1 Division of Nephrology, Department of Medicine, TuftsNew England Medical Center, Boston, MA, USA and 2 Universidad Panamericana School of Medicine, Mexico City, Mexico
Correspondence and offprint requests to: Annamaria Kausz, MD, MS, Division of Nephrology, TuftsNew England Medical Center, Box no. 391, 750 Washington Street, Boston, MA 02111, USA. Email: akausz{at}tufts-nemc.org
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Abstract |
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Methods. Data from the Dialysis Morbidity and Mortality Study Wave II, a prospective study of incident dialysis patients, were used. Late referral (LR) was defined as first nephrology visit <4 months and early referral (ER) as first nephrology visit 4 months prior to initiation of dialysis. Propensity scores (PS) were estimated using logistic regression to predict the probability that a given patient was LR. A Cox proportional hazards model was built to examine the association between timing of nephrology referral and mortality.
Results. The cohort was comprised of 2195 patients: 54% were males, 66% were Caucasians, 26% were African-Americans and 33% were referred late. A Cox proportional hazards analysis demonstrated that compared with ER patients, LR patients had a 44% higher risk of death at 1 year after initiation of dialysis [hazards ratio (HR) = 1.44; 95% confidence interval (CI): 1.151.80], which remained significant after adjusting for quintiles of PS (HR = 1.42; 95% CI: 1.121.80).
Conclusions. Among patients with chronic kidney disease (CKD) who initiated dialysis, LR was associated with higher risk of death at 1 year after initiation of dialysis compared with ER.
Keywords: chronic kidney disease; end-stage renal disease; late referral; mortality
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Introduction |
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ESRD is preceded in most cases by a prolonged course of progressive decline in kidney function. This population with earlier stages of chronic kidney disease (CKD) is the ideal target for interventions to reduce progression to ESRD and to optimize management of comorbid conditions in order to improve long-term outcomes. The population of patients with earlier stages of CKD is significantly larger than the ESRD population. Using glomerular filtration rate (GFR) <60 ml/min/1.73 m2 as a definition for CKD, the prevalence of CKD in the US among those 20 years of age was estimated to be 4.3% or 7.6 million [3].
Optimal management of patients with CKD is, at present, most likely to require nephrology specialist involvement given the complex issues that may arise, especially at the later stages of CKD. However, referral of patients with CKD to a nephrologist only shortly before the need to institute renal replacement therapy (RRT), and thus with no time for interventions to improve their health status or delay progression, is a widespread problem [4]. Late nephrology referral has been associated with suboptimal health at the initiation of dialysis [4]; however, whether care by a nephrologist in the months or years prior to the initiation of dialysis would reduce subsequent mortality among ESRD patients remains a controversial issue.
Two recent studies have examined the association between timing of nephrology referral and mortality, one using the traditional Cox model in a representative US ESRD population [5] and the other employing the propensity score (PS) analysis in a regional sample of patients [6]. As previous studies on the association of timing of nephrology referral with mortality have demonstrated conflicting results, we used the novel technique of PS analysis in a nationally representative sample of ESRD patients to examine this issue in a more robust fashion. The PS analysis was used to balance the covariates in ER and LR groups and to characterize patients who are referred late to a nephrologist. This technique helped to overcome the selection and confounding biases that are acknowledged limitations of observational studies [7].
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Subjects and methods |
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Data sources
Data were obtained from several databases of the United States Renal Data System (USRDS), including the DMMS Wave II File and the Core Standard Analysis Files (SAF). The USRDS receives data on all patients who begin dialysis in the US. The DMMS Wave II File contains data from the DMMS Wave II, a prospective, observational, cohort study of 4024 patients initiating dialysis in 199697. Patient-specific data were collected at study start date (60 days after initiation of dialysis) and after 912 months of follow-up. The data included: (i) a medical questionnaire, with information on patient demographics, comorbid conditions, treatment and laboratory tests; (ii) a patient questionnaire, with information regarding quality of life and pre-ESRD care; and (iii) a facility questionnaire, with information related to the dialysis procedures utilized in the facility. The Core SAF contains the Patient File, which provides mortality data that can be linked with a unique patient identifier to the DMMS Wave II file.
Definitions
Early nephrology referral (ER) was defined as first nephrology visit 4 months prior to initiation of dialysis and late nephrology referral (LR) as first nephrology visit <4 months prior to initiation of dialysis. PS, derived from a logistic regression analysis, provide the probability of being treated (in this case, the probability of being referred late to a nephrologist), conditioned on the individual's covariate scores. Kidney function was assessed by estimating GFR from serum creatinine levels using an equation derived from the Modification of Diet in Renal Disease Study, which is based on age, gender, race and serum creatinine [8]. This equation was well correlated with iothalamate GFR in a large group of patients with varying degrees of kidney dysfunction. Time at risk was calculated as the time in days from the study start date (60 days after initiation of dialysis) to 1 year after this date for the 1 year mortality analysis and to the earliest of death, loss to follow-up, transplantation or end of study (30 September 1998) for the overall mortality analysis. Data on dialysis patients were only available 60 days after initiation of dialysis and did not account for the patients who died during this period. Therefore, we chose 60 days after initiation of dialysis as the study start date.
