аЯрЁБс>ўџ SUўџџџRџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџьЅСq П=Gbjbjt+t+ -bAA=Bџџџџџџ]2222222FFFFF R,Ff іŠ(ВВВВВВВ       $\ єP Д9 -2ВВВВВ9 ž22ВВŠžžžВъ2В2В FF2222В žž  ѓ 22 В~ Ач]гХFFœ  KDQOL Publications – abstracts (in alphabetical order by last name of first author) Qual Life Res. 1994 Oct;3(5):329-38. Development of the kidney disease quality of life (KDQOL) instrument. Hays RD, Kallich JD, Mapes DL, Coons SJ, Carter WB. RAND, Social Policy Department, Santa Monica, CA 90407-2138. This paper describes the Kidney Disease Quality of Life (KDQOL) Instrument (dialysis version), a self-report measure that includes a 36-item health survey as the generic core, supplemented with multi-item scales targeted at particular concerns of individuals with kidney disease and on dialysis (symptom/problems, effects of kidney disease on daily life, burden of kidney disease, cognitive function, work status, sexual function, quality of social interaction, sleep). Also included were multi-item measures of social support, dialysis staff encouragement and patient satisfaction, and a single-item overall rating of health. The KDQOL was administered to 165 individuals with kidney disease (52% female; 48% male; 47% White; 27% African-American; 11% Hispanic; 8% Asian; 4% Native American; and 3% other ethnicities), sampled from nine different outpatient dialysis centres located in Southern California, the Northwest, and the Midwest. The average age of the sample was 53 years (range from 22 to 87), and 10% were 75 years or older. Internal consistency reliability estimates for the 19 multi-item scales exceeded 0.75 for every measure except one. The mean scores for individuals in this sample on the 36-item health scales were lower than the general population by one-quarter (emotional well-being) to a full standard deviation (physical function, role limitations due to physical health, general health), but similar to scores for dialysis patients in other studies. Correlations of the KDQOL scales with number of hospital days in the last 6 months were statistically significant (p < 0.05) for 14 of the 19 scales and number of medications currently being taken for nine of the scales. Results of this study provide support for the reliability and validity of the KDQOL. Am J Kidney Dis 2003 Mar;41(3):605-15 Health-related quality of life and associated outcomes among hemodialysis patients of different ethnicities in the United States: the Dialysis Outcomes and Practice Patterns Study (DOPPS). Lopes AA, Bragg-Gresham JL, Satayathum S, McCullough K, Pifer T, Goodkin DA, Mapes DL, Young EW, Wolfe RA, Held PJ, Port FK; Worldwide Dialysis Outcomes and Practice Patterns Study Committee. Department of Medicine, Federal University of Bahia, Brazil. BACKGROUND: In the United States, an association between mortality risk and ethnicity has been observed among hemodialysis patients. This study was developed to assess whether health-related quality of life (HRQOL) scores also vary among patients of different ethnic backgrounds. Associations between HRQOL and adverse dialysis outcomes (ie, death and hospitalization) also were assessed for all patients and by ethnicity. METHODS: Data are from the Dialysis Outcomes and Practice Patterns Study for 6,151 hemodialysis patients treated in 148 US dialysis facilities who filled out the Kidney Disease Quality of Life Short Form. We determined scores for three components of HRQOL: Physical Component Summary (PCS), Mental Component Summary (MCS), and Kidney Disease Component Summary (KDCS). Patients were classified by ethnicity as Hispanic and five non-Hispanic categories: white, African American, Asian, Native American, and other. Multiple linear regression models were used to estimate differences in HRQOL scores among ethnic groups, using whites as the referent category. Cox regression models were used for associations between HRQOL and outcomes. Regression models were adjusted for sociodemographic variables, delivered dialysis dose (equilibrated Kt/V), body mass index, years on dialysis therapy, and several laboratory/comorbidity variables. RESULTS: Compared with whites, African Americans showed higher HRQOL scores for all three components (MCS, PCS, and KDCS). Asians had