Assessment of health-related quality of life in renal transplant and hemodialysis patients using the SF-36 health survey

Fujisawa, Masato; Ichikawa, Yasuji; Kawaguchi, Yoshiya; Isotani, Shuji; Higuchi, Akon; Nagano, S; Arakawa, Soichi; Hamami, Gaku; Matsumoto, Osamu; Kamidono, Sadao

doi:10.1016/s0090-4295(00)00623-3

Cited by 164 publications

(140 citation statements)

References 11 publications

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“…In contrast, the relationship between creatinine and MCS was NS. We identified six studies that measured correlation coefficients for the relationship between serum creatinine and SF-36 scores in ESRD (13,31,40,61,72,73). The weighted mean r value between creatinine and SF-36 scale scores was 0.29 (95% CI 0.21 to 0.37).…”

Section: Results Stratified By Traditional Biomarkersmentioning

confidence: 99%

Biomarkers and Health-Related Quality of Life in End-Stage Renal Disease

Spiegel

Melmed

Robbins

et al. 2008

Clinical Journal of the American Society of Nephrology

118

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Background and objectives: Health-related quality of life (HRQOL) predicts mortality in ESRD, yet adoption of HRQOL monitoring is not widespread, and regulatory authorities remain predominantly concerned with monitoring traditional biologic parameters. To assist with future efforts to adopt HRQOL monitoring while acknowledging the importance of biomarkers, this study sought to establish which domains of HRQOL are most affected by ESRD and to measure the strength of evidence linking common biomarkers to HRQOL in ESRD.Design, setting, participants, & measurements: A systematic review was performed to identify studies that measured HRQOL in ESRD. Data were abstracted according to a conceptual model regarding the measurement of HRQOL differences, and HRQOL data were converted to weighted mean effect sizes and correlation coefficients.Results: The impact of ESRD was largest in the Short Form 36 domains of physical functioning (e.g., role-physical, vitality) and smallest in mental functioning (e.g., mental health, role-emotional). Dialysis adequacy, as measured by Kt/V, was a poor correlate for Short Form 36 scores. Similarly, mineral metabolism (e.g., calcium ؋ phosphorous, parathyroid hormone) and inflammatory (e.g., C-reactive protein, TNF) biomarkers had small effect sizes and correlations with HRQOL. In contrast, hematocrit demonstrated small to moderate relationships with mental and physical HRQOL, and nutritional biomarkers (e.g., albumin, creatinine, body mass index) demonstrated moderate to large relationships.Conclusions: HRQOL in ESRD is most affected in the physical domains, and nutritional biomarkers are most closely associated with these domains. In contrast, Kt/V, mineral metabolism indices, and inflammatory markers are poor HRQOL correlates.

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Section: Results Stratified By Traditional Biomarkersmentioning

confidence: 99%

Biomarkers and Health-Related Quality of Life in End-Stage Renal Disease

Spiegel

Melmed

Robbins

et al. 2008

Clinical Journal of the American Society of Nephrology

118

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“…Because the designation of a patient as being medically appropriate for renal transplantation may be viewed as a functional marker for a given set of comorbidities that may better describe baseline mortality risk (21), we hypothesized that they represent a potential cohort of patients who would be eligible and may consent for a trial to compare outcomes on the basis of modality. In this investigation, we compared mortality for patients who were placed on the renal transplant waiting list and were incident to renal replacement therapy on the basis of initial choice of dialysis modality.…”

mentioning

confidence: 99%

Mortality by Dialysis Modality among Patients Who Have End-Stage Renal Disease and Are Awaiting Renal Transplantation

