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1.  Race modifies the association between adiposity and inflammation in patients with chronic kidney disease: findings from the CRIC study 
Obesity (Silver Spring, Md.)  2014;22(5):1359-1366.
Objective
To examine the race-specific association of inflammation with adiposity and muscle mass in subjects with chronic kidney disease (CKD).
Design and Methods
Plasma concentration of IL-1β, IL-Receptor antagonist (IL-1RA), IL-6, IL-10, TNF-α, TGF-β, hs-CRP, fibrinogen, and serum albumin were measured in 3,939 Chronic Renal Insufficiency Cohort study participants. Bioelectric impedance analysis was used to determine body fat mass (BFM) and fat free mass (FFM).
Results
Plasma levels of hs-CRP, fibrinogen, IL-1RA, IL-6, and TNF-α increased and serum albumin decreased across the quartiles of body mass index. In multivariable analysis, BFM and FFM were positively associated with hs-CRP, fibrinogen, IL-1β, IL-1RA and IL-6. One standard deviation (SD) increase in BFM and FFM was associated with 0.36 (95% CI 0.33, 0.39) and 0.26 (95% CI 0.22, 0.30) SD increase in log transformed hs-CRP, respectively (p<0.001). Race stratified analysis showed that the association between biomarkers and BFM and FFM differed by race, with Caucasians demonstrating a stronger association with markers of inflammation than African Americans.
Conclusion
BFA and FFM are positively associated with markers of inflammation in patients with CKD. Race stratified analysis showed that Caucasians have a stronger association with markers of inflammation compared to African Americans.
doi:10.1002/oby.20692
PMCID: PMC4327849  PMID: 24415732
Bioelectric impedance analysis; cytokines; acute phase proteins; muscle mass; Body mass index; African Americans
2.  Response of Pediatric Uveitis to Tumor Necrosis Factor-α Inhibitors 
The Journal of rheumatology  2013;40(8):1394-1403.
Objectives
To evaluate the outcome of TNF-alpha inhibition (anti-TNFα) for pediatric uveitis.
Methods
We retrospectively assessed children (≤18 years) with non-infectious uveitis receiving anti-TNFα at five uveitis centers and one pediatric-rheumatology center. Incident treatment success was defined as minimal or no uveitis activity at ≥2 consecutive ophthalmological exams ≥28 days apart while taking no oral and ≤2 eyedrops/day of corticosteroids. Eligible children had active uveitis and/or were taking higher corticosteroid doses.
Results
Among 56 eligible children followed over 33.73 person-years, 52% had juvenile idiopathic arthritis (JIA) and 75% had anterior uveitis (AU). The Kaplan-Meier estimated proportion achieving treatment success within 12 months was 75% (95% confidence interval [95% CI]: 62–87%). Complete absence of inflammatory signs with discontinuation of all corticosteroids was observed in an estimated 64% by 12 months (95% CI: 51–76%). Diagnoses of JIA or AU were associated with greater likelihood of success, as was the oligoarticular subtype amongst JIA cases. In a multivariable model, compared to those with JIA-associated AU, those with neither or with JIA or AU alone had a 75–80% lower rate of achieving quiescence under anti-TNFα - independent of the number of immunomodulators previously or concomitantly prescribed. Uveitis re-activated within 12 months of achieving quiescence in 14% of those continuing anti-TNFα (95% CI: 6–31%). The incidence of discontinuation for adverse effects was 8%/year (95% CI: 1–43%).
Conclusion
Treatment with anti-TNFα was successful and sustained in a majority of children with non-infectious uveitis and treatment-limiting toxicity was infrequent. JIA-associated AU may be especially responsive to anti-TNFα.
doi:10.3899/jrheum.121180
PMCID: PMC3802519  PMID: 23818712
uveitis; tumor necrosis factor-alpha antagonist; juvenile idiopathic arthritis
4.  CAUSAL INFERENCE FOR CONTINUOUS-TIME PROCESSES WHEN COVARIATES ARE OBSERVED ONLY AT DISCRETE TIMES 
Annals of statistics  2011;39(1):10.1214/10-AOS830.
