Differences in Phosphate and Parathyroid Hormone Concentrations over the Day among Patients on Hemodialysis.

BACKGROUND: Elevated serum phosphate and parathyroid hormone (PTH) concentrations are associated with cardiovascular events, bone disease, and mortality in patients on maintenance hemodialysis. Although circadian changes are known in people with CKD, it is unknown whether differences occur in these parameters over the course of a day in people receiving hemodialysis. METHODS: We used clinical data from Fresenius Medical Care US dialysis clinics to determine how the time of day when measurements were collected (hemodialysis treatment start time) may be associated with serum phosphate and PTH concentrations. We used harmonic regression to assess these associations while accounting for demographic data and treatment parameters. RESULTS: A total of 96,319 patients receiving maintenance hemodialysis were included in this analysis. Patients had a mean age of 64±14 years, 43% were women, and dialysis start times ranged from 3:00 am to 7:59 pm. The mean serum phosphate concentration was 5.2±1.5 mg/dl, and the median PTH was 351 pg/ml (interquartile range [IQR], 214-547). In fully adjusted models, serum phosphate had a nadir at 11:00 am of 4.97 (IQR, 4.94-5.01) mg/dl and a peak at 7:00 pm of 5.56 (IQR, 5.50-5.62) mg/dl. Serum PTH had a nadir at 9:00 am of 385 (IQR, 375-395) pg/ml and a peak at 7:00 pm of 530 (IQR, 516-547) pg/ml. CONCLUSIONS: Among patients receiving maintenance hemodialysis, concentrations of PTH and phosphate before a dialysis session vary with the time of day that these values are measured. Consideration of whether these values were obtained at peak or nadir times of the day may be important in treatment decisions.

Mineral bone disease in autosomal dominant polycystic kidney disease.

Mice with disruption of Pkd1 in osteoblasts demonstrate reduced bone mineral density, trabecular bone volume and cortical thickness. To date, the bone phenotype in adult patients with autosomal dominant polycystic kidney disease (ADPKD) with stage I and II chronic kidney disease has not been investigated. To examine this, we characterized biochemical markers of mineral metabolism, examined bone turnover and biology, and estimated risk of fracture in patients with ADPKD. Markers of mineral metabolism were measured in 944 patients with ADPKD and other causes of kidney disease. Histomorphometry and immunohistochemistry were compared on bone biopsies from 20 patients with ADPKD with a mean eGFR of 97 ml/min/1.73m2 and 17 healthy individuals. Furthermore, adults with end stage kidney disease (ESKD) initiating hemodialysis between 2002-2013 and estimated the risk of bone fracture associated with ADPKD as compared to other etiologies of kidney disease were examined. Intact fibroblast growth factor 23 was higher and total alkaline phosphatase lower in patients with compared to patients without ADPKD with chronic kidney disease. Compared to healthy individuals, patients with ADPKD demonstrated significantly lower osteoid volume/bone volume (0.61 vs. 1.21%) and bone formation rate/bone surface (0.012 vs. 0.026 µm3/µm2/day). ESKD due to ADPKD was not associated with a higher risk of fracture as compared to ESKD due to diabetes (age adjusted incidence rate ratio: 0.53 (95% confidence interval 0.31, 0.74) or compared to other etiologies of kidney disease. Thus, individuals with ADPKD have lower alkaline phosphatase, higher circulating intact fibroblast growth factor 23 and decreased bone formation rate. However, ADPKD is not associated with higher rates of bone fracture in ESKD.

Mortality and Hospitalizations among Sickle Cell Disease Patients with End-Stage Kidney Disease Initiating Dialysis.

