J 2019

Propensity Score Weighting Using Overlap Weights: A New Method Applied to Regorafenib Clinical Data and a Cost-Effectiveness Analysis

MLCOCH, Tomas, Tereza HRNCIAROVA, Jan TUZIL, Jakub ZADAK, Marisca MARIAN et. al.

Basic information

Original name

Propensity Score Weighting Using Overlap Weights: A New Method Applied to Regorafenib Clinical Data and a Cost-Effectiveness Analysis

Authors

MLCOCH, Tomas (203 Czech Republic, guarantor), Tereza HRNCIAROVA (203 Czech Republic), Jan TUZIL (203 Czech Republic), Jakub ZADAK (203 Czech Republic), Marisca MARIAN (756 Switzerland) and Tomáš DOLEŽAL (203 Czech Republic, belonging to the institution)

Edition

Value in health, NEW YORK, ELSEVIER SCIENCE INC, 2019, 1098-3015

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30104 Pharmacology and pharmacy

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 4.748

RIV identification code

RIV/00216224:14110/19:00112595

Organization unit

Faculty of Medicine

UT WoS

000500754600004

Keywords in English

colorectal cancer; cost-effectiveness analysis; overlap weights; propensity score; propensity score weighting via overlap weights; regorafenib

Tags

Tags

International impact, Reviewed
Změněno: 20/1/2020 08:20, Mgr. Tereza Miškechová

Abstract

V originále

Background: In situations of markedly different population characteristics and weak population overlap, inverse propensity score (PS) weights suffer from extreme values. The new propensity score weighting method using overlap weights (PSOW) overcomes this limitation by estimating the overlap population at the point of highest mutual overlap, thus may be preferred to other balancing methods (trimming, target, or inverse weights) in some situations. Objectives: To evaluate the performance of PSOW with regorafenib effectiveness data from previously treated patients with metastatic colorectal cancer based on the Czech national registry data (regorafenib) and a global phase 3 randomized clinical trial (RCT) (placebo). The second goal was to assess the cost-effectiveness of regorafenib versus placebo. Methods: Individual data on progression-free survival (PFS)/overall survival (OS) were balanced via PSOW for age, sex, Eastern Cooperative Oncology Group performance status, number of treatment lines, metastatic colorectal cancer location, KRAS mutation, and time from metastases estimated using logistic regression. The weighted Kaplan-Meier PFS/OS curves were used in a 3-state partitioned survival model. The R code is provided. Results: In comparison with target or inverse PS weights, PSOW showed remarkable performance measured by effective sample size and PS weight distribution or extreme weights despite the weak overlap between the registry and RCT. In the registry or RCT cohort, regorafenib provided better survival compared with the RCT. The new PSOW hazard ratio for OS was 0.53 (RCT: 0.79), which is conservative compared with inverse or target weights with a hazard ratio of 0.44 and 0.27, respectively. Conclusion: This is the first use of PSOW for clinical data and cost-effectiveness analysis. It is promising in cases of weak or small population overlap and makes pharmacoeconomic modeling, in such cases, feasible.