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http://dx.doi.org/10.1038/bjc.2013.407

has been cited by the following article:

• TITLE: Patient-Reported Outcomes in Prostate Cancer: Prospective Changes Analysis for Prognosis Prediction

  AUTHORS: Teresa Sequeira, Pedro Lopes Ferreira, Joana Teixeira, Isabel Peres, Jorge Oliveira, Augusta Silveira

  KEYWORDS: Oncology, Prostate Cancer, Health Related Quality of Life, Patient-Reported Outcomes, Prognosis Prediction

  JOURNAL NAME: Journal of Cancer Therapy, Vol.6 No.15, December 16, 2015

  ABSTRACT: Prostate cancer is affecting a higher proportion of male population. Health Related Quality of Life assessment can guide the development of an interdisciplinary and patient-centered care intervention. This study is aimed to assess Health Related Quality of Life in prostate cancer patients. Relationships between socio-demographic, clinical characteristics and patient-reported outcomes have been considered. Consecutive outpatients with prostate cancer, admitted at the Urology Clinic of the Instituto Português de Oncologia do Porto, were studied (n = 300). Health Related Quality of Life was assessed as part of the routine practice. The European Organisation for Research and Treatment of Cancer general questionnaire, QLQ-C30, and its specific module for prostate cancer patients, QLQ-PR25, were used. Evolution along time (elapsed since diagnosis, and up to 5 years) was considered in order to search for a prognosis prediction in prostate cancer patients. This study confirms the feasibility of a systematic Health Related Quality of Life assessment. Global Health Related Quality of Life was found to be higher 6 months after diagnosis, decreasing then until the second year after diagnosis and improving thereafter. A peak with better scores was identified at the fifth year after diagnosis. Social and physical dimensions revealed a similar pattern. Clinical significance was found 6 months and 5 years after diagnosis. The prospective analysis of Health Related Quality of Life changes is able to explore the patients’ outcomes in order to find patterns and relationships for prognosis prediction along the disease course. Such approach might promote patient confidence and thus a better cancer experience.