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Observational Research Databases in Renal Disease

Michael Shlipak^* and Catherine Stehman-Breen

^* General Internal Medicine Section, Veterans Affairs Medical Center, and Departments of Medicine, Epidemiology, and Biostatistics, University of California, San Francisco, San Francisco, California; and Amgen Inc., Thousand Oaks, California, and Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington

Address correspondence to: Dr. Catherine Stehman-Breen, Amgen Inc., One Amgen Center Drive, MS 38-3-C, Thousand Oaks, CA 91362. Phone: 805-447-7791; Fax: 805-498-0946; E-mail: cstehman{at}amgen.com

	Abstract

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Observational, patient-oriented research is a term that describes clinical or community-based studies in that they do not involve an experiment or intervention. Observational research studies can be designed and implemented by a primary data collection or using previously collected patient data. The latter is less expensive, although it has some distinct limitations. Many research databases are readily available and can be used to answer important questions that are relevant to kidney disease. This review summarizes the types of research analyses that can be conducted using existing databases, the types of research databases available, and a general approach for addressing a proposed research question using existing data.

	Introduction

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Observational, patient-oriented research is a broad term used to describe clinical studies that do not involve an experiment or intervention, in contrast to clinical trials. The traditional study designs of epidemiology—case series, cross-sectional analysis, case-control, and cohort studies—all are examples of observational research. Observational research studies can be designed and implemented by a primary data collection, meaning that the investigator recruits the subjects and conducts the measurements by him- or herself. However, data collection is an expensive and lengthy process that limits the feasibility of addressing many research questions and would hinder many potential investigators from engaging in research.

A more feasible approach to addressing a research question is to use previously collected patient data so that the project can proceed straight to data analysis. Whereas this approach may seem somewhat utopian, a multitude of research databases that can be used to answer important questions that are relevant to kidney disease are currently in existence. The purpose of this review is to discuss (1) the types of research analyses that can be conducted using existing data; (2) the types of research databases that are available, examples of each, and their strengths and weaknesses; and (3) a general process for addressing a research question using an existing data source.

	Questions that Can Be Answered with Existing Data

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Observational research studies are often categorized into topics such as epidemiology, outcomes research, and health services research. All of these types of research questions related to kidney disease can be addressed using existing research databases. The distinction between these categories of research is largely based on the focus of the research question, although the actual methods often overlap.

Epidemiology is the study of the occurrence and distribution of diseases and other health-related conditions in human populations and the risk factors that determine disease risk. Epidemiologic research questions can be either descriptive or analytic. Descriptive studies are used to determine prevalence and incidence of diseases and their trends over time. Examples could include studies that demonstrate the rising incidence of ESRD over the past few decades and the disproportionate impact on people with diabetes and the elderly.

More often, epidemiologic studies are undertaken to identify the causes of disease. This approach typically involves "analytic studies" to determine whether a risk factor is an independent determinant of disease and collectively to evaluate causal relationships. A potential example of a research question, testable using existing databases, could evaluate determinants of chronic kidney disease (CKD) incidence and progression, such as dietary factors, smoking, or lipoprotein levels.

Outcomes research is a relatively new term in clinical research that refers to the study of health outcomes that are relevant to patients. Such outcomes often include clinical events, such as graft survival after kidney transplant or recurrence of heart failure. However, relevant health outcomes also include health-related quality of life, mental health, and cognitive function, which are areas of growing interest in nephrology research. Each of these outcomes is available in certain clinical cohorts. Interesting and publishable research questions can be descriptive (e.g., the prevalence of depression in patients with CKD) or analytic (e.g., determinants of survival after kidney transplantation).

Health services research broadly refers to the study of health care delivery and the factors that affect the quality of health care. Such questions could include access to health care, costs and cost-effectiveness of health care interventions, utilization of proven therapies and procedures, and regional variation in health care delivery and outcomes.

In clinical nephrology, many of these health services research questions that can be addressed using existing databases. For example, previous studies have evaluated the rates of transplantation among racial subgroups with ESRD; utilization of angiotensin-converting enzyme inhibitors in people with diabetic nephropathy could be evaluated as a well as the determinants of their use; and the health care costs related to CKD could be studied, as well as the proportion attributable to cardiovascular disease.

This summary and these examples are meant to provide snapshots of the wide variety of relevant research questions that can be addressed using existing databases. The next section discusses the types of databases that can be accessed by interested investigators and their relative suitability for addressing questions related to epidemiology, outcomes research, and health services research.

	Observational Cohorts

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Administrative Databases
One potential source for observational research is an administrative database. The term administrative database refers to information collected for the purpose of clinical care rather than data collected for research purposes. Administrative databases may range from a single clinical practice to national health care databases or insurance health plans. The completeness of administrative databases depends on the range of clinical information that is linked together. These may include any combination of the following information: Demographic characteristics, laboratory measures, comorbidity information, medication use, clinic visits, hospitalizations, cost of care, and survival.

