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Epidemiology and Outcomes |
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* Department of Pediatrics, Johns Hopkins Childrens Center, Baltimore,
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, and
The Welch Center for Prevention, Epidemiology & Clinical Research, Baltimore, Maryland;
National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland; || Montefiore Medical Center, Bronx, New York; ¶ Oregon Health & Science University, Portland, Oregon; ** University of Rochester, Rochester, New York; 
University of New Mexico, Albuquerque, New Mexico; and 
Childrens Mercy Hospital, Kansas City, Missouri
Address correspondence to: Dr. Susan L. Furth, The Johns Hopkins Medical Institutions, Departments of Pediatrics and Epidemiology, The Welch Center for Prevention, Epidemiology & Clinical Research, 2024 E. Monument Street, Baltimore MD, 21287. Phone: 410-502-7964; Fax: 410-614-3680; E-mail: sfurth{at}jhmi.edu
| Abstract |
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| Introduction |
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CKD in children carries a significant impact. The mortality that is associated with ESRD in children who receive dialysis is estimated to be at least 30 times higher than that in the general pediatric population (4). Unlike adults, who have completed their physiologic and intellectual maturation, children are in formative stages of development and therefore are particularly vulnerable to the adverse effects of CKD. Early detection and aggressive management have the potential to improve outcomes in young patients with CKD. Few sizable prospective studies of CKD in children have been performed (5,6), and relatively little is known about the natural history of early stages of CKD in this population.
With funding from the National Institute of Diabetes and Digestive and Kidney Diseases, in collaboration with the National Institute of Neurologic Disorders and Stroke, the National Institute of Child Health and Human Development and the National Heart, Lung, and Blood Institute, we have established a prospective cohort study of children with CKD, called the Chronic Kidney Disease in Children (CKiD) study. The specific aims of the CKiD study are to (1) identify novel and traditional risk factors for the progression of CKD; (2) characterize the impact of a decline in kidney function on neurodevelopment, cognitive abilities, and behavior; (3) identify the prevalence and the evolution of cardiovascular (CV) disease risk factors in children with CKD; and (4) examine the effects of declining GFR on growth and assess the consequences of growth failure on morbidity in children with CKD.
| Materials and Methods |
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Multicenter Study Coordination
To facilitate standardized data collection with a large number of active clinical sites and a complex study design with age- and gender-dependent measurements (e.g., ABPM cuff-size, intelligence tests, Tanner stage), we use interactive web-based visit schedules. These interactive visit schedules detail the questionnaires, examinations, and biologic samples that are required for a given child at a given study visit. In addition, training DVDs detailing study procedures are sent to study coordinators, and training meetings are held annually.
Study Follow-Up
Participants will be scheduled to return between 3 and 6 mo after study entry and on the anniversary of study enrollment thereafter. Participants will cease study visits after documented initiation of renal replacement therapy but will continue to be followed for clinical events and mortality by telephone contacts. Children with a high probability for ESRD (initiation of dialysis or transplantation) within the calendar year after a study visit (i.e., GFR <15 ml/min per 1.73 m2 or stage 5 CKD) will have their subsequent study visit accelerated to within 3 mo of the documentation of GFR <15 ml/min per 1.73 m2 to capture data before onset of ESRD and will have telephone follow-up every 6 mo to document the date of initiation of renal replacement therapy.
Table 3 depicts information to be obtained at baseline (i.e., follow-up month 0) and at each subsequent study visit. Tests are to be conducted on all cohort members, except when specifically targeted to a subcohort as noted in Table 3. Annually, study investigators conduct a physical examination and collect biologic specimens, and clinical site personnel assist the parent and the child to complete a set of questionnaires. For future studies, CKiD stores samples of serum, plasma, and urine as well as hair and fingernail clippings in a biosamples repository. In addition, to empower the study with a virtually inexhaustible supply of DNA, CKiD has requested that the National Institute of Diabetes and Digestive and Kidney Disease genetics repository create lymphocyte cell lines based on a sample of whole blood taken at the 6-mo visit. From annual blood and urine collection, we obtain centrally determined HPLC serum creatinine, renal panel, urine creatinine and protein, and local complete blood count and pregnancy tests.
