Abstract
Background and objectives
Low health–related quality of life is associated with increased mortality in patients with ESRD. However, little is known about demographic and clinical factors associated with health–related quality of life or its effect on outcomes in adults with CKD.
Design, settings, participants, & measurements
Data from 3837 adult participants with mild to severe CKD enrolled in the prospective observational Chronic Renal Insufficiency Cohort and Hispanic Chronic Renal Insufficiency Cohort Studies were analyzed. Health–related quality of life was assessed at baseline with the Kidney Disease Quality of Life-36 and its five subscales: mental component summary, physical component summary, burden of kidney disease (burden), effects of kidney disease (effects), and symptoms and problems of kidney disease (symptoms). Low health–related quality of life was defined as baseline score >1 SD below the mean. Using Cox proportional hazards analysis, the relationships between low health–related quality of life and the following outcomes were examined: (1) CKD progression (50% eGFR loss or incident ESRD), (2) incident cardiovascular events, and (3) all-cause death.
Results
Younger age, women, low education, diabetes, vascular disease, congestive heart failure, obesity, and lower eGFR were associated with low baseline health–related quality of life (P<0.05). During a median follow-up of 6.2 years, there were 1055 CKD progression events, 841 cardiovascular events, and 694 deaths. Significantly higher crude rates of CKD progression, incident cardiovascular events, and all-cause death were observed among participants with low health–related quality of life in all subscales (P<0.05). In fully adjusted models, low physical component summary, effects, and symptoms subscales were independently associated with a higher risk of incident cardiovascular events and death, whereas low mental component summary was independently associated with a higher risk of death (P<0.05). Low health–related quality of life was not associated with CKD progression.
Conclusions
Low health–related quality of life across several subscales was independently associated with a higher risk of incident cardiovascular events and death but not associated with CKD progression.
Keywords: chronic kidney disease; mortality risk; Cohort Studies; Disease Progression; Humans; Kidney Failure, Chronic; obesity; Prospective Studies; quality of life
Introduction
Persons with CKD and ESRD have poorer health–related quality of life (HRQOL) compared with the general population (1–4). In patients with ESRD, low HRQOL is associated with a higher risk of death and hospitalization (3–8). However, less is known about the relationship between low HRQOL and adverse outcomes in patients with predialysis CKD (9), including important disease end points, such as CKD progression. A Japanese study of patients with CKD found that increases in serum creatinine of >10%/yr were associated with statistically significant decreases in HRQOL measured over the same time period (10). In the African American Study of Kidney Disease and Hypertension (AASK), low baseline physical HRQOL was associated with a higher risk of cardiovascular (CV) events and a composite end point of CKD progression and death, whereas low baseline mental HRQOL was associated with CV events among blacks with hypertensive CKD in the United States (11).
Although these two studies provide important findings, they are limited in scope, because they did not include key subgroups with CKD, namely patients with diabetes or nonblack patients. More broadly, the association between HRQOL and longitudinal outcomes has not been examined in a multiethnic and racially diverse United States cohort of patients with CKD and a range of CKD etiologies. Furthermore, although the Kidney Disease Quality of Life-36 (KDQOL-36) was introduced in 1994 and has the advantage of being a kidney disease–specific HRQOL instrument, its use in prior studies has been infrequent and may further limit generalizability of their findings to a diverse CKD population. It is critical to better understand the relationship between HRQOL, its determinants, and outcomes because of the high prevalence of CKD in United States adults (12), and also, its symptoms, treatment side effects, and burden can have a negative effect on HRQOL (13). Lastly, HRQOL is being recognized as an important parameter of patient-centered care as evidenced by the Centers for Medicare and Medicaid Services (CMS) recently mandating HRQOL assessment for all patients with ESRD.
Leveraging the rich data and infrastructure of the prospective Chronic Renal Insufficiency Cohort (CRIC) Study and its ancillary study, the Hispanic Chronic Renal Insufficiency Cohort (H-CRIC) Study, we performed a cross-sectional analysis of demographic and clinical factors associated with low baseline HRQOL. We also examined the association of low baseline HRQOL and the risk of CKD progression, incident CV events, and death. Because we assessed HRQOL with a kidney disease–specific HRQOL instrument (KDQOL-36), we were able to examine these relationships not only with the customary mental and physical components but also, kidney disease–specific domains of HRQOL.
Materials and Methods
Study Design
We performed a cross-sectional analysis of the association of demographic and clinical factors with HRQOL at baseline and also, a longitudinal analysis of the association between low baseline KDQOL-36 scores and the risk of CKD progression, CV events, and all-cause death in participants of the CRIC Study and the H-CRIC Study during follow-up. The CRIC Study is a multicenter prospective cohort study of adults of diverse racial and ethnic backgrounds and CKD stages 2–4, and the design and methodologic details have been published previously (clinicaltrials.gov; NCT00304148; registered March 14, 2006) (14,15). Major eligibility criteria for the CRIC Study included adults ages 21–74 years old with mild to moderate CKD using age-based eGFR on the basis of the four–variable Modification of Diet in Renal Disease estimating equation (15). Aside from recruiting only participants of Hispanic ethnicity, the H-CRIC Study adopted eligibility and exclusion criteria identical to the CRIC Study (16). As noted previously, the CRIC Study included 169 Hispanics and 3443 non-Hispanics recruited at seven clinical centers from May of 2003 to March of 2007, whereas the H-CRIC Study included 327 Hispanics recruited at the University of Illinois at Chicago from October of 2005 to June of 2008. Recruitment sites included university–based, community–based, and private health clinics (17). Participants from the CRIC and H-CRIC Studies comprise the cohort for these analyses. All study participants provided written informed consent, and the study was approved by the Institutional Review Boards of the participating centers and adhered to the Declaration of Helsinki.