The primary strengths of administrative databases are typically their generalizability and large size. Although it may be costly to link together the various components of an administrative database, it is far less expensive than a primary data collection. The major limitation is that the data were not collected for the purpose of research; therefore, it might be impossible to validate their accuracy, so it is important for the investigator to evaluate critically the accuracy of the predictors and outcomes of his or her study. If the investigator is not confident of the accuracy of a particular variable (e.g., capture of ESRD outcomes) within the data set, then it should not be used.

An example of a health care organization that has linked together all of these types of information is the Kaiser Permanente Renal Study of the Kaiser of Northern California Division of Research. The Kaiser Permanente Renal Study is a unique administrative cohort because it combines so many elements of clinical care, including demographic characteristics, medication use, laboratory measurements, in-hospital survival, and cost of care. Characteristics are updated throughout the follow-up period, so changes in creatinine can be tracked longitudinally. The source population is the Kaiser Permanente Health Care System, which is diverse and includes a large number of black individuals, white individuals, Hispanic Americans, and Asian Americans. An additional unique attribute to this database is that it includes >1 million people who were followed for several years. A major paper from the cohort is by Go et al. (1), which reported a strong association of CKD with cardiovascular outcomes.

Population Surveys
Population surveys are active clinical research studies that are designed to understand the prevalence of risk factors and diseases in a population. Population surveys have been conducted for many years. The National Health and Nutrition Examination Surveys (NHANES I, II, III, and IV) have been conducted at intervals of approximately one per decade by the Centers for Disease Control and Prevention’s National Center for Heath Statistics and have tracked the prevalence of both CKD and its risk factors over the course of each survey. The NHANES studies are predominantly for cross-sectional analyses, although limited comorbidity and mortality follow-up are available from NHANES I, II, and III. Another population survey that is relevant to kidney disease is the Prevention of Renal and Vascular End Stage Disease study from the Netherlands.

The primary advantages of the NHANES surveys are their rigorous sampling strategies, their systematic data collection, and the weighting of the survey so that it approximates the US population. Disadvantages include their predominantly cross-sectional design; as a result, causal relationships between renal function and most disease outcomes cannot be studied. In addition, the earlier NHANES surveys were conducted many years ago, and the generalizability to current populations may be limited. In addition, there is public access to the data, which means that multiple research groups could investigate and publish articles that address the same research question. Although this has the advantage of allowing greater access to data to answer one’s hypotheses, it can result in large amounts of work being lost if other groups publish similar results first.

Many cross-sectional studies have evaluated correlations of CKD in NHANES III. Coresh et al. (2) evaluated BP control among Americans with CKD. A subsequent paper evaluated trends in prevalence of CKD over several decades in the United States, using the NHANES survey (3). Others have evaluated physiologic correlations of CKD, including inflammation, metabolic syndrome, and anemia (4–6).

	Longitudinal Cohorts

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Several community-based cohort studies have been funded by the National Institutes of Heath and other funding agencies. These studies have the ability to evaluate renal function and progression of disease. The National Heart, Lung, and Blood Institute has funded several cohort studies that have provided important insights in kidney disease. These cohorts include the Framingham Heart Study, Cardiovascular Heath Study (CHS), Atherosclerosis Risk in Communities study (ARIC) and the Coronary Artery Risk Development in Young Adults study (CARDIA). The last three recruited participants with distinct age groups at entry: CHS included people who were older than 65 yr, ARIC enrolled adults aged 45 to 64 yr, and CARDIA targeted young adults aged 18 to 30 yr.

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) has supported several cohort studies in clinical populations with kidney disease. These studies include the Choices for Healthy Outcomes in Caring for End-Stage Renal Disease (CHOICE) Cohort Study, a national prospective cohort study of incident dialysis patients initiated in 1995 to investigate the association of treatment choices of modality and dose with outcomes of dialysis care, and the Epidemiology of Diabetes Interventions and Complications (EDIC) study, an observational study that was designed to follow participants from the Diabetes Control and Complications Trial (DCCT) to determine the long-term effects of glycemic control on micro- and macrovascular outcomes. Each of these studies has played an important role in our understanding of CKD.

The advantages of clinical cohorts include their rigorous and systematic data collection; focus on novel, uniformly conducted measurements for research; systematic adjudication of clinical outcomes by trained reviewers; and specimens that have been collected and stored for future measurements. The primary weakness of this type of study is the potential for systematic differences between volunteers in the study and the general population. As with clinical trials, recruits into a clinical cohort may be fundamentally different from people who refuse to join. Another major limitation for studies that recruit populations of people who have CKD that does not require dialysis is that these cohorts are not large enough to accrue many ESRD outcomes.

