Association between changes in quality of life and mortality in hemodialysis patients: results from the DOPPS.
Cross-sectional health-related quality of life (HR-QOL) measures are associated with mortality in hemodialysis (HD) patients. The impact of changes in HR-QOL on outcomes remains unclear. We describe the association of prior changes in HR-QOL with subsequent mortality among HD patients.



A total of 13 784 patients in the Dialysis Outcomes and Practice Patterns Study had more than one measurement of HR-QOL. The impact of changes between two measurements of the physical (PCS) and mental (MCS) component summary scores of the SF-12 on mortality was estimated with Cox regression.



Mean age was 62 years (standard deviation: 14 years); 59% were male and 32% diabetic. Median time between HR-QOL measurements was 12 months [interquartile range (IQR): 11, 14]. Median initial PCS and MCS scores were 37.5 (IQR: 29.4, 46.2) and 46.4 (IQR: 37.2, 54.9); median changes in PCS and MCS scores were -0.2 (IQR: -5.5, 4.7) and -0.1 (IQR: -6.8, 5.9), respectively. The adjusted hazard ratio (HR) for a 5-point decline in HR-QOL score was 1.09 [95% confidence interval (CI): 1.06-1.12] for PCS and 1.05 (95% CI: 1.03-1.08) for MCS. Adjusting for the second QOL score, the change was not associated with mortality: HR = 1.01 (95% CI: 0.98-1.05) for delta PCS and 1.01 (95% CI: 0.98-1.03) for delta MCS. Categorizing the first and second scores as predictors, only the second PCS or MCS score was associated with mortality.



In our study, only the most recent HR-QOL score was associated with mortality. Hence, the predictive power of a measurement of HR-QOL is not affected by changes in HR-QOL prior to that measurement; more frequent HR-QOL measurements are needed to improve the prediction of outcomes in HD. Further studies are needed to determine the optimal frequency and appropriate instrument to be used for serial measurements.
Division of Nephrology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada.
Jeffrey
J
Perl
Arbor Research Collaborative for Health, Ann Arbor, MI, USA.
Angelo
A
Karaboyas
Arbor Research Collaborative for Health, Ann Arbor, MI, USA.|Departments of Epidemiology and Environmental Health Sciences, School of Public Health, and Department of Urology, Medical School, University of Michigan, Ann Arbor, MI, USA.
Hal
H
Morgenstern
Department of Biostatistics and Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA.
Ananda
A
Sen
Heart of England NHS Foundation Trust, Birmingham, UK.
Hugh C
HC
Rayner
University Hospital, Ghent, Belgium.
Raymond C
RC
Vanholder
Centre Hospitalier Universitaire de Bordeaux and Université de Bordeaux, Bordeaux, France.
Christian
C
Combe
Department of Innovative Research and Education for Clinicians and Trainees, Fukushima Medical University Hospital, Fukushima, Japan.|Division of Nephrology, Showa University Fujigaoka Hospital, Yokohama, Japan.
Takeshi
T
Hasegawa
Hospital of St Raphael, Yale University, New Haven, CT, USA.
Fredric O
FO
Finkelstein
Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, BA, Brazil.
Antonio A
AA
Lopes
Arbor Research Collaborative for Health, Ann Arbor, MI, USA.|Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Bruce M
BM
Robinson
Arbor Research Collaborative for Health, Ann Arbor, MI, USA.
Ronald L
RL
Pisoni
Arbor Research Collaborative for Health, Ann Arbor, MI, USA.|Vanderbilt University, Medical Center, Nashville, TN, USA.
Francesca
F
Tentori
D000368:Aged; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007676:Kidney Failure, Chronic / Q000503:physiopathology / Q000523:psychology / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D009026:Mortality; D016016:Proportional Hazards Models; D011446:Prospective Studies; D011788:Quality of Life; D006435:Renal Dialysis
Dialysis Outcomes Practice Patterns Study; hemodialysis; quality of life; survival