Askal Ayalew Ali1, Hong Xiao2, Rima Tawk1, Ellen Campbell1, Anastasia Semykina3, Alberto J Montero4, Vakaramoko Diaby1. 1. a College of Pharmacy and Pharmaceutical Sciences , Florida A&M University , Tallahassee , FL , USA. 2. b College of Pharmacy , University of Florida , Gainesville , FL , USA. 3. c Florida State University , Tallahassee , FL , USA. 4. d Cleveland Clinic, Taussig Cancer Institute , Cleveland , OH , USA.
Abstract
BACKGROUND: The selection of the most appropriate treatment combinations requires the balancing of benefits and harms of these treatment options as well as the patients' preferences for the resulting outcomes. OBJECTIVE: This research aimed at estimating and comparing the utility weights between elderly women with early stage hormone receptor positive (HR+) breast cancer receiving a combination of radiotherapy and hormonal therapy after breast conserving surgery (BCS) and those receiving a combination of BCS and hormonal therapy. METHODS: The Surveillance, Epidemiology, and End Results (SEER) linked with Medicare Health Outcomes Survey (MHOS) was used as the data source. Health utility weights were derived from the VR-12 health-related quality of life instrument using a mapping algorithm. Descriptive statistics of the sample were provided. Two sample t-tests were performed to determine potential differences in mean health utility weights between the two groups after propensity score matching. RESULTS: The average age at diagnosis was 72 vs. 76 years for the treated and the untreated groups, respectively. The results showed an inverse relationship between the receipt of radiotherapy and age. Patients who received radiotherapy had, on average, a higher health utility weight (0.70; SD = 0.123) compared with those who did not receive radiotherapy (0.676; SD = 0.130). Only treated patients who had more than two comorbid conditions had significantly higher health utility weights compared with patients who were not treated. CONCLUSIONS: The mean health utility weights estimated for the radiotherapy and no radiotherapy groups can be used to inform a comparative cost-effectiveness analysis of the treatment options. However, the results of this study may not be generalizable to those who are outside a managed care plan because MHOS data is collected on managed care beneficiaries.
BACKGROUND: The selection of the most appropriate treatment combinations requires the balancing of benefits and harms of these treatment options as well as the patients' preferences for the resulting outcomes. OBJECTIVE: This research aimed at estimating and comparing the utility weights between elderly women with early stage hormone receptor positive (HR+) breast cancer receiving a combination of radiotherapy and hormonal therapy after breast conserving surgery (BCS) and those receiving a combination of BCS and hormonal therapy. METHODS: The Surveillance, Epidemiology, and End Results (SEER) linked with Medicare Health Outcomes Survey (MHOS) was used as the data source. Health utility weights were derived from the VR-12 health-related quality of life instrument using a mapping algorithm. Descriptive statistics of the sample were provided. Two sample t-tests were performed to determine potential differences in mean health utility weights between the two groups after propensity score matching. RESULTS: The average age at diagnosis was 72 vs. 76 years for the treated and the untreated groups, respectively. The results showed an inverse relationship between the receipt of radiotherapy and age. Patients who received radiotherapy had, on average, a higher health utility weight (0.70; SD = 0.123) compared with those who did not receive radiotherapy (0.676; SD = 0.130). Only treated patients who had more than two comorbid conditions had significantly higher health utility weights compared with patients who were not treated. CONCLUSIONS: The mean health utility weights estimated for the radiotherapy and no radiotherapy groups can be used to inform a comparative cost-effectiveness analysis of the treatment options. However, the results of this study may not be generalizable to those who are outside a managed care plan because MHOS data is collected on managed care beneficiaries.
Entities:
Keywords:
Breast cancer; comparative effectiveness research; health utility weight; radiotherapy
Authors: K-J Winzer; R Sauer; W Sauerbrei; E Schneller; W Jaeger; M Braun; J Dunst; T Liersch; M Zedelius; K Brunnert; H Guski; C Schmoor; M Schumacher Journal: Eur J Cancer Date: 2004-05 Impact factor: 9.162
Authors: Alfredo J Selim; William Rogers; John A Fleishman; Shirley X Qian; Benjamin G Fincke; James A Rothendler; Lewis E Kazis Journal: Qual Life Res Date: 2008-12-03 Impact factor: 4.147
Authors: Kevin S Hughes; Lauren A Schnaper; Jennifer R Bellon; Constance T Cirrincione; Donald A Berry; Beryl McCormick; Hyman B Muss; Barbara L Smith; Clifford A Hudis; Eric P Winer; William C Wood Journal: J Clin Oncol Date: 2013-05-20 Impact factor: 44.544
Authors: Gamal Rayan; Laura A Dawson; Andrea Bezjak; Anthea Lau; Anthony W Fyles; Qi Long Yi; Pat Merante; Katherine A Vallis Journal: Int J Radiat Oncol Biol Phys Date: 2003-01-01 Impact factor: 7.038
Authors: Michael Pinkawa; Karin Fischedick; Bernd Gagel; Marc D Piroth; Branka Asadpour; Jens Klotz; Holger Borchers; Gerhard Jakse; Michael J Eble Journal: BMC Cancer Date: 2009-08-24 Impact factor: 4.430
Authors: Manraj N Kaur; Jiajun Yan; Anne F Klassen; Justin P David; Dilshan Pieris; Manraj Sharma; Louise Bordeleau; Feng Xie Journal: Med Decis Making Date: 2022-01-18 Impact factor: 2.749