Investigators from CHS have conducted both cross-sectional and longitudinal analyses to evaluate the impact of CKD on outcomes ranging from death, cardiovascular disease events, and incident heart failure (7–9). This study now includes measures of both creatinine and cystatin-C, so their relative associations with cardiovascular outcomes can be compared. The ARIC investigators have evaluated associations of CKD with the outcomes of subclinical and clinical cardiovascular disease in a middle-aged population (10). The unique aspect of CARDIA is that the study will detect incident kidney disease and its attendant risk factors (11).

Investigators from CHOICE have assessed factors that predict choice of dialysis modality and assessed predictors of cardiovascular outcomes among dialysis patients (12,13). This study is unique in developing a health-related quality-of-life measure specifically for ESRD, called The CHOICE Health Experience Questionnaire (14). The DCCT was an intervention trial that demonstrated a significant impact of glycemic control on the early markers of microvascular complications. The EDIC study continued to follow a cohort of >1400 patients who participated in the DCCT to determine the long-term effects of previous separation of glycemic levels on micro- and macrovascular outcomes. One important finding from this study was that the positive effects of tight glycemic control on albumin excretion during the DCCT persisted even 7 to 8 yr after the end of the trial, suggesting that previous intensive treatment of diabetes has a prolonged benefit in delaying progression of diabetic nephropathy (15). The unique aspect of the EDIC study is its ability to observe early diabetic nephropathy over an extended period of time.

Two new cohorts of patients with CKD are currently being launched by the NIDDK. The Chronic Renal Insufficiency Cohort will enroll 3000 participants with kidney dysfunction with a target population composed of balanced proportions of black and white Americans and participants with and without diabetes. The study will have a longitudinal follow-up with primary outcome end points of cardiovascular and kidney disease progression. This study plans to complete enrollment in 2006. The other new cohort, entitled the Family Investigation of Nephropathy of Diabetes consortium, is a genetic-based study with the goal of identifying genetic pathways that are critical for the development of diabetic nephropathy. This study’s recruitment goals include 2000 pairs of siblings for a family-based study and 1500 case patients and control subjects for an association study that included various ethnicities.

	Registries

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A registry typically refers to a compilation of clinical information on individuals with a specific disease. These studies usually involve a medical record abstraction to obtain relevant information on each patient. Registries vary on their length of follow-up and outcomes. The strengths of a registry are that they typically are generalizable and may show temporal patterns in clinical disease and outcomes. They are usually very large but may be limited in the amount of data obtained for each individual. Some of these are supported by funds from the Centers for Medicare and Medicaid Services, whereas others are funded by industry.

Several registries that are relevant to kidney disease are available, including large registries of patients with ESRD, myocardial infarction, and heart failure. The Centers for Medicare and Medicaid Services has established a myocardial infarction registry and a heart failure inpatient registry. Each of these has mortality follow-up for 1 yr. The Cooperative Cardiovascular Project and the National Heart Care registries have been used to evaluate the quality of care and outcomes of patients with myocardial infarction and heart failure complicated by CKD or ESRD (16,17).

Perhaps the most widely known registry in kidney disease is the United States Renal Data System (USRDS), a national data system that collects information about ESRD in the United States (www.usrds.org). The USRDS is funded by the NIDDK. The USRDS contains core date including demographics, comorbidities, survival, and health resource utilization. In addition, the USRDS contains data from several completed and four ongoing special studies that focus on particular aspects of renal disease. Also available through the USRDS is the Clinical Performance Measures Project data, which contain information on the quality of care provided to the ESRD dialysis patient. The data originate from yearly surveys completed by dialysis units and have been linked to USRDS data, providing a rich source of detailed information. Data from the USRDS have been used in hundreds of publications and have addressed issues related to epidemiology, outcomes, and health services research. Examples include the effect of use or nonuse of long-term dialysis on subsequent survival of renal transplants from living donors (18), survival after acute myocardial infarction on dialysis (19), and hip fracture outcomes in dialysis and transplant patients (20). Because >90% of all dialysis patients in the United States are eligible for Medicare coverage, this database is unique because it contains data on almost all dialysis patients who are treated in the United States.

The Dialysis Outcomes and Practice Patterns Study is an additional registry (21). It is a prospective, longitudinal, observational study of hemodialysis patients and facilities in 12 countries. The goal of the study is to determine which practice patterns are associated with the best patient outcomes. This registry is the only prospective international study in dialysis that allows interesting observations across geographic regions.

	Clinical Trials

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Once a clinical trial has been completed, the information collected may be used for observational research, which is independent of the original trial design. For example, a clinical trial that is designed to evaluate the effect of an antihypertensive agent on kidney disease progression could look at other determinants of progression as well. Many clinical trials in kidney disease or cardiovascular disease have been used subsequently to answer observational research questions that are relevant to kidney disease. The strengths of a clinical trial for use in observational research are that data are typically collected rigorously and outcome ascertainment is generally complete. Some of the trials may also contain stored specimens for future measurements. The primary limitation of the clinical trial is that the subjects who volunteer to be randomly assigned to a clinical trial may be fundamentally different from the general population.

