Activity Number:
|
364
- Contributed Poster Presentations: Section on Medical Devices and Diagnostics
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, July 31, 2018 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Medical Devices and Diagnostics
|
Abstract #328589
|
|
Title:
|
Using Stratified Propensity Score Matching Approach to Adjust Risk Assessment for Breast Reconstruction Patients
|
Author(s):
|
Jun Liu* and Liang Li and Summer Elizabeth Summer and Victor Joseph Hassid and Jesse Creed Selber and Charles Butler and Patrick Bryan Garvey and Donald Baumann
|
Companies:
|
UT MDACC and UT MD Anderson Cancer Center and UT MDACC and UT MDACC and UT MDACC and UT MDACC and UT MDACC and UT MDACC
|
Keywords:
|
propensity score;
stratified;
observational study;
breast cancer;
breast reconstruction
|
Abstract:
|
Propensity score matching is an effective tool to balance covariates between treatment groups in non-randomized studies. Although propensity score matching is a powerful tool to balance covariates on experiment units, unbalanced subunit covariates might still confound the treatment and outcome associations. A stratified propensity score matching method was implemented in a breast reconstruction study to balance both experiment and subunit level covariates. Patients who received new (hADM-RTU) or standard (hADM-FD) material in immediate tissue expander breast reconstructions were compared on the surgical outcomes. More than patient characteristics, unbalanced surgery and intraoperative variables on each breast might induce bias on conclusion. We developed a stratified propensity score model to match unilateral and bilateral patients separately and the outcomes from the pooled matched samples are compared. The balance of covariates before and after propensity score matching were compared between stratified patient-level propensity score-matching method and naïve breast-level propensity score matching method.
|
Authors who are presenting talks have a * after their name.