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Three-day diet records and a child version of the Willett food frequency questionnaire (13) will be obtained on a yearly basis beginning at the second visit at 3 to 6 months (V1b). Children and parents are instructed on how to complete a consecutive 3-d 24-h recall food diary by study coordinators who have undergone training to standardize instructions.
Clinical BP is measured three times at one sitting during the study visit, and the mean of the systolic and diastolic BP will be used. Hypertension will be defined as outlined in "The Fourth Report on the Diagnosis, Evaluation, and Treatment of High BP in Children and Adolescents" (14). Other CV measurements, including echocardiography, ABPM (SpaceLabs 90217 device, Issaquah, WA), and carotid artery intima-media thickness, will be taken at the same visits as the iohexol GFR beginning in month 12. A battery of neurocognitive tests (Table 4) and measures of nutrition and bone health (e.g., intact parathyroid hormone) will be taken at the 3- to 6-mo follow-up visit and then in alternate years between iohexol-based GFR measurements. The parathyroid hormone assay that will be used is the Elecsys System 2010 (Roche Diagnostics, Mannheim, Germany), a one-step sandwich electrochemiluminescence immunoassay that is based on the streptavidin-biotin technology (15).
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Primary Outcomes
The primary outcome is the rate of decline of the biomarker GFR, which is measured repeatedly over time in cohort participants. Specifically, iohexol-based GFR will be measured every 2 yr, and Schwartz-based GFR will be assessed every year. A secondary outcome is the time to ESRD, defined by transplantation, dialysis, or a 50% decrease in GFR.
Statistical Analyses
The repeated assessment of growth and development (e.g., physical measures of height, weight, and Tanner staging), cognitive and behavioral function, and health-related quality of life will allow us to assess the trajectories of these measures in children with stable kidney function and in those with declining kidney function in this cohort. The prospective nature of the cohort design will allow us to analyze properly the effect of the exposure (i.e., decline in GFR) on growth rates, sexual development, gain in cognitive and developmental function, etc. This will allow the identification of the effect of progressive kidney disease on slowing growth and development trajectories in children with CKD.
| Results |
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An important issue of longitudinal data is the intrinsic dependence of the observations measured over time within individuals (1719). One approach to handle this dependence is to use generalized estimating equations (20). Alternatively, mixed-effects approaches (21) model the correlation of the repeated observations that are obtained over time for each individual. A key feature of such methods for longitudinal data is the ability to incorporate incomplete and unbalanced data (22). Classical methods of longitudinal analyses that weight individuals according to the number of data points contributed over time can be misleading. In particular, if we censor patients who progress quickly and proceed rapidly to ESRD, then it is possible that those who contribute the most data points would be those who decline the least, and, in turn, fast progressors may be underrepresented. Missing data methods may be tailored to account for such informative censoring (23,24).
Analysis of Time-to-Event Data
In the CKiD study, some time-to-event outcomes of potential interest are (1) stage 5 CKD (ESRD), (2) initiation of renal replacement therapy with dialysis or transplant, (3) a prespecified reduction (e.g., 50%) in GFR, and (4) incident hypertension. To study the natural history of CKD rather than anchor the analysis time scale as zero at the date of enrollment, we will anchor the time scale using birth or date of diagnosis of CKD obtained from medical records. Although children may be enrolled during roughly the same calendar period, construction of risk sets would account explicitly for the time since birth (i.e., age) or CKD diagnosis. Statistical methods to handle late entries will be used (25,26). Semiparametric survival methods, such as Cox proportional hazards regression, will be used to compare groups. However, parametric survival methods (2729) will be used to provide clinical insight about the underlying disease process.