Variables and Data Sources
Sociodemographic data, such as age, sex, race or ethnicity, annual household income, education level, smoking status, and comorbid medical conditions, were reported by participants at baseline (14). Anthropometric measurements and BP were measured by trained study personnel; 24-hour urine protein was measured for all participants at baseline, and a serum creatinine was measured at baseline and annually. eGFR was calculated using an equation developed in a subgroup of the CRIC Study participants with an iothalamate GFR (18).
HRQOL was assessed using the KDQOL-36 (19), which was completed by participants at baseline. A paper KDQOL-36 form was self-completed by participants after verbal instructions from study personnel unless reading or comprehension problems precluded self-administration, in which cases, a research coordinator assisted participants in form completion. The five subscales of KDQOL-36 include mental component summary (MCS), physical component summary (PCS), burden of kidney disease (burden), effects of kidney disease (effects), and symptoms and problems of kidney disease (symptoms). The MCS and PCS were derived from the Medical Outcomes Study Short Form 12, a generic HRQOL survey instrument that can be used in healthy individuals and across all disease states (20). In the United States general population, the MCS and PCS have mean scores of 50 (21). Because the KDQOL-36 is used only in the CKD and ESRD population, there are no mean population scores available. Both the English and Spanish versions of the KDQOL-36 have been validated in the H-CRIC Study (22).
Outcomes
The primary outcomes for this analysis were (1) CKD progression defined as either loss of 50% of eGFR from baseline or ESRD (receipt of chronic dialysis or transplantation); (2) CV events defined as hospitalization for myocardial infarction, congestive heart failure, stroke, atrial fibrillation, or revascularization procedure for peripheral arterial disease; and (3) all-cause death. The assessed outcomes occurred from enrollment through March 31, 2012. Myocardial infarction, congestive heart failure, and atrial fibrillation events were adjudicated from medical records by trained physicians blinded to the participant, and revascularization procedures for peripheral arterial disease were ascertained by abstraction from medical records by a research nurse. ESRD events were obtained by participant self-report and verified by crosslinkage of participant data to the US Renal Data System. Deaths were determined on the basis of reports from patient proxies, medical records, death certificates, obituaries, or linkage of participant data with the Social Security Death Master File (14).
Statistical Methods
Participants’ baseline mean±SD and KDQOL-36 subscale scores were described according to categories of demographic and clinical characteristics, and between-group comparisons were made using t test or ANOVA. For each subscale, low baseline HRQOL score was defined as a score >1 SD below the mean for the cohort (23). Event rates for each outcome were calculated as the ratio of the number of patients reaching the event divided by 100 patient-years of observation. Associations between low HRQOL (HRQOL>1 SD below the cohort mean) and clinical factors were assessed using multivariable logistic regression analyses and reported as odds ratios and 95% confidence intervals (95% CIs). Associations between low baseline HRQOL score and outcomes were examined using Cox proportional hazards models and reported as hazard ratios (HRs) and 95% CIs with the assumption of proportional hazards checked using cumulative sums of Martingale residuals over follow-up times. Sensitivity analyses were performed using Cox regression analyses that examined the association of each outcome per 10-point decrement in HRQOL subscale score. There are several regression models, which might raise concerns about type 1 error. We chose not to adjust for multiple comparisons for two reasons. First, all of the models were prespecified. Second, as noted elsewhere, reducing type 1 error for null associations may increase the type 2 error for those associations that are not null (24). For tables, a different significance level is suggested for Bonferroni correction.
The statistical analyses were performed with SAS, version 9.3 (SAS Institute Inc., Cary, NC).
Results
Participants and Characteristics
Among a total of 3939 participants enrolled in the CRIC and H-CRIC Studies, KDQOL-36 data were not available for 102 participants. These participants were excluded, and the final analytic cohort was 3837. Their mean scores for the subscales were PCS=41.3±11.5, MCS=50.4±10.5, burden of kidney disease =82.1±23.8, effects of kidney disease =89.1±15.7, and symptoms and problems =83.4±14.9. Detailed demographic and clinical characteristics of the CRIC have been reported in detail previously (15). Briefly, at baseline, the mean age was 57.6±11.0 years old, 55% were men, 42% were white, the mean baseline eGFR was 45.0±16.9 ml/min per 1.73 m2, and the median (25th percentile, 75th percentile) urinary protein excretion was 0.18 (0.07, 0.91) g/24 h.