Most of the work on the structural nested model and g-estimation for causal inference in longitudinal data assumes a discrete-time underlying data generating process. However, in some observational studies, it is more reasonable to assume that the data are generated from a continuous-time process and are only observable at discrete time points. When these circumstances arise, the sequential randomization assumption in the observed discrete-time data, which is essential in justifying discrete-time g-estimation, may not be reasonable. Under a deterministic model, we discuss other useful assumptions that guarantee the consistency of discrete-time g-estimation. In more general cases, when those assumptions are violated, we propose a controlling-the-future method that performs at least as well as g-estimation in most scenarios and which provides consistent estimation in some cases where g-estimation is severely inconsistent. We apply the methods discussed in this paper to simulated data, as well as to a data set collected following a massive flood in Bangladesh, estimating the effect of diarrhea on children’s height. Results from different methods are compared in both simulation and the real application.
doi:10.1214/10-AOS830
PMCID: PMC3857358  PMID: 24339454
Causal inference; continuous-time process; deterministic model; diarrhea; g-estimation; longitudinal data; structural nested model
5.  Carotid Plaque, Carotid Intima-Media Thickness, and Coronary Calcification Equally Discriminate Prevalent Cardiovascular Disease in Kidney Disease 
American journal of nephrology  2012;36(4):342-347.
Background
Despite the significant morbidity and mortality attributable to cardiovascular disease (CVD), risk stratification remains an important challenge in the chronic kidney disease(CKD) population. We examined the discriminative ability of non-invasive measures of atherosclerosis, including carotid intima-media thickness(cIMT), carotid plaque, coronary artery calcification(CAC) and ascending and descending thoracic aorta calcification(TCAC), and Framingham Risk Score (FRS) to predict self-reported prevalent CVD.
Methods and Results
Participants were enrolled in the cIMT ancillary study of the Chronic Renal Insufficiency Cohort(CRIC) Study and also had all of the above measures within an 18 month period. CVD was present in 21% of study participants. C-statistics were used to ascertain the discriminatory power of each measure of atherosclerosis. The study population (n=220) was 64% male; 51% black and 45% white. The proportion of individuals with estimated glomerular filtration rate ≥60, 45–59, 30–44, and <30ml/min/1.73m2 was 21%, 41%, 28%, and 11%, respectively. In multivariable analyses adjusting for demographic factors, we failed to find a difference between CAC, carotid plaque, and cIMT as predictors of self-reported prevalent CVD (c-statistic 0.70, 95% confidence interval [CI]: 0.62–0.78; c-statistic 0.68, 95% CI: 0.60–0.75, and c-statistic 0.64, CI: 0.56–0.72, respectively). CAC was statistically better than FRS. FRS was the weakest discriminator of self-reported prevalent CVD (c-statistic 0.58).
Conclusions
There was a significant burden of atherosclerosis among individuals with CKD, ascertained by several different imaging modalities. We were unable to find a difference in the ability of CAC, carotid plaque, and cIMT to predict self-reported prevalent CVD.
doi:10.1159/000342794
PMCID: PMC3538165  PMID: 23107930
carotid intima media thickness; coronary artery calcification; kidney; plaque
6.  Estimating GFR Among Participants in the Chronic Renal Insufficiency Cohort (CRIC) Study 
Background
Glomerular filtration rate (GFR) is considered the best measure of kidney function, but repeated assessment is not feasible in most research studies.
Study Design
Cross-sectional study of 1,433 participants from the Chronic Renal Insufficiency Cohort (CRIC) Study (i.e., the GFR subcohort) to derive an internal GFR estimating equation using a split sample approach.
Setting & Participants
Adults from 7 US metropolitan areas with mild to moderate chronic kidney disease; 48% had diabetes and 37% were black.
Index Test
CRIC GFR estimating equation
Reference Test or Outcome
Urinary 125I-iothalamate clearance testing (measured GFR)
Other Measurements
Laboratory measures including serum creatinine and cystatin C, and anthropometrics
Results
In the validation dataset, the model that included serum creatinine, serum cystatin C, age, gender, and race was the most parsimonious and similarly predictive of mGFR compared to a model additionally including bioelectrical impedance analysis phase angle, CRIC clinical center, and 24-hour urinary creatinine excretion. Specifically, the root mean square errors for the separate model were 0.207 vs. 0.202, respectively. The performance of the CRIC GFR estimating equation was most accurate among the subgroups of younger participants, men, non-blacks, non-Hispanics, those without diabetes, those with body mass index <30 kg/m2, those with higher 24-hour urine creatinine excretion, those with lower levels of high-sensitivity C-reactive protein, and those with higher mGFR.
Limitations
Urinary clearance of 125I-iothalamate is an imperfect measure of true GFR; cystatin C is not standardized to certified reference material; lack of external validation; small sample sizes limit analyses of subgroup-specific predictors.