For a cohort of children with CKD, time to transplantation and time to dialysis may act as competing risks. Common methods for handling competing risks are to (1) construct a combined end point (e.g., ESRD), (2) censor one type of risk while modeling the second type of risk, or (3) fit an explicit model for the competing risks. Although some key analyses will use a combined ESRD end point (option 1), use of competing risk models (option 3) likely will yield insight that is not gleaned from the analysis of the combined end point (30,31). For example, race may have differing effects on the time to transplantation and time to dialysis.
Analytic Methods of Nested Studies
It is anticipated that many hypotheses will involve highly expensive or time-consuming laboratory assays, such that it will not be possible to investigate these hypotheses in the full cohort. In such cases, it will be necessary to either (1) identify case patients and match them to control subjects on the basis of specific characteristics to perform nested case-control analysis or (2) select a subcohort in which to perform a case-cohort analysis (32). An example of a nested case-control study in CKiD would assess a novel biomarker for CKD progression among all case patients who develop ESRD with biosamples that previously were obtained in this cohort compared with a set of age- and gender-matched children who are free of ESRD. The nested design will allow efficient estimation of the association between the novel biomarker and development of ESRD by requiring the biomarker to be measured only in the case patients and a subset of, rather than all, control subjects.
Statistical Power
The primary scientific goal of the study is to determine risk factors for rapid decline of GFR. Combining the measured GFR with the eGFR on the basis of an internally derived formula will result in a database with yearly GFR measurements. Assuming a uniform enrollment rate over the course of 24 mo, we will expect to have 270 children with four visits and 270 with three visits. We assume 10, 5, and 5% will exit follow-up before visits 2, 3, and 4, respectively, as a result of dropout and incident ESRD.
The slope of GFR decline in a group with a particular risk factor, for example hypertension (the exposed group; i.e.
1), will be compared with the slope of GFR decline in the unexposed group without hypertension, for example (i.e.,
0). This ratio
1/
0 is the primary parameter for which the study is powered. Therefore, the primary hypothesis is whether
1/
0 = 1 (i.e., there is no risk for an accelerated decline associated with a putative exposure). We present statistical power curves for
1/
0 to be between 1.1 and 1.5 (i.e., an increase in the rate of decline as a result of the exposure from 10 to 50%), with a two-sided significance level of 5% (Figure 2). We assume that the SD of the baseline GFR is 12 ml/min per 1.73 m2 on the basis of data from the Modification of Diet in Renal Disease (MDRD) and the African American Study of Kidney Disease (AASK). An overall rate of decline of 5 ml/min per 1.73 m2 per year was assumed on the basis of NAPRTCS data (8). The three power curves in Figure 2 depict 20, 30, and 40% of the cohort being exposed. For a risk factor to which 40% are exposed, the study will have 80% power to detect an increase of 24% among the exposed (i.e., ratio of slopes = 1.24) when the overall rate of decline is 5 ml/min per 1.73 m2 per year.
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50% decline in GFR, or (3) decline of at least 25 ml/min per 1.73 m2, then a rate of 9 per 100 person-years among the unexposed may be more appropriate and greater statistical power will result under such a composite end point.
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| Discussion |
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The CKiD study has several design elements that are unique. Kidney function will be measured by blood clearance of iohexol annually for the first 2 yr and then every other year. The first two iohexol-based GFR measurements will provide a precise baseline value from which to assess decline in biannual iohexol-based GFR measurements. Because it forgoes the intrinsic variability and limitations of urinary clearances of inulin, iothalamate, and indirect measures of kidney function that are based on serum creatinine, the use of iohexol GFR measurement, as proposed in CKiD, has the potential to become the standard for a precise measurement of kidney function in large population studies (35).
