Patient-Proxy Agreement Regarding Health-Related Quality of Life in Survivors with Lymphoma: A Propensity-Score Matching Analysis.
Richard Huan XuDong DongPublished in: Cancers (2022)
Objective: To assess the difference between lymphoma survivors' self- and proxy-reported health-related quality of life (HRQoL) and its association with socioeconomic and health statuses. Methods: The data used in this study were obtained from a nationwide cross-sectional online survey in 2019. Information about participants' demographics, health status and HRQoL were collected. The propensity-score matching (PSM) method was used to control the effect of potential confounders on selection bias. A chi-squared test, one-way analysis of variance, and multiple linear regression models were used to assess the relationship between HRQoL and response type adjusted to respondents' background characteristics. Results: Out of the total 4400 participants, data of 2350 ones were elicited for analysis after PSM process. Patients' self-reported outcomes indicated a slightly better physical, role and emotional functioning than proxy-reported outcomes. Regression analysis showed that patients, who were older, unemployed, and who received surgery, were more likely to report a lower HRQoL. Further analysis demonstrated that proxy-reported patients who had completed treatment were more likely to report a higher HRQoL than those who were being treated. Conclusions: Our study demonstrates that the agreement between self- and proxy-reported HRQoL is low in patients with lymphoma and the heterogeneities of HRQoL among patients with different types of aggressive NHL (Non-Hodgkin's lymphoma) is large. Differences in self- and proxy-reported HRQoL should be considered by oncologists when selecting and deciding the optimal care plan for lymphoma survivors.
Keyphrases
- cross sectional
- diffuse large b cell lymphoma
- young adults
- mental health
- minimally invasive
- physical activity
- newly diagnosed
- electronic health record
- big data
- health information
- risk assessment
- end stage renal disease
- social media
- machine learning
- case report
- coronary artery bypass
- chronic pain
- peritoneal dialysis
- smoking cessation
- artificial intelligence
- pain management