was used as the gold standard in our analysis and the results obtained from other methods were compared to the gold standard. Our analysis showed that Cox PH model treating competing event as censoring gave similar results as those obtained from the joint model. On ventilator or not, allocation type, split or nonsplit organ, presence of ascites, and presence of portal vein thrombosis at treatment were the risk factors for marginal posttransplant survival among pediatric patients with biliary atresia.
Public health significance: Risk factors of marginal posttransplant survival can be identified only if a regression model with appropriate assumption of the dependence structure between the event of interest and the competing events is used. We compare the results from three commonly used and two newly developed survival regression models for data with competing risks. The underlying assumptions of the dependence of the events and the pros and cons of these models are described and discussed. Our findings will help a researcher to appropriately choose a regression model to identify risk factors when competing risks are present in the data.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
27 September 2013 |
| Date Type: |
Publication |
| Defense Date: |
12 June 2013 |
| Approval Date: |
27 September 2013 |
| Submission Date: |
21 June 2013 |
| Access Restriction: |
1 year -- Restrict access to University of Pittsburgh for a period of 1 year. |
| Number of Pages: |
35 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Biostatistics |
| Degree: |
MS - Master of Science |
| Thesis Type: |
Master's Thesis |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Competing risks, Liver transplant, Biliary atresia, Survival analysis |
| Date Deposited: |
27 Sep 2013 16:15 |
| Last Modified: |
15 Nov 2016 14:13 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/19079 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}