KDQOL-36 Scores in Subgroups at Baseline
Older age (≥65 versus <65 years old) was associated with significantly higher mean KDQOL-36 subscale scores, except for with PCS (Table 1). Women generally reported lower mean HRQOL across KDQOL-36 subscales compared with men (P<0.05), except for in burden and effects. There were significant differences in HRQOL subscale scores across race, income, education, and smoking status (P<0.05). Compared with Hispanic and non–Hispanic black participants, non-Hispanic whites reported higher mean HRQOL across all KDQOL-36 subscales. Lower KDQOL-36 subscale scores were associated with lower incomes, lower educational attainment, current smoking, and obesity. Compared with other comorbidities, diabetes was associated with lower mean HRQOL across all KDQOL-36 subscale scores (P<0.05), whereas hypertension, a history of myocardial infarction, peripheral vascular disease, and congestive heart failure were associated with significantly lower mean HRQOL on all KDQOL-36 subscale scores (P<0.05), except for MCS (P>0.05). Participants with greater albumin-to-creatinine ratios and lower eGFR had significantly lower mean KDQOL-36 subscale scores compared with those with less proteinuria or higher eGFR (P<0.05).
Table 1.
Demographic and clinical characteristics and mean baseline Kidney Disease Quality of Life-36 subscale scores
| Variable | PCS | MCS | Burden | Effects | Symptoms | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Mean (SD) | P Value | Mean (SD) | P Value | Mean (SD) | P Value | Mean (SD) | P Value | Mean (SD) | P Value | |
| Age, yr | ||||||||||
| <65 | 41.7 (11.7) | 0.001 | 49.4 (10.8) | <0.001 | 80.8 (24.8) | <0.001 | 88.3 (16.6) | <0.001 | 82.9 (15.4) | <0.001 |
| ≥65 | 40.3 (11.0) | 52.9 (9.4) | 85.5 (20.5) | 91.2 (12.8) | 84.8 (13.2) | |||||
| Sex | ||||||||||
| Men | 43.0 (11.1) | <0.001 | 51.3 (10.1) | <0.001 | 82.6 (23.3) | 0.20 | 89.4 (15.2) | 0.35 | 85.6 (13.8) | <0.001 |
| Women | 39.2 (11.7) | 49.2 (10.9) | 81.6 (24.2) | 88.9 (16.1) | 80.8 (15.6) | |||||
| Race | ||||||||||
| Non-Hispanic white | 43.4 (11.5) | <0.001 | 51.5 (9.7) | <0.001 | 87.5 (19.8) | <0.001 | 91.5 (13.2) | <0.001 | 85.0 (13.8) | <0.001 |
| Non-Hispanic black | 39.4 (11.4) | 50.2 (10.8) | 81.9 (22.8) | 88.0 (16.9) | 82.6 (15.5) | |||||
| Hispanic | 39.5 (10.6) | 46.9 (11.6) | 65.1 (30.0) | 85.3 (17.3) | 80.2 (15.3) | |||||
| Other | 43.7 (11.9) | 51.2 (9.6) | 82.1 (23.5) | 89.2 (15.9) | 85.5 (14.7) | |||||
| Annual household income | ||||||||||
| ≤$20,000 | 36.4 (10.9) | <0.001 | 48.1 (11.7) | <0.001 | 72.8 (27.5) | <0.001 | 84.6 (18.4) | <0.001 | 78.5 (16.3) | <0.001 |
| $20,001–$50,000 | 41.1 (11.0) | 50.5 (10.5) | 84.4 (21.6) | 89.5 (15.4) | 83.6 (14.2) | |||||
| $50,001–$100,000 | 45.2 (11.0) | 52.5 (8.9) | 89.3 (17.7) | 92.8 (11.9) | 87.6 (11.8) | |||||
| >$100,000 | 48.2 (9.4) | 53.7 (7.5) | 92.4 (15.4) | 95.0 (8.6) | 90.6 (10.0) | |||||
| Do not wish to answer | 41.9 (11.3) | 50.2 (10.3) | 82.4 (22.9) | 89.7 (14.7) | 83.7 (15.0) | |||||
| Education | ||||||||||
| Less than high school | 37.6 (10.7) | <0.001 | 48.5 (11.2) | <0.001 | 71.8 (27.6) | <0.001 | 86.8 (16.2) | <0.001 | 80.6 (15.3) | <0.001 |