BACKGROUND: Sickle cell disease (SCD) is the most common inherited hematological disorder and a well-described risk factor for end-stage kidney disease (ESKD). Mortality and hospitalizations among patients with SCD who develop ESKD remain understudied. Furthermore, prior studies focused only on SCD patients where ESKD was caused by SCD. We aimed to describe mortality and hospitalization risk in all SCD patients initiating dialysis and explore risk factors for mortality and hospitalization. METHODS: We performed a national observational cohort study of African American ESKD patients initiating dialysis (2000-2014) in facilities affiliated with a large dialysis provider. SCD was identified by diagnosis codes and matched to a reference population (non-SCD) by age, sex, dialysis initiation year, and geographic region of care. Sensitivity analyses were conducted by restricting to patients where SCD was recorded as the cause of ESKD. RESULTS: We identified 504 SCD patients (mean age: 47 ± 14 years; 48% females) and 1,425 reference patients (mean age: 46 ± 14 years; 49% females). The median follow-up was 2.4 (IQR 1.0-4.5) years. Compared to the reference, SCD was associated with higher mortality risk (hazard ratio 1.66; 95% confidence interval [CI]: 1.36-2.03) and higher hospitalization rates (incidence rate ratio 2.12; 95% CI: 1.88-2.38) in multivariable analyses. Exploratory multivariable mortality risk models showed the largest mortality risk attenuation with the addition of time-varying hemoglobin and high-dose erythropoietin, but the association of SCD with mortality remained significant. Sensitivity analyses (restricted to ESKD caused by SCD) also showed significant associations between SCD and mortality and hospitalizations, but with larger effect estimates. High-dose erythropoietin was associated with the highest risk for mortality and hospitalization in SCD. CONCLUSIONS: Among ESKD patients, SCD is associated with a higher risk for mortality and hospitalization, particularly in patients where SCD is identified as the cause of ESKD.

Development and content validity of a hemodialysis symptom patient-reported outcome measure.

PURPOSE: To describe the process and preliminary qualitative development of a new symptom-based patient-reported outcome measure (PROM) intended to assess hemodialysis treatment-related physical symptoms. METHODS: Experienced interviewers conducted concept elicitation and cognitive debriefing interviews with individuals receiving in-center hemodialysis in the United States. Concept elicitation interviews involved eliciting spontaneous reports of symptom experiences and probing to further explore and confirm concepts. We used patient-reported concepts to generate a preliminary symptom PROM. We conducted 3 rounds of cognitive debriefing interviews to evaluate symptom relevance, item interpretability, and draft item structure. We iteratively refined the measure based on cognitive interview findings. RESULTS: Forty-two adults receiving in-center hemodialysis participated in the concept elicitation interviews. A total of 12 symptoms were reported by > 10% of interviewees. We developed a 13-item initial draft instrument for testing in 3 rounds of cognitive interviews with an additional 52 hemodialysis patients. Participant responses and feedback during cognitive interviews led to changes in symptom descriptions, division of the single item "nausea/vomiting" into 2 distinct items, removal of daily activity interference items, addition of instructions, and clarification about the recall period, among other changes. CONCLUSIONS: Symptom Monitoring on Renal Replacement Therapy-Hemodialysis (SMaRRT-HD™) is a 14-item PROM intended for use in hemodialysis patents. SMaRRT-HD™ uses a single treatment recall period and a 5-point Likert scale to assess symptom severity. Qualitative interview data provide evidence of its content validity. SMaRRT-HD™ is undergoing additional testing to assess measurement properties and inform measure scoring.

Time-dynamic profiling with application to hospital readmission among patients on dialysis.

Standard profiling analysis aims to evaluate medical providers, such as hospitals, nursing homes, or dialysis facilities, with respect to a patient outcome. The outcome, for instance, may be mortality, medical complications, or 30-day (unplanned) hospital readmission. Profiling analysis involves regression modeling of a patient outcome, adjusting for patient health status at baseline, and comparing each provider's outcome rate (e.g., 30-day readmission rate) to a normative standard (e.g., national "average"). Profiling methods exist mostly for non time-varying patient outcomes. However, for patients on dialysis, a unique population which requires continuous medical care, methodologies to monitor patient outcomes continuously over time are particularly relevant. Thus, we introduce a novel time-dynamic profiling (TDP) approach to assess the time-varying 30-day readmission rate. TDP is used to estimate, for the first time, the risk-standardized time-dynamic 30-day hospital readmission rate, throughout the time period that patients are on dialysis. We develop the framework for TDP by introducing the standardized dynamic readmission ratio as a function of time and a multilevel varying coefficient model with facility-specific time-varying effects. We propose estimation and inference procedures tailored to the problem of TDP and to overcome the challenge of high-dimensional parameters when examining thousands of dialysis facilities.