Conclusions
The CRIC GFR estimating equation predicts measured GFR accurately in the CRIC cohort using serum creatinine and cystatin C, age, gender, and race. Its performance was best among younger and healthier participants.
doi:10.1053/j.ajkd.2012.04.012
PMCID: PMC3565578  PMID: 22658574
glomerular filtration rate (GFR); kidney function; GFR estimation
7.  Electronically-measured adherence to immunosuppressive medications and kidney function after deceased donor kidney transplantation* 
Clinical transplantation  2010;25(2):E124-E131.
Background
Non-adherence with immunosuppressive medications can result in allograft rejection and eventually allograft loss.
Methods
In a racially diverse population, we utilized microelectronic cap monitors to determine the association of adherence with a single immunosuppressive medication and kidney allograft outcomes post-transplantation. This prospective cohort study enrolled 243 patients from eight transplant centers to provide adherence and kidney allograft outcomes data. To determine the association of adherence with change in estimated glomerular filtration rate (eGFR), we fit mixed effects models with the outcome being change in eGFR over time. We also fit Cox proportional hazards models to determine the association of adherence with time to persistent 25% and 50% decline in eGFR.
Results
The distribution of adherence post-transplant was as follows: 164 (68%), 49 (20%) and 30 (12%) had >85–100%, 50–85% and <50% adherence, respectively. 79 (33%) and 36 (15%) of the subjects experienced a persistent 25% decline in eGFR or allograft loss and 50% decline in eGFR or allograft loss during follow-up. Adherence was not associated with acute rejection or 25% decline or 50% decline in eGFR. In the adjusted and unadjusted model, adherence and black race were not associated with change in eGFR over time.
Conclusions
Non-adherence with a single immunosuppressive medication, was not associated with kidney allograft outcomes.
doi:10.1111/j.1399-0012.2010.01340.x
PMCID: PMC3566245  PMID: 20977496
kidney transplant; adherence; renal function
8.  Effects of Adjusting for Instrumental Variables on Bias and Precision of Effect Estimates 
American Journal of Epidemiology  2011;174(11):1213-1222.
Recent theoretical studies have shown that conditioning on an instrumental variable (IV), a variable that is associated with exposure but not associated with outcome except through exposure, can increase both bias and variance of exposure effect estimates. Although these findings have obvious implications in cases of known IVs, their meaning remains unclear in the more common scenario where investigators are uncertain whether a measured covariate meets the criteria for an IV or rather a confounder. The authors present results from two simulation studies designed to provide insight into the problem of conditioning on potential IVs in routine epidemiologic practice. The simulations explored the effects of conditioning on IVs, near-IVs (predictors of exposure that are weakly associated with outcome), and confounders on the bias and variance of a binary exposure effect estimate. The results indicate that effect estimates which are conditional on a perfect IV or near-IV may have larger bias and variance than the unconditional estimate. However, in most scenarios considered, the increases in error due to conditioning were small compared with the total estimation error. In these cases, minimizing unmeasured confounding should be the priority when selecting variables for adjustment, even at the risk of conditioning on IVs.
doi:10.1093/aje/kwr364
PMCID: PMC3254160  PMID: 22025356
bias (epidemiology); confounding factors (epidemiology); epidemiologic methods; instrumental variable; precision; simulation; variable selection
9.  Causal inference in longitudinal studies with history-restricted marginal structural models 
A new class of Marginal Structural Models (MSMs), History-Restricted MSMs (HRMSMs), was recently introduced for longitudinal data for the purpose of defining causal parameters which may often be better suited for public health research or at least more practicable than MSMs (6, 2). HRMSMs allow investigators to analyze the causal effect of a treatment on an outcome based on a fixed, shorter and user-specified history of exposure compared to MSMs. By default, the latter represent the treatment causal effect of interest based on a treatment history defined by the treatments assigned between the study’s start and outcome collection. We lay out in this article the formal statistical framework behind HRMSMs. Beyond allowing a more flexible causal analysis, HRMSMs improve computational tractability and mitigate statistical power concerns when designing longitudinal studies. We also develop three consistent estimators of HRMSM parameters under sufficient model assumptions: the Inverse Probability of Treatment Weighted (IPTW), G-computation and Double Robust (DR) estimators. In addition, we show that the assumptions commonly adopted for identification and consistent estimation of MSM parameters (existence of counterfactuals, consistency, time-ordering and sequential randomization assumptions) also lead to identification and consistent estimation of HRMSM parameters.