higher adjusted PCS scores than whites, but did not differ for MCS or KDCS scores. Compared with whites, Hispanic patients had significantly higher PCS scores and lower MCS and KDCS scores. Native Americans showed significantly lower adjusted MCS scores than whites. The three major components of HRQOL were significantly associated with death and hospitalization for the entire pooled population, independent of ethnicity. CONCLUSION: The data indicate important differences in HRQOL among patients of different ethnic groups in the United States. Furthermore, HRQOL scores predict death and hospitalization among these patients. Copyright 2003 by the National Kidney Foundation, Inc. Am J Kidney Dis. 2004 Nov;44(5 Suppl 3):54-60.  HYPERLINK "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Display&dopt=pubmed_pubmed&from_uid=15486875" Related Articles,  HYPERLINK "http://www2.us.elsevierhealth.com/scripts/om.dll/serve?retrieve=/pii/S0272638604011060&nav=full" Links Health-related quality of life in the Dialysis Outcomes and Practice Patterns Study (DOPPS). Mapes DL, Bragg-Gresham JL, Bommer J, Fukuhara S, McKevitt P, Wikstrom B, Lopes AA. University Renal Research and Education Association, Ann Arbor, MI 48103, USA. dopps@urrea.org BACKGROUND: Health-related quality of life (HRQOL), a validated system of measuring patients' physical, mental, and social well-being, can be of particular use in populations with chronic conditions, such as end-stage renal disease (ESRD). METHODS: The Dialysis Outcomes and Practice Patterns Study (DOPPS) has used the Kidney Disease Quality of Life Short Form (KDQOL-SF) to measure ESRD patients' self-assessment of functioning and well-being, as measured by 3 component scores: physical component summary (PCS, 4 subscales), mental component summary (4 subscales), and kidney disease component summary (11 subscales). Several DOPPS studies examined HRQOL's associations with mortality and hospitalization by country, ethnicity (United States only), and in comparison with serum albumin levels; international variations in HRQOL of ESRD patients were also evaluated. RESULTS: Lower scores for all 3 summary scores were strongly associated with higher risk of death and hospitalization; these measures, especially PCS, may better identify patients at risk for death and hospitalization than serum albumin level. Japanese patients reported a greater burden of kidney disease but higher physical functioning than patients in Europe or the United States; many other significant regional differences in HRQOL were found. In the United States, all summary scores were significantly associated with mortality risk, regardless of ethnicity. Compared with whites, blacks had higher scores for all 3 summary scores, Asians and Hispanics had higher PCS scores, and Native Americans had lower mental component summary scores. CONCLUSION: Among ESRD patients, HRQOL displays an important predictive power for adverse events. Identifying effective interventions to improve the HRQOL of patients with ESRD should be viewed as a valued health care goal. Health-related quality of life as a predictor of mortality and hospitalization: the Dialysis Outcomes and Practice Patterns Study (DOPPS). Mapes DL, Lopes AA, Satayathum S, McCullough KP, Goodkin DA, Locatelli F, Fukuhara S, Young EW, Kurokawa K, Saito A, Bommer J, Wolfe RA, Held PJ, Port FK. Amgen, Inc., Thousand Oaks, California, USA. Kidney Int. 2003 Jul;64(1):339-49 BACKGROUND: We investigated whether indicators of health-related quality of life (HRQOL) may predict the risk of death and hospitalization among hemodialysis patients treated in seven countries, taking into account serum albumin concentration and several other risk factors for death and hospitalization. We also compared HRQOL measures with serum albumin regarding their power to predict outcomes. METHODS: We analyzed data from the Dialysis Outcomes and Practice Patterns Study (DOPPS), an international, prospective, observational study of randomly selected hemodialysis patients in the United States (148 facilities), five European countries (101 facilities), and Japan (65 facilities). The total sample size was composed of 17,236 patients. Using the Kidney Disease Quality of Life Short