Associations of Body Mass Index and Body Fat With Markers of Inflammation and Nutrition Among Patients Receiving Hemodialysis.

BACKGROUND: Understanding the extent to which visceral and subcutaneous body fat are associated with markers of nutrition and inflammation in patients on dialysis therapy could shed light on the obesity paradox and the biology of subcutaneous fat. STUDY DESIGN: Cross-sectional. SETTING & PARTICIPANTS: 609 adults receiving hemodialysis who participated in the ACTIVE/ADIPOSE Study. PREDICTORS: Body mass index (BMI), waist circumference, and bioelectrical impedance spectroscopy-derived estimates of percent body fat. OUTCOMES: C-Reactive protein (CRP), interleukin 6 (IL-6), prealbumin, albumin, leptin, and adiponectin concentrations. MEASUREMENTS: We performed linear regression analyses to examine the extent to which proxies of visceral and subcutaneous fat were associated with inflammation, nutrition, and adiposity-related hormones. RESULTS: BMI was directly associated with markers of inflammation (standardized estimate for ln[CRP in mg/L]: 0.30 [95% CI, 0.22-0.38] per 10kg/m2; for ln[IL-6 in pg/mL]: 0.10 [95% CI, 0.02-0.18] per 10kg/m2), but was not associated with markers of nutrition. BMI was also inversely associated with adiponectin and directly associated with leptin. With waist circumference and percent body fat (as a proxy of visceral and subcutaneous fat, respectively) modeled together, waist circumference was associated with markers of inflammation (standardized estimate for ln[CRP in mg/L]: 0.21 [95% CI, 0.09-0.34] per 10cm; for ln[IL-6 in pg/mL]: 0.18 [95% CI, 0.07-0.29] per 10cm), whereas percent body fat was not associated with CRP (standardized estimate for ln[CRP in mg/L]: 0.03 [95% CI, -0.10 to 0.15] per 1%) and was inversely associated with IL-6 (standardized estimate for ln[IL-6 in pg/mL]: -0.15 [95% CI, -0.27 to -0.02] per 1%). In addition, waist circumference was inversely associated with prealbumin and albumin (standardized estimates of -0.12 [95% CI, -0.23 to -0.02] mg/dL per 10cm and -0.17 [95% CI, -0.28 to -0.06] g/dL per 10cm, respectively), and percent body fat was directly associated with prealbumin and albumin (0.20 [95% CI, 0.07-0.32] mg/dL and 0.15 [95% CI, 0.02-0.28] g/dL per 1%, respectively). Higher waist circumference was associated indirectly with adiponectin and directly with leptin concentrations. LIMITATIONS: Although the observed associations implicate visceral fat as the cause of inflammation, it cannot be determined in this cross-sectional study. CONCLUSIONS: Proxies of visceral and subcutaneous fat appear to have opposing associations with biomarkers of inflammation and nutrition. Subcutaneous fat may be an indicator of nutritional status, and visceral fat, an indicator of inflammation.

Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference.

Recent studies found that infection-related hospitalization was associated with increased risk of cardiovascular (CV) events, such as myocardial infarction and stroke in the dialysis population. In this work, we develop time-varying effects modeling tools in order to examine the CV outcome risk trajectories during the time periods before and after an initial infection-related hospitalization. For this, we propose partly conditional and fully conditional partially linear generalized varying coefficient models (PL-GVCMs) for modeling time-varying effects in longitudinal data with substantial follow-up truncation by death. Unconditional models that implicitly target an immortal population is not a relevant target of inference in applications involving a population with high mortality, like the dialysis population. A partly conditional model characterizes the outcome trajectory for the dynamic cohort of survivors, where each point in the longitudinal trajectory represents a snapshot of the population relationships among subjects who are alive at that time point. In contrast, a fully conditional approach models the time-varying effects of the population stratified by the actual time of death, where the mean response characterizes individual trends in each cohort stratum. We compare and contrast partly and fully conditional PL-GVCMs in our aforementioned application using hospitalization data from the United States Renal Data System. For inference, we develop generalized likelihood ratio tests. Simulation studies examine the efficacy of estimation and inference procedures.