Clinical trials often have been conducted to include patients with and without kidney disease. Consequently, several investigators have written papers to evaluate whether the particular intervention (drug or procedure) is equally efficacious in the subgroups with and without kidney disease. For example, investigators have confirmed that the benefits of pravastatin in the Cholesterol and Recurrent Events trial seemed similar in individuals with and without CKD, as were the benefits for ramipril in the Heart Outcomes and Prevention Evaluation trial (22,23).

Clinical trials that have been conducted in patients with kidney disease have particularly good potential for observational research. Examples include the Modification of Diet in Renal Disease study of patients with nondiabetic CKD, the Reduction of Endpoints in NIDDM with Angiotensin II Antagonist Losartan study, and the Irbesartan Diabetic Nephropathy Trial in patients with diabetic nephropathy and the Hemodialysis Study in patients with end stage renal disease. For example, investigators from the Modification of Diet in Renal Disease trial conducted an observational analysis to evaluate the most important predictors of declining GFR (24). In the Reduction of Endpoints in NIDDM with Angiotensin II Antagonist Losartan trial, De Zeeuw et al. (25,26) evaluated the importance of changes in albuminuria levels as determinants of cardiovascular and renal outcomes. In the Hemodialysis Study, investigators assessed the impact of hemodialysis dose and membrane flux on quality of life (27). These are examples of how observational research studies have complemented the original randomized comparisons of a clinical trial.

The studies described in this section are a few among the many databases that are available for analysis. Table 1 summarizes characteristics of many of the available databases, but it is not an exhaustive list, and many important studies may have been omitted inadvertently.

	How to Access Data for Observational Research

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The first step to conducting observational research is to develop an interesting research question. The young investigator should craft the research question with guidance from a mentor to ensure that it is feasible, interesting, and clinically relevant. The best research questions are interesting regardless of whether the association is "positive." In other words, whether the hypothesized predictor is significantly associated with the study outcome or not, the findings should be interesting and publishable. After identifying the research question, the investigator should review the studies listed in Table 1 (or other studies identified by a mentor) to find the cohort(s) most suitable to answer the question. The next step then is to contact an investigator from the study.

Some studies, particularly those funded by the National Institutes of Health or other government institutions, will have a web site that specifically details a mechanism for outside investigators to propose ideas for manuscripts. These studies will often pair the new investigator with a collaborating investigator who is knowledgeable with that cohort. Other studies will have a less formal process, and the new investigator should contact either the primary investigator of the study or an investigator who has previously published on kidney-related topics from that study. In either case, it is a good idea to carefully review previous studies from that cohort to ensure that the proposed research question is feasible and has not already been addressed.

Finally, investigators may be concerned that their research idea will be appropriated by the cohort study without the investigator’s involvement. In our experience, this is highly unusual as academic medicine is a small community and investigators are typically both genuine in their integrity and protective of their reputation. Usually, the investigator who proposes the idea not only should be allowed to pursue the project but also should be the lead author on the manuscript. Always discuss issues of author order in the earliest stages of the project development.

	Guidelines for Accessing Epidemiologic Data

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Although each data set has unique guidelines for accessing data, there are some general principles that can be applied to accessing virtually all databases. The most critical first step is to develop a general research hypothesis. Developing a sound research hypothesis helps to narrow the choice of databases. Once the hypothesis is generated, it is important to learn as much as possible about several data sets to ensure that the most appropriate data set is chosen. A variety of mechanisms provide insight into data elements, including reviewing predictors and outcomes used in previous publications. General information about a variety of data sets is provide in Table 1. Most large observational studies have web sites that are a rich source of information. Information found on the web sites includes the focus of study, a summary of data elements, instructions for accessing data, Steering Committee members, and previous publications. Information from the web site can be used to refine the research hypothesis and determine the best approach for gaining permission to use the data. It is important to note that some studies have both publicly available data sets that are often provided, with few limitations, on a CD-ROM and data that only available are through a more formal mechanism that is controlled by a publications committee. Often, the data that are available publicly are truncated to protect subject privacy and may not be as current as data that are available directly through the coordinating center.

When using a data set with which one is unfamiliar, it is often helpful to identify a collaborator who has familiarity with the data. Collaborators can include members of the Steering Committee with expertise in the area of interest, an investigator at one’s own institution who has used the data set before, or a Working Group that has been formed by the study’s leadership group to strengthen investigation in a particular area. The web site and publications can assist you in identifying such individuals. Our experience has been that contacting potential collaborators is very positive and provides additional useful information regarding not only the most appropriate collaborators but also insight into the current research direction of the study, potential funding mechanisms, and historical information that can assist in the most strategic approach for moving forward.