Analytical methods
Descriptive analyses. The demographic and clinical characteristics of the patients were described; continuous variables are presented as means±SD and categorical variables are presented as proportions. The overall mortality and causes of death were determined. Comparisons of characteristics between the ER and LR groups were made with chi-square tests or t-tests, as appropriate for the characteristics of the data. Descriptive analyses were also performed on ER and LR groups stratified by treatment modality [haemodialysis (HD) vs peritoneal dialysis (PD)] and by whether or not patients completed the patient questionnaire, to determine whether there were systematic differences between the groups.
Estimation of PS. The PS model was developed using logistic regression, with LR (vs ER) as the dependent variable. The independent variables included age, gender, race, ethnicity, marital status, employment status, educational status, insurance, GFR, comorbid conditions (diabetes mellitus, ischaemic heart disease, congestive heart failure, chronic lung disease, cerebrovascular disease and peripheral vascular disease), cause of CKD, smoking, ESRD network and functional status at initiation of dialysis. Two-factor interactions between significant covariates and employment, insurance, education and marital status were also included. The variables haematocrit, albumin and dialysis modality at initiation were deliberately left out of the model, as these could have been influenced by timely nephrology care. The predicted values from this model provided an estimate of the probability that an individual was referred late. Patients were sorted into five quintiles of PS, such that patients in the first quintile (quintile 1) had the lowest probability of being referred late and those in the fifth quintile (quintile 5) the highest probability of being referred late. The fit of the model was assessed by calculating the receiver operating characteristic (ROC) curve. The clinical and demographic characteristics of patients in each of the quintiles were determined.
Mortality analyses: KaplanMeier analysis. Survival at 1 year of follow-up was estimated by deriving KaplanMeier curves for patients in various quintiles of PS. Survival curves between strata were compared using the log-rank test.
Mortality analyses: Cox proportional hazards regression. The association between 1 year and overall mortality after study start date and the timing of nephrology referral was explored using separate Cox proportional hazards regression models. Covariates explored for the analyses were similar to those used in the logistic regression analysis for the PS, with the additional inclusion of the quintiles of PS. A stepwise selection process was used for developing the multivariate Cox proportional hazards regression model. Age, gender, race and diabetes were forced into the model and all independent variables with univariate associations of P 0.10 were allowed to enter the model-building process. Two-factor interactions between LR and other significant covariates were explored. Variables with a P-value of <0.05 or which significantly altered the estimate of the predictor of interest, or added precision, remained in the final model. The assumption of proportional hazards was tested by examining Schonfeld residuals and by the interaction between time and LR.
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Results |
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Among the 2195 patients, 1465 (67%) were ER and 730 (33%) were LR. The baseline demographic and clinical characteristics of ER and LR patients are presented in Table 1. The mean (median) overall duration of follow-up was 739.8±239.2 days (813 days; range: 581003 days). Compared with patients in the LR group, those in the ER group were more likely to be Caucasians, have private or health maintenance organization (HMO) insurance, be employed, married and college graduates, start RRT on PD and have diabetes as the cause of ESRD. Patients in the ER group were less likely to be unable to ambulate independently and to be unemployed due to disability compared with the LR group. The characteristics of ER and LR patients stratified by treatment modality (HD vs PD) and by whether or not they completed a patient questionnaire were not significantly different (data not shown).
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In the KaplanMeier analysis, the estimated survival among patients was progressively lower with higher quintiles of probability of LR, from 89% 1-year survival in PS quintile 1 to 78% 1-year survival in PS quintile 5 (P = 0.0004; Figure 1).
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Discussion |
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Previous studies on the association of timing of nephrology referral with mortality have demonstrated conflicting results. Campbell et al. [10] studied 585 patients between 1982 and 1984 and found that 1 year mortality was greater in LR (<1 month) patients compared with ER patients (34% vs 6%). Ratcliffe et al. [11] studied 55 patients and found that 13% of LR patients (<1 month) compared with 3% of ER patients died. Sesso and Belasco [12] observed a 2.05 adjusted relative risk of death during the first 6 months of dialysis among patients who were LR (<1 month) compared with those who were ER. Kinchen et al. [13] found an 80% greater risk of death among LR (<4 months) compared with ER (>12 months). In contrast, two studies have shown no difference in mortality between ER and LR (<1 month) patients. Schmidt et al. [14] reported no difference in mortality between ER and LR at 4 months among 238 patients after adjusting for age and cause of ESRD. Likewise, a study of 270 French patients showed no association between long-term (5 year) mortality and LR (<4 months) [15].