Outcomes of infection-related hospitalization in Medicare beneficiaries receiving in-center hemodialysis.

BACKGROUND: Infection is a common cause of hospitalization in adults receiving hemodialysis. Limited data are available about downstream events resulting from or following these hospitalizations. STUDY DESIGN: Retrospective cohort study using the US Renal Data System. SETTING & PARTICIPANTS: Medicare beneficiaries initiating in-center hemodialysis therapy in 2005 to 2008. FACTORS: Demographics, dual Medicare/Medicaid eligibility, body mass index, comorbid conditions, initial vascular access type, nephrology care prior to dialysis therapy initiation, residence in a care facility, tobacco use, biochemical measures, and type of infection. OUTCOMES: 30-day hospital readmission or death following first infection-related hospitalization. RESULTS: 60,270 Medicare beneficiaries had at least one hospitalization for infection. Of those who survived the initial hospitalization, 15,113 (27%) were readmitted and survived the 30 days following hospital discharge, 1,624 (3%) were readmitted to the hospital and then died within 30 days of discharge, and 2,425 (4%) died without hospital readmission. Complications related to dialysis access, sepsis, and heart failure accounted for 12%, 9%, and 7% of hospital readmissions, respectively. Factors associated with higher odds of 30-day readmission or death without readmission included non-Hispanic ethnicity, lower serum albumin level, inability to ambulate or transfer, limited nephrology care prior to dialysis therapy, and specific types of infection. In comparison, older age, select comorbid conditions, and institutionalization had stronger associations with death without readmission than with readmission. LIMITATIONS: Findings limited to Medicare beneficiaries receiving in-center hemodialysis. CONCLUSIONS: Hospitalizations for infection among patients receiving in-center hemodialysis are associated with exceptionally high rates of 30-day hospital readmission and death without readmission.

Association of Self-Reported Frailty with Falls and Fractures among Patients New to Dialysis.

BACKGROUND: Although frailty has been linked to higher risk of falls and fracture in the general population, only few studies have examined the extent to which frailty is associated with these outcomes among patients with end-stage renal disease, who are at particularly high risk for these events. METHODS: A total of 1,646 patients who were beginning maintenance hemodialysis in 297 dialysis units throughout the United States from September 2005 to June 2007 were enrolled in the Comprehensive Dialysis Study, and 1,053 Medicare beneficiaries were included in this study. Self-reported frailty was defined by the patients endorsing 2 or more of the following: poor physical functioning, exhaustion or low physical activity. Falls and fractures requiring medical attention were identified through Medicare claims data. We examined the association between frailty and the time to first fall or fracture using the Fine-Gray modification of Cox proportional hazards regression, adjusted for demographics, Quételet's body mass index, diabetes mellitus, heart failure and atherosclerosis. RESULTS: Seventy-seven percent of patients were frail by self-report. The median length of follow-up was 2.5 (1.0-3.9) years. Crude rates of first medically urgent falls or fractures were 66 and 126 per 1,000 person-years in non-frail and self-reported frail participants, respectively. After accounting for demographic factors, comorbidities and the competing risk of death, self-reported frailty was associated with a higher risk of falls or fractures requiring medical attention (hazards ratio 1.60, 95% CI 1.16-2.20). CONCLUSION: Participants reporting frailty experienced nearly twice the risk of medically urgent falls or fractures compared to those who did not report frailty.

Associations of Trimethylamine N-Oxide With Nutritional and Inflammatory Biomarkers and Cardiovascular Outcomes in Patients New to Dialysis.