doi:10.1214/07-EJS050
PMCID: PMC3475192  PMID: 23087778
causal inference; counterfactual; marginal structural model; longitudinal study; IPTW; G-computation; Double Robust
10.  Principal Stratification and Attribution Prohibition: Good Ideas Taken Too Far 
Pearl’s article provides a useful springboard for discussing further the benefits and drawbacks of principal stratification and the associated discomfort with attributing effects to post-treatment variables. The basic insights of the approach are important: pay close attention to modification of treatment effects by variables not observable before treatment decisions are made, and be careful in attributing effects to variables when counterfactuals are ill-defined. These insights have often been taken too far in many areas of application of the approach, including instrumental variables, censoring by death, and surrogate outcomes. A novel finding is that the usual principal stratification estimand in the setting of censoring by death is by itself of little practical value in estimating intervention effects.
doi:10.2202/1557-4679.1367
PMCID: PMC3204670  PMID: 22049269
principal stratification; causal inference
12.  Metabolic Syndrome, Components, and Cardiovascular Disease Prevalence in Chronic Kidney Disease: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study 
American Journal of Nephrology  2011;33(6):477-484.
Background/Aims
Metabolic syndrome may increase the risk for incident cardiovascular disease (CVD) and all-cause mortality in the general population. It is unclear whether, and to what degree, metabolic syndrome is associated with CVD in chronic kidney disease (CKD). We determined metabolic syndrome prevalence among individuals with a broad spectrum of kidney dysfunction, examining the role of the individual elements of metabolic syndrome and their relationship to prevalent CVD.
Methods
We evaluated four models to compare metabolic syndrome or its components to predict prevalent CVD using prevalence ratios in the Chronic Renal Insufficiency Cohort (CRIC) Study.
Results
Among 3,939 CKD participants, the prevalence of metabolic syndrome was 65% and there was a significant association with prevalent CVD. Metabolic syndrome was more common in diabetics (87.5%) compared with non-diabetics (44.3%). Hypertension was the most prevalent component, and increased triglycerides the least prevalent. Using the bayesian information criterion, we found that the factors defining metabolic syndrome, considered as a single interval-scaled variable, was the best of four models of metabolic syndrome, both for CKD participants overall and for diabetics and non-diabetics separately.
Conclusion
The predictive value of this model for future CVD outcomes will subsequently be validated in longitudinal analyses.
doi:10.1159/000327618
PMCID: PMC3095834  PMID: 21525746
Cardiovascular disease; Chronic kidney disease; Chronic Renal Insufficiency Cohort (CRIC) Study; Metabolic syndrome
13.  Inflammation, Coronary Artery Calcification and Cardiovascular Events in Incident Renal Transplant Recipients 
Atherosclerosis  2010;212(2):589-594.
Objective
Coronary artery calcification (CAC) predicts cardiovascular events in the general population. We conducted a prospective study to determine if inflammatory markers were predictive of CAC and if CAC predicted cardiovascular events and mortality in incident renal transplant recipients.
Methods
A prospective cohort of 112 asymptomatic incident renal transplant recipients who had no prior history of coronary artery revascularization or myocardial infarction had coronary calcifications measured early post-transplant and at least 18 months later by Agatston score and volume method.
Results
The mean CAC score was 367.7 (682.3). Inflammatory markers such as WBC and CRP were predictive of CAC severity. Recipients with cardiovascular events (n=11) or death (n=12) during the follow-up period had higher mean [675.1 (669.3) vs. 296.8(669.0), p=0.02] and median [434.8 vs. 28.9, p=0.01] CAC score compared to those without them. Recipients with CAC score less than 100 had a better cumulative survival rate compared to the recipients with CAC score greater than 100 [95.1 vs. 82.3%, p=0.03]. We found a significant unadjusted and adjusted association between CAC score and cardiovascular events and mortality. A quarter (25.9%) of recipients had CAC progression. Coronary calcification progression also predicted cardiovascular events and mortality after adjustment for diabetes, age, dialysis vintage and presence of CAC at time of transplant.
Conclusion
CAC is prevalent in renal recipients and is predictive of cardiovascular events and mortality. Changes in coronary calcification are common and predict clinical outcomes. Inflammatory markers are predictive of CAC severity at time of transplant, but are not predictive of future cardiovascular event or mortality.
doi:10.1016/j.atherosclerosis.2010.05.016
PMCID: PMC2953547  PMID: 20934074
coronary calcification; EBCT; renal transplant; inflammation; C-reactive protein
14.  Central Pulse Pressure in Chronic Kidney Disease: A CRIC Ancillary Study 
Hypertension  2010;56(3):518-524.