| High school graduate | 39.5 (11.2) | 49.6 (10.8) | 80.8 (24.4) | 88.4 (16.4) | 81.7 (15.6) | |||||
| Some college | 40.2 (11.5) | 50.7 (10.6) | 83.5 (22.0) | 88.2 (16.5) | 82.3 (15.2) | |||||
| College graduate or higher | 45.7 (10.9) | 51.8 (9.5) | 88.6 (19.2) | 92.1 (13.2) | 87.5 (12.6) | |||||
| Smoking | ||||||||||
| Current | 38.7 (11.6) | <0.001 | 48.8 (11.3) | <0.001 | 79.6 (24.0) | 0.02 | 87.5 (15.9) | 0.03 | 80.6 (15.9) | <0.001 |
| Past | 40.5 (11.5) | 51.0 (10.3) | 83.1 (23.4) | 89.3 (15.5) | 83.2 (14.3) | |||||
| Never | 42.7 (11.3) | 50.3 (10.5) | 82.1 (23.9) | 89.5 (15.6) | 84.5 (14.8) | |||||
| Illicit drug use | ||||||||||
| No | 41.1 (11.5) | 0.15 | 51.0 (10.4) | <0.001 | 82.2 (24.1) | 0.87 | 89.5 (15.2) | 0.03 | 83.7 (14.8) | 0.13 |
| Yes | 41.6 (11.6) | 49.21 (10.7) | 82.1 (23.0) | 88.4 (16.4) | 82.9 (14.9) | |||||
| DM | ||||||||||
| No | 43.9 (11.2) | <0.001 | 51.0 (10.1) | <0.001 | 85.5 (21.8) | <0.001 | 91.4 (13.9) | <0.001 | 85.6 (14.2) | <0.001 |
| Yes | 38.5 (11.2) | 49.7 (10.9) | 78.6 (25.2) | 86.8 (16.9) | 81.1 (15.1) | |||||
| HTN | ||||||||||
| No | 45.1 (11.6) | <0.001 | 50.6 (10.5) | 0.53 | 86.0 (22.5) | <0.001 | 91.4 (14.8) | <0.001 | 85.5 (14.1) | <0.001 |
| Yes | 40.6 (11.4) | 50.3 (10.5) | 81.5 (23.9) | 88.8 (15.7) | 83.1 (14.9) | |||||
| History of MI | ||||||||||
| No | 42.5 (11.3) | <0.001 | 50.3 (10.5) | 0.36 | 82.6 (23.9) | 0.03 | 89.7 (15.4) | <0.001 | 84.3 (14.8) | <0.001 |
| Yes | 36.7 (11.1) | 50.7 (10.4) | 80.6 (23.1) | 87.2 (16.2) | 80.3 (14.5) | |||||
| PVD | ||||||||||
| No | 41.7 (11.5) | <0.001 | 50.4 (10.5) | 0.14 | 82.6 (23.6) | <0.001 | 89.5 (15.4) | <0.001 | 83.9 (14.7) | <0.001 |
| Yes | 34.6 (9.4) | 49.4 (11.1) | 75.7 (25.0) | 83.7 (17.9) | 77.1 (14.9) | |||||
| CHF | ||||||||||
| No | 42.0 (11.4) | <0.001 | 50.5 (10.5) | 0.14 | 82.7 (23.6) | <0.001 | 89.9 (15.0) | <0.001 | 84.2 (14.4) | <0.001 |
| Yes | 34.2 (10.4) | 49.6 (11.0) | 77.5 (24.2) | 82.6 (19.3) | 76.6 (16.6) | |||||
| BMI, kg/m2 | ||||||||||
| <30 | 44.0 (11.0) | <0.001 | 51.0 (10.0) | 0.001 | 83.2 (23.5) | 0.02 | 90.7 (14.3) | <0.001 | 85.5 (13.9) | <0.001 |
| ≥30 | 39.1 (11.4) | 49.9 (10.9) | 81.3 (24.0) | 87.9 (16.5) | 81.8 (15.3) | |||||
| Urine albumin-to-creatinine ratio | ||||||||||
| None | 42.5 (11.7) | <0.001 | 51.1 (10.1) | <0.001 | 87.6 (20.2) | <0.001 | 91.8 (13.7) | <0.001 | 84.6 (14.6) | <0.001 |
| Microalbuminuria | 40.2 (11.4) | 50.9 (10.5) | 82.6 (22.3) | 89.2 (14.9) | 84.1 (14.0) | |||||
| ≥300 | 40.00 (11.2) | 49.2 (10.8) | 75.1 (26.6) | 85.8 (17.3) | 81.6 (15.4) | |||||
| eGFR, ml/min per 1.73 m2 | ||||||||||
| ≥60 | 46.2 (11.0) | <0.001 | 50.5 (10.2) | 0.02 | 89.2 (19.5) | <0.001 | 93.2 (14.0) | <0.001 | 86.7 (14.4) | <0.001 |
| 50–59 | 43.2 (11.3) | 51.4 (10.2) | 88.4 (19.7) | 92.3 (13.1) | 86.2 (13.3) | |||||
| 40–49 | 41.0 (11.5) | 50.4 (10.5) | 83.4 (22.3) | 89.7 (14.7) | 83.5 (15.1) | |||||
| 30–39 | 39.9 (11.2) | 50.3 (10.4) | 79.4 (24.4) | 87.8 (15.6) | 81.8 (15.0) | |||||
| <30 | 37.1 (10.7) | 49.5 (11.1) | 72.6 (27.0) | 84.0 (17.9) | 80.1 (14.9) | |||||
PCS, physical component summary; MCS, mental component summary; DM, diabetes mellitus; HTN, hypertension; MI, myocardial infarction; PVD, peripheral vascular disease; CHF, congestive heart failure; BMI, body mass index.