OBJECTIVES: Trimethylamine N-oxide (TMAO) is a product of metabolism of phosphatidylcholine (lecithin) and carnitine by the intestinal microbiome. Elevated serum concentrations of TMAO have been linked to adverse cardiovascular outcomes in the general population. We examined correlates of serum TMAO and the relations among serum TMAO concentrations, all-cause mortality, and cardiovascular mortality and hospitalizations in a nationally derived cohort of patients new to hemodialysis (HD). METHODS: We quantified serum TMAO by liquid chromatography and online tandem mass spectrometry and assessed nutritional and cardiovascular risk factors in 235 patients receiving HD and measured TMAO in pooled serum from healthy controls. We analyzed time to death and time to cardiovascular death or hospitalization using Cox proportional hazards regression. RESULTS: Serum TMAO concentrations of patients undergoing HD (median, 43 µM/L; 25th-75th percentile, 28-67 µM/L) were elevated compared with those with normal or near-normal kidney function (1.41 ± 0.49 µM/L). TMAO was directly correlated with serum albumin (Spearman rank correlation, 0.24; 95% CI, 0.12-0.35; P <.001), prealbumin (Spearman rank correlation, 0.19; 95% CI, 0.07-0.31; P = .003), and creatinine (Spearman rank correlation, 0.21; 95% CI, 0.08-0.33; P = .002) and inversely correlated with log C-reactive protein (Spearman rank correlation, -0.18; 95% CI, -0.30 to -0.06; P = .005). Higher serum concentrations of TMAO were not significantly associated with time to death (Spearman rank correlation, 0.84; CI, 0.65-1.09; P = .19) or time to cardiovascular hospitalization or cardiovascular death (Spearman rank correlation, 0.88; CI, 0.57-1.35; P = .55). CONCLUSIONS: Serum TMAO concentrations were markedly elevated and correlated directly with biochemical markers of nutritional status and inversely with markers of inflammation in patients receiving HD. There was no significant association between serum TMAO concentrations and all-cause mortality, cardiovascular death, or hospitalizations. In patients receiving dialysis-in contrast with the general population-adverse vascular effects of TMAO may be counterbalanced by associations with nutritional or inflammatory status.

Association between body composition and frailty among prevalent hemodialysis patients: a US Renal Data System special study.

Studies of frailty among patients on hemodialysis have relied on definitions that substitute self-reported functioning for measures of physical performance and omit weight loss or substitute alternate criteria. We examined the association between body composition and a definition of frailty that includes measured physical performance and weight loss in a cross-sectional analysis of 638 adult patients receiving maintenance hemodialysis at 14 centers. Frailty was defined as having three of following characteristics: weight loss, weakness, exhaustion, low physical activity, and slow gait speed. We performed logistic regression with body mass index (BMI) and bioelectrical impedance spectroscopy (BIS)-derived estimates of intracellular water (ICW), fat mass, and extracellular water (ECW) as the main predictors, and age, sex, race, and comorbidity as covariates. Overall, 30% of participants were frail. Older age (odds ratio [OR], 1.31 per 10 years; 95% confidence interval [95% CI], 1.14 to 1.50), diabetes (OR, 1.65; 95% CI, 1.13 to 2.40), higher fat mass (OR, 1.18; 95% CI, 1.02 to 1.37), and higher ECW (OR, 1.33; 95% CI, 1.20 to 1.47) associated with higher odds of frailty. Higher ICW associated with lower odds of frailty (OR, 0.80 per kg; 95% CI, 0.73 to 0.87). The addition of BMI data did not change the area under the receiver operating characteristics curve (AUC; AUC=0.66 versus 0.66; P=0.71), but the addition of BIS data did change the AUC (AUC=0.72; P<0.001). Thus, individual components of body composition but not BMI associate strongly with frailty in this cohort of patients receiving hemodialysis.

Comparison of self-report-based and physical performance-based frailty definitions among patients receiving maintenance hemodialysis.

BACKGROUND: A well-accepted definition of frailty includes measurements of physical performance, which may limit its clinical utility. STUDY DESIGN: In a cross-sectional study, we compared prevalence and patient characteristics based on a frailty definition that uses self-reported function to the classic performance-based definition and developed a modified self-report-based definition. SETTING & PARTICIPANTS: Prevalent adult patients receiving hemodialysis in 14 centers around San Francisco and Atlanta in 2009-2011. INDEX TESTS: Self-report-based frailty definition in which a score lower than 75 on the Physical Function scale of the 36-Item Short Form Health Survey (SF-36) was substituted for gait speed and grip strength in the classic definition; modified self-report definition with optimized Physical Function score cutoff points derived in a development (one-half) cohort and validated in the other half. REFERENCE TEST: Performance-based frailty defined as 3 of the following: weight loss, weakness, exhaustion, low physical activity, and slow gait speed. RESULTS: 387 (53%) patients were frail based on self-reported function, of whom 209 (29% of the cohort) met the performance-based definition. Only 23 (3%) met the performance-based definition of frailty only. The self-report definition had 90% sensitivity, 64% specificity, 54% positive predictive value, 93% negative predictive value, and 72.5% overall accuracy. Intracellular water per kilogram of body weight and serum albumin, prealbumin, and creatinine levels were highest among nonfrail individuals, intermediate among those who were frail by self-report, and lowest among those who also were frail by performance. Age, percentage of body fat, and C-reactive protein level followed an opposite pattern. The modified self-report definition had better accuracy (84%; 95% CI, 79%-89%) and superior specificity (88%) and positive predictive value (67%). LIMITATIONS: Our study did not address prediction of outcomes. CONCLUSIONS: Patients who meet the self-report-based but not the performance-based definition of frailty may represent an intermediate phenotype. A modified self-report definition can improve the accuracy of a questionnaire-based method of defining frailty.