Once the research question has been refined, it is also important to consider the mechanism of analytic support. It is important to consider the statistical expertise of the investigator when considering the most appropriate database to use. The databases vary in degree of complexity, and for some data sets, analyses may be beyond the expertise of the investigator. If this is the case, then statistical support may be provided by the coordinating center if the study is large enough. However, there is often a priority score given to paper proposals that determines the order in which the coordinating center will conduct the analysis. Building a relationship with a member of the study’s leadership group may provide guidance in the development of the proposal that may optimize the priority score that the study receives. It has been our experience that these insights are invaluable.

For many studies, gaining approval for a paper proposal involves submitting a proposal to a review group. Instructions are typically found on the study’s web site. The process can be as informal as getting approval from the principal investigator or as complicated as submission to a formal Publications and Planning Committee. The more formal process can take a month or more to receive approval, so it is important to plan carefully. Although investigators may have concerns that an idea may be stolen, it has been our experience that this is uncommon. The Publications and Planning Committees typically provide excellent guidance and insight, allowing for a stronger approach.

	Conclusions

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Observational research is a broad term that describes analytic studies in epidemiology, outcomes research, and health services research. Many important research questions in clinical nephrology require observational research designs, as they cannot be tested by clinical trials. Often the most feasible, cost-effective method for addressing these hypotheses is to use an existing research dataset. Many observational research studies have been used in clinical nephrology, and most remain available for new investigators. Broadly, we have classified the types of available research datasets into administrative studies, population surveys, longitudinal cohorts, disease-specific registries, and clinical trials. We strongly encourage new investigators to develop a novel research hypothesis with input from mentors or colleagues, identify the optimal dataset to answer the question, and submit a research proposal to the leadership of that study. This process of establishing new collaborations to answer a research question and to publish its findings can be one of the best rewards of a career in patient-oriented research.

	Acknowledgments

 
We thank Melanie Praught, MS, for extensive work in support of this manuscript. M.S.’s work on this paper was supported by RO1 DK066488-01, the American Federation for Aging Research and National Institute on Aging (Paul Beeson Scholars Program), and the Robert Wood Johnson Foundation (Generalist Faculty Scholars Program).

	Footnotes

 
Published online ahead of print. Publication date available at www.jasn.org.