Association between Demographic and Clinical Characteristics and Low Baseline HRQOL
Many participant characteristics were significantly associated with low HRQOL as defined by a mean KDQOL-36 subscale score >1 SD below cohort mean (Table 2). A significant inverse association was found between age (per 10 years older) and low HRQOL on all subscales, except for PCS (P<0.05). Women were significantly associated with higher odds for low baseline HRQOL for PCS, MCS, and symptoms (P<0.05) but not for burden or effects subscales. Race/ethnicity was not significantly associated with low HRQOL, except for the effects subscale score, for which non–Hispanic black participants were more likely to have low HRQOL compared with non–Hispanic white participants. Diabetes was significantly associated with low baseline HRQOL across all subscales. Other comorbid conditions (e.g., history of myocardial infarction, peripheral vascular disease, or congestive heart failure) were independently associated with low baseline subscale scores on PCS, effects, and symptoms subscale scores (P<0.05) but not with MCS or burden subscales (P>0.05). Mean eGFR decrements of 10 ml/min per 1.73 m2 were significantly associated with low baseline HRQOL on all subscale scores, except MCS and symptoms. Presence of proteinuria was not associated with low baseline HRQOL scores.
Table 2.
Association between low baseline Kidney Disease Quality of Life-36 subscale scores and demographic and clinical characteristics
| Participant Characteristic | PCS | MCS | Burden | Effects | Symptoms | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | OR (95% CI) | P Value | OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Age per 10-yr increase | 1.01 (0.91 to 1.12) | 0.84 | 0.78 (0.71 to 0.86) | <0.001 | 0.78 (0.71 to 0.87) | <0.001 | 0.80 (0.72 to 0.89) | <0.001 | 0.87 (0.78 to 0.97) | 0.01 |
| Women | 2.19 (1.80 to 2.67) | <0.001 | 1.65 (1.36 to 2.00) | <0.001 | 1.15 (0.94 to 1.41) | 0.17 | 1.17 (0.94 to 1.47) | 0.16 | 1.85 (1.50 to 2.28) | <0.001 |
| Hispanic versus non-Hispanic white | 1.24 (0.80 to 1.93) | 0.81 | 1.43 (0.92 to 2.22) | 0.37 | 1.54 (1.00 to 2.39) | 0.07 | 1.09 (0.63 to 1.88) | 0.04 | 1.55 (0.96 to 2.49) | 0.25 |
| Non-Hispanic black versus non-Hispanic white | 1.04 (0.84 to 1.29) | 1.11 (0.89 to 1.38) | 1.08 (0.85 to 1.37) | 1.43 (1.11 to 1.85) | 1.08 (0.85 to 1.37) | |||||
| Other versus non-Hispanic white | 1.05 (0.62 to 1.78) | 1.27 (0.76 to 2.11) | 1.70 (1.03 to 2.80) | 1.38 (0.76 to 2.51) | 1.40 (0.80 to 2.45) | |||||
| College versus less than high school education | 0.51 (0.38 to 0.68) | <0.001 | 0.68 (0.50 to 0.91) | 0.03 | 0.45 (0.33 to 0.61) | <0.001 | 0.91 (0.64 to 1.27) | 0.12 | 0.69 (0.50 to 0.95) | 0.002 |
| High school/some college versus less than high school education | 0.86 (0.69 to 1.08) | 0.87 (0.69 to 1.10) | 0.73 (0.58 to 0.93) | 1.18 (0.90 to 1.54) | 1.09 (0.85 to 1.40) | |||||
| Current versus never smoker | 1.61 (1.21 to 2.13) | <0.001 | 1.30 (0.99 to 1.71) | 0.15 | 1.07 (0.80 to 1.43) | 0.91 | 1.12 (0.81 to 1.53) | 0.50 | 1.54 (1.14 to 2.07) | 0.02 |
| Past smoking (smoked ≥100 cigarettes) versus nonsmoking (never smoked or smoked <100 cigarettes) | 1.39 (1.13 to 1.70) | 1.02 (0.83 to 1.26) | 1.01 (0.82 to 1.26) | 0.93 (0.73 to 1.18) | 1.10 (0.88 to 1.38) | |||||
| Any illicit drug use versus no illicit drug use | 1.17 (0.95 to 1.44) | 0.14 | 1.55 (1.27 to 1.90) | <0.001 | 1.15 (0.93 to 1.43) | 0.20 | 1.22 (0.97 to 1.55) | 0.09 | 1.19 (0.95 to 1.49) | 0.13 |
| Diabetes | 1.55 (1.28 to 1.88) | <0.001 | 1.33 (1.09 to 1.61) | 0.004 | 1.26 (1.02 to 1.54) | 0.03 | 1.56 (1.24 to 1.95) | <0.001 | 1.58 (1.28 to 1.96) | <0.001 |
| Hypertension | 1.04 (0.77 to 1.41) | 0.79 | 1.00 (0.75 to 1.32) | 0.98 | 0.92 (0.68 to 1.24) | 0.58 | 0.85 (0.61 to 1.18) | 0.33 | 1.20 (0.86 to 1.68) | 0.27 |
| History of MI | 1.84 (1.49 to 2.27) | <0.001 | 1.22 (0.97 to 1.55) | 0.09 | 1.20 (0.94 to 1.53) | 0.14 | 1.13 (0.87 to 1.46) | 0.37 | 1.62 (1.28 to 2.06) | <0.001 |
| Peripheral vascular disease | 1.45 (1.07 to 1.97) | 0.02 | 1.28 (0.91 to 1.79) | 0.16 | 1.32 (0.94 to 1.84) | 0.11 | 1.55 (1.10 to 2.19) | 0.01 | 1.53 (1.11 to 2.15) | <0.01 |