Form (KDQOL-SFTM), we determined scores for three components of HRQOL: (1) physical component summary (PCS), (2) mental component summary (MCS), and (3) kidney disease component summary (KDCS). Complete responses on HRQOL measures were obtained from 10,030 patients. Cox models were used to assess associations between HRQOL and the risk of death and hospitalization, adjusted for multiple sociodemographic variables, comorbidities, and laboratory factors. RESULTS: For patients in the lowest quintile of PCS, the adjusted risk (RR) of death was 93% higher (RR = 1.93, P < 0.001) and the risk of hospitalization was 56% higher (RR = 1.56, P < 0.001) than it was for patients in the highest quintile level. The adjusted relative risk values of mortality per 10-point lower HRQOL score were 1.13 for MCS, 1.25 for PCS, and 1.11 for KDCS. The corresponding adjusted values for RR for first hospitalization were 1.06 for MCS, 1.15 for PCS, and 1.07 for KDCS. Each RR differed significantly from 1 (P < 0.001). For 1 g/dL lower serum albumin concentration, the RR of death adjusted for PCS, MCS, and KDCS and the other covariates was 1.17 (P < 0.01). Albumin was not significantly associated with hospitalization (RR = 1.03, P> 0.5). CONCLUSION: Lower scores for the three major components of HRQOL were strongly associated with higher risk of death and hospitalization in hemodialysis patients, independent of a series of demographic and comorbid factors. A 10-point lower PCS score was associated with higher elevation in the adjusted mortality risk, as was a 1 g/dL lower serum albumin level. More research is needed to assess whether interventions to improve quality of life lower these risks among hemodialysis patients. American Society of Nephrology, Miami Beach, FL, November 5-8,1999 [A1261] Quality of Life Predicts Mortality and Hospitalization for Hemodialysis (HD) Patients in the US and Europe. D.L. Mapes, K.P. McCullough, D. Meredith, F. Locatelli, F. Valderrabano, P.J. Held. Amgen, Thousand Oaks, CA; URREA, Ann Arbor, MI; Lecco Hospital Lecco, Italy; Hospital Universitario Gregorio Maranon, Madrid, Spain. Friday, November 5,1999, 9:30 AM, Halls B and C Health-related quality of life (HRQOL) instruments are an increasingly common outcomes research tool and HRQOL scores have been reported to be inversely correlated with mortality and hospitalization risk. However, previous analyses have been limited to mortality and to retrospective data analyses and limited adjustment for other risk factors (e.g. comorbidity). The Dialysis Outcomes and Practice Patterns Study is a prospective observational study including a nationally representative sample of 161dialysis facilities in the US and 100 facilities in Europe (France, Germany, Italy, Spain and UK) with data on 4,600 patients (6,600 patient years) in the US and 2,600 patients and 800 patient years in Europe. the KDQOL-SF TM was administered at start and the relative risks of death and hospitalization as functions of QOL indicators were estimated by proportional hazards (stratified by DM), adjusting for demographic factors (DF), 14 comorbid conditions (CC) and baseline serum albumin. Three summary measures of QoL, namely the Physical Component Score (PCS), Mental Component Score (MCS) and the mean Kidney Disease Burden (KDB) all predict hospitalization and mortality independently of other measures. A 5 point higher (considered a clinically meaningful improvement) PCS, MCS, or mean KDB score was associated with 3-11% reduction in risk of hospitalization and 9-23% reduction in mortality. There were no significant differences between Europe and the US in the relationships between QoL and either outcome. In the following Cox models, the QoL measures have more predictive power than serum albumin, one of the best known predictors of mortality. % change in risk of outcome for 5 unit higher in QoL score Mortality 1st Hosp. PCS MCS KDB PCS MCS KDB 1. QoL alone in model 1 - 23‡ - 9 ‡ - 9 ‡ - 11 ‡ - 5 ‡ - 4 ‡ DF & CC added to 1. - 15‡ - 10 ‡ - 9 ‡ - 9 ‡ - 4 ‡ - 3 * Albumin added to 2. - 13‡ - 10 ‡ - 9 ‡ - 9 ‡ - 4 † - 3 † *p < 0.05; † p < 0.01; ‡ p < 0.0001 QOL is a powerful independent predictor of patient hospitalization and mortality risk in HD patients in the US and