	References

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1. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY: Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med351 :1296 –1305,2004[Abstract/Free Full Text]
2. Coresh J, Wei GL, McQuillan G, Brancati FL, Levey AS, Jones C, Klag MJ: Prevalence of high blood pressure and elevated serum creatinine level in the United States: Findings from the Third National Health and Nutrition Examination Survey (1988–1994). Arch Intern Med161 :1207 –1216,2001[Abstract/Free Full Text]
3. Coresh J, Byrd-Holt D, Astor BC, Briggs JP, Eggers PW, Lacher DA, Hostetter TH: Chronic kidney disease awareness, prevalence, and trends among US adults, 1999 to 2000. J Am Soc Nephrol16 :180 –188,2005[Abstract/Free Full Text]
4. Muntner P, Hamm LL, Kusek JW, Chen J, Whelton PK, He J: The prevalence of nontraditional risk factors for coronary heart disease in patients with chronic kidney disease. Ann Intern Med140 :9 –17,2004[Abstract/Free Full Text]
5. Chen J, Muntner P, Hamm LL, Jones DW, Batuman V, Fonseca V, Whelton PK, He J: The metabolic syndrome and chronic kidney disease in US adults. Ann Intern Med140 :167 –174,2004[Abstract/Free Full Text]
6. Hsu CY, McCulloch CE, Curhan GC: Epidemiology of anemia associated with chronic renal insufficiency among adults in the United States: Results from the Third National Health and Nutrition Examination Survey. J Am Soc Nephrol13 :504 –510,2002[Abstract/Free Full Text]
7. Sarnak MJ, Katz R, Stehman-Breen CO, Fried LF, Jenny NS, Psaty BM, Newman AB, Siscovick D, Shlipak MG; Cardiovascular Health Study: Cystatin C concentration as a risk factor for heart failure in older adults. Ann Intern Med142 :497 –505,2005[Abstract/Free Full Text]
8. Shlipak MG, Sarnak MJ, Katz R, Fried LF, Seliger SL, Newman AB, Siscovick DS, Stehman-Breen C: Cystatin C and the risk of death and cardiovascular events among elderly persons. N Engl J Med352 :2049 –2060,2005[Abstract/Free Full Text]
9. Fried LF, Shlipak MG, Crump C, Bleyer AJ, Gottdiener JS, Kronmal RA, Kuller LH, Newman AB: Renal insufficiency as a predictor of cardiovascular outcomes and mortality in elderly individuals. J Am Coll Cardiol41 :1364 –1372,2003[Abstract/Free Full Text]
10. Muntner P, He J, Astor BC, Folsom AR, Coresh J: Traditional and nontraditional risk factors predict coronary heart disease in chronic kidney disease: Results from the atherosclerosis risk in communities study. J Am Soc Nephrol16 :529 –538,2005[Abstract/Free Full Text]
11. Stehman-Breen CO, Gillen D, Steffes M, Jacobs DR Jr, Lewis CE, Kiefe CI, Siscovick D: Racial differences in early-onset renal disease among young adults: The coronary artery risk development in young adults (CARDIA) study. J Am Soc Nephrol14 :2352 –2357,2003[Abstract/Free Full Text]
12. Longenecker JC, Coresh J, Marcovina SM, Powe NR, Levey AS, Giaculli F, Fink NE, Klag MJ: Lipoprotein(a) and prevalent cardiovascular disease in a dialysis population: The Choices for Healthy Outcomes in Caring for ESRD (CHOICE) study. Am J Kidney Dis42 :108 –116,2003[CrossRef][Medline]
13. Miskulin DC, Meyer KB, Athienites NV, Martin AA, Terrin N, Marsh JV, Fink NE, Coresh J, Powe NR, Klag MJ, Levey AS: Comorbidity and other factors associated with modality selection in incident dialysis patients: The CHOICE Study. Choices for Healthy Outcomes in Caring for End-Stage Renal Disease. Am J Kidney Dis39 :324 –336,2002[Medline]
14. Wu AW, Fink NE, Cagney KA, Bass EB, Rubin HR, Meyer KB, Sadler JH, Powe NR: Developing a health-related quality-of-life measure for end-stage renal disease: The CHOICE Health Experience Questionnaire. Am J Kidney Dis37 :11 –21,2001[Medline]
15. Writing Team for the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group: Sustained effect of intensive treatment of type 1 diabetes mellitus on development and progression of diabetic nephropathy: The Epidemiology of Diabetes Interventions and Complications (EDIC) study. JAMA290 :2159 –2167,2003[Abstract/Free Full Text]
16. Shlipak MG, Heidenreich PA, Noguchi H, Chertow GM, Browner WS, McClellan MB: Association of renal insufficiency with treatment and outcomes after myocardial infarction in elderly patients. Ann Intern Med137 :555 –562,2002[Abstract/Free Full Text]
17. Chertow GM, Normand SL, McNeil BJ: "Renalism": Inappropriately low rates of coronary angiography in elderly individuals with renal insufficiency. J Am Soc Nephrol15 :2462 –2468,2004[Abstract/Free Full Text]
18. Mange KC, Joffe MM, Feldman HI: Effect of the use or nonuse of long-term dialysis on the subsequent survival of renal transplants from living donors. N Engl J Med344 :726 –731,2001[Abstract/Free Full Text]
19. Herzog CA, Ma JZ, Collins AJ: Poor long-term survival after acute myocardial infarction among patients on long-term dialysis. N Engl J Med339 :799 –805,1998[Abstract/Free Full Text]