Changes in serum inflammatory markers are associated with changes in apolipoprotein A1 but not B after the initiation of dialysis.

BACKGROUND: Few studies have examined the changes in lipoproteins over time and how inflammation is associated with lipoprotein concentrations among patients with end-stage renal disease on dialysis. One possible explanation for the association of low LDL cholesterol concentration and adverse outcomes is that inflammation reduces selected apolipoprotein concentrations. METHODS: Serum samples were collected from a subsample of patients enrolled into the Comprehensive Dialysis Study every 3 months for up to 1 year. We examined the relation between temporal patterns in levels of inflammatory markers and changes in apolipoproteins (apo) A1 and B and the apo B/A1 ratio using linear mixed effects modeling and adjusting for potential confounders. RESULTS: We enrolled 266 participants from 56 dialysis facilities. The mean age was 62 years, 45% were women and 26% were black. Apo A1 was lower among patients with higher Quetelet's (body mass) index (BMI), diabetes mellitus and atherosclerosis. Apo B was lower among older patients, patients with higher serum creatinine and patients with lower BMI. Over the course of a year, apo A1 changed inversely with serum concentrations of the acute phase proteins C-reactive protein (CRP) and α1 acid glycoprotein (α1AG), while apo B did not. Changes in α1AG were more strongly associated with changes in apolipoprotein concentrations than were changes in CRP; increases in α1AG were associated with decreases in apo A1 and increases in the apo B/A1 ratio. CONCLUSIONS: Changes in inflammatory markers were associated with changes in apo A1, but not apo B over 1 year, suggesting that reductions in high-density lipoprotein cholesterol are associated with inflammation, either of which could mediate cardiovascular risk, but not supporting a hypothesis linking increased risk of low levels of apo B containing lipoproteins to the risk associated with inflammation.

Cardiovascular event risk dynamics over time in older patients on dialysis: a generalized multiple-index varying coefficient model approach.

Among patients on dialysis, cardiovascular disease and infection are leading causes of hospitalization and death. Although recent studies have found that the risk of cardiovascular events is higher after an infection-related hospitalization, studies have not fully elucidated how the risk of cardiovascular events changes over time for patients on dialysis. In this work, we characterize the dynamics of cardiovascular event risk trajectories for patients on dialysis while conditioning on survival status via multiple time indices: (1) time since the start of dialysis, (2) time since the pivotal initial infection-related hospitalization, and (3) the patient's age at the start of dialysis. This is achieved by using a new class of generalized multiple-index varying coefficient (GM-IVC) models. The proposed GM-IVC models utilize a multiplicative structure and one-dimensional varying coefficient functions along each time and age index to capture the cardiovascular risk dynamics before and after the initial infection-related hospitalization among the dynamic cohort of survivors. We develop a two-step estimation procedure for the GM-IVC models based on local maximum likelihood. We report new insights on the dynamics of cardiovascular events risk using the United States Renal Data System database, which collects data on nearly all patients with end-stage renal disease in the United States. Finally, simulation studies assess the performance of the proposed estimation procedures.

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression.

Weighted hurdle regression method for joint modeling of cardiovascular events likelihood and rate in the US dialysis population.