Central pulse pressure can be non-invasively derived using the radial artery tonometric methods. Knowledge of central pressure profiles has predicted cardiovascular morbidity and mortality in several populations of patients, particularly those with known coronary artery disease and those receiving dialysis. Few data exist characterizing central pressure profiles in patients with mild-moderate chronic kidney disease who are not on dialysis. We measured central pulse pressure cross-sectionally in 2531 participants in the Chronic Renal Insufficiency Cohort study to determine correlates of the magnitude of central pulse pressure in the setting of chronic kidney disease. Tertiles of central pulse pressure (CPP) were < 36 mmHg, 36–51 mmHg and > 51 mmHg with an overall mean (± S.D.) of 46 ± 19 mmHg. Multivariable regression identified the following independent correlates of central pulse pressure: age, gender, diabetes mellitus, heart rate (negatively correlated), glycosylated hemoglobin, hemoglobin, glucose and PTH concentrations. Additional adjustment for brachial mean arterial pressure and brachial pulse pressure showed associations for age, gender, diabetes, weight and heart rate. Discrete intervals of brachial pulse pressure stratification showed substantial overlap within the associated central pulse pressure values. The large size of this unique chronic kidney disease cohort provides an ideal situation to study the role of brachial and central pressure measurements in kidney disease progression and cardiovascular disease incidence.
doi:10.1161/HYPERTENSIONAHA.110.153924
PMCID: PMC2941985  PMID: 20660819
Elasticity; epidemiology; diabetic nephropathies; hemodynamics; gender
15.  Variability of Creatinine Measurements in Clinical Laboratories: Results from the CRIC Study 
American Journal of Nephrology  2010;31(5):426-434.
Objectives
Estimating equations using serum creatinine (SCr) are often used to assess glomerular filtration rate (GFR). Such creatinine (Cr)-based formulae may produce biased estimates of GFR when using Cr measurements that have not been calibrated to reference laboratories. In this paper, we sought to examine the degree of this variation in Cr assays in several laboratories associated with academic medical centers affiliated with the Chronic Renal Insufficiency Cohort (CRIC) Study; to consider how best to correct for this variation, and to quantify the impact of such corrections on eligibility for participation in CRIC. Variability of Cr is of particular concern in the conduct of CRIC, a large multicenter study of subjects with chronic renal disease, because eligibility for the study depends on Cr-based assessment of GFR.
Methods
A library of 5 large volume plasma specimens from apheresis patients was assembled, representing levels of plasma Cr from 0.8 to 2.4 mg/dl. Samples from this library were used for measurement of Cr at each of the 14 CRIC laboratories repetitively over time. We used graphical displays and linear regression methods to examine the variability in Cr, and used linear regression to develop calibration equations. We also examined the impact of the various calibration equations on the proportion of subjects screened as potential participants who were actually eligible for the study.
Results
There was substantial variability in Cr assays across laboratories and over time. We developed calibration equations for each laboratory; these equations varied substantially among laboratories and somewhat over time in some laboratories. The laboratory site contributed the most to variability (51% of the variance unexplained by the specimen) and variation with time accounted for another 15%. In some laboratories, calibration equations resulted in differences in eligibility for CRIC of as much as 20%.
Conclusions
The substantial variability in SCr assays across laboratories necessitates calibration of SCr measures to a common standard. Failing to do so may substantially affect study eligibility and clinical interpretations when they are determined by Cr-based estimates of GFR.
doi:10.1159/000296250
PMCID: PMC2883847  PMID: 20389058
Chronic renal disease; Creatinine measurements, variability; Chronic Renal Insufficiency Cohort (CRIC) Study; Glomerular filtration rate
16.  Design and Analysis of Multiple Events Case-Control Studies 
Biometrics  2010;66(4):1220-1229.
Summary
In case-control research where there are multiple case groups, standard analyses fail to make use of all available information. Multiple events case-control (MECC) studies provide a new approach to sampling from a cohort and are useful when it is desired to study multiple types of events in the cohort. In this design, subjects in the cohort who develop any event of interest are sampled, as well as a fraction of the remaining subjects. We show that a simple case-control analysis of data arising from MECC studies is biased and develop three general estimating-equation based approaches to analyzing data from these studies. We conduct simulation studies to compare the efficiency of the various MECC analyses with each other and with the corresponding conventional analyses. It is shown that the gain in efficiency by using the new design is substantial in many situations. We demonstrate the application of our approach to a nested case-control study of the effect of oral sodium phosphate use on chronic kidney injury with multiple case definitions.