| CHF | 1.77 (1.36 to 2.31) | <0.001 | 0.95 (0.70 to 1.29) | 0.75 | 1.18 (0.87 to 1.60) | 0.28 | 1.88 (1.40 to 2.54) | <0.001 | 1.63 (1.22 to 2.17) | <0.001 |
| BMI≥30 versus <30 | 1.72 (1.42 to 2.09) | <0.001 | 1.26 (1.04 to 1.52) | 0.02 | 1.04 (0.86 to 1.27) | 0.66 | 1.34 (1.07 to 1.66) | <0.01 | 1.71 (1.39 to 2.11) | <0.001 |
| Mean eGFR per 10-ml/min per 1.73 m2 decrease | 1.09 (1.01 to 1.18) | 0.03 | 0.98 (0.91 to 1.05) | 0.54 | 1.16 (1.07 to 1.26) | <0.001 | 1.30 (1.19 to 1.42) | <0.001 | 1.07 (0.99 to 1.17) | 0.09 |
| Urine albumin-to-creatinine ratio of <30 versus 30–299 | 1.01 (0.81 to 1.27) | 0.53 | 0.89 (0.71 to 1.13) | 0.32 | 0.83 (0.65 to 1.06) | 0.20 | 1.01 (0.77 to 1.31) | 0.83 | 0.99 (0.77 to 1.27) | 0.92 |
| Urine albumin-to-creatinine ratio of ≥300 versus <30 | 0.85 (0.60 to 1.19) | 1.12 (0.80 to 1.57) | 1.05 (0.75 to 1.47) | 0.90 (0.62 to 1.32) | 0.93 (0.65 to 1.34) | |||||
Low baseline health–related quality of life is a subscale score >1 SD below cohort mean subscale score. A significance level of 0.01 can be used for Bonferroni correction for multiple comparisons. PCS, physical component summary; MCS, mental component summary; OR, odds ratio; 95% CI, 95% confidence interval; MI, myocardial infarction; CHF, congestive heart failure; BMI, body mass index.
Low Baseline KDQOL-36 Subscale Scores and Rates of CKD Progression, CV Events, and Death
During a median follow-up of 6.2 years, for participants with low baseline HRQOL, the cumulative incidence rates across HRQOL subscales ranged between 7.35 and 10.76 per 100 person-years for CKD progression, between 4.93 and 7.20 for CV events, and between 3.60 and 4.94 for death; for participants without low baseline HRQOL, the corresponding cumulative incident rates were between 5.28 and 5.86, 3.53 and 4.02, and 2.45 and 2.79 events per 100 person-years, respectively (Figure 1). Participants with low baseline KDQOL-36 subscale scores had significantly higher incidence rates of CKD progression, CV events, and death compared with those with normal baseline subscale scores (P<0.05).
Figure 1.
Incidence rates of clinical outcomes by low versus normal baseline health–related quality of life (HRQOL) scores. (A) Cumulative incidence rates of CKD progression (per 100 person-years) by baseline KDQOL-36 subscale low and normal scores. (B) Cumulative incidence rates of cardiovascular events (per 100 person-years) by baseline KDQOL-36 subscale low and normal scores. (C) Cumulative incidence rates of death (per 100 person-years) by baseline KDQOL-36 subscale low and normal scores. Low health–related quality of life is defined as >1 SD below the cohort mean. KDQOL-36, Kidney Disease Quality of Life-36; MCS, mental component summary; PCS, physical component summary.
Association between Baseline Low KDQOL-36 Subscale Scores, CKD progression, CV Events, and Death
In fully adjusted analyses, low baseline PCS score was associated with a higher risk for incident CV events (HR, 1.44; 95% CI, 1.23 to 1.69), and all-cause death (HR, 1.49; 95% CI, 1.25 to 1.77) but not CKD progression (HR, 1.09; 95% CI, 0.93 to 1.27) (Table 3). Low baseline MCS scores were associated with a higher risk of death (HR, 1.26; 95% CI, 1.04 to 1.53) but not CKD progression (HR, 1.02; 95% CI, 0.87 to 1.20) or incident CV disease (HR, 1.15; 95% CI, 0.96 to 1.38). Low baseline effects subscale scores and low baseline symptoms subscale scores were associated with a higher risk of CV events (HR, 1.32; 95% CI, 1.09 to 1.59 and HR, 1.32; 95% CI, 1.11 to 1.57, respectively) and mortality (HR, 1.39; 95% CI, 1.14 to 1.70 and HR, 1.28; 95% CI, 1.06 to 1.55, respectively) but not CKD progression (HR, 1.05; 95% CI, 0.89 to 1.25 and HR, 0.97; 95% CI, 0.82 to 1.14, respectively). Low baseline burden subscale scores were not associated with a higher risk of any of the outcomes. Sensitivity analyses examining the association between each outcome and 10-point decrements in KDQOL-36 subscale score revealed similar findings (data not shown).
Table 3.