20. Ball AM, Gillen DL, Sherrard D, Weiss NS, Emerson SS, Seliger SL, Kestenbaum BR, Stehman-Breen C: Risk of hip fracture among dialysis and renal transplant recipients. JAMA288 :3014 –3018,2002[Abstract/Free Full Text]
21. Pisoni RL, Gillespie BW, Dickinson DM, Chen K, Kutner MH, Wolfe RA: The Dialysis Outcomes and Practice Patterns Study (DOPPS): Design, data elements, and methodology. Am J Kidney Dis44[Suppl 3] :7 –15,2004[CrossRef]
22. Tonelli M, Moye L, Sacks FM, Cole T, Curhan GC: Effect of pravastatin on loss of renal function in people with moderate chronic renal insufficiency and cardiovascular disease. J Am Soc Nephrol14 :1605 –1613,2003[Abstract/Free Full Text]
23. Mann JF, Gerstein HC, Pogue J, Bosch J, Yusuf S: Renal insufficiency as a predictor of cardiovascular outcomes and the impact of ramipril: The HOPE randomized trial. Ann Intern Med134 :629 –636,2001[Abstract/Free Full Text]
24. Hunsicker LG, Adler S, Caggiula A, England BK, Greene T, Kusek JW, Rogers NL, Teschan PE: Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study. Kidney Int51 :1908 –1919,1997[Medline]
25. de Zeeuw D, Remuzzi G, Parving HH, Keane WF, Zhang Z, Shahinfar S, Snapinn S, Cooper ME, Mitch WE, Brenner BM: Proteinuria, a target for renoprotection in patients with type 2 diabetic nephropathy: Lessons from RENAAL. Kidney Int65 :2309 –2320,2004[CrossRef][Medline]
26. de Zeeuw D, Remuzzi G, Parving HH, Keane WF, Zhang Z, Shahinfar S, Snapinn S, Cooper ME, Mitch WE, Brenner BM: Albuminuria, a therapeutic target for cardiovascular protection in type 2 diabetic patients with nephropathy. Circulation.110 :921 –927,2004[Abstract/Free Full Text]
27. Unruh M, Benz R, Greene T, Yan G, Beddhu S, DeVita M, Dwyer JT, Kimmel PL, Kusek JW, Martin A, Rehm-McGillicuddy J, Teehan BP, Meyer KB; HEMO Study Group: Effects of hemodialysis dose and membrane flux on health-related quality of life in the HEMO Study. Kidney Int66 :355 –366,2004[CrossRef][Medline]
28. Kestenbaum B, Sampson JN, Rudser KD, Patterson DJ, Seliger SL, Young B, Sherrard DJ, Andress DL: Serum phosphate levels and mortality risk among people with chronic kidney disease. J Am Soc Nephrol16 :520 –528,2005[Abstract/Free Full Text]
29. Ofsthun N, Labrecque J, Lacson E, Keen M, Lazarus JM: The effects of higher hemoglobin levels on mortality and hospitalization in hemodialysis patients. Kidney Int63 :1908 –1914,2003[CrossRef][Medline]
30. Diercks GF, Janssen WM, van Boven AJ, Bak AA, de Jong PE, Crijns HJ, van Gilst WH: Rationale, design, and baseline characteristics of a trial of prevention of cardiovascular and renal disease with fosinopril and pravastatin in nonhypertensive, nonhypercholesterolemic subjects with microalbuminuria (the Prevention of REnal and Vascular ENdstage Disease Intervention Trial [PREVEND IT]). Am J Cardiol86 :635 –638,2000[CrossRef][Medline]
31. Pinto-Sietsma SJ, Mulder J, Janssen WM, Hillege HL, de Zeeuw D, de Jong PE: Smoking is related to albuminuria and abnormal renal function in nondiabetic persons. Ann Intern Med133 :585 –591,2000[Abstract/Free Full Text]
32. Perneger TV, Klag MJ, Feldman HI, Whelton PK: Projections of hypertension-related renal disease in middle-aged residents of the United States. JAMA269 :1272 –1277,1993[Abstract/Free Full Text]
33. Powe NR, Tarver-Carr ME, Eberhardt MS, Brancati FL: Receipt of renal replacement therapy in the United States: A population-based study of sociodemographic disparities from the Second National Health and Nutrition Examination Survey (NHANES II). Am J Kidney Dis42 :249 –255,2003[CrossRef][Medline]
34. Nickolas TL, Frisch GD, Opotowsky AR, Arons R, Radhakrishnan J: Awareness of kidney disease in the US population: Findings from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2000. Am J Kidney Dis44 :185 –197,2004[CrossRef][Medline]
35. Curhan GC, Willett WC, Speizer FE, Spiegelman D, Stampfer MJ: Comparison of dietary calcium with supplemental calcium and other nutrients as factors affecting the risk for kidney stones in women. Ann Intern Med126 :497 –504,1997[Abstract/Free Full Text]
36. Knight EL, Rimm EB, Pai JK, Rexrode KM, Cannuscio CC, Manson JE, Stampfer MJ, Curhan GC: Kidney dysfunction, inflammation, and coronary events: A prospective study. J Am Soc Nephrol15 :1897 –1903,2004[Abstract/Free Full Text]
37. Curhan GC, Willett WC, Rimm EB, Stampfer MJ: Family history and risk of kidney stones. J Am Soc Nephrol8 :1568 –1573,1997[Abstract]
38. Fried LP, Borhani NO, Enright P, Furberg CD, Gardin JM, Kronmal RA, Kuller LH, Manolio TA, Mittelmark MB, Newman A, et al.: The Cardiovascular Health Study: Design and rationale. Ann Epidemiol1 :263 –276,1991[Medline]
39. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, Greenland P, Jacob DR Jr, Kronmal R, Liu K, Nelson JC, O’Leary D, Saad MF, Shea S, Szklo M, Tracy RP: Multi-ethnic study of atherosclerosis: Objectives and design. Am J Epidemiol156 :871 –881,2002[Abstract/Free Full Text]