Previously published studies assessing the impact of timing of nephrology referral were observational studies and large differences in observed covariates in the LR and ER groups were often present. In addition, the studies were small and/or single centre, thus, limiting the generalizability of their results. A randomized controlled study trial would be ideal, but it is unlikely to be done. Although the use of observational studies for assessment of treatment effects is controversial, recent work has suggested that properly conducted observational studies may produce results that are neither misleading nor biased [16]. Matching is a commonly used technique to reduce bias, but it is often difficult to find subjects who can be matched on all important covariates. The PS analysis methodology can be used to balance the covariates in the two groups [17] in a more robust fashion than is possible with standard multivariable analysis, as it allows entry of an unlimited number of covariates [7]. In the current analysis, the PS technique resulted in a reasonable balance of the covariates in the LR and ER groups (Table 2), demonstrating the success of the PS technique. However, the disadvantage of estimating a PS is that information on each covariate is not available in the final model.
The PS analysis in this study showed a 44% greater risk of death at 1 year among LR compared with ER and this risk was still apparent after adjusting for quintiles of PS (HR = 1.42; 95% CI: 1.121.80). The results of our study are consistent with that of Winklemayer et al. [6], who found a 36% greater risk of death among LR (<90 days) compared with ER patients (>90 days), which decreased to 31% after adjusting for quintiles of PS. Our study also found a significant association between LR and mortality during overall follow-up (HR = 1.21; 95% CI: 1.021.43). This is consistent with a recent study by Stack et al. [18] who have reported the association of LR and mortality at 2 years of initiation of dialysis almost similar to our study (relative risk: 1.23; 95% CI: 1.021.47). One might conclude from our results that LR can be partially predicted by socioeconomic factors and that among those with the most adverse socioeconomic factors it may be associated with increased mortality in the first year of dialysis, but diminishing over a longer period of dialysis.
In the present study, older age, higher GFR at initiation of dialysis, congestive heart failure, peripheral vascular disease, inability to ambulate independently and LR were significantly associated with higher risk of death at 1 year after initiation of dialysis. Older age and higher comorbidity have been associated with a greater risk of death in previous studies [13,15]. Patients with diabetes, cardiac disease, peripheral vascular disease and poor functional status have been shown to initiate dialysis at a higher GFR [19]. Thus, patients with higher comorbidity who initiate dialysis at a higher GFR may have a greater risk of death.
The current analysis has the additional strength of using the DMMS Wave II data from the USRDS. The requirement for reporting to the Center for Medicare and Medicaid Services in order for the patient to qualify for Medicare coverage of ESRD services ensures that the majority of patients initiating dialysis in the US have the potential for inclusion in any analyses using data from the USRDS. The DMMS Wave II Study included randomly chosen patients from 25% of dialysis units in the US. Thus, the sample size is large; the patients were from a wide geographic distribution and generally representative of the larger population of patients initiating dialysis in the US (with the exception of the over-representation of patients initiating peritoneal dialysis). USRDS and DMMS Wave II data have been used for numerous cross-sectional and longitudinal analyses, evaluating the prevalence of a variety of conditions as well as outcomes [18,20]. The larger USRDS database does not provide easily accessible information on timing of nephrology referral, whereas this information is available in the DMMS Wave II dataset. Furthermore, the DMMS Wave II has more reliable comorbidity data based on chart review. Thus, the technique and database used for the current study enhance the reliability and generalizability of the results.
The results of this study should be interpreted in light of the following limitations. First, the timing of nephrology referral in DMMS Wave II was derived from a patient questionnaire and, thus, is subject to recall bias. Second, for the estimation of PS, the variables ideally should have been from the time of the first nephrology visit and not from the time of initiation of dialysis. However, most of the variables used for the estimation of PS, such as age, gender, race, insurance and educational status, would not be expected to change substantially from the first nephrology visit to the initiation of dialysis. Variables such as haematocrit and albumin, which could have been influenced by the nephrologist, were not used for the estimation of the PS. Third, it was possible to analyse outcomes only among patients who survived to or progressed to dialysis and, hence, our results only apply to patients who initiated dialysis. Finally, it is possible that the better outcome associated with ER might reflect initiation of dialysis at an earlier stage in the natural history of the disease rather than actually altering the course of the disease (lead-time bias). However, an attempt was made to overcome this bias by adjusting for level of GFR at the initiation of dialysis.
In conclusion, LR was found to be common in the US. Among patients with CKD who survived the first 60 days after initiation of dialysis, LR was associated with a higher risk of death in the first year and during overall follow-up after study start date, compared with patients with ER. Earlier referral of patients with a higher propensity for LR to a nephrologist may help improve outcomes in this era of increasing incidence of ESRD.
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Acknowledgments |
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Conflict of interest statement. None declared.
[See related article by Winkelmayer and Kurth (this issue, pp. 16711673)]
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References |
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