We propose a new weighted hurdle regression method for modeling count data, with particular interest in modeling cardiovascular events in patients on dialysis. Cardiovascular disease remains one of the leading causes of hospitalization and death in this population. Our aim is to jointly model the relationship/association between covariates and (i) the probability of cardiovascular events, a binary process, and (ii) the rate of events once the realization is positive-when the 'hurdle' is crossed-using a zero-truncated Poisson distribution. When the observation period or follow-up time, from the start of dialysis, varies among individuals, the estimated probability of positive cardiovascular events during the study period will be biased. Furthermore, when the model contains covariates, then the estimated relationship between the covariates and the probability of cardiovascular events will also be biased. These challenges are addressed with the proposed weighted hurdle regression method. Estimation for the weighted hurdle regression model is a weighted likelihood approach, where standard maximum likelihood estimation can be utilized. The method is illustrated with data from the United States Renal Data System. Simulation studies show the ability of proposed method to successfully adjust for differential follow-up times and incorporate the effects of covariates in the weighting.

Naive hypothesis testing for case series analysis with time-varying exposure onset measurement error: inference for infection-cardiovascular risk in patients on dialysis.

The case series method is useful in studying the relationship between time-varying exposures, such as infections, and acute events observed during the observation periods of individuals. It provides estimates of the relative incidences of events in risk periods (e.g., 30-day period after infections) relative to the baseline periods. When the times of exposure onsets are not known precisely, application of the case series model ignoring exposure onset measurement error leads to biased estimates. Bias-correction is necessary in order to understand the true directions and effect sizes associated with exposure risk periods, although uncorrected estimators have smaller variance. Thus, inference via hypothesis testing based on uncorrected test statistics, if valid, is potentially more powerful. Furthermore, the tests can be implemented in standard software and do not require additional auxiliary data. In this work, we examine the validity and power of naive hypothesis testing, based on applying the case series analysis to the imprecise data without correcting for the error. Based on simulation studies and theoretical calculations, we determine the validity and relative power of common hypothesis tests of interest in case series analysis. In particular, we illustrate that the tests for the global null hypothesis, the overall null hypotheses associated with all risk periods or all age effects are valid. However, tests of individual risk period parameters are not generally valid. Practical guidelines are provided and illustrated with data from patients on dialysis.

Design considerations for case series models with exposure onset measurement error.

The case series model allows for estimation of the relative incidence of events, such as cardiovascular events, within a pre-specified time window after an exposure, such as an infection. The method requires only cases (individuals with events) and controls for all fixed/time-invariant confounders. The measurement error case series model extends the original case series model to handle imperfect data, where the timing of an infection (exposure) is not known precisely. In this work, we propose a method for power/sample size determination for the measurement error case series model. Extensive simulation studies are used to assess the accuracy of the proposed sample size formulas. We also examine the magnitude of the relative loss of power due to exposure onset measurement error, compared with the ideal situation where the time of exposure is measured precisely. To facilitate the design of case series studies, we provide publicly available web-based tools for determining power/sample size for both the measurement error case series model as well as the standard case series model.

Modeling time-varying effects with generalized and unsynchronized longitudinal data.

We propose novel estimation approaches for generalized varying coefficient models that are tailored for unsynchronized, irregular and infrequent longitudinal designs/data. Unsynchronized longitudinal data refer to the time-dependent response and covariate measurements for each individual measured at distinct time points. Data from the Comprehensive Dialysis Study motivate the proposed methods. We model the potential age-varying association between infection-related hospitalization status and the inflammatory marker, C-reactive protein, within the first 2 years from initiation of dialysis. We cannot directly apply traditional longitudinal modeling to unsynchronized data, and no method exists to estimate time-varying or age-varying effects for generalized outcomes (e.g., binary or count data) to date. In addition, through the analysis of the Comprehensive Dialysis Study data and simulation studies, we show that preprocessing steps, such as binning, needed to synchronize data to apply traditional modeling can lead to significant loss of information in this context. In contrast, the proposed approaches discard no observation; they exploit the fact that although there is little information in a single subject trajectory because of irregularity and infrequency, the moments of the underlying processes can be accurately and efficiently recovered by pooling information from all subjects using functional data analysis. We derive subject-specific mean response trajectory predictions and study finite sample properties of the estimators.