40. Field TS, Gurwitz JH, Glynn RJ, Salive ME, Gaziano JM, Taylor JO, Hennekens CH: The renal effects of nonsteroidal anti-inflammatory drugs in older people: Findings from the Established Populations for Epidemiologic Studies of the Elderly. J Am Geriatr Soc47 :507 –511,1999[Medline]
41. Kurella M, Chertow GM, Fried LF, Cummings SR, Harris T, Simonsick E, Satterfield S, Ayonayon H, Yaffe K: Chronic kidney disease and cognitive impairment in the elderly: The health, aging, and body composition study. J Am Soc Nephrol16 :2127 –2133,2005[Abstract/Free Full Text]
42. Odden MC, Whooley MA, Shlipak MG: Association of chronic kidney disease and anemia with physical capacity: The heart and soul study. J Am Soc Nephrol15 :2908 –2915,2004[Abstract/Free Full Text]
43. Knowler WC, Coresh J, Elston RC, Freedman BI, Iyengar SK, Kimmel PL, Olson JM, Plaetke R, Sedor JR, Seldin MF; Family Investigation of Nephropathy and Diabetes Research Group: The Family Investigation of Nephropathy and Diabetes (FIND): Design and methods. J Diabetes Complications19 :1 –9,2005[Medline]
44. Wheeler DC, Townend JN, Landray MJ: Cardiovascular risk factors in predialysis patients: Baseline data from the Chronic Renal Impairment in Birmingham (CRIB) study. Kidney Int Suppl84 :S201 –S203,2003
45. Feldman HI, Appel LJ, Chertow GM, Cifelli D, Cizman B, Daugirdas J, Fink JC, Franklin-Becker ED, Go AS, Hamm LL, He J, Hostetter T, Hsu CY, Jamerson K, Joffe M, Kusek JW, Landis JR, Lash JP, Miller ER, Mohler ER 3rd, Muntner P, Ojo AO, Rahman M, Townsend RR, Wright JT; Chronic Renal Insufficiency Cohort (CRIC) Study Investigators: The Chronic Renal Insufficiency Cohort (CRIC) Study: Design and methods. J Am Soc Nephrol14[Suppl 2] :S148 –S153,2003
46. Havranek EP, Masoudi FA, Westfall KA, Wolfe P, Ordin DL, Krumholz HM: Spectrum of heart failure in older patients: Results from the National Heart Failure project. Am Heart J143 :412 –417,2002[CrossRef][Medline]
47. Canto JG, Shlipak MG, Rogers WJ, Malmgren JA, Frederick PD, Lambrew CT, Ornato JP, Barron HV, Kiefe CI: Prevalence, clinical characteristics, and mortality among patients with myocardial infarction presenting without chest pain. JAMA283 :3223 –3229,2000[Abstract/Free Full Text]
48. Fonarow GC, Adams KF Jr, Abraham WT, Yancy CW, Boscardin WJ: Risk stratification for in-hospital mortality in acutely decompensated heart failure: Classification and regression tree analysis. JAMA293 :572 –580,2005[Abstract/Free Full Text]
49. Schaeffner ES, Kurth T, Curhan GC, Glynn RJ, Rexrode KM, Baigent C, Buring JE, Gaziano JM: Cholesterol and the risk of renal dysfunction in apparently healthy men. J Am Soc Nephrol14 :2084 –2091,2003[Abstract/Free Full Text]
50. Rahman M, Pressel S, Davis BR, Nwachuku C, Wright JT Jr, Whelton PK, Barzilay J, Batuman V, Eckfeldt JH, Farber M, Henriquez M, Kopyt N, Louis GT, Saklayen M, Stanford C, Walworth C, Ward H, Wiegmann T: Renal outcomes in high-risk hypertensive patients treated with an angiotensin-converting enzyme inhibitor or a calcium channel blocker vs a diuretic: A report from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). Arch Intern Med165 :936 –946,2005[Abstract/Free Full Text]
51. Rodby RA, Rohde RD, Clarke WR, Hunsicker LG, Anzalone DA, Atkins RC, Ritz E, Lewis EJ: The Irbesartan type II diabetic nephropathy trial: Study design and baseline patient characteristics. For the Collaborative Study Group. Nephrol Dial Transplant15 :487 –497,2000[Abstract/Free Full Text]
52. Lewis EJ, Hunsicker LG, Clarke WR, Berl T, Pohl MA, Lewis JB, Ritz E, Atkins RC, Rohde R, Raz I; Collaborative Study Group: Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med345 :851 –860,2001[Abstract/Free Full Text]
53. Wanner C, Krane V, Ruf G, Marz W, Ritz E: Rationale and design of a trial improving outcome of type 2 diabetics on hemodialysis. Die Deutsche Diabetes Dialyse Studie Investigators. Kidney Int Suppl71 :S222 –S226,1999[Medline]
54. Appel LJ, Middleton J, Miller ER 3rd, Lipkowitz M, Norris K, Agodoa LY, Bakris G, Douglas JG, Charleston J, Gassman J, Greene T, Jamerson K, Kusek JW, Lewis JA, Phillips RA, Rostand SG, Wright JT: The rationale and design of the AASK cohort study. J Am Soc Nephrol14[Suppl 2] :S166 –S172,2003
55. Lea J, Greene T, Hebert L, Lipkowitz M, Massry S, Middleton J, Rostand SG, Miller E, Smith W, Bakris GL: The relationship between magnitude of proteinuria reduction and risk of end-stage renal disease: Results of the African American study of kidney disease and hypertension. Arch Intern Med165 :947 –953,2005[Abstract/Free Full Text]
56. Anavekar NS, McMurray JJ, Velazquez EJ, Solomon SD, Kober L, Rouleau JL, White HD, Nordlander R, Maggioni A, Dickstein K, Zelenkofske S, Leimberger JD, Califf RM, Pfeffer MA: Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction. N Engl J Med351 :1285 –1295,2004[Abstract/Free Full Text]

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