Association between baseline low Kidney Disease Quality of Life-36 subscales scores and CKD progression, cardiovascular events, and death
| KDQOL-36 Subscale (Baseline Score >1 SD Below Mean Compared with Higher Scores) | Outcome Hazard Ratio (95% CI), P Value | ||
|---|---|---|---|
| CKD Progression, 1055 events | CV Events, 841 events | Death, 694 events | |
| Unadjusted analysis | |||
| PCS | 1.40 (1.21 to 1.61), <0.001 | 2.01 (1.73 to 2.32), <0.001 | 2.03 (1.74 to 2.38), <0.001 |
| MCS | 1.26 (1.09 to 1.47), 0.002 | 1.22 (1.04 to 1.45), 0.02 | 1.31 (1.09 to 1.57), 0.003 |
| Burden | 2.07 (1.80 to 2.37), <0.001 | 1.42 (1.21 to 1.68), <0.001 | 1.53 (1.28 to 1.82), <0.001 |
| Effects | 1.80 (1.54 to 2.11), <0.001 | 1.66 (1.39 to 1.97), <0.001 | 1.86 (1.55 to 2.24), <0.001 |
| Symptoms | 1.28 (1.10 to 1.51), 0.002 | 1.69 (1.43 to 1.99), <0.001 | 1.72 (1.44 to 2.05), <0.001 |
| Adjusted analysis | |||
| PCS | 1.09 (0.93 to 1.27), 0.27 | 1.44 (1.23 to 1.69), <0.001 | 1.49 (1.25 to 1.77), <0.001 |
| MCS | 1.02 (0.87 to 1.20), 0.78 | 1.15 (0.96 to 1.38), 0.12 | 1.26 (1.04 to 1.53), 0.02 |
| Burden | 1.09 (0.93 to 1.27), 0.29 | 1.18 (0.98 to 1.41), 0.08 | 1.18 (0.97 to 1.43), 0.10 |
| Effects | 1.05 (0.89 to 1.25), 0.57 | 1.32 (1.09 to 1.59), 0.004 | 1.39 (1.14 to 1.70), 0.001 |
| Symptoms | 0.97 (0.82 to 1.14), 0.69 | 1.32 (1.11 to 1.57), 0.002 | 1.28 (1.06 to 1.55), 0.01 |
Fully adjusted model is adjusted for clinical site, age, sex, race, eGFR, log urine protein, systolic BP, history of myocardial infarction, and history of diabetes. A significance level of 0.01 can be used for Bonferroni correction for multiple comparisons. KDQOL-36, Kidney Disease Quality of Life-36; 95% CI, 95% confidence interval; CV, cardiovascular; PCS, physical component summary; MCS, mental component summary.
Discussion
In this large diverse cohort of adults with CKD, we found several sociodemographic and clinical factors significantly associated with worse HRQOL across a majority of KDQOL-36 subscales at study baseline, including younger age, women, low education, diabetes, peripheral vascular disease, congestive heart failure, obesity, and lower eGFR. In an analysis of the association between low baseline HRQOL and outcomes ascertained over time, higher crude rates of CKD progression, incident CV events, and death were consistently observed with low KDQOL-36 subscale scores. After accounting for important factors, low baseline PCS, effects, and symptoms subscales were associated with a higher risk for death and incident CV events, low baseline MCS was associated with a higher risk for death, and none of the low-subscale scores were associated with CKD progression.
Despite HRQOL being increasingly recognized as an important patient–centered outcome measure used to assess quality of care (25), such that it is required as part of conditions for coverage by the CMS for dialysis facilities, there have been fewer epidemiologic studies of HRQOL among persons with CKD than among persons with ESRD (26,27). The vast majority of previous reports focused on HRQOL in patients with ESRD receiving chronic dialysis (3–5). Our study contributes substantially to our understanding of the association between diminished HRQOL and clinical outcomes among patients with CKD before ESRD. We studied HRQOL in both men and women over a wide age range with good representation of Hispanic Americans and blacks across diverse etiologies and severity of CKD, including the presence of substantial comorbid illness, using an instrument that examines broad domains of HRQOL in populations with kidney disease (14). All of these study attributes enhance the generalizability of reported findings.
We found, overall, that the PCS but not MCS subscale of HRQOL is poor in the CRIC and H-CRIC Studies participants and further reduced in persons with lower levels of kidney function. We also observed a substantial independent association between lower eGFR and low burdens and effects subscale scores, underscoring the broad and strong relationship between kidney function and HRQOL. As we also noted in the AASK cohort (2), we found lower socioeconomic status and comorbid illness to be associated with worse HRQOL. Because of the large and diverse CKD cohort in the CRIC Study, we are able to additionally report on variation in HRQOL among different race/ethnic groups and patients with diabetes. We found that non–Hispanic black race was independently associated with a greater odds of low HRQOL in the effects subscale at baseline compared with non–Hispanic white race and that diabetes, vascular disease, congestive heart failure, and obesity were generally strongly associated with low HRQOL across its subscales. Collectively, these findings underscore the importance of heightened attention to HRQOL in patients with low socioeconomic status, certain comorbid diseases, and more advanced CKD. These findings additionally inform strategies for assessment of HRQOL in the future, including validating HRQOL instruments in disadvantaged populations and assessing and monitoring HRQOL more frequently in high-risk populations.