Furthermore, every year, we have the standard creatinine-based GFR estimates that allow for developing equations between iohexol- and creatinine-based GFR measurements. Through comparison with iohexol GFR measurement, the CKiD cohort study will provide a unique opportunity to improve on the current limitations of creatinine-based estimates of GFR in longitudinal follow-up of children with increasing muscle mass as a result of growth and puberty. Currently, creatinine-based estimates of GFR using the Schwartz formula use a different coefficient for pubertal boys; however, this alternative coefficient frequently is applied at a chronologic age cutoff, rather than more specifically associated with pubertal development and muscle mass. Delayed puberty, which is common in adolescents with CKD, may result in striking differences in eGFR depending on which Schwartz coefficient is applied. With the incorporation of age, gender, Tanner staging, height, and creatinine, compared with iohexol GFR in the CKiD study, we expect to find a continuous formula to estimate GFR from a combination of these parameters. Such an equation will be the essential means to complete the iohexol-based GFR data every year. For such purposes, we apply standard statistical procedures of imputation of missing data. Our design of collecting data on all participants every other year is stronger than alternative designs of selecting subsets of the cohort to be measured every year.
There are a number of unique challenges in conducting a multicenter cohort study of children. In contrast to studies of adults, one must obtain consent from parents as proxies for their children, as well as obtain the participating childs assent. Obtaining consent for banking biologic and genetic materials from children and their parents is complex; for these specimens to remain in the repository, we may have to obtain consent for participation from children and adolescents when they turn 18 yr old.
In children, few large prospective cohort studies have addressed risk factors for CKD progression. High serum cholesterol (5), hyperlipidemia (3638), hypertension (39), proteinuria (40), and race and ethnicity (41) each have been associated with CKD progression. This cohort study, with standardized prospective measurements and precise measures of GFR, will allow refined assessment of the risk that is associated with these clinical findings in children.
The effects of CKD on neurodevelopment and cognitive function of children remain largely unknown, but age of CKD onset (42,43), duration of kidney failure (44,45), hypertension (46), anemia (4750), and depression (5153) have been associated with impairments in cognition and neurodevelopment. Furthermore, systematic assessment of nutritional status by measurement of growth parameters (height, weight, mid-upper arm circumference, pubertal development, and nutritional intake via 3 d diet history) and food frequency questionnaire will be collected to define further the influence of CKD on these parameters and the influence of these parameters on cognition and development.
A key strength of the CKiD study is the measurement of GFR in the entire cohort. Currently, the best clinical estimate of GFR used in children is the Schwartz formula. However, studies that describe the precision of the Schwartz formula show that only approximately 75% of estimates are within 30% of the GFR measured by inulin clearance (54). Formulas such as the Cockcroft-Gault equation (55) and the more recent MDRD equation (56), which are used to estimate GFR in adults, do not generalize to children (57). The study intends to develop a novel estimating equation for GFR in children.
The proposed infrastructure for the CKiD study can serve as a platform for ancillary research grants and career development awards to enhance the scientific output of the study. Serum, plasma, and urine will be collected so that future ancillary studies potentially can examine the role of cytokines and chemokines in CV disease, malnutrition, growth failure, and CKD progression. Lymphocyte cell lines will be generated to facilitate study of genetic predisposition to CKD progression. Successful study implementation will improve understanding of the physiologic, genetic, environmental, and socioeconomic factors that are associated with CKD progression and with the impact of neurocognitive and CV sequelae on the overall well-being of children. Finally, identification of modifiable risk factors for progressive CKD, neurocognitive deficits, and CV disease may lead to intervention trials to improve the health outcomes of children and adolescents with CKD.
| Acknowledgments |
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The CKiD prospective cohort study has clinical coordinating centers (principal investigators) at Childrens Mercy Hospital and the University of MissouriKansas City (Bradley Warady, MD) and Johns Hopkins School of Medicine (Susan Furth, MD, PhD), and data coordinating center (principal investigator) at the Johns Hopkins Bloomberg School of Public Health (Alvaro Muñoz, PhD).
We acknowledge the tireless efforts of the CKiD study coordinators: Judith Jerry-Fluker, MPH, Anne Carlson, MHS, Julie Starr, RN, Wendy Wantland, RN, Jacqueline Ndirangu, MPH, and Alicia Wentz, BS.
| Footnotes |
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Received December 2, 2005. Accepted May 16, 2006.
| References |
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