Inrig

Sun

Yang

et al. 2006

Clinical Journal of the American Society of Nephrology

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Comparing outcomes related to dialysis modality is complicated by selection bias introduced by patients and physicians. To address the impact of selection bias, this study compared mortality by initial dialysis modality among patients who had ESRD and were placed on the transplant waiting list. This study was a historical prospective cohort of 12,568 patients in the United States who initiated dialysis between May 1, 1995, and October 31, 1998, and were placed on the transplant waiting list before dialysis initiation. Two-year mortality was compared using Kaplan-Meier curves and Cox proportional hazards models that analyzed patients primarily using an intention-to-treat approach and separately censored patients on a modality switch. At 2 yr, the unadjusted mortality rate was 6.6% among peritoneal dialysis (PD) patients compared with 6.9% among hemodialysis (HD) patients (hazard ratio [HR] 1.01; 95% confidence interval [CI] 0.82 to 1.23). After controlling for differences in baseline characteristics, comorbidities, and laboratory variables, the selection of PD versus HD remained associated with a similar 2-yr mortality risk (HR 1.03; 95% CI 0.83 to 1.28). In separate models, 2-yr mortality associated with PD versus HD was significant among patients with body mass index (BMI) >26 kg/m 2 (HR 1.37; 95% CI 1.01 to 1.83) but not among patients with BMI <26 kg/m 2 (HR 0.81; 95% CI 0.61 to 1.07). Results were similar after censoring on a modality switch. In conclusion, although choice of initial dialysis modality seems to be associated with equivalent outcomes among patients who have ESRD and are placed on the transplant waiting list, patients with BMI >26 kg/m 2 have increased 2-yr mortality associated with the selection of PD versus HD. Because the interpretation of observational data is highly affected by residual confounding and selection bias, further efforts should focus on the formation and testing of hypotheses to improve dialysis delivery.

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“…The minimum recommended sample size for studies of health-related quality of life of kidney transplant recipients is approximately [10][11][12][13][14][15] times the number of variables analyzed. 19 Eleven variables were evaluated in the present study (economic burden, serum creatinine level, influence of adverse effects of drugs, harm, challenge, threat, benign/irrelevant, avoidance, confront, acceptance-resignation, physical component summary [PCS] and mental component summary [MCS]), which required a sample size of 110 to 165 kidney transplant recipients.…”

Section: Patientsmentioning

confidence: 99%

“…11 Furthermore, patients with higher serum creatinine levels are known to experience poorer physical and psychological outcomes. 12,13 Moreover, the inverse relationship of the adverse effects of immunosuppressive therapy on health-related quality of life of transplant recipients, in both physical and psychological domains, is also welldocumented. 14 Likewise, severe adverse effects of immunosuppressive therapy are known to affect treatment compliance, which in turn adversely affects the patients' physical and psychological well-being.…”

Section: Introductionmentioning

confidence: 99%

Untitled

Zhang

Shi²,

Shi³

et al. 2017

Exp Clin Transplant

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Objectives: Our objective was to explore factors influencing health-related quality of life in livingdonor kidney transplant recipients. Materials and Methods: A total of 140 kidney transplant recipients, enrolled between December 2014 and April 2015, were administered questionnaires on medical outcomes, 36-item Short Form Health Survey, medical coping modes, cognitive appraisal of health scale, and adverse effects of medications. Path analysis was employed to verify the hypothesized model. Results: Increased serum creatinine level and high economic burden had direct positive effects on negative appraisal (β = 0.18, P < .05 and β = 0.46, P < .01). Adverse effects of medication had direct positive effects on confrontation; whereas negative appraisal had direct positive effect on acceptance-resignation (β = 0.21, P < .05) and direct negative effect on physical component summary (β = -0.43, P < .001) and mental component summary (β = -0.51, P < .001). In addition, confrontation directly affected mental component summary (β = -0.15, P < .05). The enrolled variables accounted for 25.0% of physical component summary variance and 35.4% of mental component summary variance. Conclusions: In this study, economic burden, serum creatinine levels, and adverse effects of immunosuppressive therapy were the key external factors, whereas patients' cognitive appraisal and coping strategies were the main internal factors affecting patients' health-related quality of life. Medical care providers attending to transplant recipients should be able to identify patients developing negative coping strategies in response to stressors and plan individualized counseling programs for these patients.

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Assessment of health-related quality of life in renal transplant and hemodialysis patients using the SF-36 health survey

Cited by 164 publications

References 11 publications

Biomarkers and Health-Related Quality of Life in End-Stage Renal Disease

Biomarkers and Health-Related Quality of Life in End-Stage Renal Disease

Mortality by Dialysis Modality among Patients Who Have End-Stage Renal Disease and Are Awaiting Renal Transplantation

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