Trajectories and Predictors of Health-related Quality of Life in Older Breast Cancer Survivors

Trajectories and Predictors of Health-related Quality of Life in Older Breast Cancer Survivors
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Book Synopsis Trajectories and Predictors of Health-related Quality of Life in Older Breast Cancer Survivors by : Sushantti Rupesh

Download or read book Trajectories and Predictors of Health-related Quality of Life in Older Breast Cancer Survivors written by Sushantti Rupesh and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this research study is to explore trajectories of health-related quality of life (HRQoL) in older breast cancer survivors, along with their predictors. HRQoL is important because patients who show severe symptoms may wish to consider therapies or treatment plans that lead to better HRQoL. Older people are more vulnerable to low HRQoL scores since old age is associated with deteriorating health, multiple comorbidities, and low-socioeconomic status. To examine the HRQoL trajectory among older women with breast cancer, we used the data queried from the Surveillance, Epidemiology and End Results Medicare Health Outcomes Survey database. A total of 1,089 older ([greater than or equal to] 65 years) women who were diagnosed with breast cancer in 1998-2012 and participated in the survey before and after the cancer diagnosis were identified. HRQoL was measured using SF-36/VR-12 questionnaire and summarized as Physical Component Summary (PCS) Score and Mental Component Summary (MCS) Score. Latent Class Growth Mixture Modeling was conducted to identify distinct groups of women with a similar trajectory of HRQoL. The results showed that there were three latent classes of HRQoL trajectories for PCS: the high-declining (46.5% of the sample), mid-declining (36.0%), and the low-improving (17.5%). Two latent classes of HRQoL trajectories were identified for MCS: high-stable (76.5%) and low-declining (23.5%). The results showed that age at diagnosis, BMI, level of education, geographic region, tumor grade, tumor size, and number of comorbidities were some of the major predictors of health-related quality of life. These predictors were further explored using multinomial logistic regression analysis which identified number of comorbidities as the most significant predictor for HRQoL-PCS scores and level of education as the most significant predictor for HRQoL-MCS scores. This suggests that future research needs to be conducted, identifying the most common comorbidities in older breast cancer survivors to develop interventions that better the physical HRQoL in patients, in addition to the development of mental HRQoL interventions for patients that are less educated.


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