Europe. Poster Session: Initiation and Adequacy of Dialysis, Anemia Management and Quality of Life Issues in Dialysis Patients (9:30 AM - 5:00PM) Clinical Therapeutics, 22, 1099-1111. Development of Subscales from the Symptom/Problems and Effects of Kidney-Disease Items in the Kidney Disease Quality of Life (KDQOL"!) Instrument. S. Rao, W. B. Carter, D.L Mapes, J. D. Kallich, C. J. Kamberg, K. L. Spritzer, R. D. Hays. UCLA Department of Medicine, Los Angeles, CA, RAND, Santa Monica, CA, Amgen, Thousand Oaks, CA . Background: The Kidney Disease Quality of Life Instrument (KDQOLTM) was developed to provide a comprehensive assessment of the important domains of health-related quality of life (HRQOL) for hemodialysis patients. Objective: To identify subscales from the 55 items comprising the symptoms/problems and effects of kidney disease scales of the KDQOLTM. Methods: Eleven multi-item subscales and four individual items were identified using an affinity mapping procedure. These subscales and items were evaluated using data from a sample of 165 individuals with kidney disease. Results: Internal consistency reliability estimates for the 11 subscales ranged from 0.66 to 0.92. These subscales correlated with the SF-36TM scales as hypothesized (e.g., corresponding pain, energy, and social functioning scales correlated most highly). In addition, several of the subscales were significantly associated with know group differences on other variables such as number of disability days. Conclusions: This study provides further support for the reliability and validity of the KDQOLTM. The new subscales yield more detailed information and provide a basis for specific quality improvement efforts by clinicians providing care to patients with kidney disease. INDEX WORDS: Dialysis, quality of life, end stage renal disease, kidney disease, instrument development, health status, patient outcomes. Bias in Assessment of Health-Related Quality of Life in a Hemodialysis Population: A Comparison of Self-Administered and Interviewer-Administered Surveys in the HEMO Study Mark Unruh MD MS1, Guofen Yan MS2, Milena Radeva MS2, Ron D. Hays PhD3, Robert Benz MD4, Nicolaos V. Athienites MD5, John Kusek PhD6, Andrew S. Levey MD5, Klemens B. Meyer MD5 and the HEMO Study Group Journal of the American Society of Neurology, in press. Abstract We examine the relationship of patient reported health-related quality of life (HRQOL) to the mode of survey administration in the HEMO Study. In addition to self-administered surveys to assess HRQOL, interviewer-administered surveys were made available in order to include patients with poor vision, decreased manual dexterity, or strong preference. To examine the predictors of participation by self-administration of the survey, multiple logistic regression was performed. To examine the relationship of HRQOL results to mode of survey administration, adjusted differences between the self-administered and interviewer-administered groups were obtained from multiple linear regression models accounting for sociodemographic and case-mix factors. 978 of the first 1000 subjects in the HEMO Study completed the survey by interview (n=427) or by self-administration (n=551). The interviewer-administered group was older, more likely black, had longer duration of end-stage renal disease, had a higher prevalence of diabetes, and more severe comorbidity (all P<0.01). After adjustment for these differences, patients in the interviewer- administered group had higher scores on scales measuring Role-Physical, Role- Emotional, and Effects of Kidney Disease (all P<0.001). Dialysis studies that restrict HRQOL measurement to patients who are able to complete surveys without assistance will not accurately represent the health of the overall hemodialysis population. Clinical studies and clinical practices using HRQOL as an outcome should include interviewer-administration or risk a selection bias against subjects with older age, minority status, and higher level of comorbidity. Future investigation should include research of survey modalities with a low response burden such as telephone interview, computer-assisted interview, and proxy-administration. 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