doi:10.1111/j.1541-0420.2009.01369.x
PMCID: PMC2980800  PMID: 20002403
Multiple events case-control study; case-cohort study; nested case-control study; sampling from a cohort; semi-parametric efficient estimator
17.  Predictors of having a potential live donor: a prospective cohort study of kidney transplant candidates 
The barriers to live donor transplantation are poorly understood. We performed a prospective cohort study of individuals undergoing renal transplant evaluation. Participants completed a questionnaire that assessed clinical characteristics as well as knowledge and beliefs about transplantation. A participant satisfied the primary outcome if anyone contacted the transplant center to be considered as a live donor for that participant. The final cohort comprised 203 transplant candidates, among whom 80 (39.4%) had a potential donor contact the center and 19 (9.4%) underwent live donor transplantation. In multivariable logistic regression, younger candidates (OR 1.65 per 10 fewer years, p<0.01) and those with annual income >=$15,000 (OR 4.22, p=0.03) were more likely to attract a potential live donor. Greater self-efficacy, a measure of the participant’s belief in his or her ability to attract a donor, was a predictor of having a potential live donor contact the center (OR 2.73 per point, p<0.01), while knowledge was not (p=0.56). The lack of association between knowledge and having a potential donor suggests that more intensive education of transplant candidates will not increase live donor transplantation. On the other hand, self-efficacy may be an important target in designing interventions to help candidates find live donors.
doi:10.1111/j.1600-6143.2009.02848.x
PMCID: PMC2864790  PMID: 19845584
live donor; kidney transplantation; health disparities
18.  Aortic PWV in Chronic Kidney Disease: A CRIC Ancillary Study 
American journal of hypertension  2009;23(3):282-289.
Background
Aortic PWV is a measure of arterial stiffness and has proved useful in predicting cardiovascular morbidity and mortality in several populations of patients, including the healthy elderly, hypertensives and those with end stage renal disease receiving hemodialysis. Little data exist characterizing aortic stiffness in patients with chronic kidney disease who are not receiving dialysis, and in particular the effect of reduced kidney function on aortic PWV.
Methods
We performed measurements of aortic PWV in a cross-sectional cohort of participants enrolled in the Chronic Renal Insufficiency Cohort (CRIC) study to determine factors which predict increased aortic PWV in chronic kidney disease.
Results
PWV measurements were obtained in 2564 participants. The tertiles of aortic PWV (adjusted for waist circumference) were < 7.7 m/sec, 7.7–10.2 m/sec and > 10.2 m/sec with an overall mean (± S.D.) value of 9.48 ± 3.03 m/sec [95% CI = 9.35–9.61 m/sec]. Multivariable regression identified significant independent positive associations of age, blood glucose concentrations, race, waist circumference, mean arterial blood pressure, gender, and presence of diabetes with aortic PWV and a significant negative association with the level of kidney function.
Conclusions
The large size of this unique cohort, and the targeted enrollment of chronic kidney disease participants provides an ideal situation to study the role of reduced kidney function as a determinant of arterial stiffness. Arterial stiffness may be a significant component of the enhanced cardiovascular risk associated with kidney failure.
doi:10.1038/ajh.2009.240
PMCID: PMC2822073  PMID: 20019670
19.  Aortic calcification predicts cardiovascular events and all-cause mortality in renal transplantation 
Nephrology Dialysis Transplantation  2009;24(4):1314-1319.
Background. Cardiovascular disease is a leading cause of death among renal transplant recipients. Aortic calcification is associated with increased mortality in dialysis subjects. The significance of aortic calcification among renal transplant recipients is unknown. Our objective was to prospectively examine the association of aortic calcification with cardiovascular events and all-cause mortality among asymptomatic incident renal transplant recipients.
Methods. One hundred and twelve renal transplant recipients underwent electron beam computed tomography. Aortic calcification was scored by the Agatston method. The mean follow-up time was 5.1 years. Cardiovascular events (heart failure, coronary artery disease, peripheral arterial disease and stroke) and all-cause mortality were recorded.
Results. The cohort consisted of 62% Caucasians, 38% African Americans and 62% male gender. The mean age was 49.0 ± 12.5 years. Thirty-four percent had aortic calcification. During follow-up, 12 cardiovascular events and 10 deaths were recorded. Subjects with aortic calcification had more cardiovascular events compared to those without aortic calcification (23.7 versus 4.1%, P = 0.001). Recipients with aortic calcification had higher mortality compared to those without aortic calcification but it did not reach statistical significance (15.8 versus 5.4%, P = 0.07). The univariate hazard ratio of aortic calcification score in a proportional hazard Cox model to assess event-free survival was 1.15 (1.04–1.27, P = 0.01). Diabetes and aortic calcification score were independently associated with survival. In addition to the predictors above, dialysis vintage was an independent predictor for combined future cardiovascular event and mortality.