In the ESRD population, poor HRQOL in both the mental and physical domains has been shown to be associated with a higher risk of hospitalization and death (3–8). The relationship between low HRQOL and clinical outcomes is less studied in individuals with CKD (9,10,28). In the AASK cohort, low baseline physical and mental HRQOL has been shown to be associated with a higher risk for CV events/CV mortality but not be associated with CKD progression, although the latter finding varied across additional analytic techniques (A. Porter, et al., unpublished data). In the CRIC and H-CRIC Studies, low baseline HRQOL subscale scores were consistently associated with a higher risk of death and generally associated with a higher risk of incident CV events but not associated with CKD progression. An understanding of the mechanism to explain the association between low HRQOL and adverse clinical events remains incomplete. Poor mental health may lead to reduced adherence to medical treatments or engagement in unhealthy lifestyle choices, such as smoking or being physically inactive, which may, in turn, increase the risk of mortality (29). Low physical domain scores may reflect physical inactivity because of poor exercise capacity related to CKD (30) or overall disease burden, which may be a possible reason for the relationship between low PCS subscale score and a higher risk for CV events and death.
In contrast to the Short Form-36 instrument used by the AASK and other instruments used to assess quality of life, the CRIC and H-CRIC Studies used the KDQOL-36, which allowed an examination of kidney disease–specific HRQOL domains. Although there is limited existing literature to facilitate contextualizing of these kidney disease–specific domains, it is noteworthy that the low symptoms and effects subscales were strongly associated with both CV events and death, which may index not only the severity of CKD complications but also, comorbid disease burden. Interestingly, we found the association between outcomes and the effects (e.g., the degree to which kidney disease interferes with a patient’s life) and symptoms (e.g., lack of appetite and shortness of breath) subscales to parallel that of the PCS subscale, whereas the burden (e.g., degree to which fluid restriction or dietary restriction is burdensome) subscale’s relationship to outcomes resembled that of the MCS subscale. Additional study is needed to more fully understand these kidney-specific subscales. The KDQOL-36 was developed in recognition of the fact that not only CKD but also, its associated treatments may have a profound effect on patient wellbeing beyond that appreciated by measurement using a generic HRQOL instrument. Therefore, a more refined assessment of HRQOL specifically in patients with CKD may provide insight into treatment decisions between such patients and nephrologists (19).
Although the CRIC Study has many strengths, including prospective observational design, robust data collection, rigorous methodology, and a diverse representative participant cohort, our specific analyses do have limitations. First, as in all observational studies, we cannot assess causality between HRQOL and the observed outcomes. However, observational studies are powerful tools to assess epidemiologic relationships, and we capitalized on multiple analytic techniques to robustly examine the influence of HRQOL and clinical relevant outcomes (31). Second, despite robust risk adjustment, our study is subject to residual bias and confounding.
In conclusion, in a large cohort of adults with CKD caused by a spectrum of causes and with a range of eGFRs, HRQOL was found to be worse in participants with poorer socioeconomic status, lower eGFR, and a greater burden of diabetes and CV disease. Moreover, low HRQOL was strongly associated with an array of adverse clinical outcomes. These findings reinforce to health care providers the importance of assessing HRQOL in their patients with CKD and incorporating this assessment into their management decisions. Additional studies are needed to identify mechanisms for the association between low HRQOL and outcomes and clarify possible areas for intervention to both improve HRQOL and reduce CV events and death.
Disclosures
None.
Supplementary Material
Acknowledgments
This work was supported by National Institutes of Diabetes and Digestive and Kidney Diseases grants U01DK60980 (to J.P.L.), R01DK72231 (to J.P.L.), K24DK092290 (to J.P.L.), K23DK094829 (to A.C.R.), K23DK097183-02 (to J.W.N.), and R01DK72231 (to M.J.F.). Funding for the Chronic Renal Insufficiency Cohort (CRIC) Study was obtained under a cooperative agreement from the National Institute of Diabetes and Digestive and Kidney Diseases (grants U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, and U01DK060902). In addition, this work was supported, in part, by Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science award National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) UL1TR000003, Johns Hopkins University grant UL1 TR-000424, University of Maryland General Clinical Research Center grant M01 RR-16500, the Clinical and Translational Science Collaborative of Cleveland, grant UL1TR000439 from the NCATS component of the NIH and NIH Roadmap for Medical Research, Michigan Institute for Clinical and Health Research grant UL1TR000433, University of Illinois at Chicago Clinical and Translational Science Award grant UL1RR029879, Tulane University Translational Research in Hypertension and Renal Biology grant P30GM103337, and Kaiser Permanente NIH/National Center for Research Resources grant UCSF-CTSI UL1 RR-024131.
The CRIC Study Investigators include Lawrence J. Appel, Harold I. Feldman, Alan S. Go, Jiang He, J.P.L., J.W.K., Akinlolu Ojo, Mahboob Rahman, and Raymond R. Townsend.
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
See related editorial, “Health–Related Quality of Life in CKD—Advancing Patient-Centered Research to Transform Patient Care,” on pages 1123–1124.
This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.09990915/-/DCSupplemental.
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