Determinants of self-reported functional status (EPIC-26) in prostate cancer patients prior to treatment

WORLD JOURNAL OF UROLOGY(2020)

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摘要
Purpose The self-reported functional status (sr-FS) of prostate cancer (PCa) patients varies substantially between patients and health-care providers before treatment. Information about this issue is important for evaluating comparisons between health-care providers and to assist in treatment decision-making. There have been few reports on correlates of pretherapeutic sr-FS. The objective of the article, therefore, is to describe clinical and sociodemographic correlates of pretherapeutic sr-FS, based on a subset of the TrueNTH Global Registry, a prospective cohort study. Methods A total of 3094 PCa patients receiving local treatment in 44 PCa centers in Germany were recruited between July 2016 and April 2018. Multilevel regression models were applied to predict five pretherapeutic sr-FS (EPIC-26) scores based on clinical characteristics (standard set suggested by the International Consortium for Health Outcomes Measurement), sociodemographic characteristics, and center characteristics. Results Impaired pretherapeutic sr-FS tended to be associated with lower educational level and poorer disease characteristics—except for “urinary incontinence” which was only associated with age. Notably, age was a risk factor (“urinary incontinence,” “urinary irritative/obstructive,” “sexual”) as well as a protective factor (“hormonal”) for pretherapeutic sr-FS. Pretherapeutic sr-FS varies little across centers. Conclusions Pretherapeutic sr-FS varies by clinical patient characteristics and age as well as by socioeconomic status. The findings point out the benefit of collecting and considering socioeconomic information in addition to clinical and demographic patient characteristics for treatment decision-making and fair comparisons between health-care providers.
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关键词
Health-service research, Prostate neoplasms, Patient-reported outcome measures, Functional status, Case-mix adjustment, Multilevel analysis
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