Conclusions. In conclusion, aortic calcification is prevalent among renal transplant recipients and is predictive of future cardiovascular events. Aortic calcification is easily identified by non-invasive testing, and should be considered when assessing cardiovascular risk in asymptomatic renal transplant recipients.
doi:10.1093/ndt/gfn753
PMCID: PMC2721431  PMID: 19164320
cardiovascular events; renal transplantation; vascular calcification
20.  Metabolic Syndrome and Coronary Artery Calcification in Renal Transplant Recipients 
Transplantation  2008;86(5):728-732.
Background
Coronary artery calcification (CAC) and Metabolic Syndrome (MS) have been associated with increased cardiovascular risk. The study objective was to examine the association of MS with CAC presence and progression in renal transplant recipients.
Methods
We measured CAC progression in asymptomatic recipients who had no prior history of coronary artery disease.
Results
MS was common (55.4%). Median CAC scores were 0, 33.1, 98, and 261.9 for patients with 1, 2, 3, and 4 or more positive components of the MS, respectively. Severe CAC scores were more common in recipients with MS (p=0.04). Although recipients with MS had higher mean CAC scores at baseline and significant CAC progression [483 (590.6) vs. 619(813.8), p=0.01 ], MS was not an independent predictor of annualized rate of CAC change in a multivariate model
Conclusion
Future studies to evaluate if MS treatment improves cardiovascular outcomes are imperative.
doi:10.1097/TP.0b013e3181826d12
PMCID: PMC2656432  PMID: 18791455
renal transplant; coronary calcification; metabolic syndrome
21.  Association of Donor Inflammation– and Apoptosis-Related Genotypes and Delayed Allograft Function after Kidney Transplantation 
Background
Delayed renal allograft survival (DGF) after a deceased donor kidney transplant is associated with an increased risk of allograft loss. Inflammatory response and apoptosis are associated with increased risk of DGF.
Study Design
Cross Sectional Study
Setting & Participants
We first recruited 616 recipients of kidneys from 512 deceased kidney donors and the donor DNA was genotyped. These recipients who were included in a prospective cohort study of 9 transplant centers in the Delaware Valley region, had their DGF outcome obtained through medical record abstraction. Then, we identified the recipient (n=349) of the contralateral deceased kidney donor, if not part of the cohort, through the USRDS registry. The final cohort consisted of 965 recipients of deceased donor kidneys from 512 donors.
Predictors
Donor single nucleotide polymorphisms (SNPs) in genes for tumor necrosis factor α (TNF), transforming growth factor β1 (TGFB1), interleukin 10 (IL10), p53 (TP53), and heme oxygenase 1 (HMOX1).
Outcomes
DGF, defined as need for dialysis in the first week post-transplant. Secondary outcomes included acute rejection and eGFR.
Measurements
Information on DGF, acute rejection and eGFR for recipients in the Delaware Valley Cohort was obtained through medical record abstraction. For other recipients, information on DGF was obtained from UNOS forms and CMS claims in the USRDS registry.
Results
The TGFB1, IL10, TP53 and HMOX1 genes were not associated with DGF. The G allele of TNF polymorphism rs3093662 was associated with DGF in an adjusted analysis (OR= 1.85 compared to A allele, 95% C.I.=1.16–2.96, p=0.01). However this association does not achieve statistical significance after adjusting for multiple comparisons.
Limitations
Inadequate sample size for infrequent genotypes and multiple comparisons.
Conclusion
Due to the low frequency of donor SNPs of interest, a larger sample size and replication are necessary for conclusive evidence for the association of donor genotypes with DGF.
doi:10.1053/j.ajkd.2008.05.006
PMCID: PMC2562522  PMID: 18640487
Kidney Transplant; Deceased Donor Genotypes; Delayed Graft Function
22.  Extended Instrumental Variables Estimation for Overall Effects* 
We consider a method for extending instrumental variables methods in order to estimate the overall effect of a treatment or exposure. The approach is designed for settings in which the instrument influences both the treatment of interest and a secondary treatment also influenced by the primary treatment. We demonstrate that, while instrumental variables methods may be used to estimate the joint effects of the primary and secondary treatments, they cannot by themselves be used to estimate the overall effect of the primary treatment. However, instrumental variables methods may be used in conjunction with approaches for estimating the effect of the primary on the secondary treatment to estimate the overall effect of the primary treatment. We consider extending the proposed methods to deal with confounding of the effect of the instrument, mediation of the effect of the instrument by other variables, failure-time outcomes, and time-varying secondary treatments. We motivate our discussion by considering estimation of the overall effect of the type of vascular access among hemodialysis patients.
PMCID: PMC2669310  PMID: 19381345
instrumental variables; causal inference
23.  Mediation Analysis with Principal Stratification 
Statistics in medicine  2009;28(7):1108-1130.
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often perform mediation analyses by analyzing if the significant intent-to-treat treatment effect on outcome occurs through or around a third intermediate or mediating variable: indirect and direct effects, respectively. Standard mediation analyses assume sequential ignorability, i.e., conditional on covariates the intermediate or mediating factor is randomly assigned, as is the treatment in a randomized clinical trial. This research focuses on the application of the principal stratification approach for estimating the direct effect of a randomized treatment but without the standard sequential ignorability assumption. This approach is used to estimate the direct effect of treatment as a difference between expectations of potential outcomes within latent sub-groups of participants for whom the intermediate variable behavior would be constant, regardless of the randomized treatment assignment. Using a Bayesian estimation procedure, we also assess the sensitivity of results based on the principal stratification approach to heterogeneity of the variances among these principal strata. We assess this approach with simulations and apply it to two psychiatric examples. Both examples and the simulations indicated robustness of our findings to the homogeneous variance assumption. However, simulations showed that the magnitude of treatment effects derived under the principal stratification approach were sensitive to model mis-specification.
doi:10.1002/sim.3533
PMCID: PMC2669107  PMID: 19184975
Principal stratification; mediating variables; direct effects; principal strata probabilities; heterogeneous variances
24.  Extended Instrumental Variables Estimation for Overall Effects 
We consider a method for extending instrumental variables methods in order to estimate the overall effect of a treatment or exposure. The approach is designed for settings in which the instrument influences both the treatment of interest and a secondary treatment also influenced by the primary treatment. We demonstrate that, while instrumental variables methods may be used to estimate the joint effects of the primary and secondary treatments, they cannot by themselves be used to estimate the overall effect of the primary treatment. However, instrumental variables methods may be used in conjunction with approaches for estimating the effect of the primary on the secondary treatment to estimate the overall effect of the primary treatment. We consider extending the proposed methods to deal with confounding of the effect of the instrument, mediation of the effect of the instrument by other variables, failure-time outcomes, and time-varying secondary treatments. We motivate our discussion by considering estimation of the overall effect of the type of vascular access among hemodialysis patients.
doi:10.2202/1557-4679.1082
PMCID: PMC2835455  PMID: 20231915
25.  Effects of Renal Replacement Therapy on Plasma Lipoprotein(a) Levels 
American Journal of Nephrology  2007;28(3):361-365.
Patients with end-stage renal disease (ESRD) have significantly higher levels of lipoprotein(a) [Lp(a)] when compared to control populations. Elevated levels of Lp(a) may play a role in the high incidence of cardiovascular disease in ESRD. We conducted a prospective study to test the hypothesis that plasma levels of Lp(a) decline rapidly after renal transplantation proportional to the improvement in renal function, but are not affected by hemodialysis. All adults that initiated hemodialysis or received a renal transplant from our institution during a 10-month period were invited to participate in the study. Lp(a) levels were obtained immediately prior to the initiation of renal replacement therapy. In transplant recipients, repeat Lp(a) measures were done at 3 days, 5 days, 1 week, 2 weeks, 3 weeks and 4 weeks post-transplant. In hemodialysis patients, repeat Lp(a) measures were done after 3 months. We used a mixed effects model to analyze the effect of time, race and creatinine on Lp(a) after transplant. Lp(a) levels decreased rapidly after renal transplantation. Mean Lp(a) levels at 2 weeks were 35.3% lower than prior to transplantation. Each reduction of 50% in creatinine was associated with a 10.6% reduction in Lp(a) (p < 0.001). In contrast, there was no significant change in Lp(a) after initiation of hemodialysis. The rapid decrease of Lp(a) levels after renal transplantation provides support for a metabolic role of the kidney in Lp(a) catabolism and suggests that the increase in Lp(a) seen in chronic kidney disease is due to loss of functioning renal tissue.
doi:10.1159/000112225
PMCID: PMC2786011  PMID: 18057868
Renal transplantation; Cardiovascular risk factors; Clinical epidemiology; Lipoprotein(a)

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